PROPER: global protein interaction network alignment through percolation matching.

PubMed

Kazemi, Ehsan; Hassani, Hamed; Grossglauser, Matthias; Pezeshgi Modarres, Hassan

2016-12-12

The alignment of protein-protein interaction (PPI) networks enables us to uncover the relationships between different species, which leads to a deeper understanding of biological systems. Network alignment can be used to transfer biological knowledge between species. Although different PPI-network alignment algorithms were introduced during the last decade, developing an accurate and scalable algorithm that can find alignments with high biological and structural similarities among PPI networks is still challenging. In this paper, we introduce a new global network alignment algorithm for PPI networks called PROPER. Compared to other global network alignment methods, our algorithm shows higher accuracy and speed over real PPI datasets and synthetic networks. We show that the PROPER algorithm can detect large portions of conserved biological pathways between species. Also, using a simple parsimonious evolutionary model, we explain why PROPER performs well based on several different comparison criteria. We highlight that PROPER has high potential in further applications such as detecting biological pathways, finding protein complexes and PPI prediction. The PROPER algorithm is available at http://proper.epfl.ch .

FACETS: multi-faceted functional decomposition of protein interaction networks

PubMed Central

Seah, Boon-Siew; Bhowmick, Sourav S.; Forbes Dewey, C.

2012-01-01

Motivation: The availability of large-scale curated protein interaction datasets has given rise to the opportunity to investigate higher level organization and modularity within the protein–protein interaction (PPI) network using graph theoretic analysis. Despite the recent progress, systems level analysis of high-throughput PPIs remains a daunting task because of the amount of data they present. In this article, we propose a novel PPI network decomposition algorithm called FACETS in order to make sense of the deluge of interaction data using Gene Ontology (GO) annotations. FACETS finds not just a single functional decomposition of the PPI network, but a multi-faceted atlas of functional decompositions that portray alternative perspectives of the functional landscape of the underlying PPI network. Each facet in the atlas represents a distinct interpretation of how the network can be functionally decomposed and organized. Our algorithm maximizes interpretative value of the atlas by optimizing inter-facet orthogonality and intra-facet cluster modularity. Results: We tested our algorithm on the global networks from IntAct, and compared it with gold standard datasets from MIPS and KEGG. We demonstrated the performance of FACETS. We also performed a case study that illustrates the utility of our approach. Contact: seah0097@ntu.edu.sg or assourav@ntu.edu.sg Supplementary information: Supplementary data are available at the Bioinformatics online. Availability: Our software is available freely for non-commercial purposes from: http://www.cais.ntu.edu.sg/∼assourav/Facets/ PMID:22908217

Stringent homology-based prediction of H. sapiens-M. tuberculosis H37Rv protein-protein interactions.

PubMed

Zhou, Hufeng; Gao, Shangzhi; Nguyen, Nam Ninh; Fan, Mengyuan; Jin, Jingjing; Liu, Bing; Zhao, Liang; Xiong, Geng; Tan, Min; Li, Shijun; Wong, Limsoon

2014-04-08

H. sapiens-M. tuberculosis H37Rv protein-protein interaction (PPI) data are essential for understanding the infection mechanism of the formidable pathogen M. tuberculosis H37Rv. Computational prediction is an important strategy to fill the gap in experimental H. sapiens-M. tuberculosis H37Rv PPI data. Homology-based prediction is frequently used in predicting both intra-species and inter-species PPIs. However, some limitations are not properly resolved in several published works that predict eukaryote-prokaryote inter-species PPIs using intra-species template PPIs. We develop a stringent homology-based prediction approach by taking into account (i) differences between eukaryotic and prokaryotic proteins and (ii) differences between inter-species and intra-species PPI interfaces. We compare our stringent homology-based approach to a conventional homology-based approach for predicting host-pathogen PPIs, based on cellular compartment distribution analysis, disease gene list enrichment analysis, pathway enrichment analysis and functional category enrichment analysis. These analyses support the validity of our prediction result, and clearly show that our approach has better performance in predicting H. sapiens-M. tuberculosis H37Rv PPIs. Using our stringent homology-based approach, we have predicted a set of highly plausible H. sapiens-M. tuberculosis H37Rv PPIs which might be useful for many of related studies. Based on our analysis of the H. sapiens-M. tuberculosis H37Rv PPI network predicted by our stringent homology-based approach, we have discovered several interesting properties which are reported here for the first time. We find that both host proteins and pathogen proteins involved in the host-pathogen PPIs tend to be hubs in their own intra-species PPI network. Also, both host and pathogen proteins involved in host-pathogen PPIs tend to have longer primary sequence, tend to have more domains, tend to be more hydrophilic, etc. And the protein domains from both host and pathogen proteins involved in host-pathogen PPIs tend to have lower charge, and tend to be more hydrophilic. Our stringent homology-based prediction approach provides a better strategy in predicting PPIs between eukaryotic hosts and prokaryotic pathogens than a conventional homology-based approach. The properties we have observed from the predicted H. sapiens-M. tuberculosis H37Rv PPI network are useful for understanding inter-species host-pathogen PPI networks and provide novel insights for host-pathogen interaction studies.

Identification of potential crucial genes and construction of microRNA-mRNA negative regulatory networks in osteosarcoma.

PubMed

Pan, Yue; Lu, Lingyun; Chen, Junquan; Zhong, Yong; Dai, Zhehao

2018-01-01

This study aimed to identify potential crucial genes and construction of microRNA-mRNA negative regulatory networks in osteosarcoma by comprehensive bioinformatics analysis. Data of gene expression profiles (GSE28424) and miRNA expression profiles (GSE28423) were downloaded from GEO database. The differentially expressed genes (DEGs) and miRNAs (DEMIs) were obtained by R Bioconductor packages. Functional and enrichment analyses of selected genes were performed using DAVID database. Protein-protein interaction (PPI) network was constructed by STRING and visualized in Cytoscape. The relationships among the DEGs and module in PPI network were analyzed by plug-in NetworkAnalyzer and MCODE seperately. Through the TargetScan and comparing target genes with DEGs, the miRNA-mRNA regulation network was established. Totally 346 DEGs and 90 DEMIs were found to be differentially expressed. These DEGs were enriched in biological processes and KEGG pathway of inflammatory immune response. 25 genes in the PPI network were selected as hub genes. Top 10 hub genes were TYROBP, HLA-DRA, VWF, PPBP, SERPING1, HLA-DPA1, SERPINA1, KIF20A, FERMT3, HLA-E. PPI network of DEGs followed a pattern of power law network and met the characteristics of small-world network. MCODE analysis identified 4 clusters and the most significant cluster consisted of 11 nodes and 55 edges. SEPP1, CKS2, TCAP, BPI were identified as the seed genes in their own clusters, respectively. The miRNA-mRNA regulation network which was composed of 89 pairs was established. MiR-210 had the highest connectivity with 12 target genes. Among the predicted target of MiR-96, HLA-DPA1 and TYROBP were the hub genes. Our study indicated possible differentially expressed genes and miRNA, and microRNA-mRNA negative regulatory networks in osteosarcoma by bioinformatics analysis, which may provide novel insights for unraveling pathogenesis of osteosarcoma.

Pharmacological interventions for stress ulcer prophylaxis in critically ill patients: a mixed treatment comparison network meta-analysis and a recursive cumulative meta-analysis.

PubMed

Sridharan, Kannan; Sivaramakrishnan, Gowri; Gnanaraj, Jerome

2018-02-01

Proton pump inhibitors (PPI), histamine-2 receptor antagonists (H2RA), sucralfate and antacids are the commonly administered agents for stress ulcer prophylaxis (SUP) in critically ill patients. The authors of this paper have conducted a network meta-analysis to compare the efficacy of these agents in SUP. Electronic databases were searched for randomized controlled trials, cohort studies and conference abstracts for studies comparing a SUP agent in critically ill patients to another active SUP agent or placebo. Overt, occult and clinically significant upper gastro-intestinal (UGI) bleeding, all-cause mortality, pneumonia, gastric colonization and ICU length of stay were considered as the outcome measures. A random effects model was used to generate pooled estimates. A total of 53 studies (4258 participants) were included. The pooled estimates were in favor of PPI and sucralfate for the overt UGI bleeding. PPI and H2RA bolus were associated with increased risk of gastric colonization and pneumonia. SUP in critically ill patients was not associated with any benefit with regard to clinically significant bleeding episodes. However, PPI and sucralfate significantly reduces overt UGI bleeding. On the contrary, PPI and H2RA bolus are associated with an increased risk of gastric colonization and pneumonia.

Discovering disease-associated genes in weighted protein-protein interaction networks

NASA Astrophysics Data System (ADS)

Cui, Ying; Cai, Meng; Stanley, H. Eugene

2018-04-01

Although there have been many network-based attempts to discover disease-associated genes, most of them have not taken edge weight - which quantifies their relative strength - into consideration. We use connection weights in a protein-protein interaction (PPI) network to locate disease-related genes. We analyze the topological properties of both weighted and unweighted PPI networks and design an improved random forest classifier to distinguish disease genes from non-disease genes. We use a cross-validation test to confirm that weighted networks are better able to discover disease-associated genes than unweighted networks, which indicates that including link weight in the analysis of network properties provides a better model of complex genotype-phenotype associations.

Completing sparse and disconnected protein-protein network by deep learning.

PubMed

Huang, Lei; Liao, Li; Wu, Cathy H

2018-03-22

Protein-protein interaction (PPI) prediction remains a central task in systems biology to achieve a better and holistic understanding of cellular and intracellular processes. Recently, an increasing number of computational methods have shifted from pair-wise prediction to network level prediction. Many of the existing network level methods predict PPIs under the assumption that the training network should be connected. However, this assumption greatly affects the prediction power and limits the application area because the current golden standard PPI networks are usually very sparse and disconnected. Therefore, how to effectively predict PPIs based on a training network that is sparse and disconnected remains a challenge. In this work, we developed a novel PPI prediction method based on deep learning neural network and regularized Laplacian kernel. We use a neural network with an autoencoder-like architecture to implicitly simulate the evolutionary processes of a PPI network. Neurons of the output layer correspond to proteins and are labeled with values (1 for interaction and 0 for otherwise) from the adjacency matrix of a sparse disconnected training PPI network. Unlike autoencoder, neurons at the input layer are given all zero input, reflecting an assumption of no a priori knowledge about PPIs, and hidden layers of smaller sizes mimic ancient interactome at different times during evolution. After the training step, an evolved PPI network whose rows are outputs of the neural network can be obtained. We then predict PPIs by applying the regularized Laplacian kernel to the transition matrix that is built upon the evolved PPI network. The results from cross-validation experiments show that the PPI prediction accuracies for yeast data and human data measured as AUC are increased by up to 8.4 and 14.9% respectively, as compared to the baseline. Moreover, the evolved PPI network can also help us leverage complementary information from the disconnected training network and multiple heterogeneous data sources. Tested by the yeast data with six heterogeneous feature kernels, the results show our method can further improve the prediction performance by up to 2%, which is very close to an upper bound that is obtained by an Approximate Bayesian Computation based sampling method. The proposed evolution deep neural network, coupled with regularized Laplacian kernel, is an effective tool in completing sparse and disconnected PPI networks and in facilitating integration of heterogeneous data sources.

Identification of infection- and defense-related genes via a dynamic host-pathogen interaction network using a Candida albicans-zebrafish infection model.

PubMed

Kuo, Zong-Yu; Chuang, Yung-Jen; Chao, Chun-Cheih; Liu, Fu-Chen; Lan, Chung-Yu; Chen, Bor-Sen

2013-01-01

Candida albicans infections and candidiasis are difficult to treat and create very serious therapeutic challenges. In this study, based on interactive time profile microarray data of C. albicans and zebrafish during infection, the infection-related protein-protein interaction (PPI) networks of the two species and the intercellular PPI network between host and pathogen were simultaneously constructed by a dynamic interaction model, modeled as an integrated network consisting of intercellular invasion and cellular defense processes during infection. The signal transduction pathways in regulating morphogenesis and hyphal growth of C. albicans were further investigated based on significant interactions found in the intercellular PPI network. Two cellular networks were also developed corresponding to the different infection stages (adhesion and invasion), and then compared with each other to identify proteins from which we can gain more insight into the pathogenic role of hyphal development in the C. albicans infection process. Important defense-related proteins in zebrafish were predicted using the same approach. The hyphal growth PPI network, zebrafish PPI network and host-pathogen intercellular PPI network were combined to form an integrated infectious PPI network that helps us understand the systematic mechanisms underlying the pathogenicity of C. albicans and the immune response of the host, and may help improve medical therapies and facilitate the development of new antifungal drugs. Copyright © 2013 S. Karger AG, Basel.

Whole-exome sequencing in obsessive-compulsive disorder identifies rare mutations in immunological and neurodevelopmental pathways

PubMed Central

Cappi, C; Brentani, H; Lima, L; Sanders, S J; Zai, G; Diniz, B J; Reis, V N S; Hounie, A G; Conceição do Rosário, M; Mariani, D; Requena, G L; Puga, R; Souza-Duran, F L; Shavitt, R G; Pauls, D L; Miguel, E C; Fernandez, T V

2016-01-01

Studies of rare genetic variation have identified molecular pathways conferring risk for developmental neuropsychiatric disorders. To date, no published whole-exome sequencing studies have been reported in obsessive-compulsive disorder (OCD). We sequenced all the genome coding regions in 20 sporadic OCD cases and their unaffected parents to identify rare de novo (DN) single-nucleotide variants (SNVs). The primary aim of this pilot study was to determine whether DN variation contributes to OCD risk. To this aim, we evaluated whether there is an elevated rate of DN mutations in OCD, which would justify this approach toward gene discovery in larger studies of the disorder. Furthermore, to explore functional molecular correlations among genes with nonsynonymous DN SNVs in OCD probands, a protein–protein interaction (PPI) network was generated based on databases of direct molecular interactions. We applied Degree-Aware Disease Gene Prioritization (DADA) to rank the PPI network genes based on their relatedness to a set of OCD candidate genes from two OCD genome-wide association studies (Stewart et al., 2013; Mattheisen et al., 2014). In addition, we performed a pathway analysis with genes from the PPI network. The rate of DN SNVs in OCD was 2.51 × 10−8 per base per generation, significantly higher than a previous estimated rate in unaffected subjects using the same sequencing platform and analytic pipeline. Several genes harboring DN SNVs in OCD were highly interconnected in the PPI network and ranked high in the DADA analysis. Nearly all the DN SNVs in this study are in genes expressed in the human brain, and a pathway analysis revealed enrichment in immunological and central nervous system functioning and development. The results of this pilot study indicate that further investigation of DN variation in larger OCD cohorts is warranted to identify specific risk genes and to confirm our preliminary finding with regard to PPI network enrichment for particular biological pathways and functions. PMID:27023170

Network-Based Comparative Analysis of Arabidopsis Immune Responses to Golovinomyces orontii and Botrytis cinerea Infections.

PubMed

Jiang, Zhenhong; Dong, Xiaobao; Zhang, Ziding

2016-01-11

A comprehensive exploration of common and specific plant responses to biotrophs and necrotrophs is necessary for a better understanding of plant immunity. Here, we compared the Arabidopsis defense responses evoked by the biotrophic fungus Golovinomyces orontii and the necrotrophic fungus Botrytis cinerea through integrative network analysis. Two time-course transcriptional datasets were integrated with an Arabidopsis protein-protein interaction (PPI) network to construct a G. orontii conditional PPI sub-network (gCPIN) and a B. cinerea conditional PPI sub-network (bCPIN). We found that hubs in gCPIN and bCPIN played important roles in disease resistance. Hubs in bCPIN evolved faster than hubs in gCPIN, indicating the different selection pressures imposed on plants by different pathogens. By analyzing the common network from gCPIN and bCPIN, we identified two network components in which the genes were heavily involved in defense and development, respectively. The co-expression relationships between interacting proteins connecting the two components were different under G. orontii and B. cinerea infection conditions. Closer inspection revealed that auxin-related genes were overrepresented in the interactions connecting these two components, suggesting a critical role of auxin signaling in regulating the different co-expression relationships. Our work may provide new insights into plant defense responses against pathogens with different lifestyles.

Stringent homology-based prediction of H. sapiens-M. tuberculosis H37Rv protein-protein interactions

PubMed Central

2014-01-01

Background H. sapiens-M. tuberculosis H37Rv protein-protein interaction (PPI) data are essential for understanding the infection mechanism of the formidable pathogen M. tuberculosis H37Rv. Computational prediction is an important strategy to fill the gap in experimental H. sapiens-M. tuberculosis H37Rv PPI data. Homology-based prediction is frequently used in predicting both intra-species and inter-species PPIs. However, some limitations are not properly resolved in several published works that predict eukaryote-prokaryote inter-species PPIs using intra-species template PPIs. Results We develop a stringent homology-based prediction approach by taking into account (i) differences between eukaryotic and prokaryotic proteins and (ii) differences between inter-species and intra-species PPI interfaces. We compare our stringent homology-based approach to a conventional homology-based approach for predicting host-pathogen PPIs, based on cellular compartment distribution analysis, disease gene list enrichment analysis, pathway enrichment analysis and functional category enrichment analysis. These analyses support the validity of our prediction result, and clearly show that our approach has better performance in predicting H. sapiens-M. tuberculosis H37Rv PPIs. Using our stringent homology-based approach, we have predicted a set of highly plausible H. sapiens-M. tuberculosis H37Rv PPIs which might be useful for many of related studies. Based on our analysis of the H. sapiens-M. tuberculosis H37Rv PPI network predicted by our stringent homology-based approach, we have discovered several interesting properties which are reported here for the first time. We find that both host proteins and pathogen proteins involved in the host-pathogen PPIs tend to be hubs in their own intra-species PPI network. Also, both host and pathogen proteins involved in host-pathogen PPIs tend to have longer primary sequence, tend to have more domains, tend to be more hydrophilic, etc. And the protein domains from both host and pathogen proteins involved in host-pathogen PPIs tend to have lower charge, and tend to be more hydrophilic. Conclusions Our stringent homology-based prediction approach provides a better strategy in predicting PPIs between eukaryotic hosts and prokaryotic pathogens than a conventional homology-based approach. The properties we have observed from the predicted H. sapiens-M. tuberculosis H37Rv PPI network are useful for understanding inter-species host-pathogen PPI networks and provide novel insights for host-pathogen interaction studies. Reviewers This article was reviewed by Michael Gromiha, Narayanaswamy Srinivasan and Thomas Dandekar. PMID:24708540

IntNetDB v1.0: an integrated protein-protein interaction network database generated by a probabilistic model

PubMed Central

Xia, Kai; Dong, Dong; Han, Jing-Dong J

2006-01-01

Background Although protein-protein interaction (PPI) networks have been explored by various experimental methods, the maps so built are still limited in coverage and accuracy. To further expand the PPI network and to extract more accurate information from existing maps, studies have been carried out to integrate various types of functional relationship data. A frequently updated database of computationally analyzed potential PPIs to provide biological researchers with rapid and easy access to analyze original data as a biological network is still lacking. Results By applying a probabilistic model, we integrated 27 heterogeneous genomic, proteomic and functional annotation datasets to predict PPI networks in human. In addition to previously studied data types, we show that phenotypic distances and genetic interactions can also be integrated to predict PPIs. We further built an easy-to-use, updatable integrated PPI database, the Integrated Network Database (IntNetDB) online, to provide automatic prediction and visualization of PPI network among genes of interest. The networks can be visualized in SVG (Scalable Vector Graphics) format for zooming in or out. IntNetDB also provides a tool to extract topologically highly connected network neighborhoods from a specific network for further exploration and research. Using the MCODE (Molecular Complex Detections) algorithm, 190 such neighborhoods were detected among all the predicted interactions. The predicted PPIs can also be mapped to worm, fly and mouse interologs. Conclusion IntNetDB includes 180,010 predicted protein-protein interactions among 9,901 human proteins and represents a useful resource for the research community. Our study has increased prediction coverage by five-fold. IntNetDB also provides easy-to-use network visualization and analysis tools that allow biological researchers unfamiliar with computational biology to access and analyze data over the internet. The web interface of IntNetDB is freely accessible at . Visualization requires Mozilla version 1.8 (or higher) or Internet Explorer with installation of SVGviewer. PMID:17112386

Network-based analysis of differentially expressed genes in cerebrospinal fluid (CSF) and blood reveals new candidate genes for multiple sclerosis

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Tabatabaei, Seyyed Mohammad; Namaki, Saeed

2016-01-01

Background The involvement of multiple genes and missing heritability, which are dominant in complex diseases such as multiple sclerosis (MS), entail using network biology to better elucidate their molecular basis and genetic factors. We therefore aimed to integrate interactome (protein–protein interaction (PPI)) and transcriptomes data to construct and analyze PPI networks for MS disease. Methods Gene expression profiles in paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from MS patients, sampled in relapse or remission and controls, were analyzed. Differentially expressed genes which determined only in CSF (MS vs. control) and PBMCs (relapse vs. remission) separately integrated with PPI data to construct the Query-Query PPI (QQPPI) networks. The networks were further analyzed to investigate more central genes, functional modules and complexes involved in MS progression. Results The networks were analyzed and high centrality genes were identified. Exploration of functional modules and complexes showed that the majority of high centrality genes incorporated in biological pathways driving MS pathogenesis. Proteasome and spliceosome were also noticeable in enriched pathways in PBMCs (relapse vs. remission) which were identified by both modularity and clique analyses. Finally, STK4, RB1, CDKN1A, CDK1, RAC1, EZH2, SDCBP genes in CSF (MS vs. control) and CDC37, MAP3K3, MYC genes in PBMCs (relapse vs. remission) were identified as potential candidate genes for MS, which were the more central genes involved in biological pathways. Discussion This study showed that network-based analysis could explicate the complex interplay between biological processes underlying MS. Furthermore, an experimental validation of candidate genes can lead to identification of potential therapeutic targets. PMID:28028462

Protein complex prediction in large ontology attributed protein-protein interaction networks.

PubMed

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng; Xu, Bo

2013-01-01

Protein complexes are important for unraveling the secrets of cellular organization and function. Many computational approaches have been developed to predict protein complexes in protein-protein interaction (PPI) networks. However, most existing approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology (GO) annotation information. In this paper, we constructed ontology attributed PPI networks with PPI data and GO resource. After constructing ontology attributed networks, we proposed a novel approach called CSO (clustering based on network structure and ontology attribute similarity). Structural information and GO attribute information are complementary in ontology attributed networks. CSO can effectively take advantage of the correlation between frequent GO annotation sets and the dense subgraph for protein complex prediction. Our proposed CSO approach was applied to four different yeast PPI data sets and predicted many well-known protein complexes. The experimental results showed that CSO was valuable in predicting protein complexes and achieved state-of-the-art performance.

"Master-Slave" Biological Network Alignment

NASA Astrophysics Data System (ADS)

Ferraro, Nicola; Palopoli, Luigi; Panni, Simona; Rombo, Simona E.

Performing global alignment between protein-protein interaction (PPI) networks of different organisms is important to infer knowledge about conservation across species. Known methods that perform this task operate symmetrically, that is to say, they do not assign a distinct role to the input PPI networks. However, in most cases, the input networks are indeed distinguishable on the basis of how well the corresponding organism is biologically well-characterized. For well-characterized organisms the associated PPI network supposedly encode in a sound manner all the information about their proteins and associated interactions, which is far from being the case for not well characterized ones. Here the new idea is developed to devise a method for global alignment of PPI networks that in fact exploit differences in the characterization of organisms at hand. We assume that the PPI network (called Master) of the best characterized is used as a fingerprint to guide the alignment process to the second input network (called Slave), so that generated results preferably retain the structural characteristics of the Master (and using the Slave) network. We tested our method showing that the results it returns are biologically relevant.

Flexible regenerated cellulose/polypyrrole composite films with enhanced dielectric properties.

PubMed

Raghunathan, Sreejesh Poikavila; Narayanan, Sona; Poulose, Aby Cheruvathur; Joseph, Rani

2017-02-10

Flexible regenerated cellulose/polypyrrole (RC-PPy) conductive composite films were prepared by insitu polymerization of pyrrole on regenerated cellulose (RC) matrix using ammonium persulphate as oxidant. FTIR, XPS and XRD analysis of RC-PPy composite films revealed strong interaction between polypyrrole (PPy) and RC matrix. XRD results indicated that crystalline structure of RC matrix remains intact even after composite formation. SEM micrographs revealed the formation of a continuous conductive network of PPy particles in the RC matrix, leading to significant improvement in electrical and dielectric properties. The electrical conductivity of RC-PPy composites with 12wt% of PPy was 3.2×10 -5 S/cm, which is approximately seven fold higher than that of RC. Composites showed high dielectric constant and low dielectric loss values, which is essential in capacitor application. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effect of curcumin on aged Drosophila melanogaster: a pathway prediction analysis.

PubMed

Zhang, Zhi-guo; Niu, Xu-yan; Lu, Ai-ping; Xiao, Gary Guishan

2015-02-01

To re-analyze the data published in order to explore plausible biological pathways that can be used to explain the anti-aging effect of curcumin. Microarray data generated from other study aiming to investigate effect of curcumin on extending lifespan of Drosophila melanogaster were further used for pathway prediction analysis. The differentially expressed genes were identified by using GeneSpring GX with a criterion of 3.0-fold change. Two Cytoscape plugins including BisoGenet and molecular complex detection (MCODE) were used to establish the protein-protein interaction (PPI) network based upon differential genes in order to detect highly connected regions. The function annotation clustering tool of Database for Annotation, Visualization and Integrated Discovery (DAVID) was used for pathway analysis. A total of 87 genes expressed differentially in D. melanogaster melanogaster treated with curcumin were identified, among which 50 were up-regulated significantly and 37 were remarkably down-regulated in D. melanogaster melanogaster treated with curcumin. Based upon these differential genes, PPI network was constructed with 1,082 nodes and 2,412 edges. Five highly connected regions in PPI networks were detected by MCODE algorithm, suggesting anti-aging effect of curcumin may be underlined through five different pathways including Notch signaling pathway, basal transcription factors, cell cycle regulation, ribosome, Wnt signaling pathway, and p53 pathway. Genes and their associated pathways in D. melanogaster melanogaster treated with anti-aging agent curcumin were identified using PPI network and MCODE algorithm, suggesting that curcumin may be developed as an alternative therapeutic medicine for treating aging-associated diseases.

Unified Alignment of Protein-Protein Interaction Networks.

PubMed

Malod-Dognin, Noël; Ban, Kristina; Pržulj, Nataša

2017-04-19

Paralleling the increasing availability of protein-protein interaction (PPI) network data, several network alignment methods have been proposed. Network alignments have been used to uncover functionally conserved network parts and to transfer annotations. However, due to the computational intractability of the network alignment problem, aligners are heuristics providing divergent solutions and no consensus exists on a gold standard, or which scoring scheme should be used to evaluate them. We comprehensively evaluate the alignment scoring schemes and global network aligners on large scale PPI data and observe that three methods, HUBALIGN, L-GRAAL and NATALIE, regularly produce the most topologically and biologically coherent alignments. We study the collective behaviour of network aligners and observe that PPI networks are almost entirely aligned with a handful of aligners that we unify into a new tool, Ulign. Ulign enables complete alignment of two networks, which traditional global and local aligners fail to do. Also, multiple mappings of Ulign define biologically relevant soft clusterings of proteins in PPI networks, which may be used for refining the transfer of annotations across networks. Hence, PPI networks are already well investigated by current aligners, so to gain additional biological insights, a paradigm shift is needed. We propose such a shift come from aligning all available data types collectively rather than any particular data type in isolation from others.

Identification of Modules in Protein-Protein Interaction Networks

NASA Astrophysics Data System (ADS)

Erten, Sinan; Koyutürk, Mehmet

In biological systems, most processes are carried out through orchestration of multiple interacting molecules. These interactions are often abstracted using network models. A key feature of cellular networks is their modularity, which contributes significantly to the robustness, as well as adaptability of biological systems. Therefore, modularization of cellular networks is likely to be useful in obtaining insights into the working principles of cellular systems, as well as building tractable models of cellular organization and dynamics. A common, high-throughput source of data on molecular interactions is in the form of physical interactions between proteins, which are organized into protein-protein interaction (PPI) networks. This chapter provides an overview on identification and analysis of functional modules in PPI networks, which has been an active area of research in the last decade.

Identifying essential proteins based on sub-network partition and prioritization by integrating subcellular localization information.

PubMed

Li, Min; Li, Wenkai; Wu, Fang-Xiang; Pan, Yi; Wang, Jianxin

2018-06-14

Essential proteins are important participants in various life activities and play a vital role in the survival and reproduction of living organisms. Identification of essential proteins from protein-protein interaction (PPI) networks has great significance to facilitate the study of human complex diseases, the design of drugs and the development of bioinformatics and computational science. Studies have shown that highly connected proteins in a PPI network tend to be essential. A series of computational methods have been proposed to identify essential proteins by analyzing topological structures of PPI networks. However, the high noise in the PPI data can degrade the accuracy of essential protein prediction. Moreover, proteins must be located in the appropriate subcellular localization to perform their functions, and only when the proteins are located in the same subcellular localization, it is possible that they can interact with each other. In this paper, we propose a new network-based essential protein discovery method based on sub-network partition and prioritization by integrating subcellular localization information, named SPP. The proposed method SPP was tested on two different yeast PPI networks obtained from DIP database and BioGRID database. The experimental results show that SPP can effectively reduce the effect of false positives in PPI networks and predict essential proteins more accurately compared with other existing computational methods DC, BC, CC, SC, EC, IC, NC. Copyright © 2018 Elsevier Ltd. All rights reserved.

Global Alignment of Pairwise Protein Interaction Networks for Maximal Common Conserved Patterns

DOE PAGES

Tian, Wenhong; Samatova, Nagiza F.

2013-01-01

A number of tools for the alignment of protein-protein interaction (PPI) networks have laid the foundation for PPI network analysis. Most of alignment tools focus on finding conserved interaction regions across the PPI networks through either local or global mapping of similar sequences. Researchers are still trying to improve the speed, scalability, and accuracy of network alignment. In view of this, we introduce a connected-components based fast algorithm, HopeMap, for network alignment. Observing that the size of true orthologs across species is small comparing to the total number of proteins in all species, we take a different approach based onmore » a precompiled list of homologs identified by KO terms. Applying this approach to S. cerevisiae (yeast) and D. melanogaster (fly), E. coli K12 and S. typhimurium , E. coli K12 and C. crescenttus , we analyze all clusters identified in the alignment. The results are evaluated through up-to-date known gene annotations, gene ontology (GO), and KEGG ortholog groups (KO). Comparing to existing tools, our approach is fast with linear computational cost, highly accurate in terms of KO and GO terms specificity and sensitivity, and can be extended to multiple alignments easily.« less

Discovering protein complexes in protein interaction networks via exploring the weak ties effect

PubMed Central

2012-01-01

Background Studying protein complexes is very important in biological processes since it helps reveal the structure-functionality relationships in biological networks and much attention has been paid to accurately predict protein complexes from the increasing amount of protein-protein interaction (PPI) data. Most of the available algorithms are based on the assumption that dense subgraphs correspond to complexes, failing to take into account the inherence organization within protein complex and the roles of edges. Thus, there is a critical need to investigate the possibility of discovering protein complexes using the topological information hidden in edges. Results To provide an investigation of the roles of edges in PPI networks, we show that the edges connecting less similar vertices in topology are more significant in maintaining the global connectivity, indicating the weak ties phenomenon in PPI networks. We further demonstrate that there is a negative relation between the weak tie strength and the topological similarity. By using the bridges, a reliable virtual network is constructed, in which each maximal clique corresponds to the core of a complex. By this notion, the detection of the protein complexes is transformed into a classic all-clique problem. A novel core-attachment based method is developed, which detects the cores and attachments, respectively. A comprehensive comparison among the existing algorithms and our algorithm has been made by comparing the predicted complexes against benchmark complexes. Conclusions We proved that the weak tie effect exists in the PPI network and demonstrated that the density is insufficient to characterize the topological structure of protein complexes. Furthermore, the experimental results on the yeast PPI network show that the proposed method outperforms the state-of-the-art algorithms. The analysis of detected modules by the present algorithm suggests that most of these modules have well biological significance in context of complexes, suggesting that the roles of edges are critical in discovering protein complexes. PMID:23046740

Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

PubMed

Yang, Jun; Hou, Ziming; Wang, Changjiang; Wang, Hao; Zhang, Hongbing

2018-04-23

Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key genes for ACP early diagnosis and treatment. Datasets GSE94349 and GSE68015 were obtained from Gene Expression Omnibus database. Consensus clustering was applied to discover the gene clusters in the expression data of GSE94349 and functional enrichment analysis was performed on gene set in each cluster. The protein-protein interaction (PPI) network was built by the Search Tool for the Retrieval of Interacting Genes, and hubs were selected. Support vector machine (SVM) model was built based on the signature genes identified from enrichment analysis and PPI network. Dataset GSE94349 was used for training and testing, and GSE68015 was used for validation. Besides, RT-qPCR analysis was performed to analyze the expression of signature genes in ACP samples compared with normal controls. Seven gene clusters were discovered in the differentially expressed genes identified from GSE94349 dataset. Enrichment analysis of each cluster identified 25 pathways that highly associated with ACP. PPI network was built and 46 hubs were determined. Twenty-five pathway-related genes that overlapped with the hubs in PPI network were used as signatures to establish the SVM diagnosis model for ACP. The prediction accuracy of SVM model for training, testing, and validation data were 94, 85, and 74%, respectively. The expression of CDH1, CCL2, ITGA2, COL8A1, COL6A2, and COL6A3 were significantly upregulated in ACP tumor samples, while CAMK2A, RIMS1, NEFL, SYT1, and STX1A were significantly downregulated, which were consistent with the differentially expressed gene analysis. SVM model is a promising classification tool for screening and early diagnosis of ACP. The ACP-related pathways and signature genes will advance our knowledge of ACP pathogenesis and benefit the therapy improvement.

PICKLE 2.0: A human protein-protein interaction meta-database employing data integration via genetic information ontology

PubMed Central

Gioutlakis, Aris; Klapa, Maria I.

2017-01-01

It has been acknowledged that source databases recording experimentally supported human protein-protein interactions (PPIs) exhibit limited overlap. Thus, the reconstruction of a comprehensive PPI network requires appropriate integration of multiple heterogeneous primary datasets, presenting the PPIs at various genetic reference levels. Existing PPI meta-databases perform integration via normalization; namely, PPIs are merged after converted to a certain target level. Hence, the node set of the integrated network depends each time on the number and type of the combined datasets. Moreover, the irreversible a priori normalization process hinders the identification of normalization artifacts in the integrated network, which originate from the nonlinearity characterizing the genetic information flow. PICKLE (Protein InteraCtion KnowLedgebasE) 2.0 implements a new architecture for this recently introduced human PPI meta-database. Its main novel feature over the existing meta-databases is its approach to primary PPI dataset integration via genetic information ontology. Building upon the PICKLE principles of using the reviewed human complete proteome (RHCP) of UniProtKB/Swiss-Prot as the reference protein interactor set, and filtering out protein interactions with low probability of being direct based on the available evidence, PICKLE 2.0 first assembles the RHCP genetic information ontology network by connecting the corresponding genes, nucleotide sequences (mRNAs) and proteins (UniProt entries) and then integrates PPI datasets by superimposing them on the ontology network without any a priori transformations. Importantly, this process allows the resulting heterogeneous integrated network to be reversibly normalized to any level of genetic reference without loss of the original information, the latter being used for identification of normalization biases, and enables the appraisal of potential false positive interactions through PPI source database cross-checking. The PICKLE web-based interface (www.pickle.gr) allows for the simultaneous query of multiple entities and provides integrated human PPI networks at either the protein (UniProt) or the gene level, at three PPI filtering modes. PMID:29023571

Three-Dimensional Networked Metal-Organic Frameworks with Conductive Polypyrrole Tubes for Flexible Supercapacitors.

PubMed

Xu, Xingtao; Tang, Jing; Qian, Huayu; Hou, Shujin; Bando, Yoshio; Hossain, Md Shahriar A; Pan, Likun; Yamauchi, Yusuke

2017-11-08

Metal-organic frameworks (MOFs) with high porosity and a regular porous structure have emerged as a promising electrode material for supercapacitors, but their poor electrical conductivity limits their utilization efficiency and capacitive performance. To increase the overall electrical conductivity as well as the efficiency of MOF particles, three-dimensional networked MOFs are developed via using preprepared conductive polypyrrole (PPy) tubes as the support for in situ growth of MOF particles. As a result, the highly conductive PPy tubes that run through the MOF particles not only increase the electron transfer between MOF particles and maintain the high effective porosity of the MOFs but also endow the MOFs with flexibility. Promoted by such elaborately designed MOF-PPy networks, the specific capacitance of MOF particles has been increased from 99.2 F g -1 for pristine zeolitic imidazolate framework (ZIF)-67 to 597.6 F g -1 for ZIF-PPy networks, indicating the importance of the design of the ZIF-PPy continuous microstructure. Furthermore, a flexible supercapacitor device based on ZIF-PPy networks shows an outstanding areal capacitance of 225.8 mF cm -2 , which is far above other MOFs-based supercapacitors reported up to date, confirming the significance of in situ synthetic chemistry as well as the importance of hybrid materials on the nanoscale.

The OncoPPi network of cancer-focused protein-protein interactions to inform biological insights and therapeutic strategies* | Office of Cancer Genomics

Cancer.gov

As genomics advances reveal the cancer gene landscape, a daunting task is to understand how these genes contribute to dysregulated oncogenic pathways. Integration of cancer genes into networks offers opportunities to reveal protein–protein interactions (PPIs) with functional and therapeutic significance. Here, we report the generation of a cancer-focused PPI network, termed OncoPPi, and identification of >260 cancer-associated PPIs not in other large-scale interactomes.

Network topological analysis reveals the functional cohesiveness for the newly discovered links by Yeast 2 Hybrid approach

NASA Astrophysics Data System (ADS)

Ghiassian, Susan; Pevzner, Sam; Rolland, Thomas; Tassan, Murat; Barabasi, Albert Laszlo; Vidal, Mark; CCNR, Northeastern University Collaboration; Dana Farber Cancer Institute Collaboration

2014-03-01

Protein-protein interaction maps and interactomes are the blueprint of Network Medicine and systems biology and are being experimentally studied by different groups. Despite the wide usage of Literature Curated Interactome (LCI), these sources are biased towards different parameters such as highly studied proteins. Yeast two hybrid method is a high throughput experimental setup which screens proteins in an unbiased fashion. Current knowledge of protein interactions is far from complete. In fact the previous offered data from Y2H method (2005), is estimated to offer only 5% of all potential protein interactions. Currently this coverage has increased to 20% of what is known as reference HI In this work we study the topological properties of Y2H protein-protein interactions network with LCI and show although they both agree on some properties, LCI shows a clear unbiased nature of interaction selections. Most importantly, we assess the properties of PPI as it evolves with increasing the coverage. We show that, the newly discovered interactions tend to connect proteins that have been closer than average in the previous PPI release. reinforcing the modular structure of PPI. Furthermore, we show, some unseen effects on PPI (as opposed to LCI) can be explained by its incompleteness.

FUSE: a profit maximization approach for functional summarization of biological networks.

PubMed

Seah, Boon-Siew; Bhowmick, Sourav S; Dewey, C Forbes; Yu, Hanry

2012-03-21

The availability of large-scale curated protein interaction datasets has given rise to the opportunity to investigate higher level organization and modularity within the protein interaction network (PPI) using graph theoretic analysis. Despite the recent progress, systems level analysis of PPIS remains a daunting task as it is challenging to make sense out of the deluge of high-dimensional interaction data. Specifically, techniques that automatically abstract and summarize PPIS at multiple resolutions to provide high level views of its functional landscape are still lacking. We present a novel data-driven and generic algorithm called FUSE (Functional Summary Generator) that generates functional maps of a PPI at different levels of organization, from broad process-process level interactions to in-depth complex-complex level interactions, through a pro t maximization approach that exploits Minimum Description Length (MDL) principle to maximize information gain of the summary graph while satisfying the level of detail constraint. We evaluate the performance of FUSE on several real-world PPIS. We also compare FUSE to state-of-the-art graph clustering methods with GO term enrichment by constructing the biological process landscape of the PPIS. Using AD network as our case study, we further demonstrate the ability of FUSE to quickly summarize the network and identify many different processes and complexes that regulate it. Finally, we study the higher-order connectivity of the human PPI. By simultaneously evaluating interaction and annotation data, FUSE abstracts higher-order interaction maps by reducing the details of the underlying PPI to form a functional summary graph of interconnected functional clusters. Our results demonstrate its effectiveness and superiority over state-of-the-art graph clustering methods with GO term enrichment.

Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

PubMed

Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

2015-01-01

In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

Linear motif-mediated interactions have contributed to the evolution of modularity in complex protein interaction networks.

PubMed

Kim, Inhae; Lee, Heetak; Han, Seong Kyu; Kim, Sanguk

2014-10-01

The modular architecture of protein-protein interaction (PPI) networks is evident in diverse species with a wide range of complexity. However, the molecular components that lead to the evolution of modularity in PPI networks have not been clearly identified. Here, we show that weak domain-linear motif interactions (DLIs) are more likely to connect different biological modules than strong domain-domain interactions (DDIs). This molecular division of labor is essential for the evolution of modularity in the complex PPI networks of diverse eukaryotic species. In particular, DLIs may compensate for the reduction in module boundaries that originate from increased connections between different modules in complex PPI networks. In addition, we show that the identification of biological modules can be greatly improved by including molecular characteristics of protein interactions. Our findings suggest that transient interactions have played a unique role in shaping the architecture and modularity of biological networks over the course of evolution.

Bioinspired Design of Strong, Tough, and Highly Conductive Polyol-Polypyrrole Composites for Flexible Electronics.

PubMed

Gao, Fengxian; Zhang, Ning; Fang, Xiaodong; Ma, Mingming

2017-02-22

Inspired by the dynamic network structure of animal dermis, we have designed and synthesized a series of polyol-polypyrrole (polyol-PPy) composites. Polyols and polypyrrole are cross-linked by hydrogen bonding and electrostatic interactions to form a dynamic network, which helps to dissipate destructive energy. We have found a clear correlation between the mechanical properties of polyol-PPy composites and the polyols structure. Particularly, the PEE-PPy film shows both high strength and flexibility, leading to a remarkable tensile toughness comparable to cocoon silk. The combination of outstanding strength, ductility, and conductivity enables polyol-PPy composites (especially PEE-PPy) as potential electronic materials for making flexible electronics.

Integrative network alignment reveals large regions of global network similarity in yeast and human.

PubMed

Kuchaiev, Oleksii; Przulj, Natasa

2011-05-15

High-throughput methods for detecting molecular interactions have produced large sets of biological network data with much more yet to come. Analogous to sequence alignment, efficient and reliable network alignment methods are expected to improve our understanding of biological systems. Unlike sequence alignment, network alignment is computationally intractable. Hence, devising efficient network alignment heuristics is currently a foremost challenge in computational biology. We introduce a novel network alignment algorithm, called Matching-based Integrative GRAph ALigner (MI-GRAAL), which can integrate any number and type of similarity measures between network nodes (e.g. proteins), including, but not limited to, any topological network similarity measure, sequence similarity, functional similarity and structural similarity. Hence, we resolve the ties in similarity measures and find a combination of similarity measures yielding the largest contiguous (i.e. connected) and biologically sound alignments. MI-GRAAL exposes the largest functional, connected regions of protein-protein interaction (PPI) network similarity to date: surprisingly, it reveals that 77.7% of proteins in the baker's yeast high-confidence PPI network participate in such a subnetwork that is fully contained in the human high-confidence PPI network. This is the first demonstration that species as diverse as yeast and human contain so large, continuous regions of global network similarity. We apply MI-GRAAL's alignments to predict functions of un-annotated proteins in yeast, human and bacteria validating our predictions in the literature. Furthermore, using network alignment scores for PPI networks of different herpes viruses, we reconstruct their phylogenetic relationship. This is the first time that phylogeny is exactly reconstructed from purely topological alignments of PPI networks. Supplementary files and MI-GRAAL executables: http://bio-nets.doc.ic.ac.uk/MI-GRAAL/.

Prior knowledge based mining functional modules from Yeast PPI networks with gene ontology

PubMed Central

2010-01-01

Background In the literature, there are fruitful algorithmic approaches for identification functional modules in protein-protein interactions (PPI) networks. Because of accumulation of large-scale interaction data on multiple organisms and non-recording interaction data in the existing PPI database, it is still emergent to design novel computational techniques that can be able to correctly and scalably analyze interaction data sets. Indeed there are a number of large scale biological data sets providing indirect evidence for protein-protein interaction relationships. Results The main aim of this paper is to present a prior knowledge based mining strategy to identify functional modules from PPI networks with the aid of Gene Ontology. Higher similarity value in Gene Ontology means that two gene products are more functionally related to each other, so it is better to group such gene products into one functional module. We study (i) to encode the functional pairs into the existing PPI networks; and (ii) to use these functional pairs as pairwise constraints to supervise the existing functional module identification algorithms. Topology-based modularity metric and complex annotation in MIPs will be used to evaluate the identified functional modules by these two approaches. Conclusions The experimental results on Yeast PPI networks and GO have shown that the prior knowledge based learning methods perform better than the existing algorithms. PMID:21172053

Filtering Gene Ontology semantic similarity for identifying protein complexes in large protein interaction networks.

PubMed

Wang, Jian; Xie, Dong; Lin, Hongfei; Yang, Zhihao; Zhang, Yijia

2012-06-21

Many biological processes recognize in particular the importance of protein complexes, and various computational approaches have been developed to identify complexes from protein-protein interaction (PPI) networks. However, high false-positive rate of PPIs leads to challenging identification. A protein semantic similarity measure is proposed in this study, based on the ontology structure of Gene Ontology (GO) terms and GO annotations to estimate the reliability of interactions in PPI networks. Interaction pairs with low GO semantic similarity are removed from the network as unreliable interactions. Then, a cluster-expanding algorithm is used to detect complexes with core-attachment structure on filtered network. Our method is applied to three different yeast PPI networks. The effectiveness of our method is examined on two benchmark complex datasets. Experimental results show that our method performed better than other state-of-the-art approaches in most evaluation metrics. The method detects protein complexes from large scale PPI networks by filtering GO semantic similarity. Removing interactions with low GO similarity significantly improves the performance of complex identification. The expanding strategy is also effective to identify attachment proteins of complexes.

Do cancer proteins really interact strongly in the human protein-protein interaction network?

PubMed

Xia, Junfeng; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

2011-06-01

Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. © 2011 Elsevier Ltd. All rights reserved.

Do cancer proteins really interact strongly in the human protein-protein interaction network?

PubMed Central

Xia, Junfeng; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

2011-01-01

Protein-protein interaction (PPI) network analysis has been widely applied in the investigation of the mechanisms of diseases, especially cancer. Recent studies revealed that cancer proteins tend to interact more strongly than other categories of proteins, even essential proteins, in the human interactome. However, it remains unclear whether this observation was introduced by the bias towards more cancer studies in humans. Here, we examined this important issue by uniquely comparing network characteristics of cancer proteins with three other sets of proteins in four organisms, three of which (fly, worm, and yeast) whose interactomes are essentially not biased towards cancer or other diseases. We confirmed that cancer proteins had stronger connectivity, shorter distance, and larger betweenness centrality than non-cancer disease proteins, essential proteins, and control proteins. Our statistical evaluation indicated that such observations were overall unlikely attributed to random events. Considering the large size and high quality of the PPI data in the four organisms, the conclusion that cancer proteins interact strongly in the PPI networks is reliable and robust. This conclusion suggests that perturbation of cancer proteins might cause major changes of cellular systems and result in abnormal cell function leading to cancer. PMID:21666777

Protein-protein interaction network of gene expression in the hydrocortisone-treated keloid.

PubMed

Chen, Rui; Zhang, Zhiliang; Xue, Zhujia; Wang, Lin; Fu, Mingang; Lu, Yi; Bai, Ling; Zhang, Ping; Fan, Zhihong

2015-01-01

In order to explore the molecular mechanism of hydrocortisone in keloid tissue, the gene expression profiles of keloid samples treated with hydrocortisone were subjected to bioinformatics analysis. Firstly, the gene expression profiles (GSE7890) of five samples of keloid treated with hydrocortisone and five untreated keloid samples were downloaded from the Gene Expression Omnibus (GEO) database. Secondly, data were preprocessed using packages in R language and differentially expressed genes (DEGs) were screened using a significance analysis of microarrays (SAM) protocol. Thirdly, the DEGs were subjected to gene ontology (GO) function and KEGG pathway enrichment analysis. Finally, the interactions of DEGs in samples of keloid treated with hydrocortisone were explored in a human protein-protein interaction (PPI) network, and sub-modules of the DEGs interaction network were analyzed using Cytoscape software. Based on the analysis, 572 DEGs in the hydrocortisone-treated samples were screened; most of these were involved in the signal transduction and cell cycle. Furthermore, three critical genes in the module, including COL1A1, NID1, and PRELP, were screened in the PPI network analysis. These findings enhance understanding of the pathogenesis of the keloid and provide references for keloid therapy. © 2015 The International Society of Dermatology.

Multi-agent-based bio-network for systems biology: protein-protein interaction network as an example.

PubMed

Ren, Li-Hong; Ding, Yong-Sheng; Shen, Yi-Zhen; Zhang, Xiang-Feng

2008-10-01

Recently, a collective effort from multiple research areas has been made to understand biological systems at the system level. This research requires the ability to simulate particular biological systems as cells, organs, organisms, and communities. In this paper, a novel bio-network simulation platform is proposed for system biology studies by combining agent approaches. We consider a biological system as a set of active computational components interacting with each other and with an external environment. Then, we propose a bio-network platform for simulating the behaviors of biological systems and modelling them in terms of bio-entities and society-entities. As a demonstration, we discuss how a protein-protein interaction (PPI) network can be seen as a society of autonomous interactive components. From interactions among small PPI networks, a large PPI network can emerge that has a remarkable ability to accomplish a complex function or task. We also simulate the evolution of the PPI networks by using the bio-operators of the bio-entities. Based on the proposed approach, various simulators with different functions can be embedded in the simulation platform, and further research can be done from design to development, including complexity validation of the biological system.

Investigation of candidate genes for osteoarthritis based on gene expression profiles.

PubMed

Dong, Shuanghai; Xia, Tian; Wang, Lei; Zhao, Qinghua; Tian, Jiwei

2016-12-01

To explore the mechanism of osteoarthritis (OA) and provide valid biological information for further investigation. Gene expression profile of GSE46750 was downloaded from Gene Expression Omnibus database. The Linear Models for Microarray Data (limma) package (Bioconductor project, http://www.bioconductor.org/packages/release/bioc/html/limma.html) was used to identify differentially expressed genes (DEGs) in inflamed OA samples. Gene Ontology function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were performed based on Database for Annotation, Visualization and Integrated Discovery data, and protein-protein interaction (PPI) network was constructed based on the Search Tool for the Retrieval of Interacting Genes/Proteins database. Regulatory network was screened based on Encyclopedia of DNA Elements. Molecular Complex Detection was used for sub-network screening. Two sub-networks with highest node degree were integrated with transcriptional regulatory network and KEGG functional enrichment analysis was processed for 2 modules. In total, 401 up- and 196 down-regulated DEGs were obtained. Up-regulated DEGs were involved in inflammatory response, while down-regulated DEGs were involved in cell cycle. PPI network with 2392 protein interactions was constructed. Moreover, 10 genes including Interleukin 6 (IL6) and Aurora B kinase (AURKB) were found to be outstanding in PPI network. There are 214 up- and 8 down-regulated transcription factor (TF)-target pairs in the TF regulatory network. Module 1 had TFs including SPI1, PRDM1, and FOS, while module 2 contained FOSL1. The nodes in module 1 were enriched in chemokine signaling pathway, while the nodes in module 2 were mainly enriched in cell cycle. The screened DEGs including IL6, AGT, and AURKB might be potential biomarkers for gene therapy for OA by being regulated by TFs such as FOS and SPI1, and participating in the cell cycle and cytokine-cytokine receptor interaction pathway. Copyright © 2016 Turkish Association of Orthopaedics and Traumatology. Production and hosting by Elsevier B.V. All rights reserved.

Prediction and functional analysis of the sweet orange protein-protein interaction network.

PubMed

Ding, Yu-Duan; Chang, Ji-Wei; Guo, Jing; Chen, Dijun; Li, Sen; Xu, Qiang; Deng, Xiu-Xin; Cheng, Yun-Jiang; Chen, Ling-Ling

2014-08-05

Sweet orange (Citrus sinensis) is one of the most important fruits world-wide. Because it is a woody plant with a long growth cycle, genetic studies of sweet orange are lagging behind those of other species. In this analysis, we employed ortholog identification and domain combination methods to predict the protein-protein interaction (PPI) network for sweet orange. The K-nearest neighbors (KNN) classification method was used to verify and filter the network. The final predicted PPI network, CitrusNet, contained 8,195 proteins with 124,491 interactions. The quality of CitrusNet was evaluated using gene ontology (GO) and Mapman annotations, which confirmed the reliability of the network. In addition, we calculated the expression difference of interacting genes (EDI) in CitrusNet using RNA-seq data from four sweet orange tissues, and also analyzed the EDI distribution and variation in different sub-networks. Gene expression in CitrusNet has significant modular features. Target of rapamycin (TOR) protein served as the central node of the hormone-signaling sub-network. All evidence supported the idea that TOR can integrate various hormone signals and affect plant growth. CitrusNet provides valuable resources for the study of biological functions in sweet orange.

Prioritization of candidate disease genes by combining topological similarity and semantic similarity.

PubMed

Liu, Bin; Jin, Min; Zeng, Pan

2015-10-01

The identification of gene-phenotype relationships is very important for the treatment of human diseases. Studies have shown that genes causing the same or similar phenotypes tend to interact with each other in a protein-protein interaction (PPI) network. Thus, many identification methods based on the PPI network model have achieved good results. However, in the PPI network, some interactions between the proteins encoded by candidate gene and the proteins encoded by known disease genes are very weak. Therefore, some studies have combined the PPI network with other genomic information and reported good predictive performances. However, we believe that the results could be further improved. In this paper, we propose a new method that uses the semantic similarity between the candidate gene and known disease genes to set the initial probability vector of a random walk with a restart algorithm in a human PPI network. The effectiveness of our method was demonstrated by leave-one-out cross-validation, and the experimental results indicated that our method outperformed other methods. Additionally, our method can predict new causative genes of multifactor diseases, including Parkinson's disease, breast cancer and obesity. The top predictions were good and consistent with the findings in the literature, which further illustrates the effectiveness of our method. Copyright © 2015 Elsevier Inc. All rights reserved.

Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

PubMed

Shen, Xianjun; Yi, Li; Jiang, Xingpeng; He, Tingting; Yang, Jincai; Xie, Wei; Hu, Po; Hu, Xiaohua

2017-01-01

How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI) data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment). It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.

Disease gene classification with metagraph representations.

PubMed

Kircali Ata, Sezin; Fang, Yuan; Wu, Min; Li, Xiao-Li; Xiao, Xiaokui

2017-12-01

Protein-protein interaction (PPI) networks play an important role in studying the functional roles of proteins, including their association with diseases. However, protein interaction networks are not sufficient without the support of additional biological knowledge for proteins such as their molecular functions and biological processes. To complement and enrich PPI networks, we propose to exploit biological properties of individual proteins. More specifically, we integrate keywords describing protein properties into the PPI network, and construct a novel PPI-Keywords (PPIK) network consisting of both proteins and keywords as two different types of nodes. As disease proteins tend to have a similar topological characteristics on the PPIK network, we further propose to represent proteins with metagraphs. Different from a traditional network motif or subgraph, a metagraph can capture a particular topological arrangement involving the interactions/associations between both proteins and keywords. Based on the novel metagraph representations for proteins, we further build classifiers for disease protein classification through supervised learning. Our experiments on three different PPI databases demonstrate that the proposed method consistently improves disease protein prediction across various classifiers, by 15.3% in AUC on average. It outperforms the baselines including the diffusion-based methods (e.g., RWR) and the module-based methods by 13.8-32.9% for overall disease protein prediction. For predicting breast cancer genes, it outperforms RWR, PRINCE and the module-based baselines by 6.6-14.2%. Finally, our predictions also turn out to have better correlations with literature findings from PubMed. Copyright © 2017 Elsevier Inc. All rights reserved.

Differential reward network functional connectivity in cannabis dependent and non-dependent users☆

PubMed Central

Filbey, Francesca M.; Dunlop, Joseph

2015-01-01

Background Emergent studies show that similar to other substances of abuse, cue-reactivity to cannabis is also associated with neural response in the brain’s reward pathway (Filbey et al., 2009). However, the inter-relatedness of brain regions during cue-reactivity in cannabis users remains unknown. Methods In this study, we conducted a series of investigations to determine functional connectivity during cue-reactivity in 71 cannabis users. First, we used psychophysiological interaction (PPI) analysis to examine coherent neural response to cannabis cues. Second, we evaluated whether these patterns of network functional connectivity differentiated dependent and non-dependent users. Finally, as an exploratory analysis, we determined the directionality of these connections via Granger connectivity analyses. Results PPI analyses showed reward network functional connectivity with the nucleus accumbens (NAc) seed region during cue exposure. Between-group contrasts found differential effects of dependence status. Dependent users (N = 31) had greater functional connectivity with amygdala and anterior cingulate gyrus (ACG) seeds while the non-dependent users (N = 24) had greater functional connectivity with the NAc, orbitofrontal cortex (OFC) and hippocampus seeds. Granger analyses showed that hippocampal and ACG activation preceded neural response in reward areas. Conclusions Both PPI and Granger analyses demonstrated strong functional coherence in reward regions during exposure to cannabis cues in current cannabis users. Functional connectivity (but not regional activation) in the reward network differentiated dependent from non-dependent cannabis users. Our findings suggest that repeated cannabis exposure causes observable changes in functional connectivity in the reward network and should be considered in intervention strategies. PMID:24838032

An examination of the Psychopathic Personality Inventory's nomological network: a meta-analytic review.

PubMed

Miller, Joshua D; Lynam, Donald R

2012-07-01

Since its publication, the Psychopathic Personality Inventory and its revision (Lilienfeld & Andrews, 1996; Lilienfeld & Widows, 2005) have become increasingly popular such that it is now among the most frequently used self-report inventories for the assessment of psychopathy. The current meta-analysis examined the relations between the two PPI factors (factor 1: Fearless Dominance; factor 2: Self-Centered Impulsivity), as well as their relations with other validated measures of psychopathy, internalizing and externalizing forms of psychopathology, general personality traits, and antisocial personality disorder symptoms. Across 61 samples reported in 49 publications, we found support for the convergent and criterion validity of both PPI factor 2 and the PPI total score. Much weaker validation was found for PPI factor 1, which manifested limited convergent validity and a pattern of correlations with central criterion variables that was inconsistent with many conceptualizations of psychopathy. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Functional connectivity patterns reflect individual differences in conflict adaptation.

PubMed

Wang, Xiangpeng; Wang, Ting; Chen, Zhencai; Hitchman, Glenn; Liu, Yijun; Chen, Antao

2015-04-01

Individuals differ in the ability to utilize previous conflict information to optimize current conflict resolution, which is termed the conflict adaptation effect. Previous studies have linked individual differences in conflict adaptation to distinct brain regions. However, the network-based neural mechanisms subserving the individual differences of the conflict adaptation effect have not been studied. The present study employed a psychophysiological interaction (PPI) analysis with a color-naming Stroop task to examine this issue. The main results were as follows: (1) the anterior cingulate cortex (ACC)-seeded PPI revealed the involvement of the salience network (SN) in conflict adaptation, while the posterior parietal cortex (PPC)-seeded PPI revealed the engagement of the central executive network (CEN). (2) Participants with high conflict adaptation effect showed higher intra-CEN connectivity and lower intra-SN connectivity; while those with low conflict adaptation effect showed higher intra-SN connectivity and lower intra-CEN connectivity. (3) The PPC-centered intra-CEN connectivity positively predicted the conflict adaptation effect; while the ACC-centered intra-SN connectivity had a negative correlation with this effect. In conclusion, our data demonstrated that conflict adaptation is likely supported by the CEN and the SN, providing a new perspective on studying individual differences in conflict adaptation on the basis of large-scale networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

Characterization of biomarkers in stroke based on ego-networks and pathways.

PubMed

Li, Haixia; Guo, Qianqian

2017-12-01

To explore potential biomarkers in stroke based on ego-networks and pathways. EgoNet method was applied to search for the underlying biomarkers in stroke using transcription profiling of E-GEOD-58294 and protein-protein interaction (PPI) data. Eight ego-genes were identified from PPI network according to the degree characteristics at the criteria of top 5% ranked z-sore and degree >1. Eight candidate ego-networks with classification accuracy ≥0.9 were selected. After performed randomization test, seven significant ego-networks with adjusted p value < 0.05 were identified. Pathway enrichment analysis was then conducted with these ego-networks to search for the significant pathways. Finally, two significant pathways were identified, and six of seven ego-networks were enriched to "3'-UTR-mediated translational regulation" pathway, indicating that this pathway performs an important role in the development of stroke. Seven ego-networks were constructed using EgoNet and two significant enriched by pathways were identified. These may provide new insights into the potential biomarkers for the development of stroke.

Efficient prediction of human protein-protein interactions at a global scale.

PubMed

Schoenrock, Andrew; Samanfar, Bahram; Pitre, Sylvain; Hooshyar, Mohsen; Jin, Ke; Phillips, Charles A; Wang, Hui; Phanse, Sadhna; Omidi, Katayoun; Gui, Yuan; Alamgir, Md; Wong, Alex; Barrenäs, Fredrik; Babu, Mohan; Benson, Mikael; Langston, Michael A; Green, James R; Dehne, Frank; Golshani, Ashkan

2014-12-10

Our knowledge of global protein-protein interaction (PPI) networks in complex organisms such as humans is hindered by technical limitations of current methods. On the basis of short co-occurring polypeptide regions, we developed a tool called MP-PIPE capable of predicting a global human PPI network within 3 months. With a recall of 23% at a precision of 82.1%, we predicted 172,132 putative PPIs. We demonstrate the usefulness of these predictions through a range of experiments. The speed and accuracy associated with MP-PIPE can make this a potential tool to study individual human PPI networks (from genomic sequences alone) for personalized medicine.

Constructing an integrated gene similarity network for the identification of disease genes.

PubMed

Tian, Zhen; Guo, Maozu; Wang, Chunyu; Xing, LinLin; Wang, Lei; Zhang, Yin

2017-09-20

Discovering novel genes that are involved human diseases is a challenging task in biomedical research. In recent years, several computational approaches have been proposed to prioritize candidate disease genes. Most of these methods are mainly based on protein-protein interaction (PPI) networks. However, since these PPI networks contain false positives and only cover less half of known human genes, their reliability and coverage are very low. Therefore, it is highly necessary to fuse multiple genomic data to construct a credible gene similarity network and then infer disease genes on the whole genomic scale. We proposed a novel method, named RWRB, to infer causal genes of interested diseases. First, we construct five individual gene (protein) similarity networks based on multiple genomic data of human genes. Then, an integrated gene similarity network (IGSN) is reconstructed based on similarity network fusion (SNF) method. Finally, we employee the random walk with restart algorithm on the phenotype-gene bilayer network, which combines phenotype similarity network, IGSN as well as phenotype-gene association network, to prioritize candidate disease genes. We investigate the effectiveness of RWRB through leave-one-out cross-validation methods in inferring phenotype-gene relationships. Results show that RWRB is more accurate than state-of-the-art methods on most evaluation metrics. Further analysis shows that the success of RWRB is benefited from IGSN which has a wider coverage and higher reliability comparing with current PPI networks. Moreover, we conduct a comprehensive case study for Alzheimer's disease and predict some novel disease genes that supported by literature. RWRB is an effective and reliable algorithm in prioritizing candidate disease genes on the genomic scale. Software and supplementary information are available at http://nclab.hit.edu.cn/~tianzhen/RWRB/ .

Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction.

PubMed

Stojanova, Daniela; Ceci, Michelangelo; Malerba, Donato; Dzeroski, Saso

2013-09-26

Ontologies and catalogs of gene functions, such as the Gene Ontology (GO) and MIPS-FUN, assume that functional classes are organized hierarchically, that is, general functions include more specific ones. This has recently motivated the development of several machine learning algorithms for gene function prediction that leverages on this hierarchical organization where instances may belong to multiple classes. In addition, it is possible to exploit relationships among examples, since it is plausible that related genes tend to share functional annotations. Although these relationships have been identified and extensively studied in the area of protein-protein interaction (PPI) networks, they have not received much attention in hierarchical and multi-class gene function prediction. Relations between genes introduce autocorrelation in functional annotations and violate the assumption that instances are independently and identically distributed (i.i.d.), which underlines most machine learning algorithms. Although the explicit consideration of these relations brings additional complexity to the learning process, we expect substantial benefits in predictive accuracy of learned classifiers. This article demonstrates the benefits (in terms of predictive accuracy) of considering autocorrelation in multi-class gene function prediction. We develop a tree-based algorithm for considering network autocorrelation in the setting of Hierarchical Multi-label Classification (HMC). We empirically evaluate the proposed algorithm, called NHMC (Network Hierarchical Multi-label Classification), on 12 yeast datasets using each of the MIPS-FUN and GO annotation schemes and exploiting 2 different PPI networks. The results clearly show that taking autocorrelation into account improves the predictive performance of the learned models for predicting gene function. Our newly developed method for HMC takes into account network information in the learning phase: When used for gene function prediction in the context of PPI networks, the explicit consideration of network autocorrelation increases the predictive performance of the learned models. Overall, we found that this holds for different gene features/ descriptions, functional annotation schemes, and PPI networks: Best results are achieved when the PPI network is dense and contains a large proportion of function-relevant interactions.

Network methods to support user involvement in qualitative data analyses: an introduction to Participatory Theme Elicitation.

PubMed

Best, Paul; Badham, Jennifer; Corepal, Rekesh; O'Neill, Roisin F; Tully, Mark A; Kee, Frank; Hunter, Ruth F

2017-11-23

While Patient and Public Involvement (PPI) is encouraged throughout the research process, engagement is typically limited to intervention design and post-analysis stages. There are few approaches to participatory data analyses within complex health interventions. Using qualitative data from a feasibility randomised controlled trial (RCT), this proof-of-concept study tests the value of a new approach to participatory data analysis called Participatory Theme Elicitation (PTE). Forty excerpts were given to eight members of a youth advisory PPI panel to sort into piles based on their perception of related thematic content. Using algorithms to detect communities in networks, excerpts were then assigned to a thematic cluster that combined the panel members' perspectives. Network analysis techniques were also used to identify key excerpts in each grouping that were then further explored qualitatively. While PTE analysis was, for the most part, consistent with the researcher-led analysis, young people also identified new emerging thematic content. PTE appears promising for encouraging user led identification of themes arising from qualitative data collected during complex interventions. Further work is required to validate and extend this method. ClinicalTrials.gov, ID: NCT02455986 . Retrospectively Registered on 21 May 2015.

Systematic analysis of molecular mechanisms for HCC metastasis via text mining approach.

PubMed

Zhen, Cheng; Zhu, Caizhong; Chen, Haoyang; Xiong, Yiru; Tan, Junyuan; Chen, Dong; Li, Jin

2017-02-21

To systematically explore the molecular mechanism for hepatocellular carcinoma (HCC) metastasis and identify regulatory genes with text mining methods. Genes with highest frequencies and significant pathways related to HCC metastasis were listed. A handful of proteins such as EGFR, MDM2, TP53 and APP, were identified as hub nodes in PPI (protein-protein interaction) network. Compared with unique genes for HBV-HCCs, genes particular to HCV-HCCs were less, but may participate in more extensive signaling processes. VEGFA, PI3KCA, MAPK1, MMP9 and other genes may play important roles in multiple phenotypes of metastasis. Genes in abstracts of HCC-metastasis literatures were identified. Word frequency analysis, KEGG pathway and PPI network analysis were performed. Then co-occurrence analysis between genes and metastasis-related phenotypes were carried out. Text mining is effective for revealing potential regulators or pathways, but the purpose of it should be specific, and the combination of various methods will be more useful.

Identification of key target genes and pathways in laryngeal carcinoma

PubMed Central

Liu, Feng; Du, Jintao; Liu, Jun; Wen, Bei

2016-01-01

The purpose of the present study was to screen the key genes associated with laryngeal carcinoma and to investigate the molecular mechanism of laryngeal carcinoma progression. The gene expression profile of GSE10935 [Gene Expression Omnibus (GEO) accession number], including 12 specimens from laryngeal papillomas and 12 specimens from normal laryngeal epithelia controls, was downloaded from the GEO database. Differentially expressed genes (DEGs) were screened in laryngeal papillomas compared with normal controls using Limma package in R language, followed by Gene Ontology (GO) enrichment analysis and pathway enrichment analysis. Furthermore, the protein-protein interaction (PPI) network of DEGs was constructed using Cytoscape software and modules were analyzed using MCODE plugin from the PPI network. Furthermore, significant biological pathway regions (sub-pathway) were identified by using iSubpathwayMiner analysis. A total of 67 DEGs were identified, including 27 up-regulated genes and 40 down-regulated genes and they were involved in different GO terms and pathways. PPI network analysis revealed that Ras association (RalGDS/AF-6) domain family member 1 (RASSF1) was a hub protein. The sub-pathway analysis identified 9 significantly enriched sub-pathways, including glycolysis/gluconeogenesis and nitrogen metabolism. Genes such as phosphoglycerate kinase 1 (PGK1), carbonic anhydrase II (CA2), and carbonic anhydrase XII (CA12) whose node degrees were >10 were identified in the disease risk sub-pathway. Genes in the sub-pathway, such as RASSF1, PGK1, CA2 and CA12 were presumed to serve critical roles in laryngeal carcinoma. The present study identified DEGs and their sub-pathways in the disease, which may serve as potential targets for treatment of laryngeal carcinoma. PMID:27446427

Systems-level analysis of risk genes reveals the modular nature of schizophrenia.

PubMed

Liu, Jiewei; Li, Ming; Luo, Xiong-Jian; Su, Bing

2018-05-19

Schizophrenia (SCZ) is a complex mental disorder with high heritability. Genetic studies (especially recent genome-wide association studies) have identified many risk genes for schizophrenia. However, the physical interactions among the proteins encoded by schizophrenia risk genes remain elusive and it is not known whether the identified risk genes converge on common molecular networks or pathways. Here we systematically investigated the network characteristics of schizophrenia risk genes using the high-confidence protein-protein interactions (PPI) from the human interactome. We found that schizophrenia risk genes encode a densely interconnected PPI network (P = 4.15 × 10 -31 ). Compared with the background genes, the schizophrenia risk genes in the interactome have significantly higher degree (P = 5.39 × 10 -11 ), closeness centrality (P = 7.56 × 10 -11 ), betweeness centrality (P = 1.29 × 10 -11 ), clustering coefficient (P = 2.22 × 10 -2 ), and shorter average shortest path length (P = 7.56 × 10 -11 ). Based on the densely interconnected PPI network, we identified 48 hub genes and 4 modules formed by highly interconnected schizophrenia genes. We showed that the proteins encoded by schizophrenia hub genes have significantly more direct physical interactions. Gene ontology (GO) analysis revealed that cell adhesion, cell cycle, immune system response, and GABR-receptor complex categories were enriched in the modules formed by highly interconnected schizophrenia risk genes. Our study reveals that schizophrenia risk genes encode a densely interconnected molecular network and demonstrates the modular nature of schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

HPIminer: A text mining system for building and visualizing human protein interaction networks and pathways.

PubMed

Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar

2015-04-01

The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks. Copyright © 2015 Elsevier Inc. All rights reserved.

Recent Coselection in Human Populations Revealed by Protein–Protein Interaction Network

PubMed Central

Qian, Wei; Zhou, Hang; Tang, Kun

2015-01-01

Genome-wide scans for signals of natural selection in human populations have identified a large number of candidate loci that underlie local adaptations. This is surprising given the relatively short evolutionary time since the divergence of the human population. One hypothesis that has not been formally examined is whether and how the recent human evolution may have been shaped by coselection in the context of complex molecular interactome. In this study, genome-wide signals of selection were scanned in East Asians, Europeans, and Africans using 1000 Genome data, and subsequently mapped onto the protein–protein interaction (PPI) network. We found that the candidate genes of recent positive selection localized significantly closer to each other on the PPI network than expected, revealing substantial clustering of selected genes. Furthermore, gene pairs of shorter PPI network distances showed higher similarities of their recent evolutionary paths than those further apart. Last, subnetworks enriched with recent coselection signals were identified, which are substantially overrepresented in biological pathways related to signal transduction, neurogenesis, and immune function. These results provide the first genome-wide evidence for association of recent selection signals with the PPI network, shedding light on the potential mechanisms of recent coselection in the human genome. PMID:25532814

Identifying protein complexes in PPI network using non-cooperative sequential game.

PubMed

Maulik, Ujjwal; Basu, Srinka; Ray, Sumanta

2017-08-21

Identifying protein complexes from protein-protein interaction (PPI) network is an important and challenging task in computational biology as it helps in better understanding of cellular mechanisms in various organisms. In this paper we propose a noncooperative sequential game based model for protein complex detection from PPI network. The key hypothesis is that protein complex formation is driven by mechanism that eventually optimizes the number of interactions within the complex leading to dense subgraph. The hypothesis is drawn from the observed network property named small world. The proposed multi-player game model translates the hypothesis into the game strategies. The Nash equilibrium of the game corresponds to a network partition where each protein either belong to a complex or form a singleton cluster. We further propose an algorithm to find the Nash equilibrium of the sequential game. The exhaustive experiment on synthetic benchmark and real life yeast networks evaluates the structural as well as biological significance of the network partitions.

The Interactomic Analysis Reveals Pathogenic Protein Networks in Phomopsis longicolla Underlying Seed Decay of Soybean.

PubMed

Li, Shuxian; Musungu, Bryan; Lightfoot, David; Ji, Pingsheng

2018-01-01

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla ) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein-protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms.

The Interactomic Analysis Reveals Pathogenic Protein Networks in Phomopsis longicolla Underlying Seed Decay of Soybean

PubMed Central

Li, Shuxian; Musungu, Bryan; Lightfoot, David; Ji, Pingsheng

2018-01-01

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein–protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms. PMID:29666630

ChiPPI: a novel method for mapping chimeric protein-protein interactions uncovers selection principles of protein fusion events in cancer.

PubMed

Frenkel-Morgenstern, Milana; Gorohovski, Alessandro; Tagore, Somnath; Sekar, Vaishnovi; Vazquez, Miguel; Valencia, Alfonso

2017-07-07

Fusion proteins, comprising peptides deriving from the translation of two parental genes, are produced in cancer by chromosomal aberrations. The expressed fusion protein incorporates domains of both parental proteins. Using a methodology that treats discrete protein domains as binding sites for specific domains of interacting proteins, we have cataloged the protein interaction networks for 11 528 cancer fusions (ChiTaRS-3.1). Here, we present our novel method, chimeric protein-protein interactions (ChiPPI) that uses the domain-domain co-occurrence scores in order to identify preserved interactors of chimeric proteins. Mapping the influence of fusion proteins on cell metabolism and pathways reveals that ChiPPI networks often lose tumor suppressor proteins and gain oncoproteins. Furthermore, fusions often induce novel connections between non-interactors skewing interaction networks and signaling pathways. We compared fusion protein PPI networks in leukemia/lymphoma, sarcoma and solid tumors finding distinct enrichment patterns for each disease type. While certain pathways are enriched in all three diseases (Wnt, Notch and TGF β), there are distinct patterns for leukemia (EGFR signaling, DNA replication and CCKR signaling), for sarcoma (p53 pathway and CCKR signaling) and solid tumors (FGFR and EGFR signaling). Thus, the ChiPPI method represents a comprehensive tool for studying the anomaly of skewed cellular networks produced by fusion proteins in cancer. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Context-based retrieval of functional modules in protein-protein interaction networks.

PubMed

Dobay, Maria Pamela; Stertz, Silke; Delorenzi, Mauro

2017-03-27

Various techniques have been developed for identifying the most probable interactants of a protein under a given biological context. In this article, we dissect the effects of the choice of the protein-protein interaction network (PPI) and the manipulation of PPI settings on the network neighborhood of the influenza A virus (IAV) network, as well as hits in genome-wide small interfering RNA screen results for IAV host factors. We investigate the potential of context filtering, which uses text mining evidence linked to PPI edges, as a complement to the edge confidence scores typically provided in PPIs for filtering, for obtaining more biologically relevant network neighborhoods. Here, we estimate the maximum performance of context filtering to isolate a Kyoto Encyclopedia of Genes and Genomes (KEGG) network Ki from a union of KEGG networks and its network neighborhood. The work gives insights on the use of human PPIs in network neighborhood approaches for functional inference. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

A network biology approach to understanding the importance of chameleon proteins in human physiology and pathology.

PubMed

Bahramali, Golnaz; Goliaei, Bahram; Minuchehr, Zarrin; Marashi, Sayed-Amir

2017-02-01

Chameleon proteins are proteins which include sequences that can adopt α-helix-β-strand (HE-chameleon) or α-helix-coil (HC-chameleon) or β-strand-coil (CE-chameleon) structures to operate their crucial biological functions. In this study, using a network-based approach, we examined the chameleon proteins to give a better knowledge on these proteins. We focused on proteins with identical chameleon sequences with more than or equal to seven residues long in different PDB entries, which adopt HE-chameleon, HC-chameleon, and CE-chameleon structures in the same protein. One hundred and ninety-one human chameleon proteins were identified via our in-house program. Then, protein-protein interaction (PPI) networks, Gene ontology (GO) enrichment, disease network, and pathway enrichment analyses were performed for our derived data set. We discovered that there are chameleon sequences which reside in protein-protein interaction regions between two proteins critical for their dual function. Analysis of the PPI networks for chameleon proteins introduced five hub proteins, namely TP53, EGFR, HSP90AA1, PPARA, and HIF1A, which were presented in four PPI clusters. The outcomes demonstrate that the chameleon regions are in critical domains of these proteins and are important in the development and treatment of human cancers. The present report is the first network-based functional study of chameleon proteins using computational approaches and might provide a new perspective for understanding the mechanisms of diseases helping us in developing new medical therapies along with discovering new proteins with chameleon properties which are highly important in cancer.

Reinforce: An Ensemble Approach for Inferring PPI Network from AP-MS Data.

PubMed

Tian, Bo; Duan, Qiong; Zhao, Can; Teng, Ben; He, Zengyou

2017-05-17

Affinity Purification-Mass Spectrometry (AP-MS) is one of the most important technologies for constructing protein-protein interaction (PPI) networks. In this paper, we propose an ensemble method, Reinforce, for inferring PPI network from AP-MS data set. The new algorithm named Reinforce is based on rank aggregation and false discovery rate control. Under the null hypothesis that the interaction scores from different scoring methods are randomly generated, Reinforce follows three steps to integrate multiple ranking results from different algorithms or different data sets. The experimental results show that Reinforce can get more stable and accurate inference results than existing algorithms. The source codes of Reinforce and data sets used in the experiments are available at: https://sourceforge.net/projects/reinforce/.

Choice vs. voice? PPI policies and the re-positioning of the state in England and Wales.

PubMed

Hughes, David; Mullen, Caroline; Vincent-Jones, Peter

2009-09-01

CONTEXT AND THESIS: Changing patient and public involvement (PPI) policies in England and Wales are analysed against the background of wider National Health Service (NHS) reforms and regulatory frameworks. We argue that the growing divergence of health policies is accompanied by a re-positioning of the state vis-à-vis PPI, characterized by different mixes of centralized and decentralized regulatory instruments. Analysis of legislation and official documents, and interviews with policy makers. In England, continued hierarchical control is combined with the delegation of responsibilities for the oversight and organization of PPI to external institutions such as the Care Quality Commission and local involvement networks, in support of the government's policy agenda of increasing marketization. In Wales, which has rejected market reforms and economic regulation, decentralization is occurring through the use of mixed regulatory approaches and networks suited to the small-country governance model, and seeks to benefit from the close proximity of central and local actors by creating new forms of engagement while maintaining central steering of service planning. Whereas English PPI policies have emerged in tandem with a pluralistic supply-side market and combine new institutional arrangements for patient 'choice' with other forms of involvement, the Welsh policies focus on 'voice' within a largely publicly-delivered service. While the English reforms draw on theories of economic regulation and the experience of independent regulation in the utilities sector, the Welsh model of local service integration has been more influenced by reforms in local government. Such transfers of governance instruments from other public service sectors to the NHS may be problematic.

Integrative topological analysis of mass spectrometry data reveals molecular features with clinical relevance in esophageal squamous cell carcinoma

PubMed Central

Gao, She-Gan; Liu, Rui-Min; Zhao, Yun-Gang; Wang, Pei; Ward, Douglas G.; Wang, Guang-Chao; Guo, Xiang-Qian; Gu, Juan; Niu, Wan-Bin; Zhang, Tian; Martin, Ashley; Guo, Zhi-Peng; Feng, Xiao-Shan; Qi, Yi-Jun; Ma, Yuan-Fang

2016-01-01

Combining MS-based proteomic data with network and topological features of such network would identify more clinically relevant molecules and meaningfully expand the repertoire of proteins derived from MS analysis. The integrative topological indexes representing 95.96% information of seven individual topological measures of node proteins were calculated within a protein-protein interaction (PPI) network, built using 244 differentially expressed proteins (DEPs) identified by iTRAQ 2D-LC-MS/MS. Compared with DEPs, differentially expressed genes (DEGs) and comprehensive features (CFs), structurally dominant nodes (SDNs) based on integrative topological index distribution produced comparable classification performance in three different clinical settings using five independent gene expression data sets. The signature molecules of SDN-based classifier for distinction of early from late clinical TNM stages were enriched in biological traits of protein synthesis, intracellular localization and ribosome biogenesis, which suggests that ribosome biogenesis represents a promising therapeutic target for treating ESCC. In addition, ITGB1 expression selected exclusively by integrative topological measures correlated with clinical stages and prognosis, which was further validated with two independent cohorts of ESCC samples. Thus the integrative topological analysis of PPI networks proposed in this study provides an alternative approach to identify potential biomarkers and therapeutic targets from MS/MS data with functional insights in ESCC. PMID:26898710

Reconstruction of the experimentally supported human protein interactome: what can we learn?

PubMed

Klapa, Maria I; Tsafou, Kalliopi; Theodoridis, Evangelos; Tsakalidis, Athanasios; Moschonas, Nicholas K

2013-10-02

Understanding the topology and dynamics of the human protein-protein interaction (PPI) network will significantly contribute to biomedical research, therefore its systematic reconstruction is required. Several meta-databases integrate source PPI datasets, but the protein node sets of their networks vary depending on the PPI data combined. Due to this inherent heterogeneity, the way in which the human PPI network expands via multiple dataset integration has not been comprehensively analyzed. We aim at assembling the human interactome in a global structured way and exploring it to gain insights of biological relevance. First, we defined the UniProtKB manually reviewed human "complete" proteome as the reference protein-node set and then we mined five major source PPI datasets for direct PPIs exclusively between the reference proteins. We updated the protein and publication identifiers and normalized all PPIs to the UniProt identifier level. The reconstructed interactome covers approximately 60% of the human proteome and has a scale-free structure. No apparent differentiating gene functional classification characteristics were identified for the unrepresented proteins. The source dataset integration augments the network mainly in PPIs. Polyubiquitin emerged as the highest-degree node, but the inclusion of most of its identified PPIs may be reconsidered. The high number (>300) of connections of the subsequent fifteen proteins correlates well with their essential biological role. According to the power-law network structure, the unrepresented proteins should mainly have up to four connections with equally poorly-connected interactors. Reconstructing the human interactome based on the a priori definition of the protein nodes enabled us to identify the currently included part of the human "complete" proteome, and discuss the role of the proteins within the network topology with respect to their function. As the network expansion has to comply with the scale-free theory, we suggest that the core of the human interactome has essentially emerged. Thus, it could be employed in systems biology and biomedical research, despite the considerable number of currently unrepresented proteins. The latter are probably involved in specialized physiological conditions, justifying the scarcity of related PPI information, and their identification can assist in designing relevant functional experiments and targeted text mining algorithms.

Polyethylene-glycol-doped polypyrrole increases the rate performance of the cathode in lithium-sulfur batteries.

PubMed

Wu, Feng; Chen, Junzheng; Li, Li; Zhao, Teng; Liu, Zhen; Chen, Renjie

2013-08-01

Polypyrrole-polyethylene glycol (PPy/PEG)-modified sulfur/aligned carbon nanotubes (PPy/PEG-S/A-CNTs) were synthesized by using an in situ polymerization method. The ratio of PPy to PEG equaled 31.7:1 after polymerization, and the PEG served as a cation dopant in the polymerization and electrochemical reactions. Elemental analysis, FTIR, Raman spectroscopy, XRD, and electrochemical methods were performed to measure the physicochemical properties of the composite. Elemental analysis demonstrated that the sulfur, PPy, PEG, A-CNT, and chloride content in the synthesized material was 64.6%, 22.1%, 0.7%, 12.1%, and 0.5%, respectively. The thickness of the polymer shell was about 15-25 nm, and FTIR confirmed the successful PPy/PEG synthesis. The cathode exhibited a high initial specific capacity of 1355 mAh g(-1) , and a sulfur usage of 81.1%. The reversible capacity of 924 mAh g(-1) was obtained after 100 cycles, showing a remarkably improved cyclability compared to equivalent systems without PEG doping and without any coatings. PPy/PEG provided an effective electronically conductive network and a stable interface structure for the cathode. Rate performance of the PPy/PEG- S/A-CNT composite was more than double that of the unmodified S/A-CNTs. Remarkably, the battery could work at a very high current density of 8 A g(-1) and reached an initial capacity of 542 mAh g(-1) ; it also retained a capacity of 480 mAh g(-1) after 100 cycles. The addition of PEG as a dopant in the PPy shell contributed to this prominent rate improvement. Lithium ions and electrons were available everywhere on the surfaces of the particles, and thus could greatly improve the electrochemical reaction; PEG is a well-known solvent for lithium salts and a very good lithium-ion catcher. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ionically Cross-Linked Polymer Networks for the Multiple-Month Release of Small Molecules

PubMed Central

2016-01-01

Long-term (multiple-week or -month) release of small, water-soluble molecules from hydrogels remains a significant pharmaceutical challenge, which is typically overcome at the expense of more-complicated drug carrier designs. Such approaches are payload-specific and include covalent conjugation of drugs to base materials or incorporation of micro- and nanoparticles. As a simpler alternative, here we report a mild and simple method for achieving multiple-month release of small molecules from gel-like polymer networks. Densely cross-linked matrices were prepared through ionotropic gelation of poly(allylamine hydrochloride) (PAH) with either pyrophosphate (PPi) or tripolyphosphate (TPP), all of which are commonly available commercial molecules. The loading of model small molecules (Fast Green FCF and Rhodamine B dyes) within these polymer networks increases with the payload/network binding strength and with the PAH and payload concentrations used during encapsulation. Once loaded into the PAH/PPi and PAH/TPP ionic networks, only a few percent of the payload is released over multiple months. This extended release is achieved regardless of the payload/network binding strength and likely reflects the small hydrodynamic mesh size within the gel-like matrices. Furthermore, the PAH/TPP networks show promising in vitro cytocompatibility with model cells (human dermal fibroblasts), though slight cytotoxic effects were exhibited by the PAH/PPi networks. Taken together, the above findings suggest that PAH/PPi and (especially) PAH/TPP networks might be attractive materials for the multiple-month delivery of drugs and other active molecules (e.g., fragrances or disinfectants). PMID:26811936

Identification of differentially expressed genes associated with the enhancement of X-ray susceptibility by RITA in a hypopharyngeal squamous cell carcinoma cell line (FaDu).

PubMed

Luan, Jinwei; Li, Xianglan; Guo, Rutao; Liu, Shanshan; Luo, Hongyu; You, Qingshan

2016-06-01

Next generation sequencing and bio-informatic analyses were conducted to investigate the mechanism of reactivation of p53 and induction of tumor cell apoptosis (RITA)-enhancing X-ray susceptibility in FaDu cells. The cDNA was isolated from FaDu cells treated with 0 X-ray, 8 Gy X-ray, or 8 Gy X-ray + RITA. Then, cDNA libraries were created and sequenced using next generation sequencing, and each assay was repeated twice. Subsequently, differentially expressed genes (DEGs) were identified using Cuffdiff in Cufflinks and their functions were predicted by pathway enrichment analyses. Genes that were constantly up- or down-regulated in 8 Gy X-ray-treated FaDu cells and 8 Gy X-ray + RITA-treated FaDu cells were obtained as RITA genes. Afterward, the protein-protein interaction (PPI) relationships were obtained from the STRING database and a PPI network was constructed using Cytoscape. Furthermore, ClueGO was used for pathway enrichment analysis of genes in the PPI network. Total 2,040 and 297 DEGs were identified in FaDu cells treated with 8 Gy X-ray or 8 Gy X-ray + RITA, respectively. PARP3 and NEIL1 were enriched in base excision repair, and CDK1 was enriched in p53 signaling pathway. RFC2 and EZH2 were identified as RITA genes. In the PPI network, many interaction relationships were identified (e.g., RFC2-CDK1, EZH2-CDK1 and PARP3-EZH2). ClueGO analysis showed that RFC2 and EZH2 were related to cell cycle. RFC2, EZH2, CDK1, PARP3 and NEIL1 may be associated, and together enhance the susceptibility of FaDu cells treated with RITA to the deleterious effects of X-ray.

Screening the molecular targets of ovarian cancer based on bioinformatics analysis.

PubMed

Du, Lei; Qian, Xiaolei; Dai, Chenyang; Wang, Lihua; Huang, Ding; Wang, Shuying; Shen, Xiaowei

2015-01-01

Ovarian cancer (OC) is the most lethal gynecologic malignancy. This study aims to explore the molecular mechanisms of OC and identify potential molecular targets for OC treatment. Microarray gene expression data (GSE14407) including 12 normal ovarian surface epithelia samples and 12 OC epithelia samples were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) between 2 kinds of ovarian tissue were identified by using limma package in R language (|log2 fold change| gt;1 and false discovery rate [FDR] lt;0.05). Protein-protein interactions (PPIs) and known OC-related genes were screened from COXPRESdb and GenBank database, respectively. Furthermore, PPI network of top 10 upregulated DEGs and top 10 downregulated DEGs was constructed and visualized through Cytoscape software. Finally, for the genes involved in PPI network, functional enrichment analysis was performed by using DAVID (FDR lt;0.05). In total, 1136 DEGs were identified, including 544 downregulated and 592 upregulated DEGs. Then, PPI network was constructed, and DEGs CDKN2A, MUC1, OGN, ZIC1, SOX17, and TFAP2A interacted with known OC-related genes CDK4, EGFR/JUN, SRC, CLI1, CTNNB1, and TP53, respectively. Moreover, functions about oxygen transport and embryonic development were enriched by the genes involved in the network of downregulated DEGs. We propose that 4 DEGs (OGN, ZIC1, SOX17, and TFAP2A) and 2 functions (oxygen transport and embryonic development) might play a role in the development of OC. These 4 DEGs and known OC-related genes might serve as therapeutic targets for OC. Further studies are required to validate these predictions.

CellMap visualizes protein-protein interactions and subcellular localization

PubMed Central

Dallago, Christian; Goldberg, Tatyana; Andrade-Navarro, Miguel Angel; Alanis-Lobato, Gregorio; Rost, Burkhard

2018-01-01

Many tools visualize protein-protein interaction (PPI) networks. The tool introduced here, CellMap, adds one crucial novelty by visualizing PPI networks in the context of subcellular localization, i.e. the location in the cell or cellular component in which a PPI happens. Users can upload images of cells and define areas of interest against which PPIs for selected proteins are displayed (by default on a cartoon of a cell). Annotations of localization are provided by the user or through our in-house database. The visualizer and server are written in JavaScript, making CellMap easy to customize and to extend by researchers and developers. PMID:29497493

Weighted gene co‑expression network analysis in identification of key genes and networks for ischemic‑reperfusion remodeling myocardium.

PubMed

Guo, Nan; Zhang, Nan; Yan, Liqiu; Lian, Zheng; Wang, Jiawang; Lv, Fengfeng; Wang, Yunfei; Cao, Xufen

2018-06-14

Acute myocardial infarction induces ventricular remodeling, which is implicated in dilated heart and heart failure. The pathogenical mechanism of myocardium remodeling remains to be elucidated. The aim of the present study was to identify key genes and networks for myocardium remodeling following ischemia‑reperfusion (IR). First, the mRNA expression data from the National Center for Biotechnology Information database were downloaded to identify differences in mRNA expression of the IR heart at days 2 and 7. Then, weighted gene co‑expression network analysis, hierarchical clustering, protein‑protein interaction (PPI) network, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were used to identify key genes and networks for the heart remodeling process following IR. A total of 3,321 differentially expressed genes were identified during the heart remodeling process. A total of 6 modules were identified through gene co‑expression network analysis. GO and KEGG analysis results suggested that each module represented a different biological function and was associated with different pathways. Finally, hub genes of each module were identified by PPI network construction. The present study revealed that heart remodeling following IR is a complicated process, involving extracellular matrix organization, neural development, apoptosis and energy metabolism. The dysregulated genes, including SRC proto‑oncogene, non‑receptor tyrosine kinase, discs large MAGUK scaffold protein 1, ATP citrate lyase, RAN, member RAS oncogene family, tumor protein p53, and polo like kinase 2, may be essential for heart remodeling following IR and may be used as potential targets for the inhibition of heart remodeling following acute myocardial infarction.

The autophagy interaction network of the aging model Podospora anserina.

PubMed

Philipp, Oliver; Hamann, Andrea; Osiewacz, Heinz D; Koch, Ina

2017-03-27

Autophagy is a conserved molecular pathway involved in the degradation and recycling of cellular components. It is active either as response to starvation or molecular damage. Evidence is emerging that autophagy plays a key role in the degradation of damaged cellular components and thereby affects aging and lifespan control. In earlier studies, it was found that autophagy in the aging model Podospora anserina acts as a longevity assurance mechanism. However, only little is known about the individual components controlling autophagy in this aging model. Here, we report a biochemical and bioinformatics study to detect the protein-protein interaction (PPI) network of P. anserina combining experimental and theoretical methods. We constructed the PPI network of autophagy in P. anserina based on the corresponding networks of yeast and human. We integrated PaATG8 interaction partners identified in an own yeast two-hybrid analysis using ATG8 of P. anserina as bait. Additionally, we included age-dependent transcriptome data. The resulting network consists of 89 proteins involved in 186 interactions. We applied bioinformatics approaches to analyze the network topology and to prove that the network is not random, but exhibits biologically meaningful properties. We identified hub proteins which play an essential role in the network as well as seven putative sub-pathways, and interactions which are likely to be evolutionary conserved amongst species. We confirmed that autophagy-associated genes are significantly often up-regulated and co-expressed during aging of P. anserina. With the present study, we provide a comprehensive biological network of the autophagy pathway in P. anserina comprising PPI and gene expression data. It is based on computational prediction as well as experimental data. We identified sub-pathways, important hub proteins, and evolutionary conserved interactions. The network clearly illustrates the relation of autophagy to aging processes and enables further specific studies to understand autophagy and aging in P. anserina as well as in other systems.

Choice vs. voice? PPI policies and the re‐positioning of the state in England and Wales

PubMed Central

Hughes, David; Mullen, Caroline; Vincent‐Jones, Peter

2009-01-01

Abstract Context and Thesis  Changing patient and public involvement (PPI) policies in England and Wales are analysed against the background of wider National Health Service (NHS) reforms and regulatory frameworks. We argue that the growing divergence of health policies is accompanied by a re‐positioning of the state vis‐à‐vis PPI, characterized by different mixes of centralized and decentralized regulatory instruments. Method  Analysis of legislation and official documents, and interviews with policy makers. Findings  In England, continued hierarchical control is combined with the delegation of responsibilities for the oversight and organization of PPI to external institutions such as the Care Quality Commission and local involvement networks, in support of the government’s policy agenda of increasing marketization. In Wales, which has rejected market reforms and economic regulation, decentralization is occurring through the use of mixed regulatory approaches and networks suited to the small‐country governance model, and seeks to benefit from the close proximity of central and local actors by creating new forms of engagement while maintaining central steering of service planning. Whereas English PPI policies have emerged in tandem with a pluralistic supply‐side market and combine new institutional arrangements for patient ‘choice’ with other forms of involvement, the Welsh policies focus on ‘voice’ within a largely publicly‐delivered service. Discussion  While the English reforms draw on theories of economic regulation and the experience of independent regulation in the utilities sector, the Welsh model of local service integration has been more influenced by reforms in local government. Such transfers of governance instruments from other public service sectors to the NHS may be problematic. PMID:19754688

Changes in functional connectivity within the fronto-temporal brain network induced by regular and irregular Russian verb production

PubMed Central

Kireev, Maxim; Slioussar, Natalia; Korotkov, Alexander D.; Chernigovskaya, Tatiana V.; Medvedev, Svyatoslav V.

2015-01-01

Functional connectivity between brain areas involved in the processing of complex language forms remains largely unexplored. Contributing to the debate about neural mechanisms underlying regular and irregular inflectional morphology processing in the mental lexicon, we conducted an fMRI experiment in which participants generated forms from different types of Russian verbs and nouns as well as from nonce stimuli. The data were subjected to a whole brain voxel-wise analysis of context dependent changes in functional connectivity [the so-called psychophysiological interaction (PPI) analysis]. Unlike previously reported subtractive results that reveal functional segregation between brain areas, PPI provides complementary information showing how these areas are functionally integrated in a particular task. To date, PPI evidence on inflectional morphology has been scarce and only available for inflectionally impoverished English verbs in a same-different judgment task. Using PPI here in conjunction with a production task in an inflectionally rich language, we found that functional connectivity between the left inferior frontal gyrus (LIFG) and bilateral superior temporal gyri (STG) was significantly greater for regular real verbs than for irregular ones. Furthermore, we observed a significant positive covariance between the number of mistakes in irregular real verb trials and the increase in functional connectivity between the LIFG and the right anterior cingulate cortex in these trails, as compared to regular ones. Our results therefore allow for dissociation between regularity and processing difficulty effects. These results, on the one hand, shed new light on the functional interplay within the LIFG-bilateral STG language-related network and, on the other hand, call for partial reconsideration of some of the previous findings while stressing the role of functional temporo-frontal connectivity in complex morphological processes. PMID:25741262

Flexible modulation of network connectivity related to cognition in Alzheimer's disease.

PubMed

McLaren, Donald G; Sperling, Reisa A; Atri, Alireza

2014-10-15

Functional neuroimaging tools, such as fMRI methods, may elucidate the neural correlates of clinical, behavioral, and cognitive performance. Most functional imaging studies focus on regional task-related activity or resting state connectivity rather than how changes in functional connectivity across conditions and tasks are related to cognitive and behavioral performance. To investigate the promise of characterizing context-dependent connectivity-behavior relationships, this study applies the method of generalized psychophysiological interactions (gPPI) to assess the patterns of associative-memory-related fMRI hippocampal functional connectivity in Alzheimer's disease (AD) associated with performance on memory and other cognitively demanding neuropsychological tests and clinical measures. Twenty-four subjects with mild AD dementia (ages 54-82, nine females) participated in a face-name paired-associate encoding memory study. Generalized PPI analysis was used to estimate the connectivity between the hippocampus and the whole brain during encoding. The difference in hippocampal-whole brain connectivity between encoding novel and encoding repeated face-name pairs was used in multiple-regression analyses as an independent predictor for 10 behavioral, neuropsychological and clinical tests. The analysis revealed connectivity-behavior relationships that were distributed, dynamically overlapping, and task-specific within and across intrinsic networks; hippocampal-whole brain connectivity-behavior relationships were not isolated to single networks, but spanned multiple brain networks. Importantly, these spatially distributed performance patterns were unique for each measure. In general, out-of-network behavioral associations with encoding novel greater than repeated face-name pairs hippocampal-connectivity were observed in the default-mode network, while correlations with encoding repeated greater than novel face-name pairs hippocampal-connectivity were observed in the executive control network (p<0.05, cluster corrected). Psychophysiological interactions revealed significantly more extensive and robust associations between paired-associate encoding task-dependent hippocampal-whole brain connectivity and performance on memory and behavioral/clinical measures than previously revealed by standard activity-behavior analysis. Compared to resting state and task-activation methods, gPPI analyses may be more sensitive to reveal additional complementary information regarding subtle within- and between-network relations. The patterns of robust correlations between hippocampal-whole brain connectivity and behavioral measures identified here suggest that there are 'coordinated states' in the brain; that the dynamic range of these states is related to behavior and cognition; and that these states can be observed and quantified, even in individuals with mild AD. Copyright © 2014 Elsevier Inc. All rights reserved.

Recent coselection in human populations revealed by protein-protein interaction network.

PubMed

Qian, Wei; Zhou, Hang; Tang, Kun

2014-12-21

Genome-wide scans for signals of natural selection in human populations have identified a large number of candidate loci that underlie local adaptations. This is surprising given the relatively short evolutionary time since the divergence of the human population. One hypothesis that has not been formally examined is whether and how the recent human evolution may have been shaped by coselection in the context of complex molecular interactome. In this study, genome-wide signals of selection were scanned in East Asians, Europeans, and Africans using 1000 Genome data, and subsequently mapped onto the protein-protein interaction (PPI) network. We found that the candidate genes of recent positive selection localized significantly closer to each other on the PPI network than expected, revealing substantial clustering of selected genes. Furthermore, gene pairs of shorter PPI network distances showed higher similarities of their recent evolutionary paths than those further apart. Last, subnetworks enriched with recent coselection signals were identified, which are substantially overrepresented in biological pathways related to signal transduction, neurogenesis, and immune function. These results provide the first genome-wide evidence for association of recent selection signals with the PPI network, shedding light on the potential mechanisms of recent coselection in the human genome. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Proton pump inhibitors are associated with increased risk of development of chronic kidney disease.

PubMed

Arora, Pradeep; Gupta, Anu; Golzy, Mojgan; Patel, Nilang; Carter, Randolph L; Jalal, Kabir; Lohr, James W

2016-08-03

Acute interstitial nephritis secondary to proton pump inhibitors (PPIs) frequently goes undiagnosed due to its subacute clinical presentation, which may later present as chronic kidney disease (CKD). We investigated the association of PPI use with the development of CKD and death. Two separate retrospective case-control study designs were employed with a prospective logistic regression analysis of data to evaluate the association of development of CKD and death with PPI use. The population included 99,269 patients who were seen in primary care VISN2 clinics from 4/2001 until 4/2008. For evaluation of the CKD outcome, 22,807 with preexisting CKD at the first observation in Veterans Affairs Health Care Upstate New York (VISN2) network data system were excluded. Data obtained included use of PPI (Yes/No), demographics, laboratory data, pre-PPI comorbidity variables. A total of 19,311/76,462 patients developed CKD. Of those who developed CKD 24.4 % were on PPI. Patients receiving PPI were less likely to have vascular disease, COPD, cancer and diabetes. Of the total of 99,269 patients analyzed for mortality outcome, 11,758 died. A prospective logistic analysis of case-control data showed higher odds for development of CKD (OR 1.10 95 % CI 1.05-1.16) and mortality (OR 1.76, 95 % CI 1.67-1.84) among patients taking PPIs versus those not on PPIs. Use of proton pump inhibitors is associated with increased risk of development of CKD and death. With the large number of patients being treated with proton pump inhibitors, healthcare providers need to be better educated about the potential side effects of these medications.

Microarray and network-based identification of functional modules and pathways of active tuberculosis.

PubMed

Bian, Zhong-Rui; Yin, Juan; Sun, Wen; Lin, Dian-Jie

2017-04-01

Diagnose of active tuberculosis (TB) is challenging and treatment response is also difficult to efficiently monitor. The aim of this study was to use an integrated analysis of microarray and network-based method to the samples from publically available datasets to obtain a diagnostic module set and pathways in active TB. Towards this goal, background protein-protein interactions (PPI) network was generated based on global PPI information and gene expression data, following by identification of differential expression network (DEN) from the background PPI network. Then, ego genes were extracted according to the degree features in DEN. Next, module collection was conducted by ego gene expansion based on EgoNet algorithm. After that, differential expression of modules between active TB and controls was evaluated using random permutation test. Finally, biological significance of differential modules was detected by pathways enrichment analysis based on Reactome database, and Fisher's exact test was implemented to extract differential pathways for active TB. Totally, 47 ego genes and 47 candidate modules were identified from the DEN. By setting the cutoff-criteria of gene size >5 and classification accuracy ≥0.9, 7 ego modules (Module 4, Module 7, Module 9, Module 19, Module 25, Module 38 and Module 43) were extracted, and all of them had the statistical significance between active TB and controls. Then, Fisher's exact test was conducted to capture differential pathways for active TB. Interestingly, genes in Module 4, Module 25, Module 38, and Module 43 were enriched in the same pathway, formation of a pool of free 40S subunits. Significant pathway for Module 7 and Module 9 was eukaryotic translation termination, and for Module 19 was nonsense mediated decay enhanced by the exon junction complex (EJC). Accordingly, differential modules and pathways might be potential biomarkers for treating active TB, and provide valuable clues for better understanding of molecular mechanism of active TB. Copyright © 2017 Elsevier Ltd. All rights reserved.

Reconstruction of the experimentally supported human protein interactome: what can we learn?

PubMed Central

2013-01-01

Background Understanding the topology and dynamics of the human protein-protein interaction (PPI) network will significantly contribute to biomedical research, therefore its systematic reconstruction is required. Several meta-databases integrate source PPI datasets, but the protein node sets of their networks vary depending on the PPI data combined. Due to this inherent heterogeneity, the way in which the human PPI network expands via multiple dataset integration has not been comprehensively analyzed. We aim at assembling the human interactome in a global structured way and exploring it to gain insights of biological relevance. Results First, we defined the UniProtKB manually reviewed human “complete” proteome as the reference protein-node set and then we mined five major source PPI datasets for direct PPIs exclusively between the reference proteins. We updated the protein and publication identifiers and normalized all PPIs to the UniProt identifier level. The reconstructed interactome covers approximately 60% of the human proteome and has a scale-free structure. No apparent differentiating gene functional classification characteristics were identified for the unrepresented proteins. The source dataset integration augments the network mainly in PPIs. Polyubiquitin emerged as the highest-degree node, but the inclusion of most of its identified PPIs may be reconsidered. The high number (>300) of connections of the subsequent fifteen proteins correlates well with their essential biological role. According to the power-law network structure, the unrepresented proteins should mainly have up to four connections with equally poorly-connected interactors. Conclusions Reconstructing the human interactome based on the a priori definition of the protein nodes enabled us to identify the currently included part of the human “complete” proteome, and discuss the role of the proteins within the network topology with respect to their function. As the network expansion has to comply with the scale-free theory, we suggest that the core of the human interactome has essentially emerged. Thus, it could be employed in systems biology and biomedical research, despite the considerable number of currently unrepresented proteins. The latter are probably involved in specialized physiological conditions, justifying the scarcity of related PPI information, and their identification can assist in designing relevant functional experiments and targeted text mining algorithms. PMID:24088582

Identifying Hierarchical and Overlapping Protein Complexes Based on Essential Protein-Protein Interactions and “Seed-Expanding” Method

PubMed Central

Ren, Jun; Zhou, Wei; Wang, Jianxin

2014-01-01

Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks. Meanwhile, the large size of PPI network wants complex detection methods have low time complexity. Up to now, few methods can identify overlapping and hierarchical protein complexes in a PPI network quickly. In this paper, a novel method, called MCSE, is proposed based on λ-module and “seed-expanding.” First, it chooses seeds as essential PPIs or edges with high edge clustering values. Then, it identifies protein complexes by expanding each seed to a λ-module. MCSE is suitable for large PPI networks because of its low time complexity. MCSE can identify overlapping protein complexes naturally because a protein can be visited by different seeds. MCSE uses the parameter λ_th to control the range of seed expanding and can detect a hierarchical organization of protein complexes by tuning the value of λ_th. Experimental results of S. cerevisiae show that this hierarchical organization is similar to that of known complexes in MIPS database. The experimental results also show that MCSE outperforms other previous competing algorithms, such as CPM, CMC, Core-Attachment, Dpclus, HC-PIN, MCL, and NFC, in terms of the functional enrichment and matching with known protein complexes. PMID:25143945

Prognostic factors and genes associated with endometrial cancer based on gene expression profiling by bioinformatics analysis.

PubMed

Zhang, Ying; Zhang, Wei; Li, Xinglan; Li, Dapeng; Zhang, Xiaoling; Yin, Yajie; Deng, Xiangyun; Sheng, Xiugui

2016-06-01

Endometrial cancer (EC) is the most prevalent malignancy worldwide. Although several efforts had been made to explore the molecular mechanism responsible for EC progression, it is still not fully understood. To evaluate the clinical characteristics and prognostic factors of patients with EC, and further to search for novel genes associated with EC progression. We recruited 328 patients with EC and analyzed prognostic factors using Cox proportional hazard regression model. Further, a gene expression profile of EC was used to identify the differentially expressed genes (DEGs) between normal samples and tumor samples. Subsequently, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis ( http://www.genome.jp/kegg/ ) for DEGs were performed, and then protein-protein interaction (PPI) network of DEGs as well as the subnetwork of PPI were constructed with plug-in, MCODE by mapping DEGs into the Search Tool for the Retrieval of Interacting Genes database. Our results showed that body mass index (BMI), hypertension, myometrial invasion, pathological type, and Glut4 positive expression were prognostic factors in EC (P < 0.05). Bioinformatics analysis showed that upregulated DEGs were associated with cell cycle, and downregulated DEGs were related to MAPK pathway. Meanwhile, PPI network analysis revealed that upregulated CDK1 and CCNA2 as well as downregulated JUN and FOS were listed in top two nodes with high degrees. Patients with EC should be given more focused attentions in respect of pathological type, BMI, hypertension, and Glut4-positive expression. In addition, CDK1, CCNA2, JUN, and FOS might play important roles in EC development.

The Semantic Network at Work and Rest: Differential Connectivity of Anterior Temporal Lobe Subregions.

PubMed

Jackson, Rebecca L; Hoffman, Paul; Pobric, Gorana; Lambon Ralph, Matthew A

2016-02-03

The anterior temporal lobe (ATL) makes a critical contribution to semantic cognition. However, the functional connectivity of the ATL and the functional network underlying semantic cognition has not been elucidated. In addition, subregions of the ATL have distinct functional properties and thus the potential differential connectivity between these subregions requires investigation. We explored these aims using both resting-state and active semantic task data in humans in combination with a dual-echo gradient echo planar imaging (EPI) paradigm designed to ensure signal throughout the ATL. In the resting-state analysis, the ventral ATL (vATL) and anterior middle temporal gyrus (MTG) were shown to connect to areas responsible for multimodal semantic cognition, including bilateral ATL, inferior frontal gyrus, medial prefrontal cortex, angular gyrus, posterior MTG, and medial temporal lobes. In contrast, the anterior superior temporal gyrus (STG)/superior temporal sulcus was connected to a distinct set of auditory and language-related areas, including bilateral STG, precentral and postcentral gyri, supplementary motor area, supramarginal gyrus, posterior temporal cortex, and inferior and middle frontal gyri. Complementary analyses of functional connectivity during an active semantic task were performed using a psychophysiological interaction (PPI) analysis. The PPI analysis highlighted the same semantic regions suggesting a core semantic network active during rest and task states. This supports the necessity for semantic cognition in internal processes occurring during rest. The PPI analysis showed additional connectivity of the vATL to regions of occipital and frontal cortex. These areas strongly overlap with regions found to be sensitive to executively demanding, controlled semantic processing. Previous studies have shown that semantic cognition depends on subregions of the anterior temporal lobe (ATL). However, the network of regions functionally connected to these subregions has not been demarcated. Here, we show that these ventrolateral anterior temporal subregions form part of a network responsible for semantic processing during both rest and an explicit semantic task. This demonstrates the existence of a core functional network responsible for multimodal semantic cognition regardless of state. Distinct connectivity is identified in the superior ATL, which is connected to auditory and language areas. Understanding the functional connectivity of semantic cognition allows greater understanding of how this complex process may be performed and the role of distinct subregions of the anterior temporal cortex. Copyright © 2016 Jackson et al.

The Semantic Network at Work and Rest: Differential Connectivity of Anterior Temporal Lobe Subregions

PubMed Central

Jackson, Rebecca L.; Hoffman, Paul; Pobric, Gorana

2016-01-01

The anterior temporal lobe (ATL) makes a critical contribution to semantic cognition. However, the functional connectivity of the ATL and the functional network underlying semantic cognition has not been elucidated. In addition, subregions of the ATL have distinct functional properties and thus the potential differential connectivity between these subregions requires investigation. We explored these aims using both resting-state and active semantic task data in humans in combination with a dual-echo gradient echo planar imaging (EPI) paradigm designed to ensure signal throughout the ATL. In the resting-state analysis, the ventral ATL (vATL) and anterior middle temporal gyrus (MTG) were shown to connect to areas responsible for multimodal semantic cognition, including bilateral ATL, inferior frontal gyrus, medial prefrontal cortex, angular gyrus, posterior MTG, and medial temporal lobes. In contrast, the anterior superior temporal gyrus (STG)/superior temporal sulcus was connected to a distinct set of auditory and language-related areas, including bilateral STG, precentral and postcentral gyri, supplementary motor area, supramarginal gyrus, posterior temporal cortex, and inferior and middle frontal gyri. Complementary analyses of functional connectivity during an active semantic task were performed using a psychophysiological interaction (PPI) analysis. The PPI analysis highlighted the same semantic regions suggesting a core semantic network active during rest and task states. This supports the necessity for semantic cognition in internal processes occurring during rest. The PPI analysis showed additional connectivity of the vATL to regions of occipital and frontal cortex. These areas strongly overlap with regions found to be sensitive to executively demanding, controlled semantic processing. SIGNIFICANCE STATEMENT Previous studies have shown that semantic cognition depends on subregions of the anterior temporal lobe (ATL). However, the network of regions functionally connected to these subregions has not been demarcated. Here, we show that these ventrolateral anterior temporal subregions form part of a network responsible for semantic processing during both rest and an explicit semantic task. This demonstrates the existence of a core functional network responsible for multimodal semantic cognition regardless of state. Distinct connectivity is identified in the superior ATL, which is connected to auditory and language areas. Understanding the functional connectivity of semantic cognition allows greater understanding of how this complex process may be performed and the role of distinct subregions of the anterior temporal cortex. PMID:26843633

Identifying protein complexes based on brainstorming strategy.

PubMed

Shen, Xianjun; Zhou, Jin; Yi, Li; Hu, Xiaohua; He, Tingting; Yang, Jincai

2016-11-01

Protein complexes comprising of interacting proteins in protein-protein interaction network (PPI network) play a central role in driving biological processes within cells. Recently, more and more swarm intelligence based algorithms to detect protein complexes have been emerging, which have become the research hotspot in proteomics field. In this paper, we propose a novel algorithm for identifying protein complexes based on brainstorming strategy (IPC-BSS), which is integrated into the main idea of swarm intelligence optimization and the improved K-means algorithm. Distance between the nodes in PPI network is defined by combining the network topology and gene ontology (GO) information. Inspired by human brainstorming process, IPC-BSS algorithm firstly selects the clustering center nodes, and then they are separately consolidated with the other nodes with short distance to form initial clusters. Finally, we put forward two ways of updating the initial clusters to search optimal results. Experimental results show that our IPC-BSS algorithm outperforms the other classic algorithms on yeast and human PPI networks, and it obtains many predicted protein complexes with biological significance. Copyright © 2016 Elsevier Inc. All rights reserved.

Characterizing biomarkers in osteosarcoma metastasis based on an ego-network.

PubMed

Liu, Zhen; Song, Yan

2017-06-01

To characterize biomarkers that underlie osteosarcoma (OS) metastasis based on an ego-network. From the microarray data, we obtained 13,326 genes. By combining PPI data and microarray data, 10,520 shared genes were found and constructed into ego-networks. 17 significant ego-networks were identified with p < 0.05. In the pathway enrichment analysis, seven ego-networks were identified with the most significant pathway. These significant ego-modules were potential biomarkers that reveal the potential mechanisms in OS metastasis, which may contribute to understanding cancer prognoses and providing new perspectives in the treatment of cancer.

The role of HiPPI switches in mass storage systems: A five year prospective

NASA Technical Reports Server (NTRS)

Gilbert, T. A.

1992-01-01

New standards are evolving which provide the foundation for novel multi-gigabit per second data communication structures. The lowest layer protocols are so generalized that they encourage a wide range of application. Specifically, the ANSI High Performance Parallel Interface (HiPPI) is being applied to computer peripheral attachment as well as general data communication networks. This paper introduces the HiPPI standards suite and technology products which incorporate the standards. The use of simple HiPPI crosspoint switches to build potentially complex extended 'fabrics' is discussed in detail. Several near term applications of the HiPPI technology are briefly described with additional attention to storage systems. Finally, some related standards are mentioned which may further expand the concepts above.

The role of HiPPI switches in mass storage systems: A five year prospective

NASA Technical Reports Server (NTRS)

Gilbert, T. A.

1991-01-01

New standards are evolving which provide the foundation for multi-gigabit per second data communication structures. The lowest layer protocols are so generalized that they encourage a wide range of application. Specifically, the ANSI High Performance Parallel Interface (HiPPI) is being applied to computer peripheral attachment as well as general data communication networks. The HiPPI Standards suite and technology products which incorporate the standards are introduced. The use of simple HiPPI crosspoint switches to build potentially complex extended 'fabrics' is discussed in detail. Several near term applications of the HiPPI technology are briefly described with additional attention to storage systems. Finally, some related standards are mentioned which may further expand the concepts above.

Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis

NASA Astrophysics Data System (ADS)

Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen

2015-03-01

The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

MCL-CAw: a refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure

PubMed Central

2010-01-01

Background The reconstruction of protein complexes from the physical interactome of organisms serves as a building block towards understanding the higher level organization of the cell. Over the past few years, several independent high-throughput experiments have helped to catalogue enormous amount of physical protein interaction data from organisms such as yeast. However, these individual datasets show lack of correlation with each other and also contain substantial number of false positives (noise). Over these years, several affinity scoring schemes have also been devised to improve the qualities of these datasets. Therefore, the challenge now is to detect meaningful as well as novel complexes from protein interaction (PPI) networks derived by combining datasets from multiple sources and by making use of these affinity scoring schemes. In the attempt towards tackling this challenge, the Markov Clustering algorithm (MCL) has proved to be a popular and reasonably successful method, mainly due to its scalability, robustness, and ability to work on scored (weighted) networks. However, MCL produces many noisy clusters, which either do not match known complexes or have additional proteins that reduce the accuracies of correctly predicted complexes. Results Inspired by recent experimental observations by Gavin and colleagues on the modularity structure in yeast complexes and the distinctive properties of "core" and "attachment" proteins, we develop a core-attachment based refinement method coupled to MCL for reconstruction of yeast complexes from scored (weighted) PPI networks. We combine physical interactions from two recent "pull-down" experiments to generate an unscored PPI network. We then score this network using available affinity scoring schemes to generate multiple scored PPI networks. The evaluation of our method (called MCL-CAw) on these networks shows that: (i) MCL-CAw derives larger number of yeast complexes and with better accuracies than MCL, particularly in the presence of natural noise; (ii) Affinity scoring can effectively reduce the impact of noise on MCL-CAw and thereby improve the quality (precision and recall) of its predicted complexes; (iii) MCL-CAw responds well to most available scoring schemes. We discuss several instances where MCL-CAw was successful in deriving meaningful complexes, and where it missed a few proteins or whole complexes due to affinity scoring of the networks. We compare MCL-CAw with several recent complex detection algorithms on unscored and scored networks, and assess the relative performance of the algorithms on these networks. Further, we study the impact of augmenting physical datasets with computationally inferred interactions for complex detection. Finally, we analyse the essentiality of proteins within predicted complexes to understand a possible correlation between protein essentiality and their ability to form complexes. Conclusions We demonstrate that core-attachment based refinement in MCL-CAw improves the predictions of MCL on yeast PPI networks. We show that affinity scoring improves the performance of MCL-CAw. PMID:20939868

ModuleRole: a tool for modulization, role determination and visualization in protein-protein interaction networks.

PubMed

Li, Guipeng; Li, Ming; Zhang, Yiwei; Wang, Dong; Li, Rong; Guimerà, Roger; Gao, Juntao Tony; Zhang, Michael Q

2014-01-01

Rapidly increasing amounts of (physical and genetic) protein-protein interaction (PPI) data are produced by various high-throughput techniques, and interpretation of these data remains a major challenge. In order to gain insight into the organization and structure of the resultant large complex networks formed by interacting molecules, using simulated annealing, a method based on the node connectivity, we developed ModuleRole, a user-friendly web server tool which finds modules in PPI network and defines the roles for every node, and produces files for visualization in Cytoscape and Pajek. For given proteins, it analyzes the PPI network from BioGRID database, finds and visualizes the modules these proteins form, and then defines the role every node plays in this network, based on two topological parameters Participation Coefficient and Z-score. This is the first program which provides interactive and very friendly interface for biologists to find and visualize modules and roles of proteins in PPI network. It can be tested online at the website http://www.bioinfo.org/modulerole/index.php, which is free and open to all users and there is no login requirement, with demo data provided by "User Guide" in the menu Help. Non-server application of this program is considered for high-throughput data with more than 200 nodes or user's own interaction datasets. Users are able to bookmark the web link to the result page and access at a later time. As an interactive and highly customizable application, ModuleRole requires no expert knowledge in graph theory on the user side and can be used in both Linux and Windows system, thus a very useful tool for biologist to analyze and visualize PPI networks from databases such as BioGRID. ModuleRole is implemented in Java and C, and is freely available at http://www.bioinfo.org/modulerole/index.php. Supplementary information (user guide, demo data) is also available at this website. API for ModuleRole used for this program can be obtained upon request.

Construction and analysis of protein-protein interaction networks based on proteomics data of prostate cancer

PubMed Central

CHEN, CHEN; SHEN, HONG; ZHANG, LI-GUO; LIU, JIAN; CAO, XIAO-GE; YAO, AN-LIANG; KANG, SHAO-SAN; GAO, WEI-XING; HAN, HUI; CAO, FENG-HONG; LI, ZHI-GUO

2016-01-01

Currently, using human prostate cancer (PCa) tissue samples to conduct proteomics research has generated a large amount of data; however, only a very small amount has been thoroughly investigated. In this study, we manually carried out the mining of the full text of proteomics literature that involved comparisons between PCa and normal or benign tissue and identified 41 differentially expressed proteins verified or reported more than 2 times from different research studies. We regarded these proteins as seed proteins to construct a protein-protein interaction (PPI) network. The extended network included one giant network, which consisted of 1,264 nodes connected via 1,744 edges, and 3 small separate components. The backbone network was then constructed, which was derived from key nodes and the subnetwork consisting of the shortest path between seed proteins. Topological analyses of these networks were conducted to identify proteins essential for the genesis of PCa. Solute carrier family 2 (facilitated glucose transporter), member 4 (SLC2A4) had the highest closeness centrality located in the center of each network, and the highest betweenness centrality and largest degree in the backbone network. Tubulin, beta 2C (TUBB2C) had the largest degree in the giant network and subnetwork. In addition, using module analysis of the whole PPI network, we obtained a densely connected region. Functional annotation indicated that the Ras protein signal transduction biological process, mitogen-activated protein kinase (MAPK), neurotrophin and the gonadotropin-releasing hormone (GnRH) signaling pathway may play an important role in the genesis and development of PCa. Further investigation of the SLC2A4, TUBB2C proteins, and these biological processes and pathways may therefore provide a potential target for the diagnosis and treatment of PCa. PMID:27121963

Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein⁻Protein Interaction Network.

PubMed

Cao, Buwen; Deng, Shuguang; Qin, Hua; Ding, Pingjian; Chen, Shaopeng; Li, Guanghui

2018-06-15

High-throughput technology has generated large-scale protein interaction data, which is crucial in our understanding of biological organisms. Many complex identification algorithms have been developed to determine protein complexes. However, these methods are only suitable for dense protein interaction networks, because their capabilities decrease rapidly when applied to sparse protein⁻protein interaction (PPI) networks. In this study, based on penalized matrix decomposition ( PMD ), a novel method of penalized matrix decomposition for the identification of protein complexes (i.e., PMD pc ) was developed to detect protein complexes in the human protein interaction network. This method mainly consists of three steps. First, the adjacent matrix of the protein interaction network is normalized. Second, the normalized matrix is decomposed into three factor matrices. The PMD pc method can detect protein complexes in sparse PPI networks by imposing appropriate constraints on factor matrices. Finally, the results of our method are compared with those of other methods in human PPI network. Experimental results show that our method can not only outperform classical algorithms, such as CFinder, ClusterONE, RRW, HC-PIN, and PCE-FR, but can also achieve an ideal overall performance in terms of a composite score consisting of F-measure, accuracy (ACC), and the maximum matching ratio (MMR).

How Structure Defines Affinity in Protein-Protein Interactions

PubMed Central

Erijman, Ariel; Rosenthal, Eran; Shifman, Julia M.

2014-01-01

Protein-protein interactions (PPI) in nature are conveyed by a multitude of binding modes involving various surfaces, secondary structure elements and intermolecular interactions. This diversity results in PPI binding affinities that span more than nine orders of magnitude. Several early studies attempted to correlate PPI binding affinities to various structure-derived features with limited success. The growing number of high-resolution structures, the appearance of more precise methods for measuring binding affinities and the development of new computational algorithms enable more thorough investigations in this direction. Here, we use a large dataset of PPI structures with the documented binding affinities to calculate a number of structure-based features that could potentially define binding energetics. We explore how well each calculated biophysical feature alone correlates with binding affinity and determine the features that could be used to distinguish between high-, medium- and low- affinity PPIs. Furthermore, we test how various combinations of features could be applied to predict binding affinity and observe a slow improvement in correlation as more features are incorporated into the equation. In addition, we observe a considerable improvement in predictions if we exclude from our analysis low-resolution and NMR structures, revealing the importance of capturing exact intermolecular interactions in our calculations. Our analysis should facilitate prediction of new interactions on the genome scale, better characterization of signaling networks and design of novel binding partners for various target proteins. PMID:25329579

A novel method to identify hub pathways of rheumatoid arthritis based on differential pathway networks.

PubMed

Wei, Shi-Tong; Sun, Yong-Hua; Zong, Shi-Hua

2017-09-01

The aim of the current study was to identify hub pathways of rheumatoid arthritis (RA) using a novel method based on differential pathway network (DPN) analysis. The present study proposed a DPN where protein‑protein interaction (PPI) network was integrated with pathway‑pathway interactions. Pathway data was obtained from background PPI network and the Reactome pathway database. Subsequently, pathway interactions were extracted from the pathway data by building randomized gene‑gene interactions and a weight value was assigned to each pathway interaction using Spearman correlation coefficient (SCC) to identify differential pathway interactions. Differential pathway interactions were visualized using Cytoscape to construct a DPN. Topological analysis was conducted to identify hub pathways that possessed the top 5% degree distribution of DPN. Modules of DPN were mined according to ClusterONE. A total of 855 pathways were selected to build pathway interactions. By filtrating pathway interactions of weight values >0.7, a DPN with 312 nodes and 791 edges was obtained. Topological degree analysis revealed 15 hub pathways, such as heparan sulfate/heparin‑glycosaminoglycan (HS‑GAG) degradation, HS‑GAG metabolism and keratan sulfate degradation for RA based on DPN. Furthermore, hub pathways were also important in modules, which validated the significance of hub pathways. In conclusion, the proposed method is a computationally efficient way to identify hub pathways of RA, which identified 15 hub pathways that may be potential biomarkers and provide insight to future investigation and treatment of RA.

Identification of key candidate genes and pathways in hepatitis B virus-associated acute liver failure by bioinformatical analysis

PubMed Central

Lin, Huapeng; Zhang, Qian; Li, Xiaocheng; Wu, Yushen; Liu, Ye; Hu, Yingchun

2018-01-01

Abstract Hepatitis B virus-associated acute liver failure (HBV-ALF) is a rare but life-threatening syndrome that carried a high morbidity and mortality. Our study aimed to explore the possible molecular mechanisms of HBV-ALF by means of bioinformatics analysis. In this study, genes expression microarray datasets of HBV-ALF from Gene Expression Omnibus were collected, and then we identified differentially expressed genes (DEGs) by the limma package in R. After functional enrichment analysis, we constructed the protein–protein interaction (PPI) network by the Search Tool for the Retrieval of Interacting Genes online database and weighted genes coexpression network by the WGCNA package in R. Subsequently, we picked out the hub genes among the DEGs. A total of 423 DEGs with 198 upregulated genes and 225 downregulated genes were identified between HBV-ALF and normal samples. The upregulated genes were mainly enriched in immune response, and the downregulated genes were mainly enriched in complement and coagulation cascades. Orosomucoid 1 (ORM1), orosomucoid 2 (ORM2), plasminogen (PLG), and aldehyde oxidase 1 (AOX1) were picked out as the hub genes that with a high degree in both PPI network and weighted genes coexpression network. The weighted genes coexpression network analysis found out 3 of the 5 modules that upregulated genes enriched in were closely related to immune system. The downregulated genes enriched in only one module, and the genes in this module majorly enriched in the complement and coagulation cascades pathway. In conclusion, 4 genes (ORM1, ORM2, PLG, and AOX1) with immune response and the complement and coagulation cascades pathway may take part in the pathogenesis of HBV-ALF, and these candidate genes and pathways could be therapeutic targets for HBV-ALF. PMID:29384847

From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

PubMed

Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

Discovering functional interdependence relationship in PPI networks for protein complex identification.

PubMed

Lam, Winnie W M; Chan, Keith C C

2012-04-01

Protein molecules interact with each other in protein complexes to perform many vital functions, and different computational techniques have been developed to identify protein complexes in protein-protein interaction (PPI) networks. These techniques are developed to search for subgraphs of high connectivity in PPI networks under the assumption that the proteins in a protein complex are highly interconnected. While these techniques have been shown to be quite effective, it is also possible that the matching rate between the protein complexes they discover and those that are previously determined experimentally be relatively low and the "false-alarm" rate can be relatively high. This is especially the case when the assumption of proteins in protein complexes being more highly interconnected be relatively invalid. To increase the matching rate and reduce the false-alarm rate, we have developed a technique that can work effectively without having to make this assumption. The name of the technique called protein complex identification by discovering functional interdependence (PCIFI) searches for protein complexes in PPI networks by taking into consideration both the functional interdependence relationship between protein molecules and the network topology of the network. The PCIFI works in several steps. The first step is to construct a multiple-function protein network graph by labeling each vertex with one or more of the molecular functions it performs. The second step is to filter out protein interactions between protein pairs that are not functionally interdependent of each other in the statistical sense. The third step is to make use of an information-theoretic measure to determine the strength of the functional interdependence between all remaining interacting protein pairs. Finally, the last step is to try to form protein complexes based on the measure of the strength of functional interdependence and the connectivity between proteins. For performance evaluation, PCIFI was used to identify protein complexes in real PPI network data and the protein complexes it found were matched against those that were previously known in MIPS. The results show that PCIFI can be an effective technique for the identification of protein complexes. The protein complexes it found can match more known protein complexes with a smaller false-alarm rate and can provide useful insights into the understanding of the functional interdependence relationships between proteins in protein complexes.

A systems biology approach to study systemic inflammation.

PubMed

Chen, Bor-Sen; Wu, Chia-Chou

2014-01-01

Systemic inflammation needs a precise control on the sequence and magnitude of occurring events. The high throughput data on the host-pathogen interactions gives us an opportunity to have a glimpse on the systemic inflammation. In this article, a dynamic Candida albicans-zebrafish interactive infectious network is built as an example to demonstrate how systems biology approach can be used to study systematic inflammation. In particular, based on microarray data of C. albicans and zebrafish during infection, the hyphal growth, zebrafish, and host-pathogen intercellular PPI networks were combined to form an integrated infectious PPI network that helps us understand the systematic mechanisms underlying the pathogenicity of C. albicans and the immune response of the host. The signaling pathways for morphogenesis and hyphal growth of C. albicans were 2 significant interactions found in the intercellular PPI network. Two cellular networks were also developed corresponding to the different infection stages (adhesion and invasion), and then compared with each other to identify proteins to gain more insight into the pathogenic role of hyphal development in the C. albicans infection process. Important defense-related proteins in zebrafish were predicted using the same approach. This integrated network consisting of intercellular invasion and cellular defense processes during infection can improve medical therapies and facilitate development of new antifungal drugs.

Identification of key genes related to high-risk gastrointestinal stromal tumors using bioinformatics analysis.

PubMed

Jin, Shuan; Zhu, Wenhua; Li, Jun

2018-01-01

The purpose of this study was to identify predictive biomarkers used for clinical therapy and prognostic evaluation of high-risk gastrointestinal stromal tumors (GISTs). In this study, microarray data GSE31802 were used to identify differentially expressed genes (DEGs) between high-risk GISTs and low-risk GISTs. Then, enrichment analysis of DEGs was conducted based on the gene ontology and kyoto encyclopedia of genes and genomes pathway database. In addition, the transcription factors and cancer-related genes in DEGs were screened according to the TRANSFAC, TSGene, and TAG database. Finally, protein-protein interaction (PPI) network was constructed and analyzed to look for critical genes involved in high-risk GISTs. A total of forty DEGs were obtained and these genes were mainly involved in four pathways, including melanogenesis, neuroactive ligand-receptor interaction, malaria, and hematopoietic cell lineage. The enriched biological processes were related to the regulation of insulin secretion, integrin activation, and neuropeptide signaling pathway. Transcription factor analysis of DEGs indicated that POU domain, class 2, associating factor 1 (POU2AF1) was significantly downregulated in high-risk GISTs. By constructing the PPI network of DEGs, ten genes with high degrees formed local networks, such as PNOC, P2RY14, and SELP. Four genes as POU2AF1, PNOC, P2RY14, and SELP might be used as biomarkers for prognosis of high-risk GISTs.

The identification of key genes and pathways in hepatocellular carcinoma by bioinformatics analysis of high-throughput data.

PubMed

Zhang, Chaoyang; Peng, Li; Zhang, Yaqin; Liu, Zhaoyang; Li, Wenling; Chen, Shilian; Li, Guancheng

2017-06-01

Liver cancer is a serious threat to public health and has fairly complicated pathogenesis. Therefore, the identification of key genes and pathways is of much importance for clarifying molecular mechanism of hepatocellular carcinoma (HCC) initiation and progression. HCC-associated gene expression dataset was downloaded from Gene Expression Omnibus database. Statistical software R was used for significance analysis of differentially expressed genes (DEGs) between liver cancer samples and normal samples. Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, based on R software, were applied for the identification of pathways in which DEGs significantly enriched. Cytoscape software was for the construction of protein-protein interaction (PPI) network and module analysis to find the hub genes and key pathways. Finally, weighted correlation network analysis (WGCNA) was conducted to further screen critical gene modules with similar expression pattern and explore their biological significance. Significance analysis identified 1230 DEGs with fold change >2, including 632 significantly down-regulated DEGs and 598 significantly up-regulated DEGs. GO term enrichment analysis suggested that up-regulated DEG significantly enriched in immune response, cell adhesion, cell migration, type I interferon signaling pathway, and cell proliferation, and the down-regulated DEG mainly enriched in response to endoplasmic reticulum stress and endoplasmic reticulum unfolded protein response. KEGG pathway analysis found DEGs significantly enriched in five pathways including complement and coagulation cascades, focal adhesion, ECM-receptor interaction, antigen processing and presentation, and protein processing in endoplasmic reticulum. The top 10 hub genes in HCC were separately GMPS, ACACA, ALB, TGFB1, KRAS, ERBB2, BCL2, EGFR, STAT3, and CD8A, which resulted from PPI network. The top 3 gene interaction modules in PPI network enriched in immune response, organ development, and response to other organism, respectively. WGCNA revealed that the confirmed eight gene modules significantly enriched in monooxygenase and oxidoreductase activity, response to endoplasmic reticulum stress, type I interferon signaling pathway, processing, presentation and binding of peptide antigen, cellular response to cadmium and zinc ion, cell locomotion and differentiation, ribonucleoprotein complex and RNA processing, and immune system process, respectively. In conclusion, we identified some key genes and pathways closely related with HCC initiation and progression by a series of bioinformatics analysis on DEGs. These screened genes and pathways provided for a more detailed molecular mechanism underlying HCC occurrence and progression, holding promise for acting as biomarkers and potential therapeutic targets.

Identification of the Key Genes and Pathways in Esophageal Carcinoma.

PubMed

Su, Peng; Wen, Shiwang; Zhang, Yuefeng; Li, Yong; Xu, Yanzhao; Zhu, Yonggang; Lv, Huilai; Zhang, Fan; Wang, Mingbo; Tian, Ziqiang

2016-01-01

Objective . Esophageal carcinoma (EC) is a frequently common malignancy of gastrointestinal cancer in the world. This study aims to screen key genes and pathways in EC and elucidate the mechanism of it. Methods . 5 microarray datasets of EC were downloaded from Gene Expression Omnibus. Differentially expressed genes (DEGs) were screened by bioinformatics analysis. Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein-protein interaction (PPI) network construction were performed to obtain the biological roles of DEGs in EC. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression level of DEGs in EC. Results . A total of 1955 genes were filtered as DEGs in EC. The upregulated genes were significantly enriched in cell cycle and the downregulated genes significantly enriched in Endocytosis. PPI network displayed CDK4 and CCT3 were hub proteins in the network. The expression level of 8 dysregulated DEGs including CDK4, CCT3, THSD4, SIM2, MYBL2, CENPF, CDCA3, and CDKN3 was validated in EC compared to adjacent nontumor tissues and the results were matched with the microarray analysis. Conclusion . The significantly DEGs including CDK4, CCT3, THSD4, and SIM2 may play key roles in tumorigenesis and development of EC involved in cell cycle and Endocytosis.

Electrochemical and XPS study of LiFePO4 cathode nanocomposite with PPy/PEG conductive network

NASA Astrophysics Data System (ADS)

Fedorková, A.; Oriňáková, R.; Oriňák, A.; Kupková, M.; Wiemhöfer, H.-D.; Audinot, J. N.; Guillot, J.

2012-08-01

High performance PPy/PEG-LiFePO4 nanocomposites as cathode materials were synthesized by solvothermal method and simple chemical oxidative polymerization of pyrrole (Py) monomer on the surface of LiFePO4 particles. The samples were characterized by scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDX), X-ray photoelectron spectrometry (XPS) and charge-discharge tests. PPyPEG hybrid layers decrease particle to particle contact resistance while the impedance measurements confirmed that the coating of PPy-PEG significantly decreases the charge transfer resistance of the electrode material. The initial discharge capacities of this sample at C/5 and 1C are 150 and 128 mAh/g, respectively. The results show that PPy/PEGLiFePO4 composites are more effective than bare LiFePO4 as cathode material.

Revealing protein functions based on relationships of interacting proteins and GO terms.

PubMed

Teng, Zhixia; Guo, Maozu; Liu, Xiaoyan; Tian, Zhen; Che, Kai

2017-09-20

In recent years, numerous computational methods predicted protein function based on the protein-protein interaction (PPI) network. These methods supposed that two proteins share the same function if they interact with each other. However, it is reported by recent studies that the functions of two interacting proteins may be just related. It will mislead the prediction of protein function. Therefore, there is a need for investigating the functional relationship between interacting proteins. In this paper, the functional relationship between interacting proteins is studied and a novel method, called as GoDIN, is advanced to annotate functions of interacting proteins in Gene Ontology (GO) context. It is assumed that the functional difference between interacting proteins can be expressed by semantic difference between GO term and its relatives. Thus, the method uses GO term and its relatives to annotate the interacting proteins separately according to their functional roles in the PPI network. The method is validated by a series of experiments and compared with the concerned method. The experimental results confirm the assumption and suggest that GoDIN is effective on predicting functions of protein. This study demonstrates that: (1) interacting proteins are not equal in the PPI network, and their function may be same or similar, or just related; (2) functional difference between interacting proteins can be measured by their degrees in the PPI network; (3) functional relationship between interacting proteins can be expressed by relationship between GO term and its relatives.

Embedded Carbide-derived Carbon (CDC) particles in polypyrrole (PPy) for linear actuator

NASA Astrophysics Data System (ADS)

Zondaka, Zane; Valner, Robert; Aabloo, Alvo; Tamm, Tarmo; Kiefer, Rudolf

2016-04-01

Conducting polymer linear actuators, for example sodium dodecylbenzenesulfonate (NaDBS) doped polypyrrole (PPy/DBS), have shown moderate strain and stress. The goal of this work was to increase the obtainable strain and stress by adding additional active material to PPy/DBS. In recent year's carbide-derived carbon (CDC)-based materials have been applied in actuators; however, the obtained displacement and actuation speed has been low comparing to conducting polymer based actuators. In the present work, a CDC-PPy hybrid was synthesized electrochemically and polyoxometalate (POM) - phosphotungstic acid - was used to attach charge to CDC particles. The CDC-POM served in the presence of NaDBS as an additional electrolyte. Cyclic voltammetry and chronopotentiometric electrochemomechanical deformation (ECMD) measurements were performed in Lithium bis(trifluoromethanesulfonyl)- imide (LiTFSI) aqueous electrolyte. The ECMD measurements revealed that the hybrid CDC-PPy material exhibited higher force and strain in comparison to PPy/DBS films. The new material was investigated by scanning electron microscopy (SEM) to evaluate CDC particle embedding in the polymer network.

Influence of Protein Abundance on High-Throughput Protein-Protein Interaction Detection

DTIC Science & Technology

2009-06-05

the interaction data sets we determined, via comparisons with strict randomized simulations , the propensity for essential proteins to selectively...and analysis of high- quality PPI data sets. Materials and Methods We analyzed protein interaction networks for yeast and E. coli determined from Y2H...we reinvestigated the centrality-lethality rule, which implies that proteins having more interactions are more likely to be essential. From analysis

A hybrid network-based method for the detection of disease-related genes

NASA Astrophysics Data System (ADS)

Cui, Ying; Cai, Meng; Dai, Yang; Stanley, H. Eugene

2018-02-01

Detecting disease-related genes is crucial in disease diagnosis and drug design. The accepted view is that neighbors of a disease-causing gene in a molecular network tend to cause the same or similar diseases, and network-based methods have been recently developed to identify novel hereditary disease-genes in available biomedical networks. Despite the steady increase in the discovery of disease-associated genes, there is still a large fraction of disease genes that remains under the tip of the iceberg. In this paper we exploit the topological properties of the protein-protein interaction (PPI) network to detect disease-related genes. We compute, analyze, and compare the topological properties of disease genes with non-disease genes in PPI networks. We also design an improved random forest classifier based on these network topological features, and a cross-validation test confirms that our method performs better than previous similar studies.

Triangle network motifs predict complexes by complementing high-error interactomes with structural information.

PubMed

Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

2009-06-27

A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient for finding complexes involving most of the proteins and interactions in a typical PPIN.

Triangle network motifs predict complexes by complementing high-error interactomes with structural information

PubMed Central

Andreopoulos, Bill; Winter, Christof; Labudde, Dirk; Schroeder, Michael

2009-01-01

Background A lot of high-throughput studies produce protein-protein interaction networks (PPINs) with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs) were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs) representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. Results We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS). PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Conclusion Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that relatively little structural information would be sufficient for finding complexes involving most of the proteins and interactions in a typical PPIN. PMID:19558694

Large-scale protein-protein interaction analysis in Arabidopsis mesophyll protoplasts by split firefly luciferase complementation.

PubMed

Li, Jian-Feng; Bush, Jenifer; Xiong, Yan; Li, Lei; McCormack, Matthew

2011-01-01

Protein-protein interactions (PPIs) constitute the regulatory network that coordinates diverse cellular functions. There are growing needs in plant research for creating protein interaction maps behind complex cellular processes and at a systems biology level. However, only a few approaches have been successfully used for large-scale surveys of PPIs in plants, each having advantages and disadvantages. Here we present split firefly luciferase complementation (SFLC) as a highly sensitive and noninvasive technique for in planta PPI investigation. In this assay, the separate halves of a firefly luciferase can come into close proximity and transiently restore its catalytic activity only when their fusion partners, namely the two proteins of interest, interact with each other. This assay was conferred with quantitativeness and high throughput potential when the Arabidopsis mesophyll protoplast system and a microplate luminometer were employed for protein expression and luciferase measurement, respectively. Using the SFLC assay, we could monitor the dynamics of rapamycin-induced and ascomycin-disrupted interaction between Arabidopsis FRB and human FKBP proteins in a near real-time manner. As a proof of concept for large-scale PPI survey, we further applied the SFLC assay to testing 132 binary PPIs among 8 auxin response factors (ARFs) and 12 Aux/IAA proteins from Arabidopsis. Our results demonstrated that the SFLC assay is ideal for in vivo quantitative PPI analysis in plant cells and is particularly powerful for large-scale binary PPI screens.

Low temperature hall effect investigation of conducting polymer-carbon nanotubes composite network.

PubMed

Bahrami, Afarin; Talib, Zainal Abidin; Yunus, Wan Mahmood Mat; Behzad, Kasra; M Abdi, Mahnaz; Din, Fasih Ud

2012-11-14

Polypyrrole (PPy) and polypyrrole-carboxylic functionalized multi wall carbon nanotube composites (PPy/f-MWCNT) were synthesized by in situ chemical oxidative polymerization of pyrrole on the carbon nanotubes (CNTs). The structure of the resulting complex nanotubes was characterized by transmission electron microscopy (TEM) and X-ray diffraction (XRD). The effects of f-MWCNT concentration on the electrical properties of the resulting composites were studied at temperatures between 100 K and 300 K. The Hall mobility and Hall coefficient of PPy and PPy/f-MWCNT composite samples with different concentrations of f-MWCNT were measured using the van der Pauw technique. The mobility decreased slightly with increasing temperature, while the conductivity was dominated by the gradually increasing carrier density.

Identification of Biological Targets of Therapeutic Intervention for Hepatocellular Carcinoma by Integrated Bioinformatical Analysis.

PubMed

Hu, Wei Qi; Wang, Wei; Fang, Di Long; Yin, Xue Feng

2018-05-24

BACKGROUND We screened the potential molecular targets and investigated the molecular mechanisms of hepatocellular carcinoma (HCC). MATERIAL AND METHODS Microarray data of GSE47786, including the 40 μM berberine-treated HepG2 human hepatoma cell line and 0.08% DMSO-treated as control cells samples, was downloaded from the GEO database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed; the protein-protein interaction (PPI) networks were constructed using STRING database and Cytoscape; the genetic alteration, neighboring genes networks, and survival analysis of hub genes were explored by cBio portal; and the expression of mRNA level of hub genes was obtained from the Oncomine databases. RESULTS A total of 56 upregulated and 8 downregulated DEGs were identified. The GO analysis results were significantly enriched in cell-cycle arrest, regulation of transcription, DNA-dependent, protein amino acid phosphorylation, cell cycle, and apoptosis. The KEGG pathway analysis showed that DEGs were enriched in MAPK signaling pathway, ErbB signaling pathway, and p53 signaling pathway. JUN, EGR1, MYC, and CDKN1A were identified as hub genes in PPI networks. The genetic alteration of hub genes was mainly concentrated in amplification. TP53, NDRG1, and MAPK15 were found in neighboring genes networks. Altered genes had worse overall survival and disease-free survival than unaltered genes. The expressions of EGR1, MYC, and CDKN1A were significantly increased, but expression of JUN was not, in the Roessler Liver datasets. CONCLUSIONS We found that JUN, EGR1, MYC, and CDKN1A might be used as diagnostic and therapeutic molecular biomarkers and broaden our understanding of the molecular mechanisms of HCC.

Identification and functional analysis of risk-related microRNAs for the prognosis of patients with bladder urothelial carcinoma.

PubMed

Gao, Ji; Li, Hongyan; Liu, Lei; Song, Lide; Lv, Yanting; Han, Yuping

2017-12-01

The aim of the present study was to investigate risk-related microRNAs (miRs) for bladder urothelial carcinoma (BUC) prognosis. Clinical and microRNA expression data downloaded from the Cancer Genome Atlas were utilized for survival analysis. Risk factor estimation was performed using Cox's proportional regression analysis. A microRNA-regulated target gene network was constructed and presented using Cytoscape. In addition, the Database for Annotation, Visualization and Integrated Discovery was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment, followed by protein-protein interaction (PPI) network analysis. Finally, the K-clique method was applied to analyze sub-pathways. A total of 16 significant microRNAs, including hsa-miR-3622a and hsa-miR-29a, were identified (P<0.05). Following Cox's proportional regression analysis, hsa-miR-29a was screened as a prognostic marker of BUC risk (P=0.0449). A regulation network of hsa-miR-29a comprising 417 target genes was constructed. These target genes were primarily enriched in GO terms, including collagen fibril organization, extracellular matrix (ECM) organization and pathways, such as focal adhesion (P<0.05). A PPI network including 197 genes and 510 interactions, was constructed. The top 21 genes in the network module were enriched in GO terms, including collagen fibril organization and pathways, such as ECM receptor interaction (P<0.05). Finally, 4 sub-pathways of cysteine and methionine metabolism, including paths 00270_4, 00270_1, 00270_2 and 00270_5, were obtained (P<0.01) and identified to be enriched through DNA (cytosine-5)-methyltransferase ( DNMT)3A, DNMT3B , methionine adenosyltransferase 2α ( MAT2A ) and spermine synthase ( SMS ). The identified microRNAs, particularly hsa-miR-29a and its 4 associated target genes DNMT3A, DNMT3B, MAT2A and SMS , may participate in the prognostic risk mechanism of BUC.

[Chemical libraries dedicated to protein-protein interactions].

PubMed

Sperandio, Olivier; Villoutreix, Bruno O; Morelli, Xavier; Roche, Philippe

2015-03-01

The identification of complete networks of protein-protein interactions (PPI) within a cell has contributed to major breakthroughs in understanding biological pathways, host-pathogen interactions and cancer development. As a consequence, PPI have emerged as a new class of promising therapeutic targets. However, they are still considered as a challenging class of targets for drug discovery programs. Recent successes have allowed the characterization of structural and physicochemical properties of protein-protein interfaces leading to a better understanding of how they can be disrupted with small molecule compounds. In addition, characterization of the profiles of PPI inhibitors has allowed the development of PPI-focused libraries. In this review, we present the current efforts at developing chemical libraries dedicated to these innovative targets. © 2015 médecine/sciences – Inserm.

L-GRAAL: Lagrangian graphlet-based network aligner.

PubMed

Malod-Dognin, Noël; Pržulj, Nataša

2015-07-01

Discovering and understanding patterns in networks of protein-protein interactions (PPIs) is a central problem in systems biology. Alignments between these networks aid functional understanding as they uncover important information, such as evolutionary conserved pathways, protein complexes and functional orthologs. A few methods have been proposed for global PPI network alignments, but because of NP-completeness of underlying sub-graph isomorphism problem, producing topologically and biologically accurate alignments remains a challenge. We introduce a novel global network alignment tool, Lagrangian GRAphlet-based ALigner (L-GRAAL), which directly optimizes both the protein and the interaction functional conservations, using a novel alignment search heuristic based on integer programming and Lagrangian relaxation. We compare L-GRAAL with the state-of-the-art network aligners on the largest available PPI networks from BioGRID and observe that L-GRAAL uncovers the largest common sub-graphs between the networks, as measured by edge-correctness and symmetric sub-structures scores, which allow transferring more functional information across networks. We assess the biological quality of the protein mappings using the semantic similarity of their Gene Ontology annotations and observe that L-GRAAL best uncovers functionally conserved proteins. Furthermore, we introduce for the first time a measure of the semantic similarity of the mapped interactions and show that L-GRAAL also uncovers best functionally conserved interactions. In addition, we illustrate on the PPI networks of baker's yeast and human the ability of L-GRAAL to predict new PPIs. Finally, L-GRAAL's results are the first to show that topological information is more important than sequence information for uncovering functionally conserved interactions. L-GRAAL is coded in C++. Software is available at: http://bio-nets.doc.ic.ac.uk/L-GRAAL/. n.malod-dognin@imperial.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Effects of 5-h multimodal stress on the molecules and pathways involved in dendritic morphology and cognitive function.

PubMed

Xu, Yiran; Cheng, Xiaorui; Cui, Xiuliang; Wang, Tongxing; Liu, Gang; Yang, Ruishang; Wang, Jianhui; Bo, Xiaochen; Wang, Shengqi; Zhou, Wenxia; Zhang, Yongxiang

2015-09-01

Stress induces cognitive impairments, which are likely related to the damaged dendritic morphology in the brain. Treatments for stress-induced impairments remain limited because the molecules and pathways underlying these impairments are unknown. Therefore, the aim of this study was to find the potential molecules and pathways related to damage of the dendritic morphology induced by stress. To do this, we detected gene expression, constructed a protein-protein interaction (PPI) network, and analyzed the molecular pathways in the brains of mice exposed to 5-h multimodal stress. The results showed that stress increased plasma corticosterone concentration, decreased cognitive function, damaged dendritic morphologies, and altered APBB1, CLSTN1, KCNA4, NOTCH3, PLAU, RPS6KA1, SYP, TGFB1, KCNA1, NTRK3, and SNCA expression in the brains of mice. Further analyses found that the abnormal expressions of CLSTN1, PLAU, NOTCH3, and TGFB1 induced by stress were related to alterations in the dendritic morphology. These four genes demonstrated interactions with 55 other genes, and configured a closed PPI network. Molecular pathway analysis use the Database for Annotation, Visualization, and Integrated Discovery (DAVID), specifically the gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG), each identified three pathways that were significantly enriched in the gene list of the PPI network, with genes belonging to the Notch and transforming growth factor-beta (TGF-B) signaling pathways being the most enriched. Our results suggest that TGFB1, PLAU, NOTCH3, and CLSTN1 may be related to the alterations in dendritic morphology induced by stress, and imply that the Notch and TGF-B signaling pathways may be involved. Copyright © 2015 Elsevier Inc. All rights reserved.

PPI-IRO: a two-stage method for protein-protein interaction extraction based on interaction relation ontology.

PubMed

Li, Chuan-Xi; Chen, Peng; Wang, Ru-Jing; Wang, Xiu-Jie; Su, Ya-Ru; Li, Jinyan

2014-01-01

Mining Protein-Protein Interactions (PPIs) from the fast-growing biomedical literature resources has been proven as an effective approach for the identification of biological regulatory networks. This paper presents a novel method based on the idea of Interaction Relation Ontology (IRO), which specifies and organises words of various proteins interaction relationships. Our method is a two-stage PPI extraction method. At first, IRO is applied in a binary classifier to determine whether sentences contain a relation or not. Then, IRO is taken to guide PPI extraction by building sentence dependency parse tree. Comprehensive and quantitative evaluations and detailed analyses are used to demonstrate the significant performance of IRO on relation sentences classification and PPI extraction. Our PPI extraction method yielded a recall of around 80% and 90% and an F1 of around 54% and 66% on corpora of AIMed and BioInfer, respectively, which are superior to most existing extraction methods.

In silico prediction of protein-protein interactions in human macrophages

PubMed Central

2014-01-01

Background Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. Results We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. Conclusion Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level. PMID:24636261

Exploring Wound-Healing Genomic Machinery with a Network-Based Approach

PubMed Central

Vitali, Francesca; Marini, Simone; Balli, Martina; Grosemans, Hanne; Sampaolesi, Maurilio; Lussier, Yves A.; Cusella De Angelis, Maria Gabriella; Bellazzi, Riccardo

2017-01-01

The molecular mechanisms underlying tissue regeneration and wound healing are still poorly understood despite their importance. In this paper we develop a bioinformatics approach, combining biology and network theory to drive experiments for better understanding the genetic underpinnings of wound healing mechanisms and for selecting potential drug targets. We start by selecting literature-relevant genes in murine wound healing, and inferring from them a Protein-Protein Interaction (PPI) network. Then, we analyze the network to rank wound healing-related genes according to their topological properties. Lastly, we perform a procedure for in-silico simulation of a treatment action in a biological pathway. The findings obtained by applying the developed pipeline, including gene expression analysis, confirms how a network-based bioinformatics method is able to prioritize candidate genes for in vitro analysis, thus speeding up the understanding of molecular mechanisms and supporting the discovery of potential drug targets. PMID:28635674

Covalent organic framework-derived microporous carbon nanoparticles coated with conducting polypyrrole as an electrochemical capacitor

NASA Astrophysics Data System (ADS)

Kim, Dong Jun; Yoon, Jung Woon; Lee, Chang Soo; Bae, Youn-Sang; Kim, Jong Hak

2018-05-01

We report a high-performance electrochemical capacitor based on covalent organic framework (COF)-derived microporous carbon (MPC) nanoparticles and electrochemically polymerized polypyrrole (Ppy) as a pseudocapacitive material. The COF, Schiff-based network-1 (SNW-1) nanoparticles are prepared via a condensation reaction between melamine and terephthalaldehyde, and the resultant MPC film is prepared via a screen-printing method. The MPC film exhibits a bimodal porous structure with micropores and macropores, resulting in both a large surface area and good electrolyte infiltration. Ppy is synthesized potentio-statically (0.8 V vs. Ag/AgCl) by varying the reaction time, and successful synthesis of Ppy is confirmed via Raman spectroscopy. The specific capacitance with the Ppy coating is enhanced by up to 2.55 F cm-2 due to the synergetic effect of pseudocapacitance and reduced resistance.

Proton Pump Inhibitor Initiation and Withdrawal affects Gut Microbiota and Readmission Risk in Cirrhosis.

PubMed

Bajaj, Jasmohan S; Acharya, Chathur; Fagan, Andrew; White, Melanie B; Gavis, Edith; Heuman, Douglas M; Hylemon, Phillip B; Fuchs, Michael; Puri, Puneet; Schubert, Mitchell L; Sanyal, Arun J; Sterling, Richard K; Stravitz, R Todd; Siddiqui, Mohammad S; Luketic, Velimir; Lee, Hannah; Sikaroodi, Masoumeh; Gillevet, Patrick M

2018-06-06

Cirrhosis is associated with gut microbial dysbiosis, high readmissions and proton pump inhibitor (PPI) overuse, which could be inter-linked. Our aim was to determine the effect of PPI use, initiation and withdrawl on gut microbiota and readmissions in cirrhosis. Four cohorts were enrolled. Readmissions study: Cirrhotic inpatients were followed throughout the hospitalization and 30/90-days post-discharge. PPI initiation, withdrawal/continuation patterns were analyzed between those with/without readmissions. Cross-sectional microbiota study: Cirrhotic outpatients and controls underwent stool microbiota analysis. Beneficial autochthonous and oral-origin taxa analysis vis-à-vis PPI use was performed. Longitudinal studies: Two cohorts of decompensated cirrhotic outpatients were enrolled. Patients on chronic unindicated PPI use were withdrawn for 14 days. Patients not on PPI were started on omeprazole for 14 days. Microbial analysis for oral-origin taxa was performed pre/post-intervention. Readmissions study: 343 inpatients (151 on admission PPI) were enrolled. 21 were withdrawn and 45 were initiated on PPI resulting in a PPI use increase of 21%. PPIs were associated with higher 30 (p = 0.002) and 90-day readmissions (p = 0.008) independent of comorbidities, medications, MELD and age. Cross-sectional microbiota: 137 cirrhotics (59 on PPI) and 45 controls (17 on PPI) were included. PPI users regardless of cirrhosis had higher oral-origin microbiota while cirrhotics on PPI had lower autochthonous taxa compared to the rest. Longitudinal studies: Fifteen decompensated cirrhotics tolerated omeprazole initiation with an increase in oral-origin microbial taxa compared to baseline. PPIs were withdrawn from an additional 15 outpatients, which resulted in a significant reduction of oral-origin taxa compared to baseline. PPIs modulate readmission risk and microbiota composition in cirrhosis, which responds to withdrawal. The systematic withdrawal and judicious use of PPIs is needed from a clinical and microbiological perspective in decompensated cirrhosis.

Risk of Community-Acquired Pneumonia with Outpatient Proton-Pump Inhibitor Therapy: A Systematic Review and Meta-Analysis

PubMed Central

Lambert, Allison A.; Lam, Jennifer O.; Paik, Julie J.; Ugarte-Gil, Cesar; Drummond, M. Bradley; Crowell, Trevor A.

2015-01-01

Background Proton-pump inhibitors (PPIs) are among the most frequently prescribed medications. Community-acquired pneumonia (CAP) is a common cause of morbidity, mortality and healthcare spending. Some studies suggest an increased risk of CAP among PPI users. We conducted a systematic review and meta-analysis to determine the association between outpatient PPI therapy and risk of CAP in adults. Methods We conducted systematic searches of MEDLINE, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials, Scopus and Web of Science on February 3, 2014. Case-control studies, case-crossover, cohort studies and randomized controlled trials reporting outpatient PPI exposure and CAP diagnosis for patients ≥18 years old were eligible. Our primary outcome was the association between CAP and PPI therapy. A secondary outcome examined the risk of hospitalization for CAP and subgroup analyses evaluated the association between PPI use and CAP among patients of different age groups, by different PPI doses, and by different durations of PPI therapy. Results Systematic review of 33 studies was performed, of which 26 studies were included in the meta-analysis. These 26 studies included 226,769 cases of CAP among 6,351,656 participants. We observed a pooled risk of CAP with ambulatory PPI therapy of 1.49 (95% CI 1.16, 1.92; I2 99.2%). This risk was increased during the first month of therapy (OR 2.10; 95% CI 1.39, 3.16), regardless of PPI dose or patient age. PPI therapy also increased risk for hospitalization for CAP (OR 1.61; 95% CI: 1.12, 2.31). Discussion Outpatient PPI use is associated with a 1.5-fold increased risk of CAP, with the highest risk within the first 30 days after initiation of therapy. Providers should be aware of this risk when considering PPI use, especially in cases where alternative regimens may be available or the benefits of PPI use are uncertain. PMID:26042842

Identification of hub subnetwork based on topological features of genes in breast cancer

PubMed Central

ZHUANG, DA-YONG; JIANG, LI; HE, QING-QING; ZHOU, PENG; YUE, TAO

2015-01-01

The aim of this study was to provide functional insight into the identification of hub subnetworks by aggregating the behavior of genes connected in a protein-protein interaction (PPI) network. We applied a protein network-based approach to identify subnetworks which may provide new insight into the functions of pathways involved in breast cancer rather than individual genes. Five groups of breast cancer data were downloaded and analyzed from the Gene Expression Omnibus (GEO) database of high-throughput gene expression data to identify gene signatures using the genome-wide global significance (GWGS) method. A PPI network was constructed using Cytoscape and clusters that focused on highly connected nodes were obtained using the molecular complex detection (MCODE) clustering algorithm. Pathway analysis was performed to assess the functional relevance of selected gene signatures based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Topological centrality was used to characterize the biological importance of gene signatures, pathways and clusters. The results revealed that, cluster1, as well as the cell cycle and oocyte meiosis pathways were significant subnetworks in the analysis of degree and other centralities, in which hub nodes mostly distributed. The most important hub nodes, with top ranked centrality, were also similar with the common genes from the above three subnetwork intersections, which was viewed as a hub subnetwork with more reproducible than individual critical genes selected without network information. This hub subnetwork attributed to the same biological process which was essential in the function of cell growth and death. This increased the accuracy of identifying gene interactions that took place within the same functional process and was potentially useful for the development of biomarkers and networks for breast cancer. PMID:25573623

UDoNC: An Algorithm for Identifying Essential Proteins Based on Protein Domains and Protein-Protein Interaction Networks.

PubMed

Peng, Wei; Wang, Jianxin; Cheng, Yingjiao; Lu, Yu; Wu, Fangxiang; Pan, Yi

2015-01-01

Prediction of essential proteins which are crucial to an organism's survival is important for disease analysis and drug design, as well as the understanding of cellular life. The majority of prediction methods infer the possibility of proteins to be essential by using the network topology. However, these methods are limited to the completeness of available protein-protein interaction (PPI) data and depend on the network accuracy. To overcome these limitations, some computational methods have been proposed. However, seldom of them solve this problem by taking consideration of protein domains. In this work, we first analyze the correlation between the essentiality of proteins and their domain features based on data of 13 species. We find that the proteins containing more protein domain types which rarely occur in other proteins tend to be essential. Accordingly, we propose a new prediction method, named UDoNC, by combining the domain features of proteins with their topological properties in PPI network. In UDoNC, the essentiality of proteins is decided by the number and the frequency of their protein domain types, as well as the essentiality of their adjacent edges measured by edge clustering coefficient. The experimental results on S. cerevisiae data show that UDoNC outperforms other existing methods in terms of area under the curve (AUC). Additionally, UDoNC can also perform well in predicting essential proteins on data of E. coli.

Multichannel Convolutional Neural Network for Biological Relation Extraction.

PubMed

Quan, Chanqin; Hua, Lei; Sun, Xiao; Bai, Wenjun

2016-01-01

The plethora of biomedical relations which are embedded in medical logs (records) demands researchers' attention. Previous theoretical and practical focuses were restricted on traditional machine learning techniques. However, these methods are susceptible to the issues of "vocabulary gap" and data sparseness and the unattainable automation process in feature extraction. To address aforementioned issues, in this work, we propose a multichannel convolutional neural network (MCCNN) for automated biomedical relation extraction. The proposed model has the following two contributions: (1) it enables the fusion of multiple (e.g., five) versions in word embeddings; (2) the need for manual feature engineering can be obviated by automated feature learning with convolutional neural network (CNN). We evaluated our model on two biomedical relation extraction tasks: drug-drug interaction (DDI) extraction and protein-protein interaction (PPI) extraction. For DDI task, our system achieved an overall f -score of 70.2% compared to the standard linear SVM based system (e.g., 67.0%) on DDIExtraction 2013 challenge dataset. And for PPI task, we evaluated our system on Aimed and BioInfer PPI corpus; our system exceeded the state-of-art ensemble SVM system by 2.7% and 5.6% on f -scores.

What Difference Does Patient and Public Involvement Make and What Are Its Pathways to Impact? Qualitative Study of Patients and Researchers from a Cohort of Randomised Clinical Trials

PubMed Central

Dudley, Louise; Gamble, Carrol; Preston, Jennifer; Buck, Deborah; Hanley, Bec; Williamson, Paula; Young, Bridget

2015-01-01

Background Patient and public involvement (PPI) is advocated in clinical trials yet evidence on how to optimise its impact is limited. We explored researchers' and PPI contributors' accounts of the impact of PPI within trials and factors likely to influence its impact. Methods Semi-structured qualitative interviews with researchers and PPI contributors accessed through a cohort of randomised clinical trials. Analysis of transcripts of audio-recorded interviews was informed by the principles of the constant comparative method, elements of content analysis and informant triangulation. Results We interviewed 21 chief investigators, 10 trial managers and 17 PPI contributors from 28 trials. The accounts of informants within the same trials were largely in agreement. Over half the informants indicted PPI had made a difference within a trial, through contributions that influenced either an aspect of a trial, or how researchers thought about a trial. According to informants, the opportunity for PPI to make a difference was influenced by two main factors: whether chief investigators had goals and plans for PPI and the quality of the relationship between the research team and the PPI contributors. Early involvement of PPI contributors and including them in responsive (e.g. advisory groups) and managerial (e.g. trial management groups) roles were more likely to achieve impact compared to late involvement and oversight roles (e.g. trial steering committees). Conclusion Those seeking to enhance PPI in trials should develop goals for PPI at an early stage that fits the needs of the trial, plan PPI implementation in accordance with these goals, invest in developing good relationships between PPI contributors and researchers, and favour responsive and managerial roles for contributors in preference to oversight-only roles. These features could be used by research funders in judging PPI in trial grant applications and to inform policies to optimise PPI within trials. PMID:26053063

Screening key candidate genes and pathways involved in insulinoma by microarray analysis.

PubMed

Zhou, Wuhua; Gong, Li; Li, Xuefeng; Wan, Yunyan; Wang, Xiangfei; Li, Huili; Jiang, Bin

2018-06-01

Insulinoma is a rare type tumor and its genetic features remain largely unknown. This study aimed to search for potential key genes and relevant enriched pathways of insulinoma.The gene expression data from GSE73338 were downloaded from Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified between insulinoma tissues and normal pancreas tissues, followed by pathway enrichment analysis, protein-protein interaction (PPI) network construction, and module analysis. The expressions of candidate key genes were validated by quantitative real-time polymerase chain reaction (RT-PCR) in insulinoma tissues.A total of 1632 DEGs were obtained, including 1117 upregulated genes and 514 downregulated genes. Pathway enrichment results showed that upregulated DEGs were significantly implicated in insulin secretion, and downregulated DEGs were mainly enriched in pancreatic secretion. PPI network analysis revealed 7 hub genes with degrees more than 10, including GCG (glucagon), GCGR (glucagon receptor), PLCB1 (phospholipase C, beta 1), CASR (calcium sensing receptor), F2R (coagulation factor II thrombin receptor), GRM1 (glutamate metabotropic receptor 1), and GRM5 (glutamate metabotropic receptor 5). DEGs involved in the significant modules were enriched in calcium signaling pathway, protein ubiquitination, and platelet degranulation. Quantitative RT-PCR data confirmed that the expression trends of these hub genes were similar to the results of bioinformatic analysis.The present study demonstrated that candidate DEGs and enriched pathways were the potential critical molecule events involved in the development of insulinoma, and these findings were useful for better understanding of insulinoma genesis.

A knowledge-driven probabilistic framework for the prediction of protein-protein interaction networks.

PubMed

Browne, Fiona; Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

2010-03-01

This study applied a knowledge-driven data integration framework for the inference of protein-protein interactions (PPI). Evidence from diverse genomic features is integrated using a knowledge-driven Bayesian network (KD-BN). Receiver operating characteristic (ROC) curves may not be the optimal assessment method to evaluate a classifier's performance in PPI prediction as the majority of the area under the curve (AUC) may not represent biologically meaningful results. It may be of benefit to interpret the AUC of a partial ROC curve whereby biologically interesting results are represented. Therefore, the novel application of the assessment method referred to as the partial ROC has been employed in this study to assess predictive performance of PPI predictions along with calculating the True positive/false positive rate and true positive/positive rate. By incorporating domain knowledge into the construction of the KD-BN, we demonstrate improvement in predictive performance compared with previous studies based upon the Naive Bayesian approach. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Network analysis of ChIP-Seq data reveals key genes in prostate cancer.

PubMed

Zhang, Yu; Huang, Zhen; Zhu, Zhiqiang; Liu, Jianwei; Zheng, Xin; Zhang, Yuhai

2014-09-03

Prostate cancer (PC) is the second most common cancer among men in the United States, and it imposes a considerable threat to human health. A deep understanding of its underlying molecular mechanisms is the premise for developing effective targeted therapies. Recently, deep transcriptional sequencing has been used as an effective genomic assay to obtain insights into diseases and may be helpful in the study of PC. In present study, ChIP-Seq data for PC and normal samples were compared, and differential peaks identified, based upon fold changes (with P-values calculated with t-tests). Annotations of these peaks were performed. Protein-protein interaction (PPI) network analysis was performed with BioGRID and constructed with Cytoscape, following which the highly connected genes were screened. We obtained a total of 5,570 differential peaks, including 3,726 differentially enriched peaks in tumor samples and 1,844 differentially enriched peaks in normal samples. There were eight significant regions of the peaks. The intergenic region possessed the highest score (51%), followed by intronic (31%) and exonic (11%) regions. The analysis revealed the top 35 highly connected genes, which comprised 33 differential genes (such as YWHAQ, tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein and θ polypeptide) from ChIP-Seq data and 2 differential genes retrieved from the PPI network: UBA52 (ubiquitin A-52 residue ribosomal protein fusion product (1) and SUMO2 (SMT3 suppressor of mif two 3 homolog (2) . Our findings regarding potential PC-related genes increase the understanding of PC and provides direction for future research.

Common variants of OPA1 conferring genetic susceptibility to leprosy in Han Chinese from Southwest China.

PubMed

Xiang, Yang-Lin; Zhang, Deng-Feng; Wang, Dong; Li, Yu-Ye; Yao, Yong-Gang

2015-11-01

Leprosy is an ancient chronic infection caused by Mycobacterium leprae. Onset of leprosy was highly affected by host nutritional condition and energy production, (partially) due to genomic loss and parasitic life style of M. leprae. The optic atrophy 1 (OPA1) gene plays an essential role in mitochondria, which function in cellular energy supply and innate immunity. To investigate the potential involvement of OPA1 in leprosy. We analyzed 7 common genetic variants of OPA1 in 1110 Han Chinese subjects with and without leprosy, followed by mRNA expression profiling and protein-protein interaction (PPI) network analysis. We observed positive associations between OPA1 variants rs9838374 (Pgenotypic=0.003) and rs414237 (Pgenotypic=0.002) with lepromatous leprosy. expression quantitative trait loci (eQTL) analysis showed that the leprosy-related risk allele C of rs414237 is correlated with lower OPA1 mRNA expression level. Indeed, we identified a decrease of OPA1 mRNA expression in both with patients and cellular model of leprosy. In addition, the PPI analysis showed that OPA1 protein was actively involved in the interaction network of M. leprae induced differentially expressed genes. Our results indicated that OPA1 variants confer risk of leprosy and may affect OPA1 expression, mitochondrial function and antimicrobial pathways. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Immunoinformatics Features Linked to Leishmania Vaccine Development: Data Integration of Experimental and In Silico Studies

PubMed Central

Brito, Rory C. F.; Guimarães, Frederico G.; Velloso, João P. L.; Corrêa-Oliveira, Rodrigo; Ruiz, Jeronimo C.; Reis, Alexandre B.; Resende, Daniela M.

2017-01-01

Leishmaniasis is a wide-spectrum disease caused by parasites from Leishmania genus. There is no human vaccine available and it is considered by many studies as apotential effective tool for disease control. To discover novel antigens, computational programs have been used in reverse vaccinology strategies. In this work, we developed a validation antigen approach that integrates prediction of B and T cell epitopes, analysis of Protein-Protein Interaction (PPI) networks and metabolic pathways. We selected twenty candidate proteins from Leishmania tested in murine model, with experimental outcome published in the literature. The predictions for CD4+ and CD8+ T cell epitopes were correlated with protection in experimental outcomes. We also mapped immunogenic proteins on PPI networks in order to find Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with them. Our results suggest that non-protective antigens have lowest frequency of predicted T CD4+ and T CD8+ epitopes, compared with protective ones. T CD4+ and T CD8+ cells are more related to leishmaniasis protection in experimental outcomes than B cell predicted epitopes. Considering KEGG analysis, the proteins considered protective are connected to nodes with few pathways, including those associated with ribosome biosynthesis and purine metabolism. PMID:28208616

Immunoinformatics Features Linked to Leishmania Vaccine Development: Data Integration of Experimental and In Silico Studies.

PubMed

Brito, Rory C F; Guimarães, Frederico G; Velloso, João P L; Corrêa-Oliveira, Rodrigo; Ruiz, Jeronimo C; Reis, Alexandre B; Resende, Daniela M

2017-02-10

Leishmaniasis is a wide-spectrum disease caused by parasites from Leishmania genus. There is no human vaccine available and it is considered by many studies as apotential effective tool for disease control. To discover novel antigens, computational programs have been used in reverse vaccinology strategies. In this work, we developed a validation antigen approach that integrates prediction of B and T cell epitopes, analysis of Protein-Protein Interaction (PPI) networks and metabolic pathways. We selected twenty candidate proteins from Leishmania tested in murine model, with experimental outcome published in the literature. The predictions for CD4⁺ and CD8⁺ T cell epitopes were correlated with protection in experimental outcomes. We also mapped immunogenic proteins on PPI networks in order to find Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with them. Our results suggest that non-protective antigens have lowest frequency of predicted T CD4⁺ and T CD8⁺ epitopes, compared with protective ones. T CD4⁺ and T CD8⁺ cells are more related to leishmaniasis protection in experimental outcomes than B cell predicted epitopes. Considering KEGG analysis, the proteins considered protective are connected to nodes with few pathways, including those associated with ribosome biosynthesis and purine metabolism.

Fabrication and electrochemical properties of carbon nanotube/polypyrrole composite film electrodes with controlled pore size

NASA Astrophysics Data System (ADS)

Kim, Ji-Young; Kim, Kwang Heon; Kim, Kwang Bum

Carbon nanotube (CNT)/polypyrrole (PPy) composites with controlled pore size in a three-dimensional entangled structure of a CNT film are prepared as electrode materials for a pseudocapacitor. A CNT film electrode containing nanosize silica between the CNTs is first fabricated using an electrostatic spray deposition of a mixed suspension of CNTs and nanosize silica on to a platinium-coated silicon wafer. Later, nanosize silica is removed leaving a three-dimensional entangled structure of a CNT film. Before removal of the silica from the CNT/silica film electrode, PPy is electrochemically deposited on to the CNTs to anchor them in their entangled structure. Control of the pore size of the final CNT/PPy composite film can be achieved by changing the amount of silica in the mixed suspension of CNTs and nanosize silica. Nanosize silica acts as a sacrificial filler to change the pore size of the entangled CNT film. Scanning electron microscopy of the electrochemically prepared PPy on the CNT film substrate shows that the PPy nucleated heterogeneously and deposited on the surface of the CNTs. The specific capacitance and rate capability of the CNT/PPy composite electrode with a heavy loading of PPy of around 80 wt.% can be improved when it is made to have a three-dimensional network of entangled CNTs with interconnected pores through pore size control.

Key genes and pathways in measles and their interaction with environmental chemicals.

PubMed

Zhang, Rongqiang; Jiang, Hualin; Li, Fengying; Su, Ning; Ding, Yi; Mao, Xiang; Ren, Dan; Wang, Jing

2018-06-01

The aim of the present study was to explore key genes that may have a role in the pathology of measles virus infection and to clarify the interaction networks between environmental factors and differentially expressed genes (DEGs). After screening the database of the Gene Expression Omnibus of the National Center for Biotechnology Information, the dataset GSE5808 was downloaded and analyzed. A global normalization method was performed to minimize data inconsistencies and heterogeneity. DEGs during different stages of measles virus infection were explored using R software (v3.4.0). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the DEGs were performed using Cytoscape 3.4.0 software. A protein-protein interaction (PPI) network of the DEGs was obtained from the STRING database v9.05. A total of 43 DEGs were obtained from four analyzed sample groups, including 10 highly expressed genes and 33 genes with decreased expression. The most enriched pathways based on KEGG analysis were fatty acid elongation, cytokine-cytokine receptor interaction and RNA degradation. The genes mentioned in the PPI network were mainly associated with protein binding and chemokine activity. A total of 219 chemicals were identified that may, jointly or on their own, interact with the 6 DEGs between the control group and patients with measles (at hospital entry), including benzo(a)pyrene (BaP) and tetrachlorodibenzodioxin (TCDD). In conclusion, the present study revealed that chemokines and environmental chemicals, e.g. BaP and TCDD, may affect the development of measles.

Novelty seeking and reward dependence-related large-scale brain networks functional connectivity variation during salience expectancy.

PubMed

Li, Shijia; Demenescu, Liliana Ramona; Sweeney-Reed, Catherine M; Krause, Anna Linda; Metzger, Coraline D; Walter, Martin

2017-08-01

A salience network (SN) anchored in the anterior insula (AI) and dorsal anterior cingulate cortex (dACC) plays a key role in switching between brain networks during salience detection and attention regulation. Previous fMRI studies have associated expectancy behaviors and SN activation with novelty seeking (NS) and reward dependence (RD) personality traits. To address the question of how functional connectivity (FC) in the SN is modulated by internal (expectancy-related) salience assignment and different personality traits, 68 healthy participants performed a salience expectancy task using functional magnetic resonance imaging, and psychophysiological interaction analysis (PPI) was conducted to determine salience-related connectivity changes during these anticipation periods. Correlation was then evaluated between PPI and personality traits, assessed using the temperament and character inventory of 32 male participants. During high salience expectancy, SN-seed regions showed reduced FC to visual areas and parts of the default mode network, but increased FC to the central executive network. With increasing NS, participants showed significantly increasing disconnection between right AI and middle cingulate cortex when expecting high-salience pictures as compared to low-salience pictures, while increased RD also predicted decreased right dACC and caudate FC for high salience expectancy. Our findings suggest a direct link between personality traits and internal salience processing mediated by differential network integration of the SN. SN activity and coordination may therefore be moderated by novelty seeking and reward dependency personality traits, which are associated with risk of addiction. Hum Brain Mapp 38:4064-4077, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Public and patient involvement in quantitative health research: A statistical perspective.

PubMed

Hannigan, Ailish

2018-06-19

The majority of studies included in recent reviews of impact for public and patient involvement (PPI) in health research had a qualitative design. PPI in solely quantitative designs is underexplored, particularly its impact on statistical analysis. Statisticians in practice have a long history of working in both consultative (indirect) and collaborative (direct) roles in health research, yet their perspective on PPI in quantitative health research has never been explicitly examined. To explore the potential and challenges of PPI from a statistical perspective at distinct stages of quantitative research, that is sampling, measurement and statistical analysis, distinguishing between indirect and direct PPI. Statistical analysis is underpinned by having a representative sample, and a collaborative or direct approach to PPI may help achieve that by supporting access to and increasing participation of under-represented groups in the population. Acknowledging and valuing the role of lay knowledge of the context in statistical analysis and in deciding what variables to measure may support collective learning and advance scientific understanding, as evidenced by the use of participatory modelling in other disciplines. A recurring issue for quantitative researchers, which reflects quantitative sampling methods, is the selection and required number of PPI contributors, and this requires further methodological development. Direct approaches to PPI in quantitative health research may potentially increase its impact, but the facilitation and partnership skills required may require further training for all stakeholders, including statisticians. © 2018 The Authors Health Expectations published by John Wiley & Sons Ltd.

Construction of phosphorylation interaction networks by text mining of full-length articles using the eFIP system.

PubMed

Tudor, Catalina O; Ross, Karen E; Li, Gang; Vijay-Shanker, K; Wu, Cathy H; Arighi, Cecilia N

2015-01-01

Protein phosphorylation is a reversible post-translational modification where a protein kinase adds a phosphate group to a protein, potentially regulating its function, localization and/or activity. Phosphorylation can affect protein-protein interactions (PPIs), abolishing interaction with previous binding partners or enabling new interactions. Extracting phosphorylation information coupled with PPI information from the scientific literature will facilitate the creation of phosphorylation interaction networks of kinases, substrates and interacting partners, toward knowledge discovery of functional outcomes of protein phosphorylation. Increasingly, PPI databases are interested in capturing the phosphorylation state of interacting partners. We have previously developed the eFIP (Extracting Functional Impact of Phosphorylation) text mining system, which identifies phosphorylated proteins and phosphorylation-dependent PPIs. In this work, we present several enhancements for the eFIP system: (i) text mining for full-length articles from the PubMed Central open-access collection; (ii) the integration of the RLIMS-P 2.0 system for the extraction of phosphorylation events with kinase, substrate and site information; (iii) the extension of the PPI module with new trigger words/phrases describing interactions and (iv) the addition of the iSimp tool for sentence simplification to aid in the matching of syntactic patterns. We enhance the website functionality to: (i) support searches based on protein roles (kinases, substrates, interacting partners) or using keywords; (ii) link protein entities to their corresponding UniProt identifiers if mapped and (iii) support visual exploration of phosphorylation interaction networks using Cytoscape. The evaluation of eFIP on full-length articles achieved 92.4% precision, 76.5% recall and 83.7% F-measure on 100 article sections. To demonstrate eFIP for knowledge extraction and discovery, we constructed phosphorylation-dependent interaction networks involving 14-3-3 proteins identified from cancer-related versus diabetes-related articles. Comparison of the phosphorylation interaction network of kinases, phosphoproteins and interactants obtained from eFIP searches, along with enrichment analysis of the protein set, revealed several shared interactions, highlighting common pathways discussed in the context of both diseases. © The Author(s) 2015. Published by Oxford University Press.

Time-gated detection of protein-protein interactions with transcriptional readout

PubMed Central

Sanchez, Mateo I; Coukos, Robert; von Zastrow, Mark

2017-01-01

Transcriptional assays, such as yeast two-hybrid and TANGO, that convert transient protein-protein interactions (PPIs) into stable expression of transgenes are powerful tools for PPI discovery, screens, and analysis of cell populations. However, such assays often have high background and lose information about PPI dynamics. We have developed SPARK (Specific Protein Association tool giving transcriptional Readout with rapid Kinetics), in which proteolytic release of a membrane-tethered transcription factor (TF) requires both a PPI to deliver a protease proximal to its cleavage peptide and blue light to uncage the cleavage site. SPARK was used to detect 12 different PPIs in mammalian cells, with 5 min temporal resolution and signal ratios up to 37. By shifting the light window, we could reconstruct PPI time-courses. Combined with FACS, SPARK enabled 51 fold enrichment of PPI-positive over PPI-negative cells. Due to its high specificity and sensitivity, SPARK has the potential to advance PPI analysis and discovery. PMID:29189201

Making patient and public involvement in cancer and palliative research a reality: academic support is vital for success.

PubMed

Collins, Karen; Boote, Jonathan; Ardron, David; Gath, Jacqui; Green, Tracy; Ahmedzai, Sam H

2015-06-01

Patient and public involvement (PPI) has become an established theme within the UK health research policy and is recognised as an essential force in the drive to improve the quality of services and research. These developments have been particularly rapid in the cancer field. This paper outlines a model of PPI in research (known as the North Trent Cancer Research Network Consumer Research Panel, NTCRN CRP; comprising 38 cancer and palliative care patients/carers) and the key benefits and challenges to effective PPI in cancer research. The PPI model has become a sustainable, inclusive and effective way of implementing PPI within the cancer context. Challenges include (1) a lack of time and funding available to support the PPI model; (2) tensions between different stakeholder groups when developing and conducting health research; (3) panel members finding it difficult to effectively integrate into research meetings when their role and contribution is not made clear at the outset or when unfamiliar language and jargon are used and not explained; (4) some professionals remain unclear about the role and practical implications of PPI in research. However, notwithstanding its financial and organisational challenges, the way that the NTCRN CRP is supported has provided a solid base for it to flourish. PPI provides considerable opportunities for patients and the public to work collaboratively with professionals to influence the cancer research agenda, with the contribution of PPI to the research process being integral to the entire process from the outset, rather than appended to it. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Additive Effects of Rebamipide Plus Proton Pump Inhibitors on the Expression of Tight Junction Proteins in a Rat Model of Gastro-Esophageal Reflux Disease.

PubMed

Gweon, Tae-Geun; Park, Jong-Hyung; Kim, Byung-Wook; Choi, Yang Kyu; Kim, Joon Sung; Park, Sung Min; Kim, Chang Whan; Kim, Hyung-Gil; Chung, Jun-Won

2018-01-15

The aim of this study was to investigate the effects of rebamipide on tight junction proteins in the esophageal mucosa in a rat model of gastroesophageal reflux disease (GERD). GERD was created in rats by tying the proximal stomach. The rats were divided into a control group, a proton pump inhibitor (PPI) group, and a PPI plus rebamipide (PPI+R) group. Pantoprazole (5 mg/kg) was administered intraperitoneally to the PPI and PPI+R groups. An additional dose of rebamipide (100 mg/kg) was administered orally to the PPI+R group. Mucosal erosions, epithelial thickness, and leukocyte infiltration into the esophageal mucosa were measured in isolated esophagi 14 days after the procedure. A Western blot analysis was conducted to measure the expression of claudin-1, -3, and -4. The mean surface area of mucosal erosions, epithelial thickness, and leukocyte infiltration were lower in the PPI group and the PPI+R group than in the control group. Western blot analysis revealed that the expression of claudin-3 and -4 was significantly higher in the PPI+R group than in the control group. Rebamipide may exert an additive effect in combination with PPI to modify the tight junction proteins of the esophageal mucosa in a rat model of GERD. This treatment might be associated with the relief of GERD symptoms.

Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis.

PubMed

You, Zhu-Hong; Lei, Ying-Ke; Zhu, Lin; Xia, Junfeng; Wang, Bing

2013-01-01

Protein-protein interactions (PPIs) play crucial roles in the execution of various cellular processes and form the basis of biological mechanisms. Although large amount of PPIs data for different species has been generated by high-throughput experimental techniques, current PPI pairs obtained with experimental methods cover only a fraction of the complete PPI networks, and further, the experimental methods for identifying PPIs are both time-consuming and expensive. Hence, it is urgent and challenging to develop automated computational methods to efficiently and accurately predict PPIs. We present here a novel hierarchical PCA-EELM (principal component analysis-ensemble extreme learning machine) model to predict protein-protein interactions only using the information of protein sequences. In the proposed method, 11188 protein pairs retrieved from the DIP database were encoded into feature vectors by using four kinds of protein sequences information. Focusing on dimension reduction, an effective feature extraction method PCA was then employed to construct the most discriminative new feature set. Finally, multiple extreme learning machines were trained and then aggregated into a consensus classifier by majority voting. The ensembling of extreme learning machine removes the dependence of results on initial random weights and improves the prediction performance. When performed on the PPI data of Saccharomyces cerevisiae, the proposed method achieved 87.00% prediction accuracy with 86.15% sensitivity at the precision of 87.59%. Extensive experiments are performed to compare our method with state-of-the-art techniques Support Vector Machine (SVM). Experimental results demonstrate that proposed PCA-EELM outperforms the SVM method by 5-fold cross-validation. Besides, PCA-EELM performs faster than PCA-SVM based method. Consequently, the proposed approach can be considered as a new promising and powerful tools for predicting PPI with excellent performance and less time.

Development and application of a DNA microarray-based yeast two-hybrid system

PubMed Central

Suter, Bernhard; Fontaine, Jean-Fred; Yildirimman, Reha; Raskó, Tamás; Schaefer, Martin H.; Rasche, Axel; Porras, Pablo; Vázquez-Álvarez, Blanca M.; Russ, Jenny; Rau, Kirstin; Foulle, Raphaele; Zenkner, Martina; Saar, Kathrin; Herwig, Ralf; Andrade-Navarro, Miguel A.; Wanker, Erich E.

2013-01-01

The yeast two-hybrid (Y2H) system is the most widely applied methodology for systematic protein–protein interaction (PPI) screening and the generation of comprehensive interaction networks. We developed a novel Y2H interaction screening procedure using DNA microarrays for high-throughput quantitative PPI detection. Applying a global pooling and selection scheme to a large collection of human open reading frames, proof-of-principle Y2H interaction screens were performed for the human neurodegenerative disease proteins huntingtin and ataxin-1. Using systematic controls for unspecific Y2H results and quantitative benchmarking, we identified and scored a large number of known and novel partner proteins for both huntingtin and ataxin-1. Moreover, we show that this parallelized screening procedure and the global inspection of Y2H interaction data are uniquely suited to define specific PPI patterns and their alteration by disease-causing mutations in huntingtin and ataxin-1. This approach takes advantage of the specificity and flexibility of DNA microarrays and of the existence of solid-related statistical methods for the analysis of DNA microarray data, and allows a quantitative approach toward interaction screens in human and in model organisms. PMID:23275563

Multifaceted intervention to curb in-hospital over-prescription of proton pump inhibitors: A longitudinal multicenter quasi-experimental before-and-after study.

PubMed

Del Giorno, Rosaria; Ceschi, Alessandro; Pironi, Michela; Zasa, Anna; Greco, Angela; Gabutti, Luca

2018-04-01

Proton pump inhibitors (PPIs) are indicated for a restricted number of clinical conditions, and their misuse can lead to several adverse effects. Despite that, the proportion of overuse is alarmingly high. To test the efficacy of a multifaceted strategy in order to achieve a significant reduction of new PPI prescriptions at discharge in hospitalized patients. Multicenter longitudinal quasi-experimental before-and-after study conducted from July 1st, 2014 to June 30th, 2017. 44,973 admissions in a network of 5 public teaching hospitals of the Italian-speaking region of Switzerland. Multifaceted strategy consisting in a continuous transparent monitoring-benchmarking and in capillary educational interventions applied in the internal medicine departments. To confirm the causality of the results we monitored the trend of new PPI prescriptions in the, not exposed to the intervention, surgery departments of the same hospital network. New PPI prescriptions at hospital discharge. Over the 36month study period 44,973 patient files were analyzed. At admission, comparing internal medicine vs. surgery departments, 44.9% vs. 23.3% of patients were already being treated with a PPI. The annual rate of new PPI prescriptions, for internal medicine showed a decreasing trend: 19, 19, 18, 16% in years 2014, 2015, 2016, 2017, respectively (p<0.001, 2014 vs. 2017; p-for-trend <0.001), while an increasing rate was found in the surgery departments in the same years: 30, 29, 36, 36%, respectively (p<0.001, 2014 vs. 2017; p-for-trend <0.001). The case mix was significantly associated with the probability of new PPI prescriptions in both departments (OR1.35, 95% CI 1.26-1.44 for internal medicine and 1.24, 95% CI 1.19-1.30 for surgery). The introduction of a multifaceted intervention significantly reduced the time trend of PPI prescriptions at hospital discharge in internal medicine departments. Further studies are needed to confirm whether the strategy proposed could contribute to optimize the in-hospital drug prescription behavior in other healthcare settings as well. Copyright © 2017 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Insights into significant pathways and gene interaction networks underlying breast cancer cell line MCF-7 treated with 17β-estradiol (E2).

PubMed

Huan, Jinliang; Wang, Lishan; Xing, Li; Qin, Xianju; Feng, Lingbin; Pan, Xiaofeng; Zhu, Ling

2014-01-01

Estrogens are known to regulate the proliferation of breast cancer cells and to alter their cytoarchitectural and phenotypic properties, but the gene networks and pathways by which estrogenic hormones regulate these events are only partially understood. We used global gene expression profiling by Affymetrix GeneChip microarray analysis, with KEGG pathway enrichment, PPI network construction, module analysis and text mining methods to identify patterns and time courses of genes that are either stimulated or inhibited by estradiol (E2) in estrogen receptor (ER)-positive MCF-7 human breast cancer cells. Of the genes queried on the Affymetrix Human Genome U133 plus 2.0 microarray, we identified 628 (12h), 852 (24h) and 880 (48 h) differentially expressed genes (DEGs) that showed a robust pattern of regulation by E2. From pathway enrichment analysis, we found out the changes of metabolic pathways of E2 treated samples at each time point. At 12h time point, the changes of metabolic pathways were mainly focused on pathways in cancer, focal adhesion, and chemokine signaling pathway. At 24h time point, the changes were mainly enriched in neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction and calcium signaling pathway. At 48 h time point, the significant pathways were pathways in cancer, regulation of actin cytoskeleton, cell adhesion molecules (CAMs), axon guidance and ErbB signaling pathway. Of interest, our PPI network analysis and module analysis found that E2 treatment induced enhancement of PRSS23 at the three time points and PRSS23 was in the central position of each module. Text mining results showed that the important genes of DEGs have relationship with signal pathways, such as ERbB pathway (AREG), Wnt pathway (NDP), MAPK pathway (NTRK3, TH), IP3 pathway (TRA@) and some transcript factors (TCF4, MAF). Our studies highlight the diverse gene networks and metabolic and cell regulatory pathways through which E2 operates to achieve its widespread effects on breast cancer cells. © 2013 Elsevier B.V. All rights reserved.

Proton pump inhibitor co-prescription with dual antiplatelet therapy among patients with acute coronary syndrome in Qatar.

PubMed

Awaisu, Ahmed; Hamou, Fatima; Mekideche, Lylia; El Muabby, Nisrine; Mahfouz, Ahmed; Mohammed, Shaban; Saad, Ahmad

2016-04-01

There are increasing concerns about clinically significant interactions between proton pump inhibitors (PPIs) and clopidogrel, resulting in adverse cardiovascular outcomes in patients with acute coronary syndromes (ACS). However, published evidence on the prevalence and predictors of PPI use with dual antiplatelet therapy (DAPT) is scarce. This study investigated the prevalence of PPI use among patients with ACS receiving DAPT and possible predictors of co-prescribing the PPIs with the DAPT. Heart Hospital, a specialized tertiary care center in Qatar. A retrospective observational study of a prescription database was conducted. Subjects included 626 patients admitted between January and December 2012 with the diagnosis of ACS who received DAPT and discharged with or without a PPI. Univariate analysis and multivariate binary logistic regression analysis were performed to determine the predictors of PPI-DAPT co-prescription. Prevalence of PPI co-prescribing with DAPT in proportions and percentages and odd ratios for the predictors of PPI-DAPT co-prescribing. A total of 626 patients were analyzed for PPI prevalence, with 200 patients (32 %) being prescribed PPI with DAPT upon discharge. After controlling for confounders, PPI use on admission (aOR 14.5; 95 % CI 7.6-27.6, p < 0.001), nationality (aOR 3.2; 95 % CI 1.1-9.9, p = 0.041), and having a history of diabetes (aOR 0.5; 95 % CI 0.24-0.99, p = 0.046) significantly influenced PPI-DAPT co-prescribing. Users of PPI on admission compared to nonusers were about 15 times more likely to be prescribed PPI with DAPT upon discharge; likewise, having Qatari nationality increased the likelihood of co-prescribing PPI with DAPT upon discharge by three folds. Lastly, patients with a history of diabetes were 50 % less likely to be prescribed PPIs upon discharge compared to those with no history of diabetes. The rate of PPI co-prescribing with DAPT in the population studied was relatively high. The strongest predictor of PPI co-prescription with DAPT upon discharge was PPI use on admission. Furthermore, PPI prescribing was significantly predicted by nationality and not having diabetes. Further studies are warranted to better predict the factors associated with PPI-DAPT co-prescription and to investigate rational prescribing of PPIs among ACS patients.

Taking patient and public involvement online: qualitative evaluation of an online forum for palliative care and rehabilitation research.

PubMed

Brighton, Lisa Jane; Pask, Sophie; Benalia, Hamid; Bailey, Sylvia; Sumerfield, Marion; Witt, Jana; de Wolf-Linder, Susanne; Etkind, Simon Noah; Murtagh, Fliss E M; Koffman, Jonathan; Evans, Catherine J

2018-01-01

Patient and public involvement (PPI) is increasingly recognised as important in research. Most PPI takes place face-to-face, but this can be difficult for people who are unwell or have caring responsibilities. As these challenges are particularly common in palliative care and rehabilitation research, we developed an online forum for PPI: www.csipublicinvolvement.co.uk. In this study, we explored how well the online forum worked, if it is a suitable method for PPI, and how PPI members and researchers reacted to using it. We used an existing theory about online interventions to help choose the 'right' questions to ask participants. We invited PPI members and researchers who had used the online forum to participate in focus groups, and identified the most important themes discussed. Within this study, PPI members have helped with the interview questions, analysis, and write up. Overall, four PPI members and five researchers participated in the focus groups. Participants felt the online forum worked well and had multiple benefits. From the discussions, we identified four key questions to consider when developing online methods for PPI: how does the forum work, how does it engage people, how does it empower people, and what is the impact? Participants suggested the forum could be improved by being more PPI and less researcher focused. We conclude that when developing online methods of PPI, a functioning forum is not enough: it also needs to be engaging and empowering to have an impact. Future work can use these four domains when developing their own online PPI methods. Patient and public involvement (PPI) in research is increasingly recognised as important. Most PPI activities take place face-to-face, yet this can be difficult for people with ill health or caring responsibilities, and may exclude people from hard-to-reach populations (e.g. living in vulnerable social circumstances and/or remote geographical locations). These challenges are particularly pertinent in palliative care and rehabilitation research where people often live with, or care for someone with, advanced illness. In response to this, we aimed to test the functionality, feasibility, and acceptability of an online forum for PPI for palliative care and rehabilitation research (www.csipublicinvolvement.co.uk). We conducted separate focus groups with PPI members and researchers who had used the online forum. Data collection was underpinned by DeLone and Mclean's model of information systems success. Focus groups were recorded, transcribed, and analysed using inductive thematic analysis. Dual coding by two authors ensured rigour, and attention was paid to divergent cases. Four PPI members and five researchers participated in the focus groups (two PPI focus groups, one researcher focus group). The online forum was perceived as functional, feasible, and acceptable. Our analysis identified four key questions to consider when developing online methods for PPI: (1) how does the forum work, (2) how does it engage people, (3) how does it empower people, and (4) what is the impact? PPI members felt that the online forum was too researcher led, and needed to be more PPI focussed. When developing online methods of PPI, a functioning forum is not enough: it also needs to be engaging and empowering to have an impact. To optimise online involvement, future work should refer to these four domains and balance the needs of researchers and PPI members.

Nucleation and growth kinetics of electrodeposited sulfate-doped polypyrrole: determination of the diffusion coefficient of SO(4)(2-) in the polymeric membrane.

PubMed

Licona-Sánchez, T de J; Alvarez-Romero, G A; Mendoza-Huizar, L H; Galán-Vidal, C A; Palomar-Pardavé, M; Romero-Romo, M; Herrera-Hernández, H; Uruchurtu, J; Juárez-García, J M

2010-08-05

A kinetic study for the electrosynthesis of polypyrrole (Ppy) doped with SO(4)(2-) ions is presented. Ppy films were electrochemically polymerized onto a graphite-epoxy resin electrode. Experimental current density transients (j-t) were obtained for three different potentiometric behaviors: anionic, cationic, and a combination. Theoretical models were used to fit the experimental j-t data to determine the nucleation and growth processes controlling the polymer synthesis. It was encountered that, in all cases, pyrrole electropolimerization involves two concomitant processes, namely, a Ppy diffusion limited multiple 3D nucleation and growth and pyrrole electro-oxidation on the growing surface of the Ppy nuclei. SEM analysis of the electrodes surfaces reveals that Ppy deposition occurred over most of the electrode surface by multiple nucleation of hemispheres, as the theoretical model used for the analysis of the current transients required. Hemispherical particles formed the polymeric film displaying different sizes. The order for the particle size was as follows: anionic > anionic-cationic > cationic. These results are congruent with those obtained by theoretical analysis of the corresponding current transients. Analysis of the impedance measurements recorded on the anionic Ppy film, immersed in an aqueous solution with different sulfate ion concentrations evidenced that SO(4)(2-) ions diffuse through the Ppy film provoking a decrease of its electrical resistance and an increase of its dielectric constant. From the Warburg impedance coefficient, the sulfate coefficient of diffusion in the Ppy film was 1.38 x 10(-9) cm(2) s(-1).

Integration of RNA-Seq and RPPA data for survival time prediction in cancer patients.

PubMed

Isik, Zerrin; Ercan, Muserref Ece

2017-10-01

Integration of several types of patient data in a computational framework can accelerate the identification of more reliable biomarkers, especially for prognostic purposes. This study aims to identify biomarkers that can successfully predict the potential survival time of a cancer patient by integrating the transcriptomic (RNA-Seq), proteomic (RPPA), and protein-protein interaction (PPI) data. The proposed method -RPBioNet- employs a random walk-based algorithm that works on a PPI network to identify a limited number of protein biomarkers. Later, the method uses gene expression measurements of the selected biomarkers to train a classifier for the survival time prediction of patients. RPBioNet was applied to classify kidney renal clear cell carcinoma (KIRC), glioblastoma multiforme (GBM), and lung squamous cell carcinoma (LUSC) patients based on their survival time classes (long- or short-term). The RPBioNet method correctly identified the survival time classes of patients with between 66% and 78% average accuracy for three data sets. RPBioNet operates with only 20 to 50 biomarkers and can achieve on average 6% higher accuracy compared to the closest alternative method, which uses only RNA-Seq data in the biomarker selection. Further analysis of the most predictive biomarkers highlighted genes that are common for both cancer types, as they may be driver proteins responsible for cancer progression. The novelty of this study is the integration of a PPI network with mRNA and protein expression data to identify more accurate prognostic biomarkers that can be used for clinical purposes in the future. Copyright © 2017 Elsevier Ltd. All rights reserved.

From plans to actions in patient and public involvement: qualitative study of documented plans and the accounts of researchers and patients sampled from a cohort of clinical trials

PubMed Central

Buck, Deborah; Gamble, Carrol; Dudley, Louise; Preston, Jennifer; Hanley, Bec; Williamson, Paula R; Young, Bridget

2014-01-01

Patient and public involvement (PPI) in research is increasingly required, although evidence to inform its implementation is limited. Objective Inform the evidence base by describing how plans for PPI were implemented within clinical trials and identifying the challenges and lessons learnt by research teams. Methods We compared PPI plans extracted from clinical trial grant applications (funded by the National Institute for Health Research Health Technology Assessment Programme between 2006 and 2010) with researchers’ and PPI contributors’ interview accounts of PPI implementation. Analysis of PPI plans and transcribed qualitative interviews drew on the Framework technique. Results Of 28 trials, 25 documented plans for PPI in funding applications and half described implementing PPI before applying for funding. Plans varied from minimal to extensive, although almost all anticipated multiple modes of PPI. Interview accounts indicated that PPI plans had been fully implemented in 20/25 trials and even expanded in some. Nevertheless, some researchers described PPI within their trials as tokenistic. Researchers and contributors noted that late or minimal PPI engagement diminished its value. Both groups perceived uncertainty about roles in relation to PPI, and noted contributors’ lack of confidence and difficulties attending meetings. PPI contributors experienced problems in interacting with researchers and understanding technical language. Researchers reported difficulties finding ‘the right’ PPI contributors, and advised caution when involving investigators’ current patients. Conclusions Engaging PPI contributors early and ensuring ongoing clarity about their activities, roles and goals, is crucial to PPI's success. Funders, reviewers and regulators should recognise the value of preapplication PPI and allocate further resources to it. They should also consider whether PPI plans in grant applications match a trial's distinct needs. Monitoring and reporting PPI before, during and after trials will help the research community to optimise PPI, although the need for ongoing flexibility in implementing PPI should also be recognised. PMID:25475243

OmicsNet: a web-based tool for creation and visual analysis of biological networks in 3D space.

PubMed

Zhou, Guangyan; Xia, Jianguo

2018-06-07

Biological networks play increasingly important roles in omics data integration and systems biology. Over the past decade, many excellent tools have been developed to support creation, analysis and visualization of biological networks. However, important limitations remain: most tools are standalone programs, the majority of them focus on protein-protein interaction (PPI) or metabolic networks, and visualizations often suffer from 'hairball' effects when networks become large. To help address these limitations, we developed OmicsNet - a novel web-based tool that allows users to easily create different types of molecular interaction networks and visually explore them in a three-dimensional (3D) space. Users can upload one or multiple lists of molecules of interest (genes/proteins, microRNAs, transcription factors or metabolites) to create and merge different types of biological networks. The 3D network visualization system was implemented using the powerful Web Graphics Library (WebGL) technology that works natively in most major browsers. OmicsNet supports force-directed layout, multi-layered perspective layout, as well as spherical layout to help visualize and navigate complex networks. A rich set of functions have been implemented to allow users to perform coloring, shading, topology analysis, and enrichment analysis. OmicsNet is freely available at http://www.omicsnet.ca.

Molecular mechanisms of pathogenesis in hepatocellular carcinoma revealed by RNA‑sequencing.

PubMed

Liu, Yao; Yang, Zhe; Du, Feng; Yang, Qiao; Hou, Jie; Yan, Xiaohong; Geng, Yi; Zhao, Yaning; Wang, Hua

2017-11-01

The present study aimed to explore the underlying molecular mechanisms of hepatocellular carcinoma (HCC). RNA‑sequencing profiles GSM629264 and GSM629265, from the GSE25599 data set, were downloaded from the Gene Expression Omnibus database and processed by quality evaluation. GSM629264 and GSM629265 were from HCC and adjacent non‑cancerous tissues, respectively. TopHat software was used for alignment analysis, followed by the detection of novel splicing sites. In addition, the Cufflinks software package was used to analyze gene expressions, and the Cuffdiff program was used to screen for differently expressed genes (DEGs) and differentially expressed splicing variants. Gene ontology functional enrichment and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of DEGs were also performed. Transcription factors (TFs) and microRNAs (miRNAs) that regulate DEGs were identified, and a protein‑protein interaction (PPI) network was constructed. The hub node in the PPI network was obtained, and the TFs and miRNAs that regulated the hub node were further predicted. The quality of the sequencing data met the standards for analysis, and the clean reads were ~65%. Most sequencing reads mapped into coding sequence exons (CDS_exons), whereas other reads mapped into exon 3' untranslated regions (UTR_Exons), 5'UTR_Exons and Introns. Upregulated and downregulated DEGs between HCC and adjacent non‑cancerous tissues were screened. Genes of differentially expressed splicing variants were identified, including vesicle‑associated membrane protein 4, phosphatidylinositol glycan anchor biosynthesis class C, protein disulfide isomerase family A member 4 and growth arrest specific 5. Screened DEGs were enriched in the complement pathway. In the PPI network, ubiquitin C (UBC) was the hub node. UBC was predicted to be regulated by several TFs, including specificity protein 1 (SP1), FBJ murine osteosarcoma viral oncogene homolog (FOS), proto‑oncogene c‑JUN (JUN), FOS‑like antigen 2 (FOSL2) and SWI/SNF‑related, matrix‑associated, actin‑dependent regulator of chromatin, subfamily A, member 4 (SMARCA4), and several miRNAs, including miR‑30 and miR‑181. Results from the present study demonstrated that UBC, SP1, FOS, JUN, FOSL2, SMARCA4, miR‑30 and miR‑181 may participate in the development of HCC.

Global quantitative analysis of phosphorylation underlying phencyclidine signaling and sensorimotor gating in the prefrontal cortex.

PubMed

McClatchy, D B; Savas, J N; Martínez-Bartolomé, S; Park, S K; Maher, P; Powell, S B; Yates, J R

2016-02-01

Prepulse inhibition (PPI) is an example of sensorimotor gating and deficits in PPI have been demonstrated in schizophrenia patients. Phencyclidine (PCP) suppression of PPI in animals has been studied to elucidate the pathological elements of schizophrenia. However, the molecular mechanisms underlying PCP treatment or PPI in the brain are still poorly understood. In this study, quantitative phosphoproteomic analysis was performed on the prefrontal cortex from rats that were subjected to PPI after being systemically injected with PCP or saline. PCP downregulated phosphorylation events were significantly enriched in proteins associated with long-term potentiation (LTP). Importantly, this data set identifies functionally novel phosphorylation sites on known LTP-associated signaling molecules. In addition, mutagenesis of a significantly altered phosphorylation site on xCT (SLC7A11), the light chain of system xc-, the cystine/glutamate antiporter, suggests that PCP also regulates the activity of this protein. Finally, new insights were also derived on PPI signaling independent of PCP treatment. This is the first quantitative phosphorylation proteomic analysis providing new molecular insights into sensorimotor gating.

MPact: the MIPS protein interaction resource on yeast.

PubMed

Güldener, Ulrich; Münsterkötter, Martin; Oesterheld, Matthias; Pagel, Philipp; Ruepp, Andreas; Mewes, Hans-Werner; Stümpflen, Volker

2006-01-01

In recent years, the Munich Information Center for Protein Sequences (MIPS) yeast protein-protein interaction (PPI) dataset has been used in numerous analyses of protein networks and has been called a gold standard because of its quality and comprehensiveness [H. Yu, N. M. Luscombe, H. X. Lu, X. Zhu, Y. Xia, J. D. Han, N. Bertin, S. Chung, M. Vidal and M. Gerstein (2004) Genome Res., 14, 1107-1118]. MPact and the yeast protein localization catalog provide information related to the proximity of proteins in yeast. Beside the integration of high-throughput data, information about experimental evidence for PPIs in the literature was compiled by experts adding up to 4300 distinct PPIs connecting 1500 proteins in yeast. As the interaction data is a complementary part of CYGD, interactive mapping of data on other integrated data types such as the functional classification catalog [A. Ruepp, A. Zollner, D. Maier, K. Albermann, J. Hani, M. Mokrejs, I. Tetko, U. Güldener, G. Mannhaupt, M. Münsterkötter and H. W. Mewes (2004) Nucleic Acids Res., 32, 5539-5545] is possible. A survey of signaling proteins and comparison with pathway data from KEGG demonstrates that based on these manually annotated data only an extensive overview of the complexity of this functional network can be obtained in yeast. The implementation of a web-based PPI-analysis tool allows analysis and visualization of protein interaction networks and facilitates integration of our curated data with high-throughput datasets. The complete dataset as well as user-defined sub-networks can be retrieved easily in the standardized PSI-MI format. The resource can be accessed through http://mips.gsf.de/genre/proj/mpact.

Additive Effects of Rebamipide Plus Proton Pump Inhibitors on the Expression of Tight Junction Proteins in a Rat Model of Gastro-Esophageal Reflux Disease

PubMed Central

Gweon, Tae-Geun; Park, Jong-Hyung; Kim, Byung-Wook; Choi, Yang Kyu; Kim, Joon Sung; Park, Sung Min; Kim, Chang Whan; Kim, Hyung-Gil; Chung, Jun-Won; Incheon

2018-01-01

Background/Aims The aim of this study was to investigate the effects of rebamipide on tight junction proteins in the esophageal mucosa in a rat model of gastroesophageal reflux disease (GERD). Methods GERD was created in rats by tying the proximal stomach. The rats were divided into a control group, a proton pump inhibitor (PPI) group, and a PPI plus rebamipide (PPI+R) group. Pantoprazole (5 mg/kg) was administered intraperitoneally to the PPI and PPI+R groups. An additional dose of rebamipide (100 mg/kg) was administered orally to the PPI+R group. Mucosal erosions, epithelial thickness, and leukocyte infiltration into the esophageal mucosa were measured in isolated esophagi 14 days after the procedure. A Western blot analysis was conducted to measure the expression of claudin-1, -3, and -4. Results The mean surface area of mucosal erosions, epithelial thickness, and leukocyte infiltration were lower in the PPI group and the PPI+R group than in the control group. Western blot analysis revealed that the expression of claudin-3 and -4 was significantly higher in the PPI+R group than in the control group. Conclusions Rebamipide may exert an additive effect in combination with PPI to modify the tight junction proteins of the esophageal mucosa in a rat model of GERD. This treatment might be associated with the relief of GERD symptoms. PMID:29069891

Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

PubMed Central

Li, Min; Chen, Weijie; Wang, Jianxin; Pan, Yi

2014-01-01

Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481

Methods for protein complex prediction and their contributions towards understanding the organisation, function and dynamics of complexes.

PubMed

Srihari, Sriganesh; Yong, Chern Han; Patil, Ashwini; Wong, Limsoon

2015-09-14

Complexes of physically interacting proteins constitute fundamental functional units responsible for driving biological processes within cells. A faithful reconstruction of the entire set of complexes is therefore essential to understand the functional organisation of cells. In this review, we discuss the key contributions of computational methods developed till date (approximately between 2003 and 2015) for identifying complexes from the network of interacting proteins (PPI network). We evaluate in depth the performance of these methods on PPI datasets from yeast, and highlight their limitations and challenges, in particular at detecting sparse and small or sub-complexes and discerning overlapping complexes. We describe methods for integrating diverse information including expression profiles and 3D structures of proteins with PPI networks to understand the dynamics of complex formation, for instance, of time-based assembly of complex subunits and formation of fuzzy complexes from intrinsically disordered proteins. Finally, we discuss methods for identifying dysfunctional complexes in human diseases, an application that is proving invaluable to understand disease mechanisms and to discover novel therapeutic targets. We hope this review aptly commemorates a decade of research on computational prediction of complexes and constitutes a valuable reference for further advancements in this exciting area. Copyright © 2015 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Reliability and Construct Validity of the Psychopathic Personality Inventory-Revised in a Swedish Non-Criminal Sample - A Multimethod Approach including Psychophysiological Correlates of Empathy for Pain.

PubMed

Sörman, Karolina; Nilsonne, Gustav; Howner, Katarina; Tamm, Sandra; Caman, Shilan; Wang, Hui-Xin; Ingvar, Martin; Edens, John F; Gustavsson, Petter; Lilienfeld, Scott O; Petrovic, Predrag; Fischer, Håkan; Kristiansson, Marianne

2016-01-01

Cross-cultural investigation of psychopathy measures is important for clarifying the nomological network surrounding the psychopathy construct. The Psychopathic Personality Inventory-Revised (PPI-R) is one of the most extensively researched self-report measures of psychopathic traits in adults. To date however, it has been examined primarily in North American criminal or student samples. To address this gap in the literature, we examined PPI-R's reliability, construct validity and factor structure in non-criminal individuals (N = 227) in Sweden, using a multimethod approach including psychophysiological correlates of empathy for pain. PPI-R construct validity was investigated in subgroups of participants by exploring its degree of overlap with (i) the Psychopathy Checklist: Screening Version (PCL:SV), (ii) self-rated empathy and behavioral and physiological responses in an experiment on empathy for pain, and (iii) additional self-report measures of alexithymia and trait anxiety. The PPI-R total score was significantly associated with PCL:SV total and factor scores. The PPI-R Coldheartedness scale demonstrated significant negative associations with all empathy subscales and with rated unpleasantness and skin conductance responses in the empathy experiment. The PPI-R higher order Self-Centered Impulsivity and Fearless Dominance dimensions were associated with trait anxiety in opposite directions (positively and negatively, respectively). Overall, the results demonstrated solid reliability (test-retest and internal consistency) and promising but somewhat mixed construct validity for the Swedish translation of the PPI-R.

Reliability and Construct Validity of the Psychopathic Personality Inventory-Revised in a Swedish Non-Criminal Sample – A Multimethod Approach including Psychophysiological Correlates of Empathy for Pain

PubMed Central

Sörman, Karolina; Nilsonne, Gustav; Howner, Katarina; Tamm, Sandra; Caman, Shilan; Wang, Hui-Xin; Ingvar, Martin; Edens, John F.; Gustavsson, Petter; Lilienfeld, Scott O; Petrovic, Predrag; Fischer, Håkan; Kristiansson, Marianne

2016-01-01

Cross-cultural investigation of psychopathy measures is important for clarifying the nomological network surrounding the psychopathy construct. The Psychopathic Personality Inventory-Revised (PPI-R) is one of the most extensively researched self-report measures of psychopathic traits in adults. To date however, it has been examined primarily in North American criminal or student samples. To address this gap in the literature, we examined PPI-R’s reliability, construct validity and factor structure in non-criminal individuals (N = 227) in Sweden, using a multimethod approach including psychophysiological correlates of empathy for pain. PPI-R construct validity was investigated in subgroups of participants by exploring its degree of overlap with (i) the Psychopathy Checklist: Screening Version (PCL:SV), (ii) self-rated empathy and behavioral and physiological responses in an experiment on empathy for pain, and (iii) additional self-report measures of alexithymia and trait anxiety. The PPI-R total score was significantly associated with PCL:SV total and factor scores. The PPI-R Coldheartedness scale demonstrated significant negative associations with all empathy subscales and with rated unpleasantness and skin conductance responses in the empathy experiment. The PPI-R higher order Self-Centered Impulsivity and Fearless Dominance dimensions were associated with trait anxiety in opposite directions (positively and negatively, respectively). Overall, the results demonstrated solid reliability (test-retest and internal consistency) and promising but somewhat mixed construct validity for the Swedish translation of the PPI-R. PMID:27300292

SpirPro: A Spirulina proteome database and web-based tools for the analysis of protein-protein interactions at the metabolic level in Spirulina (Arthrospira) platensis C1.

PubMed

Senachak, Jittisak; Cheevadhanarak, Supapon; Hongsthong, Apiradee

2015-07-29

Spirulina (Arthrospira) platensis is the only cyanobacterium that in addition to being studied at the molecular level and subjected to gene manipulation, can also be mass cultivated in outdoor ponds for commercial use as a food supplement. Thus, encountering environmental changes, including temperature stresses, is common during the mass production of Spirulina. The use of cyanobacteria as an experimental platform, especially for photosynthetic gene manipulation in plants and bacteria, is becoming increasingly important. Understanding the mechanisms and protein-protein interaction networks that underlie low- and high-temperature responses is relevant to Spirulina mass production. To accomplish this goal, high-throughput techniques such as OMICs analyses are used. Thus, large datasets must be collected, managed and subjected to information extraction. Therefore, databases including (i) proteomic analysis and protein-protein interaction (PPI) data and (ii) domain/motif visualization tools are required for potential use in temperature response models for plant chloroplasts and photosynthetic bacteria. A web-based repository was developed including an embedded database, SpirPro, and tools for network visualization. Proteome data were analyzed integrated with protein-protein interactions and/or metabolic pathways from KEGG. The repository provides various information, ranging from raw data (2D-gel images) to associated results, such as data from interaction and/or pathway analyses. This integration allows in silico analyses of protein-protein interactions affected at the metabolic level and, particularly, analyses of interactions between and within the affected metabolic pathways under temperature stresses for comparative proteomic analysis. The developed tool, which is coded in HTML with CSS/JavaScript and depicted in Scalable Vector Graphics (SVG), is designed for interactive analysis and exploration of the constructed network. SpirPro is publicly available on the web at http://spirpro.sbi.kmutt.ac.th . SpirPro is an analysis platform containing an integrated proteome and PPI database that provides the most comprehensive data on this cyanobacterium at the systematic level. As an integrated database, SpirPro can be applied in various analyses, such as temperature stress response networking analysis in cyanobacterial models and interacting domain-domain analysis between proteins of interest.

RNA sequencing reveals significant miRNAs in Atypical endometrial hyperplasia.

PubMed

Tang, Shiqian; Dai, Yinmei

2018-06-01

In this paper, we aimed to investigate the miRNAs that played a regulatory role in the development of atypical endometrial hyperplasia (AEH). RNA sequencing was performed for endometrial tissues from 3 AEH patients and 3 endometrial normal hyperplasia patients. RNA sequencing data were processed and differentially expressed (DE) miRNAs were identified between AEH and controls. The target genes for DE miRNAs were identified and mapped to the protein-protein interaction (PPI) network. The miRNA related functions were predicted and miRNA-disease gene network was constructed. Total 18 DE miRNAs were overlapped in three sample groups, among which hsa-miR-577, hsa-miR-182-5p and hsa-miR-183-5p were top three miRNAs that targeting largest number of genes. Function analysis showed that the 18 overlapped miRNAs mainly related with cancer and signaling transduction related pathways. PPI network showed that total 12 genes were among top 20 genes based on three network topological features including BCL2, UMPS, MAPK13, PRKCB, CREB1, IGF1, SP1, SMAD3, IGF1R, NOTCH2, WNT5A, TK2. Top 10 miRNAs in miRNA-disease gene network were identified such as hsa-miR-577 (degree = 17), hsa-miR-182-5p (degree = 16) and hsa-miR-3609 (degree = 13). hsa-miR-577 and hsa-miR-182-5p may play regulatory role in AEH through AMPK signal pathway and Wnt signaling pathway. Copyright © 2018 Elsevier B.V. All rights reserved.

Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data.

PubMed

Li, Xiaomei; Dong, Weiwei; Qu, Xueling; Zhao, Huixia; Wang, Shuo; Hao, Yixin; Li, Qiuwen; Zhu, Jianhua; Ye, Min; Xiao, Wenhua

2017-05-01

Gastric cancer (GC) is often diagnosed in the advanced stages and is associated with a poor prognosis. Obtaining an in depth understanding of the molecular mechanisms of GC has lagged behind compared with other cancers. This study aimed to identify candidate biomarkers for GC. An integrated analysis of microarray datasets was performed to identify differentially expressed genes (DEGs) between GC and normal tissues. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then performed to identify the functions of the DEGs. Furthermore, a protein-protein interaction (PPI) network of the DEGs was constructed. The expression levels of the DEGs were validated in human GC tissues using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A set of 689 DEGs were identified in GC tissues, as compared with normal tissues, including 202 upregulated DEGs and 487 downregulated DEGs. The KEGG pathway analysis suggested that various pathways may play important roles in the pathology of GC, including pathways related to protein digestion and absorption, extracellular matrix-receptor interaction, and the metabolism of xenobiotics by cytochrome P450. The PPI network analysis indicated that the significant hub proteins consisted of SPP1, TOP2A and ARPC1B. RT-qPCR validation indicated that the expression levels of the top 10 most significantly dysexpressed genes were consistent with the illustration of the integrated analysis. The present study yielded a reference list of reliable DEGs, which represents a robust pool of candidates for further evaluation of GC pathogenesis and treatment.

Comparison of the gene expression profiles between gallstones and gallbladder polyps.

PubMed

Li, Quanfu; Ge, Xin; Xu, Xu; Zhong, Yonggang; Qie, Zengwang

2014-01-01

Gallstones and gallbladder polyps (GPs) are two major types of gallbladder diseases that share multiple common symptoms. However, their pathological mechanism remains largely unknown. The aim of our study is to identify gallstones and GPs related-genes and gain an insight into the underlying genetic basis of these diseases. We enrolled 7 patients with gallstones and 2 patients with GP for RNA-Seq and we conducted functional enrichment analysis and protein-protein interaction (PPI) networks analysis for identified differentially expressed genes (DEGs). RNA-Seq produced 41.7 million in gallstones and 32.1 million pairs in GPs. A total of 147 DEGs was identified between gallstones and GPs. We found GO terms for molecular functions significantly enriched in antigen binding (GO:0003823, P=5.9E-11), while for biological processes, the enriched GO terms were immune response (GO:0006955, P=2.6E-15), and for cellular component, the enriched GO terms were extracellular region (GO:0005576, P=2.7E-15). To further evaluate the biological significance for the DEGs, we also performed the KEGG pathway enrichment analysis. The most significant pathway in our KEGG analysis was Cytokine-cytokine receptor interaction (P=7.5E-06). PPI network analysis indicated that the significant hub proteins containing S100A9 (S100 calcium binding protein A9, Degree=94) and CR2 (complement component receptor 2, Degree=8). This present study suggests some promising genes and may provide a clue to the role of these genes playing in the development of gallstones and GPs.

Integration of multiple biological features yields high confidence human protein interactome.

PubMed

Karagoz, Kubra; Sevimoglu, Tuba; Arga, Kazim Yalcin

2016-08-21

The biological function of a protein is usually determined by its physical interaction with other proteins. Protein-protein interactions (PPIs) are identified through various experimental methods and are stored in curated databases. The noisiness of the existing PPI data is evident, and it is essential that a more reliable data is generated. Furthermore, the selection of a set of PPIs at different confidence levels might be necessary for many studies. Although different methodologies were introduced to evaluate the confidence scores for binary interactions, a highly reliable, almost complete PPI network of Homo sapiens is not proposed yet. The quality and coverage of human protein interactome need to be improved to be used in various disciplines, especially in biomedicine. In the present work, we propose an unsupervised statistical approach to assign confidence scores to PPIs of H. sapiens. To achieve this goal PPI data from six different databases were collected and a total of 295,288 non-redundant interactions between 15,950 proteins were acquired. The present scoring system included the context information that was assigned to PPIs derived from eight biological attributes. A high confidence network, which included 147,923 binary interactions between 13,213 proteins, had scores greater than the cutoff value of 0.80, for which sensitivity, specificity, and coverage were 94.5%, 80.9%, and 82.8%, respectively. We compared the present scoring method with others for evaluation. Reducing the noise inherent in experimental PPIs via our scoring scheme increased the accuracy significantly. As it was demonstrated through the assessment of process and cancer subnetworks, this study allows researchers to construct and analyze context-specific networks via valid PPI sets and one can easily achieve subnetworks around proteins of interest at a specified confidence level. Copyright © 2016 Elsevier Ltd. All rights reserved.

Characteristics of children and adolescents first prescribed proton pump inhibitors or histamine-2-receptor antagonists: an observational cohort study.

PubMed

Ruigómez, Ana; Kool-Houweling, Leanne M A; García Rodríguez, Luis A; Penning-van Beest, Fernie J A; Herings, Ron M C

2017-12-01

To describe the characteristics of pediatric patients prescribed proton pump inhibitors (PPIs) vs those of pediatric patients prescribed histamine-2-receptor antagonists (H 2 RAs). Observational studies were conducted using The Health Improvement Network (THIN) and the PHARMO Database Network. Patients aged 0-18 years who were first prescribed a PPI or H 2 RA between October 1, 2009 and September 30, 2012 (THIN) or between September 1, 2008 and August 31, 2011 (PHARMO) were included. Patient characteristics were identified and compared between the PPI and H 2 RA cohorts using odds ratios (ORs) and 95% confidence intervals (CIs) adjusted for age and sex. The mean age (years) was higher in the PPI than in the H 2 RA cohorts (THIN 12.3 [n = 8204] vs 5.4 [n = 7937], PHARMO 11.0 [n = 15 362] vs 7.1 [n = 6168]). Previous respiratory disease was more common in the PPI than in the H 2 RA cohort in THIN (OR = 1.19, 95% CI = 1.08-1.30), as were asthma and respiratory medication use in PHARMO (OR = 1.27, 95% CI = 1.12-1.45 and OR = 1.23, 95% CI = 1.10-1.38, respectively) and oral corticosteroid use in both databases (OR = 1.45, 95% CI = 1.10-1.92 [THIN]; OR = 2.80, 95% CI = 2.11-3.71 [PHARMO]). Non-steroidal anti-inflammatory drugs, antibiotics, and oral contraceptives were also more common in PPI than in H 2 RA cohorts in both databases. Pediatric patients receiving PPIs and those receiving H 2 RAs may represent different patient populations. PPIs may be more commonly prescribed than H 2 RAs among patients with respiratory diseases.

Generic Information Can Retrieve Known Biological Associations: Implications for Biomedical Knowledge Discovery

PubMed Central

van Haagen, Herman H. H. B. M.; 't Hoen, Peter A. C.; Mons, Barend; Schultes, Erik A.

2013-01-01

Motivation Weighted semantic networks built from text-mined literature can be used to retrieve known protein-protein or gene-disease associations, and have been shown to anticipate associations years before they are explicitly stated in the literature. Our text-mining system recognizes over 640,000 biomedical concepts: some are specific (i.e., names of genes or proteins) others generic (e.g., ‘Homo sapiens’). Generic concepts may play important roles in automated information retrieval, extraction, and inference but may also result in concept overload and confound retrieval and reasoning with low-relevance or even spurious links. Here, we attempted to optimize the retrieval performance for protein-protein interactions (PPI) by filtering generic concepts (node filtering) or links to generic concepts (edge filtering) from a weighted semantic network. First, we defined metrics based on network properties that quantify the specificity of concepts. Then using these metrics, we systematically filtered generic information from the network while monitoring retrieval performance of known protein-protein interactions. We also systematically filtered specific information from the network (inverse filtering), and assessed the retrieval performance of networks composed of generic information alone. Results Filtering generic or specific information induced a two-phase response in retrieval performance: initially the effects of filtering were minimal but beyond a critical threshold network performance suddenly drops. Contrary to expectations, networks composed exclusively of generic information demonstrated retrieval performance comparable to unfiltered networks that also contain specific concepts. Furthermore, an analysis using individual generic concepts demonstrated that they can effectively support the retrieval of known protein-protein interactions. For instance the concept “binding” is indicative for PPI retrieval and the concept “mutation abnormality” is indicative for gene-disease associations. Conclusion Generic concepts are important for information retrieval and cannot be removed from semantic networks without negative impact on retrieval performance. PMID:24260124

Cost-Effectiveness of Proton Pump Inhibitor Co-Therapy in Patients Taking Aspirin for Secondary Prevention of Ischemic Stroke.

PubMed

Takabayashi, Nobuyoshi; Murata, Kyoko; Tanaka, Shiro; Kawakami, Koji

2015-10-01

Low-dose aspirin (ASA) is effective for secondary prevention of ischemic stroke but can increase the risks of hemorrhagic stroke, upper gastrointestinal bleeding (UGIB), and dyspepsia. Prophylactic administration of proton pump inhibitors (PPIs) reduces the risks of these digestive symptoms. We investigated the cost effectiveness of adding a PPI to ASA therapy for ischemic stroke patients in Japan. A Markov state-transition model was developed to compare the cost effectiveness of ASA monotherapy with ASA plus PPI co-therapy in patients with histories of upper gastrointestinal ulcers and ischemic stroke. The model takes into account ASA adherence rate and adverse effects due to ASA, including hemorrhagic stroke and UGIB. The analysis was performed from the perspective of healthcare payers in 2013. In the base case, total life-years by PPI co-therapy and monotherapy were 16.005 and 15.932, respectively. The difference in duration of no therapy (no ASA or PPI) between the therapies was 558.5 days, which would prevent 30.3 recurrences of ischemic stroke per 1000 person-years. The incremental cost-effectiveness ratio of PPI co-therapy relative to monotherapy was ¥1,191,665 (US$11,458) per life-year gained. In a one-way sensitivity analysis, PPI co-therapy was consistently cost effective at a willingness to pay of ¥5,000,000 (US$48,077) per life-year gained. In a probabilistic sensitivity analysis, the probability that PPI co-therapy was cost effective was 89.74% at the willingness to pay. Co-therapy with ASA plus PPI appears to be cost-effective compared with ASA monotherapy. The addition of PPI also appeared to prolong the duration of ASA therapy, thereby reducing the risk of ischemic stroke.

Proton-pump inhibitors use, and risk of acute kidney injury: a meta-analysis of observational studies.

PubMed

Yang, Yi; George, Kaisha C; Shang, Wei-Feng; Zeng, Rui; Ge, Shu-Wang; Xu, Gang

2017-01-01

Recent studies have suggested a potential increased risk of acute kidney injury (AKI) among proton-pump inhibitor (PPI) users. However, the present results are conflicting. Thus, we performed a meta-analysis to investigate the association between PPI therapy and the risk of AKI. EMBASE, PubMed, Web of Science, and Cochrane Library databases (up to September 23, 2016) were systematically searched for any studies assessing the relationship between PPI use and risk of AKI. Studies that reported relevant risk ratios (RRs), odds ratios, or hazard ratios were included. We calculated the pooled RRs with 95% confidence intervals (CI) using a random-effects model of the meta-analysis. Subgroup analysis was conducted to explore the source of heterogeneity. Seven observational studies (five cohort studies and two case-control studies) were identified and included, and a total of 513,696 cases of PPI use among 2,404,236 participants were included in the meta-analysis. The pooled adjusted RR of AKI in patients with PPIs use was 1.61 (95% CI: 1.16-2.22; I 2 =98.1%). Furthermore, higher risks of AKI were found in the subgroups of cohort studies, participant's average age <60 years, participants with and without baseline PPI excluded, sample size <300,000, and number of adjustments ≥11. Subgroup analyses revealed that participants with or without baseline PPI excluded might be a source of heterogeneity. PPI use could be a risk factor for AKI and should be administered carefully. Nevertheless, some confounding factors might impact the outcomes. More well-designed prospective studies are needed to clarify the association.

P-Finder: Reconstruction of Signaling Networks from Protein-Protein Interactions and GO Annotations.

PubMed

Young-Rae Cho; Yanan Xin; Speegle, Greg

2015-01-01

Because most complex genetic diseases are caused by defects of cell signaling, illuminating a signaling cascade is essential for understanding their mechanisms. We present three novel computational algorithms to reconstruct signaling networks between a starting protein and an ending protein using genome-wide protein-protein interaction (PPI) networks and gene ontology (GO) annotation data. A signaling network is represented as a directed acyclic graph in a merged form of multiple linear pathways. An advanced semantic similarity metric is applied for weighting PPIs as the preprocessing of all three methods. The first algorithm repeatedly extends the list of nodes based on path frequency towards an ending protein. The second algorithm repeatedly appends edges based on the occurrence of network motifs which indicate the link patterns more frequently appearing in a PPI network than in a random graph. The last algorithm uses the information propagation technique which iteratively updates edge orientations based on the path strength and merges the selected directed edges. Our experimental results demonstrate that the proposed algorithms achieve higher accuracy than previous methods when they are tested on well-studied pathways of S. cerevisiae. Furthermore, we introduce an interactive web application tool, called P-Finder, to visualize reconstructed signaling networks.

Transoral Incisionless Fundoplication (TIF 2.0): A Meta-Analysis of Three Randomized, Controlled Clinical Trials.

PubMed

Gerson, Lauren; Stouch, Bruce; Lobonţiu, Adrian

2018-01-01

The TIF procedure has emerged as an endoscopic treatment for patients with refractory gastro-esophageal reflux disease (GERD). Previous systematic reviews of the TIF procedure conflated findings from studies with modalities that do not reflect the current 2.0 procedure technique or refined data-backed patient selection criteria. A meta-analysis was conducted using data only from randomized studies that assessed the TIF 2.0 procedure compared to a control. The purpose of the meta-analysis was to determine the efficacy and long-term outcomes associated with performance of the TIF 2.0 procedure in patients with chronic long-term refractory GERD on optimized PPI therapy, including esophageal pH, PPI utilization and quality of life. Methods: Three prospective research questions were predicated on the outcomes of the TIF procedure compared to patients who received PPI therapy or sham, concomitant treatment for GERD, and the patient-reported quality of life. Event rates were calculated using the random effect model. Since the time of follow-up post-TIF procedure was variable, analysis was performed to incorporate the time of follow-up for each individual patient at the 3-year time point. Results: Results from this meta-analysis, including data from 233 patients, demonstrated that TIF subjects at 3 years had improved esophageal pH, a decrease in PPI utilization, and improved quality of life. Conclusions: In a meta-analysis of randomized, controlled trials (RCTs), the TIF procedure data for patients with GERD refractory to PPI's produces significant changes, compared with sham or PPI therapy, in esophageal pH, decreased PPI utilization, and improved quality of life. Celsius.

Target gene screening and evaluation of prognostic values in non-small cell lung cancers by bioinformatics analysis.

PubMed

Piao, Junjie; Sun, Jie; Yang, Yang; Jin, Tiefeng; Chen, Liyan; Lin, Zhenhua

2018-03-20

Non-small cell lung cancer (NSCLC) is the major leading cause of cancer-related deaths worldwide. This study aims to explore molecular mechanism of NSCLC. Microarray dataset was obtained from the Gene Expression Omnibus (GEO) database, and analyzed by using GEO2R. Functional and pathway enrichment analysis were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Then, STRING, Cytoscape and MCODE were applied to construct the Protein-protein interaction (PPI) network and screen hub genes. Following, overall survival (OS) analysis of hub genes was performed by using the Kaplan-Meier plotter online tool. Moreover, miRecords was also applied to predict the targets of the differentially expressed microRNAs (DEMs). A total of 228 DEGs were identified, and they were mainly enriched in the terms of cell adhesion molecules, leukocyte transendothelial migration and ECM-receptor interaction. A PPI network was constructed, and 16 hub genes were identified, including TEK, ANGPT1, MMP9, VWF, CDH5, EDN1, ESAM, CCNE1, CDC45, PRC1, CCNB2, AURKA, MELK, CDC20, TOP2A and PTTG1. Among the genes, expressions of 14 hub genes were associated with prognosis of NSCLC patients. Additionally, a total of 11 DEMs were also identified. Our results provide some potential underlying biomarkers for NSCLC. Further studies are required to elucidate the pathogenesis of NSCLC. Copyright © 2018 Elsevier B.V. All rights reserved.

Gastroprotective strategies in chronic NSAID users: a cost-effectiveness analysis comparing single-tablet formulations with individual components.

PubMed

de Groot, N L; Spiegel, B M R; van Haalen, H G M; de Wit, N J; Siersema, P D; van Oijen, M G H

2013-01-01

To evaluate the cost-effectiveness of competing gastroprotective strategies, including single-tablet formulations, in the prevention of gastrointestinal (GI) complications in patients with chronic arthritis taking nonsteroidal anti-inflammatory drugs (NSAIDs). We performed a cost-utility analysis to compare eight gastroprotective strategies including NSAIDs, cyclooxygenase-2 inhibitors, proton pump inhibitors (PPIs), histamine-2 receptor antagonists, misoprostol, and single-tablet formulations. We derived estimates for outcomes and costs from medical literature. The primary outcome was incremental cost per quality-adjusted life-year gained. We performed sensitivity analyses to assess the effect of GI complications, compliance rates, and drug costs. For average-risk patients, NSAID + PPI cotherapy was most cost-effective. The NSAID/PPI single-tablet formulation became cost-effective only when its price decreased from €0.78 to €0.56 per tablet, or when PPI compliance fell below 51% in the NSAID + PPI strategy. All other strategies were more costly and less effective. The model was highly sensitive to the GI complication risk, costs of PPI and NSAID/PPI single-tablet formulation, and compliance to PPI. In patients with a threefold higher risk of GI complications, both NSAID + PPI cotherapy and single-tablet formulation were cost-effective. NSAID + PPI cotherapy is the most cost-effective strategy in all patients with chronic arthritis irrespective of their risk for GI complications. For patients with increased GI risk, the NSAID/PPI single-tablet formulation is also cost-effective. Copyright © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Forensic genetic study of 29 Y-STRs in Korean population.

PubMed

Jung, Ju Yeon; Park, Ji-Hye; Oh, Yu-Li; Kwon, Han-Sol; Park, Hyun-Chul; Park, Kyung-Hwa; Kim, Eun Hye; Lee, Dong-Sub; Lim, Si-Keun

2016-11-01

In this study, we compared two recently released commercial Y-chromosomal short tandem repeat (Y-STR) kits: the PowerPlex Y23 System (PPY23) and Yfiler® Plus PCR amplification kit (YPlus). We performed validation studies, including sensitivity, tolerance to PCR inhibitors, and mixture analysis, and a population genetics study using 306 unrelated South Korean males. PPY23 and YPlus showed similar sensitivity, but PPY23 showed higher tolerance to humic acid than YPlus. Furthermore, the detection rate of unique minor alleles called from male/male mixtures was higher for PPY23 than for YPlus. Comparing the newly added loci, the mean values of gene diversity for PPY23 and YPlus were 0.6715 and 0.8158, respectively. The discrimination capacity in the 306 unrelated South Korean males for PPY23 was 0.9837, and that for YPlus was 0.9935. These results will inform the selection of suitable Y-STR kits based on the purpose of forensic DNA analysis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Increased functional connectivity with puberty in the mentalising network involved in social emotion processing

PubMed Central

Klapwijk, Eduard T.; Goddings, Anne-Lise; Heyes, Stephanie Burnett; Bird, Geoffrey; Viner, Russell M.; Blakemore, Sarah-Jayne

2015-01-01

There is increasing evidence that puberty plays an important role in the structural and functional brain development seen in adolescence, but little is known of the pubertal influence on changes in functional connectivity. We explored how pubertal indicators (salivary concentrations of testosterone, oestradiol and DHEA; pubertal stage; menarcheal status) relate to functional connectivity between components of a mentalising network identified to be engaged in social emotion processing by our prior work, using psychophysiological interaction (PPI) analysis. Female adolescents aged 11 to 13 years were scanned whilst silently reading scenarios designed to evoke either social emotions (guilt and embarrassment) or basic emotions (disgust and fear), of which only social compared to basic emotions require the representation of another person’s mental states. Pubertal stage and menarcheal status were used to assign participants to pre/early or mid/late puberty groups. We found increased functional connectivity between the dorsomedial prefrontal cortex (DMPFC) and the right posterior superior temporal sulcus (pSTS) and right temporo-parietal junction (TPJ) during social relative to basic emotion processing. Moreover, increasing oestradiol concentrations were associated with increased functional connectivity between the DMPFC and the right TPJ during social relative to basic emotion processing, independent of age. Our analysis of the PPI data by phenotypic pubertal status showed that more advanced puberty stage was associated with enhanced functional connectivity between the DMPFC and the left anterior temporal cortex (ATC) during social relative to basic emotion processing, also independent of age. Our results suggest increased functional maturation of the social brain network with the advancement of puberty in girls. PMID:23998674

Key genes and pathways in measles and their interaction with environmental chemicals

PubMed Central

Zhang, Rongqiang; Jiang, Hualin; Li, Fengying; Su, Ning; Ding, Yi; Mao, Xiang; Ren, Dan; Wang, Jing

2018-01-01

The aim of the present study was to explore key genes that may have a role in the pathology of measles virus infection and to clarify the interaction networks between environmental factors and differentially expressed genes (DEGs). After screening the database of the Gene Expression Omnibus of the National Center for Biotechnology Information, the dataset GSE5808 was downloaded and analyzed. A global normalization method was performed to minimize data inconsistencies and heterogeneity. DEGs during different stages of measles virus infection were explored using R software (v3.4.0). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the DEGs were performed using Cytoscape 3.4.0 software. A protein-protein interaction (PPI) network of the DEGs was obtained from the STRING database v9.05. A total of 43 DEGs were obtained from four analyzed sample groups, including 10 highly expressed genes and 33 genes with decreased expression. The most enriched pathways based on KEGG analysis were fatty acid elongation, cytokine-cytokine receptor interaction and RNA degradation. The genes mentioned in the PPI network were mainly associated with protein binding and chemokine activity. A total of 219 chemicals were identified that may, jointly or on their own, interact with the 6 DEGs between the control group and patients with measles (at hospital entry), including benzo(a)pyrene (BaP) and tetrachlorodibenzodioxin (TCDD). In conclusion, the present study revealed that chemokines and environmental chemicals, e.g. BaP and TCDD, may affect the development of measles. PMID:29805511

Sliding-window analysis tracks fluctuations in amygdala functional connectivity associated with physiological arousal and vigilance during fear conditioning.

PubMed

Baczkowski, Blazej M; Johnstone, Tom; Walter, Henrik; Erk, Susanne; Veer, Ilya M

2017-06-01

We evaluated whether sliding-window analysis can reveal functionally relevant brain network dynamics during a well-established fear conditioning paradigm. To this end, we tested if fMRI fluctuations in amygdala functional connectivity (FC) can be related to task-induced changes in physiological arousal and vigilance, as reflected in the skin conductance level (SCL). Thirty-two healthy individuals participated in the study. For the sliding-window analysis we used windows that were shifted by one volume at a time. Amygdala FC was calculated for each of these windows. Simultaneously acquired SCL time series were averaged over time frames that corresponded to the sliding-window FC analysis, which were subsequently regressed against the whole-brain seed-based amygdala sliding-window FC using the GLM. Surrogate time series were generated to test whether connectivity dynamics could have occurred by chance. In addition, results were contrasted against static amygdala FC and sliding-window FC of the primary visual cortex, which was chosen as a control seed, while a physio-physiological interaction (PPI) was performed as cross-validation. During periods of increased SCL, the left amygdala became more strongly coupled with the bilateral insula and anterior cingulate cortex, core areas of the salience network. The sliding-window analysis yielded a connectivity pattern that was unlikely to have occurred by chance, was spatially distinct from static amygdala FC and from sliding-window FC of the primary visual cortex, but was highly comparable to that of the PPI analysis. We conclude that sliding-window analysis can reveal functionally relevant fluctuations in connectivity in the context of an externally cued task. Copyright © 2017 Elsevier Inc. All rights reserved.

Effect of graphene oxide on the structural and electrochemical behavior of polypyrrole deposited on cotton fabric

NASA Astrophysics Data System (ADS)

Yaghoubidoust, Fatemeh; Wicaksono, Dedy H. B.; Chandren, Sheela; Nur, Hadi

2014-10-01

Improving the electrical response of polypyrrole-cotton composite is the key issue in making flexible electrode with favorable mechanical strength and large capacitance. Flexible graphene oxide/cotton (GO/Cotton) composite has been prepared by dipping pristine cotton in GO ink. The composite‘s surface was further modified with polypyrrole (Ppy) via chemical polymerization to obtain Ppy/GO/Cotton composite. The composite was characterized using SEM, FTIR and XRD measurements, while the influence of GO in modifying the physicochemical properties of the composite was also examined using TG and cyclic voltammetry. The achieved mean particle size for Ppy/Cotton, Ppy/GO/Cotton and GO estimated using Scherrer formula are 58, 67 and 554 nm, respectively. FTIR spectra revealed prominent fundamental absorption bands in the range of 1400-1800 cm-1. The increased electrical conductivity as much as 2.2 × 10-1 S cm-1 for Ppy/GO/Cotton composite measured by complex impedance, is attributed to the formation of continuous conducting network. The partial reduction of GO on the surface of cotton (GO/Cotton) during chemical polymerization can also affect the conductivity. This simple, economic and environmental-friendly preparation method may contribute towards the controlled growth of quality and stable Ppy/GO/Cotton composites for potential applications in microwave attenuation, energy storage system, static electric charge dissipation and electrotherapy.

Evolutionary model selection and parameter estimation for protein-protein interaction network based on differential evolution algorithm

PubMed Central

Huang, Lei; Liao, Li; Wu, Cathy H.

2016-01-01

Revealing the underlying evolutionary mechanism plays an important role in understanding protein interaction networks in the cell. While many evolutionary models have been proposed, the problem about applying these models to real network data, especially for differentiating which model can better describe evolutionary process for the observed network urgently remains as a challenge. The traditional way is to use a model with presumed parameters to generate a network, and then evaluate the fitness by summary statistics, which however cannot capture the complete network structures information and estimate parameter distribution. In this work we developed a novel method based on Approximate Bayesian Computation and modified Differential Evolution (ABC-DEP) that is capable of conducting model selection and parameter estimation simultaneously and detecting the underlying evolutionary mechanisms more accurately. We tested our method for its power in differentiating models and estimating parameters on the simulated data and found significant improvement in performance benchmark, as compared with a previous method. We further applied our method to real data of protein interaction networks in human and yeast. Our results show Duplication Attachment model as the predominant evolutionary mechanism for human PPI networks and Scale-Free model as the predominant mechanism for yeast PPI networks. PMID:26357273

Determining Effects of Non-synonymous SNPs on Protein-Protein Interactions using Supervised and Semi-supervised Learning

PubMed Central

Zhao, Nan; Han, Jing Ginger; Shyu, Chi-Ren; Korkin, Dmitry

2014-01-01

Single nucleotide polymorphisms (SNPs) are among the most common types of genetic variation in complex genetic disorders. A growing number of studies link the functional role of SNPs with the networks and pathways mediated by the disease-associated genes. For example, many non-synonymous missense SNPs (nsSNPs) have been found near or inside the protein-protein interaction (PPI) interfaces. Determining whether such nsSNP will disrupt or preserve a PPI is a challenging task to address, both experimentally and computationally. Here, we present this task as three related classification problems, and develop a new computational method, called the SNP-IN tool (non-synonymous SNP INteraction effect predictor). Our method predicts the effects of nsSNPs on PPIs, given the interaction's structure. It leverages supervised and semi-supervised feature-based classifiers, including our new Random Forest self-learning protocol. The classifiers are trained based on a dataset of comprehensive mutagenesis studies for 151 PPI complexes, with experimentally determined binding affinities of the mutant and wild-type interactions. Three classification problems were considered: (1) a 2-class problem (strengthening/weakening PPI mutations), (2) another 2-class problem (mutations that disrupt/preserve a PPI), and (3) a 3-class classification (detrimental/neutral/beneficial mutation effects). In total, 11 different supervised and semi-supervised classifiers were trained and assessed resulting in a promising performance, with the weighted f-measure ranging from 0.87 for Problem 1 to 0.70 for the most challenging Problem 3. By integrating prediction results of the 2-class classifiers into the 3-class classifier, we further improved its performance for Problem 3. To demonstrate the utility of SNP-IN tool, it was applied to study the nsSNP-induced rewiring of two disease-centered networks. The accurate and balanced performance of SNP-IN tool makes it readily available to study the rewiring of large-scale protein-protein interaction networks, and can be useful for functional annotation of disease-associated SNPs. SNIP-IN tool is freely accessible as a web-server at http://korkinlab.org/snpintool/. PMID:24784581

Reporting and appraising the context, process and impact of PPI on contributors, researchers and the trial during a randomised controlled trial - the 3D study.

PubMed

Mann, Cindy; Chilcott, Simon; Plumb, Katrina; Brooks, Edmund; Man, Mei-See

2018-01-01

Including patient and public involvement (PPI) in health research is thought to improve research but it is hard to be clear exactly how it helps. This is because PPI takes many forms, is sometimes only token and is not always reported clearly. This makes it difficult to combine the evidence so that clear conclusions can be reached about the ingredients of successful PPI and what PPI achieves. Previous research that has tried to combine the evidence has led to several guidelines for researchers to use in setting up and reporting PPI.This paper was written jointly by researchers and PPI contributors as a reflection on our experiences. The aim was to add to the evidence, by giving detail about the use of PPI in a large randomised controlled trial and the effect it had. We were guided by published PPI reporting guidelines. The effects on the trial are shown in a table of changes made because of suggestions from the PPI group. A survey was used to ask PPI contributors and researchers about their experience and effects they had noticed. Three themes were noted: impact on the trial, the effect of involvement on individual researchers and group members, and group environment. The PPI work affected the trial in many ways, including changes to documents used in the trial and advice on qualitative data collection methods and analysis. Individuals reported positive effects, including enjoying being in the group, gaining confidence, and learning how to share views. Patient and public involvement (PPI) is believed to enhance health care delivery research, and is widely required in research proposals. Detailed, standardised reporting of PPI is needed so that strategies to implement more than token PPI that achieves impact can be identified, properly evaluated and reproduced. Impact includes effects on the research, PPI contributors and researchers. Using contributor and researcher perspectives and drawing on published guidelines for reporting PPI, we aimed to reflect on our experience and contribute evidence relevant to two important questions: 'What difference does PPI make?' and 'What's the best way to do it?' Fourteen people living with multiple long-term conditions (multimorbidity) were PPI contributors to a randomised controlled trial to improve care for people with multimorbidity. Meetings took place approximately four times a year throughout the trial, beginning at grant application stage. Meeting notes were recorded and a log of PPI involvement was kept. At the end of the trial, seven PPI contributors and four researchers completed free-text questionnaires about their experience of PPI involvement and their perception of PPI impact. The responses were analysed thematically by two PPI contributors and one researcher. The PPI group proposed writing this report, which was co-authored by three PPI contributors and two researchers. Meeting attendance averaged nine PPI contributors and three to four researchers. The involvement log and meeting notes recorded a wide range of activities and impact including changes to participant documentation, advice on qualitative data collection, contribution to data analysis and dissemination advice. Three themes were identified from the questionnaires: impact on the study, including keeping the research grounded in patient experience; impact on individuals, including learning from group diversity and feeling valued; and an environment that facilitated participation. The size of the group influenced impact. Researchers and PPI contributors described a rewarding interaction that benefitted them and the research. PPI was wide-ranging and had impact on the trial, contributors and researchers. The group environment facilitated involvement. Feedback and group interactions benefitted individuals. The insights gained from this study will postitively influence the researchers' and contributors' future involvement with PPI.

Analysis of nonformulary use of PPIs and excess drug cost in a Veterans Affairs population.

PubMed

Ajumobi, Adewale B; Vuong, Ronald; Ahaneku, Hycienth

2012-01-01

In the Veterans Affairs (VA) health care system, a formulary-based approach without beneficiary cost-share incentives is used to limit the pharmacy cost of proton pump inhibitors (PPIs). However, the effectiveness of this approach in reducing the cost of PPIs is unknown. To (a) compare cost differences between the formulary PPI (generic omeprazole) and nonformulary PPIs and (b) evaluate reasons for nonformulary PPI use in order to identify opportunities to increase formulary drug use and discourage unnecessary use of nonformulary PPIs. A list of patients with receipt of PPIs from July 1, 2008, through June 30, 2009, was obtained from the Loma Linda VA Healthcare System pharmacy. Subjects with receipt of at least 120 units (capsules or tablets) of any PPI in the study period were considered long-term users. Demographic information was collected. Pharmacy consult records were reviewed to identify reasons for nonformulary use and dosing regimen of the formulary PPI prior to the switch. Cost analysis was done based on the VA contract prices for the drugs at the time of the study. Of 58,605 unique patients seen in this VA health care system in the 12-month period from July 1, 2008, through June 30, 2009, 13,713 (23.4%) received a PPI, and of these, 10,483 (76.4%) received at least 120 PPI units and were defined as long-term users. Of the long-term users, 9,462 (90.3%) were on the formulary PPI generic omeprazole, and 1,021 were nonformulary PPI users. Use of nonformulary PPIs (esomeprazole, pantoprazole, lansoprazole, rabeprazole) accounted for 10.5% of the PPI units and 9.7% of the users but 57.3% of total PPI cost. This pattern resulted in $570,263 in excess spending (i.e., $570,263 would have been saved in the study period if the nonformulary PPI users had used the formulary drug). The most common reason for nonformulary long-term PPI use was persistent symptoms (n=901, 88.2%). Adverse reaction was cited by 111 (10.9%) of nonformulary PPI users, 33.3% (n=37) of whom reported diarrhea. Of those who switched to a nonformulary PPI due to persistent symptoms, 363 (40.3%) were on once-daily dosing prior to the switch; 379 (42.1%) were on twice-daily dosing; and 159 (17.6%) were transfers from other places in which prior dosing information was not available in the hospital pharmacy records. One-year PPI use prevalence was 23% in this VA population, and long-term use prevalence was 18%. Nonformulary PPI use accounted for 10.5% of the PPI units and 9.7% of the users but 57.3% of total PPI drug cost. Opportunities to reduce nonformulary PPI use in order to reduce overall expenditures on PPIs include verification of optimal formulary PPI use, titration to twice-daily dosing, and confirmation of adverse reaction as being attributable to PPI use.

Integrative Analysis of GWASs, Human Protein Interaction, and Gene Expression Identified Gene Modules Associated With BMDs

PubMed Central

He, Hao; Zhang, Lei; Li, Jian; Wang, Yu-Ping; Zhang, Ji-Gang; Shen, Jie; Guo, Yan-Fang

2014-01-01

Context: To date, few systems genetics studies in the bone field have been performed. We designed our study from a systems-level perspective by integrating genome-wide association studies (GWASs), human protein-protein interaction (PPI) network, and gene expression to identify gene modules contributing to osteoporosis risk. Methods: First we searched for modules significantly enriched with bone mineral density (BMD)-associated genes in human PPI network by using 2 large meta-analysis GWAS datasets through a dense module search algorithm. One included 7 individual GWAS samples (Meta7). The other was from the Genetic Factors for Osteoporosis Consortium (GEFOS2). One was assigned as a discovery dataset and the other as an evaluation dataset, and vice versa. Results: In total, 42 modules and 129 modules were identified significantly in both Meta7 and GEFOS2 datasets for femoral neck and spine BMD, respectively. There were 3340 modules identified for hip BMD only in Meta7. As candidate modules, they were assessed for the biological relevance to BMD by gene set enrichment analysis in 2 expression profiles generated from circulating monocytes in subjects with low versus high BMD values. Interestingly, there were 2 modules significantly enriched in monocytes from the low BMD group in both gene expression datasets (nominal P value <.05). Two modules had 16 nonredundant genes. Functional enrichment analysis revealed that both modules were enriched for genes involved in Wnt receptor signaling and osteoblast differentiation. Conclusion: We highlighted 2 modules and novel genes playing important roles in the regulation of bone mass, providing important clues for therapeutic approaches for osteoporosis. PMID:25119315

Analysis of gene expression profile microarray data in complex regional pain syndrome.

PubMed

Tan, Wulin; Song, Yiyan; Mo, Chengqiang; Jiang, Shuangjian; Wang, Zhongxing

2017-09-01

The aim of the present study was to predict key genes and proteins associated with complex regional pain syndrome (CRPS) using bioinformatics analysis. The gene expression profiling microarray data, GSE47603, which included peripheral blood samples from 4 patients with CRPS and 5 healthy controls, was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) in CRPS patients compared with healthy controls were identified using the GEO2R online tool. Functional enrichment analysis was then performed using The Database for Annotation Visualization and Integrated Discovery online tool. Protein‑protein interaction (PPI) network analysis was subsequently performed using Search Tool for the Retrieval of Interaction Genes database and analyzed with Cytoscape software. A total of 257 DEGs were identified, including 243 upregulated genes and 14 downregulated ones. Genes in the human leukocyte antigen (HLA) family were most significantly differentially expressed. Enrichment analysis demonstrated that signaling pathways, including immune response, cell motion, adhesion and angiogenesis were associated with CRPS. PPI network analysis revealed that key genes, including early region 1A binding protein p300 (EP300), CREB‑binding protein (CREBBP), signal transducer and activator of transcription (STAT)3, STAT5A and integrin α M were associated with CRPS. The results suggest that the immune response may therefore serve an important role in CRPS development. In addition, genes in the HLA family, such as HLA‑DQB1 and HLA‑DRB1, may present potential biomarkers for the diagnosis of CRPS. Furthermore, EP300, its paralog CREBBP, and the STAT family genes, STAT3 and STAT5 may be important in the development of CRPS.

A novel method based on new adaptive LVQ neural network for predicting protein-protein interactions from protein sequences.

PubMed

Yousef, Abdulaziz; Moghadam Charkari, Nasrollah

2013-11-07

Protein-Protein interaction (PPI) is one of the most important data in understanding the cellular processes. Many interesting methods have been proposed in order to predict PPIs. However, the methods which are based on the sequence of proteins as a prior knowledge are more universal. In this paper, a sequence-based, fast, and adaptive PPI prediction method is introduced to assign two proteins to an interaction class (yes, no). First, in order to improve the presentation of the sequences, twelve physicochemical properties of amino acid have been used by different representation methods to transform the sequence of protein pairs into different feature vectors. Then, for speeding up the learning process and reducing the effect of noise PPI data, principal component analysis (PCA) is carried out as a proper feature extraction algorithm. Finally, a new and adaptive Learning Vector Quantization (LVQ) predictor is designed to deal with different models of datasets that are classified into balanced and imbalanced datasets. The accuracy of 93.88%, 90.03%, and 89.72% has been found on S. cerevisiae, H. pylori, and independent datasets, respectively. The results of various experiments indicate the efficiency and validity of the method. © 2013 Published by Elsevier Ltd.

Construction and analysis of protein-protein interaction network correlated with ankylosing spondylitis.

PubMed

Kanwal, Attiya; Fazal, Sahar

2018-01-05

Ankylosing spondylitis, a systemic illness is a foundation of progressing joint swelling that for the most part influences the spine. However, it frequently causes aggravation in different joints far from the spine, and in addition organs, for example, the eyes, heart, lungs, and kidneys. It's an immune system ailment that may be activated by specific sorts of bacterial or viral diseases that initiate an invulnerable reaction that don't close off after the contamination is recuperated. The particular reason for ankylosing spondylitis is obscure, yet hereditary qualities assume a huge part in this condition. The rising apparatuses of network medicine offer a stage to investigate an unpredictable illness at framework level. In this study, we meant to recognize the key proteins and the biological regulator pathways including in AS and further investigating the molecular connectivity between these pathways by the topological examination of the Protein-protein communication (PPI) system. The extended network including of 93 nodes and have 199 interactions respectively scanned from STRING database and some separated small networks. 24 proteins with high BC at the threshold of 0.01 and 55 proteins with large degree at the threshold of 1 have been identified. CD4 with highest BC and Closeness centrality located in the centre of the network. The backbone network derived from high BC proteins presents a clear and visual overview which shows all important regulatory pathways for AS and the crosstalk between them. The finding of this research suggests that AS variation is orchestrated by an integrated PPI network centered on CD4 out of 93 nodes. Ankylosing spondylitis, a systemic disease is an establishment of advancing joint swelling that generally impacts the spine. Be that as it may, it as often as possible causes disturbance in various joints a long way from the spine, and what's more organs. It's a resistant framework affliction that might be actuated by particular sorts of bacterial or viral ailments that start an immune response that don't shut off after the pollution is recovered. The specific explanation behind AS is dark, yet innate qualities expect a colossal part in this condition. The rising devices of system solution offer a phase to examine an erratic ailment at structure level. In this study, we intended to perceive the key proteins and the natural controller pathways incorporating into AS. The finding of this research proposes that AS variety is organized by a coordinated PPI system focused on CD4. Copyright © 2017 Elsevier B.V. All rights reserved.

Proton pump inhibitors increase the incidence of bone fractures in hepatitis C patients.

PubMed

Mello, Michael; Weideman, Rick A; Little, Bertis B; Weideman, Mark W; Cryer, Byron; Brown, Geri R

2012-09-01

While proton pump inhibitors (PPI) may increase the risk of bone fractures, the incidence of new bone fractures in a chronic hepatitis C virus (HCV) infected cohort, with or without PPI exposure, has not been explored. A retrospective cohort study of the incidence of bone fractures over 10 years in 9,437 HCV antibody positive patients in the Dallas VA Hepatitis C Registry was performed. The study endpoint was the incidence of verified new bone fractures per patient-years (pt-yrs) in PPI users compared to non-PPI users. PPI use was defined as those taking a PPI for ≥360 days. Pt-yrs of exposure for PPI users began on the first PPI prescription date, and pt-yrs of exposure for non-PPI users began with first date of any non-PPI prescription. For both HCV groups, the final date of patients' study duration was defined by end of PPI exposure, bone fracture occurrence, death or end of study evaluation period. Exclusion criteria included use of bone health modifying medications ≥30 days. Statistical differences in fracture incidence between groups were determined by multivariate regression analysis. Among the total study population analyzed (n = 2,573), 109 bone fractures occurred. Unadjusted bone fracture incidences were 13.99/1,000 pt-yrs vs. 5.86/1,000 pt-yrs in PPI and non-PPI users, respectively. The adjusted hazard ratio for new bone fractures was 3.87 (95 % CI 2.46-6.08) (p < 0.001) in PPI users. In patients with chronic HCV, use of PPI for >1 year increased the risk of new bone fractures by more than threefold.

Evidence of Probabilistic Behaviour in Protein Interaction Networks

DTIC Science & Technology

2008-01-31

Evidence of degree-weighted connectivity in nine PPI networks. a, Homo sapiens (human); b, Drosophila melanogaster (fruit fly); c-e, Saccharomyces...illustrates maps for the networks of Homo sapiens and Dro- sophila melanogaster, while maps for the remaining net- works are provided in Additional file 2. As...protein-protein interaction networks. a, Homo sapiens ; b, Drosophila melanogaster. Distances shown as average shortest path lengths L(k1, k2) between

Identification of potential crucial genes associated with steroid-induced necrosis of femoral head based on gene expression profile.

PubMed

Lin, Zhe; Lin, Yongsheng

2017-09-05

The aim of this study was to explore potential crucial genes associated with the steroid-induced necrosis of femoral head (SINFH) and to provide valid biological information for further investigation of SINFH. Gene expression profile of GSE26316, generated from 3 SINFH rat samples and 3 normal rat samples were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were identified using LIMMA package. After functional enrichment analyses of DEGs, protein-protein interaction (PPI) network and sub-PPI network analyses were conducted based on the STRING database and cytoscape. In total, 59 up-regulated DEGs and 156 downregulated DEGs were identified. The up-regulated DEGs were mainly involved in functions about immunity (e.g. Fcer1A and Il7R), and the downregulated DEGs were mainly enriched in muscle system process (e.g. Tnni2, Mylpf and Myl1). The PPI network of DEGs consisted of 123 nodes and 300 interactions. Tnni2, Mylpf, and Myl1 were the top 3 outstanding genes based on both subgraph centrality and degree centrality evaluation. These three genes interacted with each other in the network. Furthermore, the significant network module was composed of 22 downregulated genes (e.g. Tnni2, Mylpf and Myl1). These genes were mainly enriched in functions like muscle system process. The DEGs related to the regulation of immune system process (e.g. Fcer1A and Il7R), and DEGs correlated with muscle system process (e.g. Tnni2, Mylpf and Myl1) may be closely associated with the progress of SINFH, which is still needed to be confirmed by experiments. Copyright © 2017 Elsevier B.V. All rights reserved.

Querying graphs in protein-protein interactions networks using feedback vertex set.

PubMed

Blin, Guillaume; Sikora, Florian; Vialette, Stéphane

2010-01-01

Recent techniques increase rapidly the amount of our knowledge on interactions between proteins. The interpretation of these new information depends on our ability to retrieve known substructures in the data, the Protein-Protein Interactions (PPIs) networks. In an algorithmic point of view, it is an hard task since it often leads to NP-hard problems. To overcome this difficulty, many authors have provided tools for querying patterns with a restricted topology, i.e., paths or trees in PPI networks. Such restriction leads to the development of fixed parameter tractable (FPT) algorithms, which can be practicable for restricted sizes of queries. Unfortunately, Graph Homomorphism is a W[1]-hard problem, and hence, no FPT algorithm can be found when patterns are in the shape of general graphs. However, Dost et al. gave an algorithm (which is not implemented) to query graphs with a bounded treewidth in PPI networks (the treewidth of the query being involved in the time complexity). In this paper, we propose another algorithm for querying pattern in the shape of graphs, also based on dynamic programming and the color-coding technique. To transform graphs queries into trees without loss of informations, we use feedback vertex set coupled to a node duplication mechanism. Hence, our algorithm is FPT for querying graphs with a bounded size of their feedback vertex set. It gives an alternative to the treewidth parameter, which can be better or worst for a given query. We provide a python implementation which allows us to validate our implementation on real data. Especially, we retrieve some human queries in the shape of graphs into the fly PPI network.

Exploring of the molecular mechanism of rhinitis via bioinformatics methods

PubMed Central

Song, Yufen; Yan, Zhaohui

2018-01-01

The aim of this study was to analyze gene expression profiles for exploring the function and regulatory network of differentially expressed genes (DEGs) in pathogenesis of rhinitis by a bioinformatics method. The gene expression profile of GSE43523 was downloaded from the Gene Expression Omnibus database. The dataset contained 7 seasonal allergic rhinitis samples and 5 non-allergic normal samples. DEGs between rhinitis samples and normal samples were identified via the limma package of R. The webGestal database was used to identify enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the DEGs. The differentially co-expressed pairs of the DEGs were identified via the DCGL package in R, and the differential co-expression network was constructed based on these pairs. A protein-protein interaction (PPI) network of the DEGs was constructed based on the Search Tool for the Retrieval of Interacting Genes database. A total of 263 DEGs were identified in rhinitis samples compared with normal samples, including 125 downregulated ones and 138 upregulated ones. The DEGs were enriched in 7 KEGG pathways. 308 differential co-expression gene pairs were obtained. A differential co-expression network was constructed, containing 212 nodes. In total, 148 PPI pairs of the DEGs were identified, and a PPI network was constructed based on these pairs. Bioinformatics methods could help us identify significant genes and pathways related to the pathogenesis of rhinitis. Steroid biosynthesis pathway and metabolic pathways might play important roles in the development of allergic rhinitis (AR). Genes such as CDC42 effector protein 5, solute carrier family 39 member A11 and PR/SET domain 10 might be also associated with the pathogenesis of AR, which provided references for the molecular mechanisms of AR. PMID:29257233

A Generalized Form of Context-Dependent Psychophysiological Interactions (gPPI): A Comparison to Standard Approaches

PubMed Central

McLaren, Donald G.; Ries, Michele L.; Xu, Guofan; Johnson, Sterling C.

2012-01-01

Functional MRI (fMRI) allows one to study task-related regional responses and task-dependent connectivity analysis using psychophysiological interaction (PPI) methods. The latter affords the additional opportunity to understand how brain regions interact in a task-dependent manner. The current implementation of PPI in Statistical Parametric Mapping (SPM8) is configured primarily to assess connectivity differences between two task conditions, when in practice fMRI tasks frequently employ more than two conditions. Here we evaluate how a generalized form of context-dependent PPI (gPPI; http://www.nitrc.org/projects/gppi), which is configured to automatically accommodate more than two task conditions in the same PPI model by spanning the entire experimental space, compares to the standard implementation in SPM8. These comparisons are made using both simulations and an empirical dataset. In the simulated dataset, we compare the interaction beta estimates to their expected values and model fit using the Akaike Information Criterion (AIC). We found that interaction beta estimates in gPPI were robust to different simulated data models, were not different from the expected beta value, and had better model fits than when using standard PPI (sPPI) methods. In the empirical dataset, we compare the model fit of the gPPI approach to sPPI. We found that the gPPI approach improved model fit compared to sPPI. There were several regions that became non-significant with gPPI. These regions all showed significantly better model fits with gPPI. Also, there were several regions where task-dependent connectivity was only detected using gPPI methods, also with improved model fit. Regions that were detected with all methods had more similar model fits. These results suggest that gPPI may have greater sensitivity and specificity than standard implementation in SPM. This notion is tempered slightly as there is no gold standard; however, data simulations with a known outcome support our conclusions about gPPI. In sum, the generalized form of context-dependent PPI approach has increased flexibility of statistical modeling, and potentially improves model fit, specificity to true negative findings, and sensitivity to true positive findings. PMID:22484411

Stringent DDI-based prediction of H. sapiens-M. tuberculosis H37Rv protein-protein interactions.

PubMed

Zhou, Hufeng; Rezaei, Javad; Hugo, Willy; Gao, Shangzhi; Jin, Jingjing; Fan, Mengyuan; Yong, Chern-Han; Wozniak, Michal; Wong, Limsoon

2013-01-01

H. sapiens-M. tuberculosis H37Rv protein-protein interaction (PPI) data are very important information to illuminate the infection mechanism of M. tuberculosis H37Rv. But current H. sapiens-M. tuberculosis H37Rv PPI data are very scarce. This seriously limits the study of the interaction between this important pathogen and its host H. sapiens. Computational prediction of H. sapiens-M. tuberculosis H37Rv PPIs is an important strategy to fill in the gap. Domain-domain interaction (DDI) based prediction is one of the frequently used computational approaches in predicting both intra-species and inter-species PPIs. However, the performance of DDI-based host-pathogen PPI prediction has been rather limited. We develop a stringent DDI-based prediction approach with emphasis on (i) differences between the specific domain sequences on annotated regions of proteins under the same domain ID and (ii) calculation of the interaction strength of predicted PPIs based on the interacting residues in their interaction interfaces. We compare our stringent DDI-based approach to a conventional DDI-based approach for predicting PPIs based on gold standard intra-species PPIs and coherent informative Gene Ontology terms assessment. The assessment results show that our stringent DDI-based approach achieves much better performance in predicting PPIs than the conventional approach. Using our stringent DDI-based approach, we have predicted a small set of reliable H. sapiens-M. tuberculosis H37Rv PPIs which could be very useful for a variety of related studies. We also analyze the H. sapiens-M. tuberculosis H37Rv PPIs predicted by our stringent DDI-based approach using cellular compartment distribution analysis, functional category enrichment analysis and pathway enrichment analysis. The analyses support the validity of our prediction result. Also, based on an analysis of the H. sapiens-M. tuberculosis H37Rv PPI network predicted by our stringent DDI-based approach, we have discovered some important properties of domains involved in host-pathogen PPIs. We find that both host and pathogen proteins involved in host-pathogen PPIs tend to have more domains than proteins involved in intra-species PPIs, and these domains have more interaction partners than domains on proteins involved in intra-species PPI. The stringent DDI-based prediction approach reported in this work provides a stringent strategy for predicting host-pathogen PPIs. It also performs better than a conventional DDI-based approach in predicting PPIs. We have predicted a small set of accurate H. sapiens-M. tuberculosis H37Rv PPIs which could be very useful for a variety of related studies.

The Topology of the Growing Human Interactome Data.

PubMed

Janjić, Vuk; Pržulj, Nataša

2014-06-01

We have long moved past the one-gene-one-function concept originally proposed by Beadle and Tatum back in 1941; but the full understanding of genotype-phenotype relations still largely relies on the analysis of static, snapshot-like, interaction data sets. Here, we look at what global patterns can be uncovered if we simply trace back the human interactome network over the last decade of protein-protein interaction (PPI) screening. We take a purely topological approach and find that as the human interactome is getting denser, it is not only gaining in structure (in terms of now being better fit by structured network models than before), but also there are patterns in the way in which it is growing: (a) newly added proteins tend to get linked to existing proteins in the interactome that are not know to interact; and (b) new proteins tend to link to already well connected proteins. Moreover, the alignment between human and yeast interactomes spanning over 40% of yeast's proteins - that are involved in regulation of transcription, RNA splicing and other cellcycle- related processes-suggests the existence of a part of the interactome which remains topologically and functionally unaffected through evolution. Furthermore, we find a small sub-network, specific to the "core" of the human interactome and involved in regulation of transcription and cancer development, whose wiring has not changed within the human interactome over the last 10 years of interacome data acquisition. Finally, we introduce a generalisation of the clustering coefficient of a network as a new measure called the cycle coefficient, and use it to show that PPI networks of human and model organisms are wired in a tight way which forbids the occurrence large cycles.

The topology of the growing human interactome data.

PubMed

Janjić, Vuk; Pržulj, Nataša

2014-06-23

We have long moved past the one-gene–one-function concept originally proposed by Beadle and Tatum back in 1941; but the full understanding of genotype–phenotype relations still largely relies on the analysis of static, snapshot-like, interaction data sets. Here, we look at what global patterns can be uncovered if we simply trace back the human interactome network over the last decade of protein- protein interaction (PPI) screening. We take a purely topological approach and find that as the human interactome is getting denser, it is not only gaining in structure (in terms of now being better fit by structured network models than before), but also there are patterns in the way in which it is growing: (a) newly added proteins tend to get linked to existing proteins in the interactome that are not know to interact; and (b) new proteins tend to link to already well connected proteins. Moreover, the alignment between human and yeast interactomes spanning over 40% of yeast’s proteins — that are involved in regulation of transcription, RNA splicing and other cellcycle-related processes—suggests the existence of a part of the interactome which remains topologically and functionally unaffected through evolution. Furthermore, we find a small sub-network, specific to the “core” of the human interactome and involved in regulation of transcription and cancer development, whose wiring has not changed within the human interactome over the last 10 years of interacome data acquisition. Finally, we introduce a generalisation of the clustering coefficient of a network as a new measure called the cycle coefficient, and use it to show that PPI networks of human and model organisms are wired in a tight way which forbids the occurrence large cycles.

Default Mode Network (DMN) Deactivation during Odor-Visual Association

PubMed Central

Karunanayaka, Prasanna R.; Wilson, Donald A.; Tobia, Michael J.; Martinez, Brittany; Meadowcroft, Mark; Eslinger, Paul J.; Yang, Qing X.

2017-01-01

Default mode network (DMN) deactivation has been shown to be functionally relevant for goal-directed cognition. In this study, we investigated the DMN’s role during olfactory processing using two complementary functional magnetic resonance imaging (fMRI) paradigms with identical timing, visual-cue stimulation and response monitoring protocols. Twenty-nine healthy, non-smoking, right-handed adults (mean age = 26±4 yrs., 16 females) completed an odor-visual association fMRI paradigm that had two alternating odor+visual and visual-only trial conditions. During odor+visual trials, a visual cue was presented simultaneously with an odor, while during visual-only trial conditions the same visual cue was presented alone. Eighteen of the 29 participants (mean age = 27.0 ± 6.0 yrs.,11 females) also took part in a control no-odor fMRI paradigm that consisted of visual-only trial conditions which were identical to the visual-only trials in the odor-visual association paradigm. We used Independent Component Analysis (ICA), extended unified structural equation modeling (euSEM), and psychophysiological interaction (PPI) to investigate the interplay between the DMN and olfactory network. In the odor-visual association paradigm, DMN deactivation was evoked by both the odor+visual and visual-only trial conditions. In contrast, the visual-only trials in the no-odor paradigm did not evoke consistent DMN deactivation. In the odor-visual association paradigm, the euSEM and PPI analyses identified a directed connectivity between the DMN and olfactory network which was significantly different between odor+visual and visual-only trial conditions. The results support a strong interaction between the DMN and olfactory network and highlights DMN’s role in task-evoked brain activity and behavioral responses during olfactory processing. PMID:27785847

Use of proton pump inhibitors is associated with increased mortality due to nosocomial pneumonia in bedridden patients receiving tube feeding.

PubMed

Hamai, Kosuke; Iwamoto, Hiroshi; Ohshimo, Shinichiro; Wakabayashi, Yu; Ihara, Daisuke; Fujitaka, Kazunori; Hamada, Hironobu; Ono, Koichi; Hattori, Noboru

2018-05-22

To investigate the association between the use of proton pump inhibitors (PPI) and nosocomial pneumonia and gastrointestinal bleeding in bedridden patients receiving tube feeding. A total of 116 bedridden hospitalized patients receiving tube feeding, of which 80 were supported by percutaneous endoscopic gastrostomy and 36 by nasogastric tube, were included in the present study. The patients were divided into two groups: 62 patients treated with PPI (PPI group) and 54 patients without PPI (non-PPI group). Mortality due to nosocomial pneumonia was evaluated using the Kaplan-Meier approach and the log-rank test. A total of 36 patients (31%) died of nosocomial pneumonia during the observation period; the mortality rate due to nosocomial pneumonia was significantly higher in the PPI group than in the non-PPI group (P = 0.0395). Cox proportional hazard analysis showed that the use of PPI and lower levels of serum albumin were independent predictors of 2-year mortality due to nosocomial pneumonia. Gastrointestinal bleeding was observed in four patients in the non-PPI group (7.7%) and in one patient in the PPI group (1.6%); there was no significant difference between the two groups. The use of PPI in bedridden tube-fed patients was independently associated with mortality due to nosocomial pneumonia, and the PPI group had a non-significant lower incidence of gastrointestinal bleeding than the non-PPI group. Geriatr Gerontol Int 2018; ••: ••-••. © 2018 The Authors Geriatrics & Gerontology International published by John Wiley & Sons Australia, Ltd on behalf of Japan Geriatrics Society.

On the integration of protein-protein interaction networks with gene expression and 3D structural data: What can be gained?

NASA Astrophysics Data System (ADS)

Bertolazzi, Paola; Bock, Mary Ellen; Guerra, Concettina; Paci, Paola; Santoni, Daniele

2014-06-01

The biological role of proteins has been analyzed from different perspectives, initially by considering proteins as isolated biological entities, then as cooperating entities that perform their function by interacting with other molecules. There are other dimensions that are important for the complete understanding of the biological processes: time and location. However a protein is rarely annotated with temporal and spatial information. Experimental Protein-Proteins Interaction (PPI) data are static; furthermore they generally do not include transient interactions which are a considerable fraction of the interactome of many organisms. One way to incorporate temporal and condition information is to use other sources of information, such as gene expression data and 3D structural data. Here we review work done to understand the insight that can be gained by enriching PPI data with gene expression and 3D structural data. In particular, we address the following questions: Can the dynamics of a single protein or of an interaction be accurately derived from these data? Can the assembly-disassembly of protein complexes be traced over time? What type of topological changes occur in a PPI network architecture over time?

Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis

PubMed Central

2013-01-01

Background Protein-protein interactions (PPIs) play crucial roles in the execution of various cellular processes and form the basis of biological mechanisms. Although large amount of PPIs data for different species has been generated by high-throughput experimental techniques, current PPI pairs obtained with experimental methods cover only a fraction of the complete PPI networks, and further, the experimental methods for identifying PPIs are both time-consuming and expensive. Hence, it is urgent and challenging to develop automated computational methods to efficiently and accurately predict PPIs. Results We present here a novel hierarchical PCA-EELM (principal component analysis-ensemble extreme learning machine) model to predict protein-protein interactions only using the information of protein sequences. In the proposed method, 11188 protein pairs retrieved from the DIP database were encoded into feature vectors by using four kinds of protein sequences information. Focusing on dimension reduction, an effective feature extraction method PCA was then employed to construct the most discriminative new feature set. Finally, multiple extreme learning machines were trained and then aggregated into a consensus classifier by majority voting. The ensembling of extreme learning machine removes the dependence of results on initial random weights and improves the prediction performance. Conclusions When performed on the PPI data of Saccharomyces cerevisiae, the proposed method achieved 87.00% prediction accuracy with 86.15% sensitivity at the precision of 87.59%. Extensive experiments are performed to compare our method with state-of-the-art techniques Support Vector Machine (SVM). Experimental results demonstrate that proposed PCA-EELM outperforms the SVM method by 5-fold cross-validation. Besides, PCA-EELM performs faster than PCA-SVM based method. Consequently, the proposed approach can be considered as a new promising and powerful tools for predicting PPI with excellent performance and less time. PMID:23815620

The OncoPPi Portal: an integrative resource to explore and prioritize protein-protein interactions for cancer target discovery. | Office of Cancer Genomics

Cancer.gov

Motivation: As cancer genomics initiatives move toward comprehensive identification of genetic alterations in cancer, attention is now turning to understanding how interactions among these genes lead to the acquisition of tumor hallmarks. Emerging pharmacological and clinical data suggest a highly promising role of cancer-specific protein-protein interactions (PPIs) as druggable cancer targets. However, large-scale experimental identification of cancer-related PPIs remains challenging, and currently available resources to explore oncogenic PPI networks are limited.

A little more conversation please? Qualitative study of researchers' and patients' interview accounts of training for patient and public involvement in clinical trials.

PubMed

Dudley, Louise; Gamble, Carrol; Allam, Alison; Bell, Philip; Buck, Deborah; Goodare, Heather; Hanley, Bec; Preston, Jennifer; Walker, Alison; Williamson, Paula; Young, Bridget

2015-04-27

Training in patient and public involvement (PPI) is recommended, yet little is known about what training is needed. We explored researchers' and PPI contributors' accounts of PPI activity and training to inform the design of PPI training for both parties. We used semi-structured qualitative interviews with researchers (chief investigators and trial managers) and PPI contributors, accessed through a cohort of clinical trials, which had been funded between 2006 and 2010. An analysis of transcripts of audio-recorded interviews drew on the constant comparative method. We interviewed 31 researchers and 17 PPI contributors from 28 trials. Most researchers could see some value in PPI training for researchers, although just under half had received such training themselves, and some had concerns about the purpose and evidence base for PPI training. PPI contributors were evenly split in their perceptions of whether researchers needed training in PPI. Few PPI contributors had themselves received training for their roles. Many informants across all groups felt that training PPI contributors was unnecessary because they already possessed the skills needed. Informants were also concerned that training would professionalise PPI contributors, limiting their ability to provide an authentic patient perspective. However, informants welcomed informal induction 'conversations' to help contributors understand their roles and support them in voicing their opinions. Informants believed that PPI contributors should be confident, motivated, intelligent, focussed on helping others and have relevant experience. Researchers looked for these qualities when selecting contributors, and spoke of how finding 'the right' contributor was more important than accessing 'the right' training. While informants were broadly receptive to PPI training for researchers, they expressed considerable reluctance to training PPI contributors. Providers of training will need to address these reservations. Our findings point to the importance of reconsidering how training is conceptualised, designed and promoted and of providing flexible, learning opportunities in ways that flow from researchers' and contributors' needs and preferences. We also identify some areas of training content and the need for further consideration to be given to the selection of PPI contributors and models for implementing PPI to ensure clinical trials benefit from a diversity of patient perspectives.

A retrospective analysis of the role of proton pump inhibitors in colorectal cancer disease survival

PubMed Central

Graham, C.; Orr, C.; Bricks, C.S.; Hopman, W.M.; Hammad, N.; Ramjeesingh, R.

2016-01-01

Background Proton pump inhibitors (ppis) are a commonly used medication. A limited number of studies have identified a weak-to-moderate association between ppi use and colorectal cancer (crc) risk, but none to date have identified an effect of ppi use on crc survival. We therefore postulated that an association between ppi use and crc survival might potentially exist. Methods We performed a retrospective chart review of 1304 crc patients diagnosed from January 2005 to December 2011 and treated at the Cancer Centre of Southeastern Ontario. Kaplan–Meier analysis and Cox proportional hazards regression models were used to evaluate overall survival (os). Results We identified 117 patients (9.0%) who were taking ppis at the time of oncology consult. Those taking a ppi were also more often taking asa or statins (or both) and had a statistically significantly increased rate of cardiac disease. No identifiable difference in tumour characteristics was evident in the two groups, including tumour location, differentiation, lymph node status, and stage. Univariate analysis identified a statistically nonsignificant difference in survival, with those taking a ppi experiencing lesser 1-year (82.1% vs. 86.7%, p = 0.161), 2-year (70.1% vs. 76.8%, p = 0.111), and 5-year os (55.2% vs. 62.9%, p = 0.165). When controlling for patient demographics and tumour characteristics, multivariate Cox regression analysis identified a statistically significant effect of ppi in our patient population (hazard ratio: 1.343; 95% confidence interval: 1.011 to 1.785; p = 0.042). Conclusions Our results suggest a potential adverse effect of ppi use on os in crc patients. These results need further evaluation in prospective analyses. PMID:28050148

The impact of patient and public involvement on UK NHS health care: a systematic review.

PubMed

Mockford, Carole; Staniszewska, Sophie; Griffiths, Frances; Herron-Marx, Sandra

2012-02-01

Patient and public involvement (PPI) has become an integral part of health care with its emphasis on including and empowering individuals and communities in the shaping of health and social care services. The aims of this study were to identify the impact of PPI on UK National Health Service (NHS) healthcare services and to identify the economic cost. It also examined how PPI is being defined, theorized and conceptualized, and how the impact of PPI is captured or measured. Seventeen key online databases and websites were searched, e.g. Medline and the King's Fund. UK studies from 1997 to 2009 which included service user involvement in NHS healthcare services. Date extraction Key themes were identified and a narrative analysis was undertaken. The review indicates that PPI has a range of impacts on healthcare services. There is little evidence of any economic analysis of the costs involved. A key limitation of the PPI evidence base is the poor quality of reporting impact. Few studies define PPI, there is little theoretical underpinning or conceptualization reported, there is an absence of robust measurement of impact and descriptive evidence lacked detail. There is a need for significant development of the PPI evidence base particularly around guidance for the reporting of user activity and impact. The evidence base needs to be significantly strengthened to ensure the full impact of involving service users in NHS healthcare services is fully understood.

Quality improvement of a rice-substituted fried noodle by utilizing the protein-polyphenol interaction between a pea protein isolate and green tea (Camellia sinensis) extract.

PubMed

Song, Youngwoon; Yoo, Sang-Ho

2017-11-15

The quality of rice-substituted fried noodles was improved by applying interaction between pea protein isolate (PPI) and green tea extract (GTE). Radical-scavenging activities of GTE were stably maintained when exposed to acidic pH, UV light, and fluorescent light, but decreased by approximately 65% when exposed to 80°C for 168h. The RVA profiles of noodle dough showed that peak viscosity and breakdown increased significantly but that setback and final viscosity remained unchanged with 20% rice flour replacement. PPI significantly decreased the viscosity parameters of rice-supplemented dough, and the addition of GTE recovered these values significantly. The cooking loss and viscoelasticity (R max ) of cooked rice-supplemented noodles were fully restored by combined treatment of PPI and GTE. GTE decreased the peroxide value of fried noodles by 14% after storage at 63°C for 16days. Therefore, PPI+GTE treatment has great potential for use in fried noodles owing to the reinforced network and antioxidant activity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Targeting Hsp90-Cdc37: A Promising Therapeutic Strategy by Inhibiting Hsp90 Chaperone Function.

PubMed

Wang, Lei; Li, Li; Gu, Kai; Xu, Xiao-Li; Sun, Yuan; You, Qi-Dong

2017-01-01

The Hsp90 chaperone protein regulates the folding, maturation and stability of a wide variety of oncoproteins. In recent years, many Hsp90 inhibitors have entered into the clinical trials while all of them target ATPase showing similar binding capacity and kinds of side-effects so that none have reached to the market. During the regulation progress, numerous protein- protein interactions (PPI) such as Hsp90 and client proteins or cochaperones are involved. With the Hsp90-cochaperones PPI networks being more and more clear, many cancerous proteins have been reported to be tightly correlated to Hsp90-cochaperones PPI. Among them, Hsp90-Cdc37 PPI has been widely reported to associate with numerous protein kinases, making it a novel target for the treatment of cancers. In this paper, we briefly review the strategies and modulators targeting Hsp90-Cdc37 complex including direct and indirect regulation mechanism. Through these discussions we expect to present inspirations for new insights into an alternative way to inhibit Hsp90 chaperone function. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Proton Pump Inhibitor Use and Risk of Chronic Kidney Disease

PubMed Central

Lazarus, Benjamin; Chen, Yuan; Wilson, Francis P.; Sang, Yingying; Chang, Alex R.; Coresh, Josef; Grams, Morgan E.

2016-01-01

Context Proton pump inhibitors (PPIs) are among the most commonly used drugs worldwide, and have been linked to acute interstitial nephritis. Less is known about the relationship between PPI use and chronic kidney disease (CKD). Objective To quantify the association between PPI use and incident CKD in a population-based cohort. Design, Setting and Participants 10,482 participants in the Atherosclerosis Risk in Communities (ARIC) study with an estimated glomerular filtration rate (eGFR) of ≥60mL/min/1.73m2 were followed from a baseline visit (1996–1999) to December 31, 2011. Findings were replicated in an administrative cohort of 248,751 patients with eGFR ≥60mL/min/1.73m2 from Geisinger Health System. Exposure Self-reported PPI use in ARIC, or an outpatient PPI prescription in the replication cohort. Histamine-2 receptor (H2) antagonist use was considered a negative control and active comparator. Main Outcome Measure Incident CKD, using diagnostic codes indicating CKD at hospital discharge or death. In the replication cohort, incident CKD was defined by outpatient eGFR <60 mL/min/1.73 m2. Results Compared to non-users, PPI-users were more often white, obese, and taking antihypertensive medication. In ARIC, PPI use was associated with incident CKD in unadjusted analysis (hazard ratio [HR], 1.45; 95% confidence interval [CI], 1.11–1.90), analysis adjusted for demographic, socioeconomic, and clinical parameters (HR, 1.50; 95% CI, 1.14–1.96), and in analysis with PPI ever-use modeled as a time-varying variable (adjusted HR, 1.35; 95% CI, 1.17–1.55). The association persisted when baseline PPI users were compared directly to H2-antagonist users (adjusted HR, 1.39; 95% CI, 1.01–1.91), and to propensity-score matched non-users (HR, 1.76; 95% CI, 1.13–2.74). In the replication cohort, PPI use was associated with CKD in all analyses, including a time-varying new user design (adjusted HR 1.24; 95% CI, 1.20–1.28). Twice-daily PPI dosing was associated with a higher risk (adjusted HR, 1.46; 95% CI, 1.28–1.67) than once-daily dosing (adjusted HR, 1.15; 95% CI, 1.09–1.21). Conclusions PPI use is associated with a 20%–50% higher risk of incident CKD. Future research should evaluate whether limiting PPI use reduces the incidence of CKD. PMID:26752337

A computational interactome for prioritizing genes associated with complex agronomic traits in rice (Oryza sativa).

PubMed

Liu, Shiwei; Liu, Yihui; Zhao, Jiawei; Cai, Shitao; Qian, Hongmei; Zuo, Kaijing; Zhao, Lingxia; Zhang, Lida

2017-04-01

Rice (Oryza sativa) is one of the most important staple foods for more than half of the global population. Many rice traits are quantitative, complex and controlled by multiple interacting genes. Thus, a full understanding of genetic relationships will be critical to systematically identify genes controlling agronomic traits. We developed a genome-wide rice protein-protein interaction network (RicePPINet, http://netbio.sjtu.edu.cn/riceppinet) using machine learning with structural relationship and functional information. RicePPINet contained 708 819 predicted interactions for 16 895 non-transposable element related proteins. The power of the network for discovering novel protein interactions was demonstrated through comparison with other publicly available protein-protein interaction (PPI) prediction methods, and by experimentally determined PPI data sets. Furthermore, global analysis of domain-mediated interactions revealed RicePPINet accurately reflects PPIs at the domain level. Our studies showed the efficiency of the RicePPINet-based method in prioritizing candidate genes involved in complex agronomic traits, such as disease resistance and drought tolerance, was approximately 2-11 times better than random prediction. RicePPINet provides an expanded landscape of computational interactome for the genetic dissection of agronomically important traits in rice. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Investigating ego modules and pathways in osteosarcoma by integrating the EgoNet algorithm and pathway analysis.

PubMed

Chen, X Y; Chen, Y H; Zhang, L J; Wang, Y; Tong, Z C

2017-02-16

Osteosarcoma (OS) is the most common primary bone malignancy, but current therapies are far from effective for all patients. A better understanding of the pathological mechanism of OS may help to achieve new treatments for this tumor. Hence, the objective of this study was to investigate ego modules and pathways in OS utilizing EgoNet algorithm and pathway-related analysis, and reveal pathological mechanisms underlying OS. The EgoNet algorithm comprises four steps: constructing background protein-protein interaction (PPI) network (PPIN) based on gene expression data and PPI data; extracting differential expression network (DEN) from the background PPIN; identifying ego genes according to topological features of genes in reweighted DEN; and collecting ego modules using module search by ego gene expansion. Consequently, we obtained 5 ego modules (Modules 2, 3, 4, 5, and 6) in total. After applying the permutation test, all presented statistical significance between OS and normal controls. Finally, pathway enrichment analysis combined with Reactome pathway database was performed to investigate pathways, and Fisher's exact test was conducted to capture ego pathways for OS. The ego pathway for Module 2 was CLEC7A/inflammasome pathway, while for Module 3 a tetrasaccharide linker sequence was required for glycosaminoglycan (GAG) synthesis, and for Module 6 was the Rho GTPase cycle. Interestingly, genes in Modules 4 and 5 were enriched in the same pathway, the 2-LTR circle formation. In conclusion, the ego modules and pathways might be potential biomarkers for OS therapeutic index, and give great insight of the molecular mechanism underlying this tumor.

Investigating ego modules and pathways in osteosarcoma by integrating the EgoNet algorithm and pathway analysis

PubMed Central

Chen, X.Y.; Chen, Y.H.; Zhang, L.J.; Wang, Y.; Tong, Z.C.

2017-01-01

Osteosarcoma (OS) is the most common primary bone malignancy, but current therapies are far from effective for all patients. A better understanding of the pathological mechanism of OS may help to achieve new treatments for this tumor. Hence, the objective of this study was to investigate ego modules and pathways in OS utilizing EgoNet algorithm and pathway-related analysis, and reveal pathological mechanisms underlying OS. The EgoNet algorithm comprises four steps: constructing background protein-protein interaction (PPI) network (PPIN) based on gene expression data and PPI data; extracting differential expression network (DEN) from the background PPIN; identifying ego genes according to topological features of genes in reweighted DEN; and collecting ego modules using module search by ego gene expansion. Consequently, we obtained 5 ego modules (Modules 2, 3, 4, 5, and 6) in total. After applying the permutation test, all presented statistical significance between OS and normal controls. Finally, pathway enrichment analysis combined with Reactome pathway database was performed to investigate pathways, and Fisher's exact test was conducted to capture ego pathways for OS. The ego pathway for Module 2 was CLEC7A/inflammasome pathway, while for Module 3 a tetrasaccharide linker sequence was required for glycosaminoglycan (GAG) synthesis, and for Module 6 was the Rho GTPase cycle. Interestingly, genes in Modules 4 and 5 were enriched in the same pathway, the 2-LTR circle formation. In conclusion, the ego modules and pathways might be potential biomarkers for OS therapeutic index, and give great insight of the molecular mechanism underlying this tumor. PMID:28225867

Regulatory interactions between long noncoding RNA LINC00968 and miR-9-3p in non-small cell lung cancer: A bioinformatic analysis based on miRNA microarray, GEO and TCGA.

PubMed

Li, Dong-Yao; Chen, Wen-Jie; Shang, Jun; Chen, Gang; Li, Shi-Kang

2018-06-01

Long non-coding RNAs (lncRNAs) have been demonstrated to mediate carcinogenesis in various types of cancer. However, the regulatory role of lncRNA LINC00968 in lung adenocarcinoma remains unclear. The microRNA (miRNA) expression in LINC00968-overexpressing human lung adenocarcinoma A549 cells was detected using miRNA microarray analysis. miR-9-3p was selected for further analysis, and its expression was verified in the Gene Expression Omnibus (GEO) database. In addition, the regulatory axis of LINC00968 was validated using The Cancer Genome Atlas (TCGA) database. Results of the GEO database indicated miR-9-3p expression in lung adenocarcinoma was significantly higher compared with normal tissues. Functional enrichment analyses of the target genes of miR-9-3p indicated protein binding and the AMP-activated protein kinase pathway were the most enriched Gene Ontology and KEGG terms, respectively. Combining target genes with the correlated genes of LINC00968 and miR-9-3p, 120 objective genes were obtained, which were used to construct a protein-protein interaction (PPI) network. Cyclin A2 (CCNA2) was identified to have a vital role in the PPI network. Significant correlations were detected between LINC00968, miR-9-3p and CCNA2 in lung adenocarcinoma. The LINC00968/miR-9-3p/CCNA2 regulatory axis provides a new foundation for further evaluating the regulatory mechanisms of LINC00968 in lung adenocarcinoma.

A Network Approach to Rare Disease Modeling

NASA Astrophysics Data System (ADS)

Ghiassian, Susan; Rabello, Sabrina; Sharma, Amitabh; Wiest, Olaf; Barabasi, Albert-Laszlo

2011-03-01

Network approaches have been widely used to better understand different areas of natural and social sciences. Network Science had a particularly great impact on the study of biological systems. In this project, using biological networks, candidate drugs as a potential treatment of rare diseases were identified. Developing new drugs for more than 2000 rare diseases (as defined by ORPHANET) is too expensive and beyond expectation. Disease proteins do not function in isolation but in cooperation with other interacting proteins. Research on FDA approved drugs have shown that most of the drugs do not target the disease protein but a protein which is 2 or 3 steps away from the disease protein in the Protein-Protein Interaction (PPI) network. We identified the already known drug targets in the disease gene's PPI subnetwork (up to the 3rd neighborhood) and among them those in the same sub cellular compartment and higher coexpression coefficient with the disease gene are expected to be stronger candidates. Out of 2177 rare diseases, 1092 were found not to have any drug target. Using the above method, we have found the strongest candidates among the rest in order to further experimental validations.

The role of TGF-β signaling and apoptosis in innate and adaptive immunity in zebrafish: a systems biology approach.

PubMed

Lin, Che; Lin, Chin-Nan; Wang, Yu-Chao; Liu, Fang-Yu; Chuang, Yung-Jen; Lan, Chung-Yu; Hsieh, Wen-Ping; Chen, Bor-Sen

2014-10-24

The immune system is a key biological system present in vertebrates. Exposure to pathogens elicits various defensive immune mechanisms that protect the host from potential threats and harmful substances derived from pathogens such as parasites, bacteria, and viruses. The complex immune system of humans and many other vertebrates can be divided into two major categories: the innate and the adaptive immune systems. At present, analysis of the complex interactions between the two subsystems that regulate host defense and inflammatory responses remains challenging. Based on time-course microarray data following primary and secondary infection of zebrafish by Candida albicans, we constructed two intracellular protein-protein interaction (PPI) networks for primary and secondary responses of the host. 57 proteins and 341 PPIs were identified for primary infection while 90 proteins and 385 PPIs were identified for secondary infection. There were 20 proteins in common while 37 and 70 proteins specific to primary and secondary infection. By inspecting the hub proteins of each network and comparing significant changes in the number of linkages between the two PPI networks, we identified TGF-β signaling and apoptosis as two of the main functional modules involved in primary and secondary infection. Our initial in silico analyses pave the way for further investigation into the interesting roles played by the TGF-β signaling pathway and apoptosis in innate and adaptive immunity in zebrafish. Such insights could lead to therapeutic advances and improved drug design in the continual battle against infectious diseases.

Neural bases of different cognitive strategies for facial affect processing in schizophrenia.

PubMed

Fakra, Eric; Salgado-Pineda, Pilar; Delaveau, Pauline; Hariri, Ahmad R; Blin, Olivier

2008-03-01

To examine the neural basis and dynamics of facial affect processing in schizophrenic patients as compared to healthy controls. Fourteen schizophrenic patients and fourteen matched controls performed a facial affect identification task during fMRI acquisition. The emotional task included an intuitive emotional condition (matching emotional faces) and a more cognitively demanding condition (labeling emotional faces). Individual analysis for each emotional condition, and second-level t-tests examining both within-, and between-group differences, were carried out using a random effects approach. Psychophysiological interactions (PPI) were tested for variations in functional connectivity between amygdala and other brain regions as a function of changes in experimental conditions (labeling versus matching). During the labeling condition, both groups engaged similar networks. During the matching condition, schizophrenics failed to activate regions of the limbic system implicated in the automatic processing of emotions. PPI revealed an inverse functional connectivity between prefrontal regions and the left amygdala in healthy volunteers but there was no such change in patients. Furthermore, during the matching condition, and compared to controls, patients showed decreased activation of regions involved in holistic face processing (fusiform gyrus) and increased activation of regions associated with feature analysis (inferior parietal cortex, left middle temporal lobe, right precuneus). Our findings suggest that schizophrenic patients invariably adopt a cognitive approach when identifying facial affect. The distributed neocortical network observed during the intuitive condition indicates that patients may resort to feature-based, rather than configuration-based, processing and may constitute a compensatory strategy for limbic dysfunction.

Hub Protein Controversy: Taking a Closer Look at Plant Stress Response Hubs

PubMed Central

Vandereyken, Katy; Van Leene, Jelle; De Coninck, Barbara; Cammue, Bruno P. A.

2018-01-01

Plant stress responses involve numerous changes at the molecular and cellular level and are regulated by highly complex signaling pathways. Studying protein-protein interactions (PPIs) and the resulting networks is therefore becoming increasingly important in understanding these responses. Crucial in PPI networks are the so-called hubs or hub proteins, commonly defined as the most highly connected central proteins in scale-free PPI networks. However, despite their importance, a growing amount of confusion and controversy seems to exist regarding hub protein identification, characterization and classification. In order to highlight these inconsistencies and stimulate further clarification, this review critically analyses the current knowledge on hub proteins in the plant interactome field. We focus on current hub protein definitions, including the properties generally seen as hub-defining, and the challenges and approaches associated with hub protein identification. Furthermore, we give an overview of the most important large-scale plant PPI studies of the last decade that identified hub proteins, pointing out the lack of overlap between different studies. As such, it appears that although major advances are being made in the plant interactome field, defining hub proteins is still heavily dependent on the quality, origin and interpretation of the acquired PPI data. Nevertheless, many hub proteins seem to have a reported role in the plant stress response, including transcription factors, protein kinases and phosphatases, ubiquitin proteasome system related proteins, (co-)chaperones and redox signaling proteins. A significant number of identified plant stress hubs are however still functionally uncharacterized, making them interesting targets for future research. This review clearly shows the ongoing improvements in the plant interactome field but also calls attention to the need for a more comprehensive and precise identification of hub proteins, allowing a more efficient systems biology driven unraveling of complex processes, including those involved in stress responses. PMID:29922309

Factor Structure of the Psychopathic Personality Inventory (PPI): Findings from a Large Incarcerated Sample

ERIC Educational Resources Information Center

Neumann, Craig S.; Malterer, Melanie B.; Newman, Joseph P.

2008-01-01

Exploratory factor analysis (EFA) of the Psychopathic Personality Inventory (PPI; S. O. Lilienfeld, 1990; S. O. Lilienfeld & B. P. Andrews, 1996) with a community sample has suggested that the PPI subscales may comprise 2 higher order factors (S. D. Benning, C. J. Patrick, B. M. Hicks, D. M. Blonigen, & R. F. Krueger, 2003). However,…

In silico pathway analysis in cervical carcinoma reveals potential new targets for treatment

PubMed Central

van Dam, Peter A.; van Dam, Pieter-Jan H. H.; Rolfo, Christian; Giallombardo, Marco; van Berckelaer, Christophe; Trinh, Xuan Bich; Altintas, Sevilay; Huizing, Manon; Papadimitriou, Kostas; Tjalma, Wiebren A. A.; van Laere, Steven

2016-01-01

An in silico pathway analysis was performed in order to improve current knowledge on the molecular drivers of cervical cancer and detect potential targets for treatment. Three publicly available Affymetrix gene expression data-sets (GSE5787, GSE7803, GSE9750) were retrieved, vouching for a total of 9 cervical cancer cell lines (CCCLs), 39 normal cervical samples, 7 CIN3 samples and 111 cervical cancer samples (CCSs). Predication analysis of microarrays was performed in the Affymetrix sets to identify cervical cancer biomarkers. To select cancer cell-specific genes the CCSs were compared to the CCCLs. Validated genes were submitted to a gene set enrichment analysis (GSEA) and Expression2Kinases (E2K). In the CCSs a total of 1,547 probe sets were identified that were overexpressed (FDR < 0.1). Comparing to CCCLs 560 probe sets (481 unique genes) had a cancer cell-specific expression profile, and 315 of these genes (65%) were validated. GSEA identified 5 cancer hallmarks enriched in CCSs (P < 0.01 and FDR < 0.25) showing that deregulation of the cell cycle is a major component of cervical cancer biology. E2K identified a protein-protein interaction (PPI) network of 162 nodes (including 20 drugable kinases) and 1626 edges. This PPI-network consists of 5 signaling modules associated with MYC signaling (Module 1), cell cycle deregulation (Module 2), TGFβ-signaling (Module 3), MAPK signaling (Module 4) and chromatin modeling (Module 5). Potential targets for treatment which could be identified were CDK1, CDK2, ABL1, ATM, AKT1, MAPK1, MAPK3 among others. The present study identified important driver pathways in cervical carcinogenesis which should be assessed for their potential therapeutic drugability. PMID:26701206

Dissection of the cis-2-decenoic acid signaling network in Pseudomonas aeruginosa using microarray technique

PubMed Central

Rahmani-Badi, Azadeh; Sepehr, Shayesteh; Fallahi, Hossein; Heidari-Keshel, Saeed

2015-01-01

Many bacterial pathogens use quorum-sensing (QS) signaling to regulate the expression of factors contributing to virulence and persistence. Bacteria produce signals of different chemical classes. The signal molecule, known as diffusible signal factor (DSF), is a cis-unsaturated fatty acid that was first described in the plant pathogen Xanthomonas campestris. Previous works have shown that human pathogen, Pseudomonas aeruginosa, also synthesizes a structurally related molecule, characterized as cis-2-decenoic acid (C10: Δ2, CDA) that induces biofilm dispersal by multiple types of bacteria. Furthermore, CDA has been shown to be involved in inter-kingdom signaling that modulates fungal behavior. Therefore, an understanding of its signaling mechanism could suggest strategies for interference, with consequences for disease control. To identify the components of CDA signaling pathway in this pathogen, a comparative transcritpome analysis was conducted, in the presence and absence of CDA. A protein-protein interaction (PPI) network for differentially expressed (DE) genes with known function was then constructed by STRING and Cytoscape. In addition, the effects of CDA in combination with antimicrobial agents on the biofilm surface area and bacteria viability were evaluated using fluorescence microscopy and digital image analysis. Microarray analysis identified 666 differentially expressed genes in the presence of CDA and gene ontology (GO) analysis revealed that in P. aeruginosa, CDA mediates dispersion of biofilms through signaling pathways, including enhanced motility, metabolic activity, virulence as well as persistence at different temperatures. PPI data suggested that a cluster of five genes (PA4978, PA4979, PA4980, PA4982, PA4983) is involved in the CDA synthesis and perception. Combined treatments using both CDA and antimicrobial agents showed that following exposure of the biofilms to CDA, remaining cells on the surface were easily removed and killed by antimicrobials. PMID:25972860

Predictors of short-term and long-term incontinence after robot-assisted radical prostatectomy.

PubMed

Shao, I-Hung; Chang, Ying-Hsu; Hou, Chun-Ming; Lin, Zheng-Feng; Wu, Chun-Te

2018-01-01

Purpose To determine retrospectively the prognostic factors for urinary incontinence following robot-assisted radical prostatectomy (RARP). Methods Altogether, 180 patients with localized prostate cancer underwent RARP (same surgeon). Preoperative physical status, disease characteristics, laboratory findings, and surgical technique were recorded and the patients checked 1, 6, 12, and 24 months after RARP regarding their contribution to predicting post-prostatectomy urinary incontinence (PPI). Results Overall, 114 (63.3%) patients had PPI 1 month after RARP and 19 patients (16.0%) at 24 months. Univariate analysis showed that age was a significant factor for predicting PPI at 1 month. PPI predictors at 24 months were age, body mass index, preoperative serum albumin level, previous transurethral resection of the prostate, total operative time, and bladder neck sparing. Multivariate analysis indicated that age and total operative time were significant predictors. Conclusion Older age and longer operative time were highly relevant to short- and long-term PPI occurrence after RARP.

P³DB 3.0: From plant phosphorylation sites to protein networks.

PubMed

Yao, Qiuming; Ge, Huangyi; Wu, Shangquan; Zhang, Ning; Chen, Wei; Xu, Chunhui; Gao, Jianjiong; Thelen, Jay J; Xu, Dong

2014-01-01

In the past few years, the Plant Protein Phosphorylation Database (P(3)DB, http://p3db.org) has become one of the most significant in vivo data resources for studying plant phosphoproteomics. We have substantially updated P(3)DB with respect to format, new datasets and analytic tools. In the P(3)DB 3.0, there are altogether 47 923 phosphosites in 16 477 phosphoproteins curated across nine plant organisms from 32 studies, which have met our multiple quality standards for acquisition of in vivo phosphorylation site data. Centralized by these phosphorylation data, multiple related data and annotations are provided, including protein-protein interaction (PPI), gene ontology, protein tertiary structures, orthologous sequences, kinase/phosphatase classification and Kinase Client Assay (KiC Assay) data--all of which provides context for the phosphorylation event. In addition, P(3)DB 3.0 incorporates multiple network viewers for the above features, such as PPI network, kinase-substrate network, phosphatase-substrate network, and domain co-occurrence network to help study phosphorylation from a systems point of view. Furthermore, the new P(3)DB reflects a community-based design through which users can share datasets and automate data depository processes for publication purposes. Each of these new features supports the goal of making P(3)DB a comprehensive, systematic and interactive platform for phosphoproteomics research.

Symptom-specific amygdala hyperactivity modulates motor control network in conversion disorder.

PubMed

Hassa, Thomas; Sebastian, Alexandra; Liepert, Joachim; Weiller, Cornelius; Schmidt, Roger; Tüscher, Oliver

2017-01-01

Initial historical accounts as well as recent data suggest that emotion processing is dysfunctional in conversion disorder patients and that this alteration may be the pathomechanistic neurocognitive basis for symptoms in conversion disorder. However, to date evidence of direct interaction of altered negative emotion processing with motor control networks in conversion disorder is still lacking. To specifically study the neural correlates of emotion processing interacting with motor networks we used a task combining emotional and sensorimotor stimuli both separately as well as simultaneously during functional magnetic resonance imaging in a well characterized group of 13 conversion disorder patients with functional hemiparesis and 19 demographically matched healthy controls. We performed voxelwise statistical parametrical mapping for a priori regions of interest within emotion processing and motor control networks. Psychophysiological interaction (PPI) was used to test altered functional connectivity of emotion and motor control networks. Only during simultaneous emotional stimulation and passive movement of the affected hand patients displayed left amygdala hyperactivity. PPI revealed increased functional connectivity in patients between the left amygdala and the (pre-)supplemental motor area and the subthalamic nucleus, key regions within the motor control network. These findings suggest a novel mechanistic direct link between dysregulated emotion processing and motor control circuitry in conversion disorder.

Preparation of PPy-Coated MnO2 Hybrid Micromaterials and Their Improved Cyclic Performance as Anode for Lithium-Ion Batteries

NASA Astrophysics Data System (ADS)

Feng, Lili; Zhang, Yinyin; Wang, Rui; Zhang, Yanli; Bai, Wei; Ji, Siping; Xuan, Zhewen; Yang, Jianhua; Zheng, Ziguang; Guan, Hongjin

2017-09-01

MnO2@PPy core-shell micromaterials are prepared by chemical polymerization of pyrrole on the MnO2 surface. The polypyrrole (PPy) is formed as a homogeneous organic shell on the MnO2 surface. The thickness of PPy shell can be adjusted by the usage of pyrrole. The analysis of SEM, FT-IR, X-ray photoelectron spectroscopy (XPS), thermo-gravimetric analysis (TGA), and XRD are used to confirm the formation of PPy shell. Galvanostatic cell cycling and electrochemical impedance spectroscopy (EIS) are used to evaluate the electrochemical performance as anode for lithium-ion batteries. The results show that after formation of MnO2@PPy core-shell micromaterials, the cyclic performance as anode for lithium-ion batteries is improved. Fifty microliters of PPy-coated caddice-clew-like MnO2 has the best cyclic performances as has 620 mAh g-1 discharge specific capacities after 300 cycles. As a comparison, the discharge specific capacity of bare MnO2 materials falls to below 200 mAh g-1 after 10 cycles. The improved lithium-storage cyclic stability of the MnO2@PPy samples attributes to the core-shell hybrid structure which can buffer the structural expansion and contraction of MnO2 caused by the repeated embedding and disengagement of Li ions and can prevent the pulverization of MnO2. This experiment provides an effective way to mitigate the problem of capacity fading of the transition metal oxide materials as anode materials for (lithium-ion batteries) LIBs.

Preparation of PPy-Coated MnO2 Hybrid Micromaterials and Their Improved Cyclic Performance as Anode for Lithium-Ion Batteries.

PubMed

Feng, Lili; Zhang, Yinyin; Wang, Rui; Zhang, Yanli; Bai, Wei; Ji, Siping; Xuan, Zhewen; Yang, Jianhua; Zheng, Ziguang; Guan, Hongjin

2017-09-02

MnO 2 @PPy core-shell micromaterials are prepared by chemical polymerization of pyrrole on the MnO 2 surface. The polypyrrole (PPy) is formed as a homogeneous organic shell on the MnO 2 surface. The thickness of PPy shell can be adjusted by the usage of pyrrole. The analysis of SEM, FT-IR, X-ray photoelectron spectroscopy (XPS), thermo-gravimetric analysis (TGA), and XRD are used to confirm the formation of PPy shell. Galvanostatic cell cycling and electrochemical impedance spectroscopy (EIS) are used to evaluate the electrochemical performance as anode for lithium-ion batteries. The results show that after formation of MnO 2 @PPy core-shell micromaterials, the cyclic performance as anode for lithium-ion batteries is improved. Fifty microliters of PPy-coated caddice-clew-like MnO 2 has the best cyclic performances as has 620 mAh g -1 discharge specific capacities after 300 cycles. As a comparison, the discharge specific capacity of bare MnO 2 materials falls to below 200 mAh g -1 after 10 cycles. The improved lithium-storage cyclic stability of the MnO 2 @PPy samples attributes to the core-shell hybrid structure which can buffer the structural expansion and contraction of MnO 2 caused by the repeated embedding and disengagement of Li ions and can prevent the pulverization of MnO 2 . This experiment provides an effective way to mitigate the problem of capacity fading of the transition metal oxide materials as anode materials for (lithium-ion batteries) LIBs.

Fabrication of polypyrrole-coated carbon nanotubes using oxidant-surfactant nanocrystals for supercapacitor electrodes with high mass loading and enhanced performance.

PubMed

Shi, Kaiyuan; Zhitomirsky, Igor

2013-12-26

A conceptually new approach to the fabrication of polypyrrole (PPy)-coated multiwalled carbon nanotubes (MWCNT) for application in electrodes of electrochemical supercapacitors (ES) is proposed. Cetrimonium persulfate (CTA)2S2O8 in the form of nanocrystals is used as an oxidant for the chemical polymerization of PPy. Ponceau S (PS) dye is investigated as a new anionic dopant. Testing results show that PS allows reduced PPy particle size and improved electrochemical performance, whereas (CTA)2S2O8 nanocrystals promote the formation of PPy nanofibers. We demonstrate for the first time that MWCNT can be efficiently dispersed using (CTA)2S2O8 nanocrystals. The analysis of the dispersion mechanism indicates that (CTA)2S2O8 dissociation is catalyzed by MWCNT. This new finding opens a new and promising strategy in MWCNT dispersion for colloidal processing of nanomaterials and electrophoretic nanotechnology. Uniformly coated MWCNT are obtained using (CTA)2S2O8 as a dispersant for MWCNT and oxidant for PPy polymerization and utilizing advantages of PS as an efficient dopant and nanostructure controlling agent. The analysis of the testing results provides an insight into the influence of PS molecular structure on PPy nanostructure and electrochemical properties. The PPy-coated MWCNT show superior electrochemical performance compared to PPy nanoparticles. The proof-of-principle is demonstrated by the fabrication of ES electrodes with excellent electrochemical performance at high active material loadings, good capacitance retention at high charge-discharge rates, and excellent cycling stability.

Exploring the Therapeutic Mechanism of Desmodium styracifolium on Oxalate Crystal-Induced Kidney Injuries Using Comprehensive Approaches Based on Proteomics and Network Pharmacology.

PubMed

Hou, Jiebin; Chen, Wei; Lu, Hongtao; Zhao, Hongxia; Gao, Songyan; Liu, Wenrui; Dong, Xin; Guo, Zhiyong

2018-01-01

Purpose: As a Chinese medicinal herb, Desmodium styracifolium (Osb.) Merr (DS) has been applied clinically to alleviate crystal-induced kidney injuries, but its effective components and their specific mechanisms still need further exploration. This research first combined the methods of network pharmacology and proteomics to explore the therapeutic protein targets of DS on oxalate crystal-induced kidney injuries to provide a reference for relevant clinical use. Methods: Oxalate-induced kidney injury mouse, rat, and HK-2 cell models were established. Proteins differentially expressed between the oxalate and control groups were respectively screened using iTRAQ combined with MALDI-TOF-MS. The common differential proteins of the three models were further analyzed by molecular docking with DS compounds to acquire differential targets. The inverse docking targets of DS were predicted through the platform of PharmMapper. The protein-protein interaction (PPI) relationship between the inverse docking targets and the differential proteins was established by STRING. Potential targets were further validated by western blot based on a mouse model with DS treatment. The effects of constituent compounds, including luteolin, apigenin, and genistein, were investigated based on an oxalate-stimulated HK-2 cell model. Results: Thirty-six common differentially expressed proteins were identified by proteomic analysis. According to previous research, the 3D structures of 15 major constituents of DS were acquired. Nineteen differential targets, including cathepsin D (CTSD), were found using molecular docking, and the component-differential target network was established. Inverse-docking targets including p38 MAPK and CDK-2 were found, and the network of component-reverse docking target was established. Through PPI analysis, 17 inverse-docking targets were linked to differential proteins. The combined network of component-inverse docking target-differential proteins was then constructed. The expressions of CTSD, p-p38 MAPK, and p-CDK-2 were shown to be increased in the oxalate group and decreased in kidney tissue by the DS treatment. Luteolin, apigenin, and genistein could protect oxalate-stimulated tubular cells as active components of DS. Conclusion: The potential targets including the CTSD, p38 MAPK, and CDK2 of DS in oxalate-induced kidney injuries and the active components (luteolin, apigenin, and genistein) of DS were successfully identified in this study by combining proteomics analysis, network pharmacology prediction, and experimental validation.

The Role of Specific Alcohol-Related Problems in Predicting Depressive Experiences in a Cross-Sectional National Household Survey.

PubMed

McBride, Orla; Cheng, Hui G; Slade, Tim; Lynskey, Michael T

2016-11-01

This study examines the type of alcohol-related problems that commonly occur before the onset of depressive experiences to shed light on the mechanisms underlying the alcohol-depression comorbidity relationship. Data were from the 1992 USA National Longitudinal Alcohol Epidemiologic Survey. Analytical sample comprised of drinkers with a prior to past year (PPY) history of alcohol-related problems with or without any experiences of depressed mood in the past year (PY). The prevalence of PPY alcohol-related problems was examined, as well as the ability of specific alcohol problems to predict PY experiences of depressed mood. The type of depressed mood experienced by drinkers with PPY history of alcohol-related problems was compared to those without. All but one alcohol-related problem PPY was more frequently endorsed among drinkers with PY experiences of depressed mood. Controlling for confounders, five alcohol-related problems experienced PPY were significantly predictive of depressed mood PY: tolerance, drinking longer than intended, inability to perform important social and occupational roles/obligations, as well as drinking in physically hazardous situations. Drinkers with alcohol-related problems PPY more frequently experienced difficulties with concentration, energy, and thoughts of death, than those without. Alcohol-related problems are likely associated with depressive experiences through a complex network, whereby experiences of physical dependence and negative consequences increase the likelihood of negative affect. Novel study designs are necessary to fully understand the complex mechanisms underlying this comorbidity. © The Author 2016. Medical Council on Alcohol and Oxford University Press. All rights reserved.

Polypyrrole/carbon nanotube nanocomposite enhanced the electrochemical capacitance of flexible graphene film for supercapacitors

NASA Astrophysics Data System (ADS)

Lu, Xiangjun; Dou, Hui; Yuan, Changzhou; Yang, Sudong; Hao, Liang; Zhang, Fang; Shen, Laifa; Zhang, Luojiang; Zhang, Xiaogang

2012-01-01

The flexible electrodes have important potential applications in energy storage of portable electronic devices for their powerful structural properties. In this work, unique flexible films with polypyrrole/carbon nanotube (PPy/CNT) composite homogeneously distributed between graphene (GN) sheets are successfully prepared by flow-assembly of the mixture dispersion of GN and PPy/CNT. In such layered structure, the coaxial PPy/CNT nanocables can not only enlarge the space between GN sheets but also provide pseudo-capacitance to enhance the total capacitance of electrodes. According to the galvanostatic charge/discharge analysis, the mass and volume specific capacitances of GN-PPy/CNT (52 wt% PPy/CNT) are 211 F g-1 and 122 F cm-3 at a current density of 0.2 A g-1, higher than those of the GN film (73 F g-1 and 79 F cm-3) and PPy/CNT (164 F g-1 and 67 F cm-3). Significantly, the GN-PPy/CNT electrode shows excellent cycling stability (5% capacity loss after 5000 cycles) due to the flexible GN layer and the rigid CNT core synergistical releasing the intrinsic differential strain of PPy chains during long-term charge/discharge cycles.

Preparation and characterization of RuO2/polypyrrole electrodes for supercapacitors

NASA Astrophysics Data System (ADS)

Li, Xiang; Wu, Yujiao; Zheng, Feng; Ling, Min; Lu, Fanghai

2014-11-01

Polypyrrole (PPy) embedded RuO2 electrodes were prepared by the composite method. Precursor solution of RuO2 was coated on tantalum sheet and annealed at 260 °C for 2.5 h to develop a thin film. PPy particles were deposited on RuO2 films and dried at 80 °C for 12 h to form composite electrode. Microstructure and morphology of RuO2/PPy electrode were characterized using Fourier transform infrared spectrometer, X-ray diffraction and scanning electron microscopy, respectively. Our results confirmed that counter ions are incorporated into RuO2 matrix. Structure of the composite with amorphous phase was verified by X-ray diffraction. Analysis by scanning electron microscopy reveals that during grain growth of RuO2/PPy, PPy particle size sharply increases as deposition time is over 20 min. Electrochemical properties of RuO2/PPy electrode were calculated using cyclic voltammetry. As deposition times of PPy are 10, 20, 25 and 30 min, specific capacitances of composite electrodes reach 657, 553, 471 and 396 F g-1, respectively. Cyclic behaviors of RuO2/PPy composite electrodes are stable.

Deficient prepulse inhibition in schizophrenia detected by the multi-site COGS.

PubMed

Swerdlow, Neal R; Light, Gregory A; Sprock, Joyce; Calkins, Monica E; Green, Michael F; Greenwood, Tiffany A; Gur, Raquel E; Gur, Ruben C; Lazzeroni, Laura C; Nuechterlein, Keith H; Radant, Allen D; Ray, Amrita; Seidman, Larry J; Siever, Larry J; Silverman, Jeremy M; Stone, William S; Sugar, Catherine A; Tsuang, Debby W; Tsuang, Ming T; Turetsky, Bruce I; Braff, David L

2014-02-01

Startle inhibition by weak prepulses (PPI) is studied to understand the biology of information processing in schizophrenia patients and healthy comparison subjects (HCS). The Consortium on the Genetics of Schizophrenia (COGS) identified associations between PPI and single nucleotide polymorphisms in schizophrenia probands and unaffected relatives, and linkage analyses extended evidence for the genetics of PPI deficits in schizophrenia in the COGS-1 family study. These findings are being extended in a 5-site "COGS-2" study of 1800 patients and 1200 unrelated HCS to facilitate genetic analyses. We describe a planned interim analysis of COGS-2 PPI data. Eyeblink startle was measured in carefully screened HCS and schizophrenia patients (n=1402). Planned analyses of PPI (60 ms intervals) assessed effects of diagnosis, sex and test site, PPI-modifying effects of medications and smoking, and relationships between PPI and neurocognitive measures. 884 subjects met strict inclusion criteria. ANOVA of PPI revealed significant effects of diagnosis (p=0.0005) and sex (p<0.002), and a significant diagnosis×test site interaction. HCS>schizophrenia PPI differences were greatest among patients not taking 2nd generation antipsychotics, and were independent of smoking status. Modest but significant relationships were detected between PPI and performance in specific neurocognitive measures. The COGS-2 multi-site study detects schizophrenia-related PPI deficits reported in single-site studies, including patterns related to diagnosis, prepulse interval, sex, medication and other neurocognitive measures. Site differences were detected and explored. The target COGS-2 schizophrenia "endophenotype" of reduced PPI should prove valuable for identifying and confirming schizophrenia risk genes in future analyses. Copyright © 2013 Elsevier B.V. All rights reserved.

Deficient prepulse inhibition in schizophrenia detected by the multi-site COGS

PubMed Central

Swerdlow, Neal R.; Light, Gregory A.; Sprock, Joyce; Calkins, Monica E.; Green, Michael F.; Greenwood, Tiffany A.; Gur, Raquel E.; Gur, Ruben C.; Lazzeroni, Laura C.; Nuechterlein, Keith H.; Radant, Allen D.; Ray, Amrita; Seidman, Larry J.; Siever, Larry J.; Silverman, Jeremy M.; Stone, William S.; Sugar, Catherine A.; Tsuang, Debby W.; Tsuang, Ming T.; Turetsky, Bruce I.; Braff, David L.

2014-01-01

Background Startle inhibition by weak prepulses (PPI) is studied to understand the biology of information processing in schizophrenia patients and healthy comparison subjects (HCS). The Consortium on the Genetics of Schizophrenia (COGS) identified associations between PPI and single nucleotide polymorphisms in schizophrenia probands and unaffected relatives, and linkage analyses extended evidence for the genetics of PPI deficits in schizophrenia in the COGS-1 family study. These findings are being extended in a 5-site “COGS-2” study of 1800 patients and 1200 unrelated HCS to facilitate genetic analyses. We describe a planned interim analysis of COGS-2 PPI data. Methods Eyeblink startle was measured in carefully screened HCS and schizophrenia patients (n=1402). Planned analyses of PPI (60 ms intervals) assessed effects of diagnosis, sex and test site, PPI-modifying effects of medications and smoking, and relationships between PPI and neurocognitive measures. Results 884 subjects met strict inclusion criteria. ANOVA of PPI revealed significant effects of diagnosis (p=0.0005) and sex (p<0.002), and a significant diagnosis × test site interaction. HCS > schizophrenia PPI differences were greatest among patients not taking 2nd generation antipsychotics, and were independent of smoking status. Modest but significant relationships were detected between PPI and performance in specific neurocognitive measures. Discussion The COGS-2 multi-site study detects schizophrenia-related PPI deficits reported in single-site studies, including patterns related to diagnosis, prepulse interval, sex, medication and other neurocognitive measures. Site differences were detected and explored. The target COGS-2 schizophrenia “endophenotype” of reduced PPI should prove valuable for identifying and confirming schizophrenia risk genes in future analyses. PMID:24405980

Polypyrrole/Alginate Hybrid Hydrogels: Electrically Conductive and Soft Biomaterials for Human Mesenchymal Stem Cell Culture and Potential Neural Tissue Engineering Applications.

PubMed

Yang, Sumi; Jang, LindyK; Kim, Semin; Yang, Jongcheol; Yang, Kisuk; Cho, Seung-Woo; Lee, Jae Young

2016-11-01

Electrically conductive biomaterials that can efficiently deliver electrical signals to cells or improve electrical communication among cells have received considerable attention for potential tissue engineering applications. Conductive hydrogels are desirable particularly for neural applications, as they can provide electrical signals and soft microenvironments that can mimic native nerve tissues. In this study, conductive and soft polypyrrole/alginate (PPy/Alg) hydrogels are developed by chemically polymerizing PPy within ionically cross-linked alginate hydrogel networks. The synthesized hydrogels exhibit a Young's modulus of 20-200 kPa. Electrical conductance of the PPy/Alg hydrogels could be enhanced by more than one order of magnitude compared to that of pristine alginate hydrogels. In vitro studies with human bone marrow-derived mesenchymal stem cells (hMSCs) reveal that cell adhesion and growth are promoted on the PPy/Alg hydrogels. Additionally, the PPy/Alg hydrogels support and greatly enhance the expression of neural differentiation markers (i.e., Tuj1 and MAP2) of hMSCs compared to tissue culture plate controls. Subcutaneous implantation of the hydrogels for eight weeks induces mild inflammatory reactions. These soft and conductive hydrogels will serve as a useful platform to study the effects of electrical and mechanical signals on stem cells and/or neural cells and to develop multifunctional neural tissue engineering scaffolds. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Coactivation of cognitive control networks during task switching.

PubMed

Yin, Shouhang; Deák, Gedeon; Chen, Antao

2018-01-01

The ability to flexibly switch between tasks is considered an important component of cognitive control that involves frontal and parietal cortical areas. The present study was designed to characterize network dynamics across multiple brain regions during task switching. Functional magnetic resonance images (fMRI) were captured during a standard rule-switching task to identify switching-related brain regions. Multiregional psychophysiological interaction (PPI) analysis was used to examine effective connectivity between these regions. During switching trials, behavioral performance declined and activation of a generic cognitive control network increased. Concurrently, task-related connectivity increased within and between cingulo-opercular and fronto-parietal cognitive control networks. Notably, the left inferior frontal junction (IFJ) was most consistently coactivated with the 2 cognitive control networks. Furthermore, switching-dependent effective connectivity was negatively correlated with behavioral switch costs. The strength of effective connectivity between left IFJ and other regions in the networks predicted individual differences in switch costs. Task switching was supported by coactivated connections within cognitive control networks, with left IFJ potentially acting as a key hub between the fronto-parietal and cingulo-opercular networks. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Proton pump inhibitor for non-erosive reflux disease: A meta-analysis

PubMed Central

Zhang, Ji-Xiang; Ji, Meng-Yao; Song, Jia; Lei, Hong-Bo; Qiu, Shi; Wang, Jing; Ai, Ming-Hua; Wang, Jun; Lv, Xiao-Guang; Yang, Zi-Rong; Dong, Wei-Guo

2013-01-01

AIM: To evaluate the efficacy, safety and influential factors of proton pump inhibitor (PPI) treatment for non-erosive reflux disease (NERD). METHODS: PubMed, MEDLINE, EMBASE and the Cochrane Library were searched up to April 2013 to identify eligible randomized controlled trials (RCTs) that probed into the efficacy, safety and influential factors of PPI treatment for NERD. The rates of symptomatic relief and adverse events were measured as the outcomes. After RCT selection, assessment and data collection, the pooled RRs and 95%CI were calculated. This meta-analysis was performed using the Stata 12.0 software (Stata Corporation, College Station, Texas, United States). The level of evidence was estimated by the Grading of Recommendations Assessment, Development and Evaluation system. RESULTS: Seventeen RCTs including 6072 patients met the inclusion criteria. The results of the meta-analysis showed that PPI treatment was significantly superior to H2 receptor antagonists (H2RA) treatment (RR = 1.629, 95%CI: 1.422-1.867, P = 0.000) and placebo (RR = 1.903, 95%CI: 1.573-2.302, P = 0.000) for the symptomatic relief of NERD. However, there were no obvious differences between PPI and H2RA (RR = 0.928, 95%CI: 0.776-1.110, P = 0.414) or PPI and the placebo (RR = 1.000, 95%CI: 0.896-1.116, P = 0.997) regarding the rate of adverse events. The overall rate of symptomatic relief of PPI against NERD was 51.4% (95%CI: 0.433-0.595, P = 0.000), and relief was influenced by hiatal hernia (P = 0.030). The adverse rate of PPI against NERD was 21.0% (95%CI: 0.152-0.208, P = 0.000), and was affected by hiatal hernia (P = 0.081) and drinking (P = 0.053). CONCLUSION: PPI overmatched H2RA on symptomatic relief rate but not on adverse rate for NERD. Its relief rate and adverse rate were influenced by hiatal hernia and drinking. PMID:24363534

Integrated Modules Analysis to Explore the Molecular Mechanisms of Phlegm-Stasis Cementation Syndrome with Ischemic Heart Disease.

PubMed

Xu, Wei-Ming; Yang, Kuo; Jiang, Li-Jie; Hu, Jing-Qing; Zhou, Xue-Zhong

2018-01-01

Background: Ischemic heart disease (IHD) has been the leading cause of death for several decades globally, IHD patients usually hold the symptoms of phlegm-stasis cementation syndrome (PSCS) as significant complications. However, the underlying molecular mechanisms of PSCS complicated with IHD have not yet been fully elucidated. Materials and Methods: Network medicine methods were utilized to elucidate the underlying molecular mechanisms of IHD phenotypes. Firstly, high-quality IHD-associated genes from both human curated disease-gene association database and biomedical literatures were integrated. Secondly, the IHD disease modules were obtained by dissecting the protein-protein interaction (PPI) topological modules in the String V9.1 database and the mapping of IHD-associated genes to the PPI topological modules. After that, molecular functional analyses (e.g., Gene Ontology and pathway enrichment analyses) for these IHD disease modules were conducted. Finally, the PSCS syndrome modules were identified by mapping the PSCS related symptom-genes to the IHD disease modules, which were further validated by both pharmacological and physiological evidences derived from published literatures. Results: The total of 1,056 high-quality IHD-associated genes were integrated and evaluated. In addition, eight IHD disease modules (the PPI sub-networks significantly relevant to IHD) were identified, in which two disease modules were relevant to PSCS syndrome (i.e., two PSCS syndrome modules). These two modules had enriched pathways on Toll-like receptor signaling pathway (hsa04620) and Renin-angiotensin system (hsa04614), with the molecular functions of angiotensin maturation (GO:0002003) and response to bacterium (GO:0009617), which had been validated by classical Chinese herbal formulas-related targets, IHD-related drug targets, and the phenotype features derived from human phenotype ontology (HPO) and published biomedical literatures. Conclusion: A network medicine-based approach was proposed to identify the underlying molecular modules of PSCS complicated with IHD, which could be used for interpreting the pharmacological mechanisms of well-established Chinese herbal formulas ( e.g., Tao Hong Si Wu Tang, Dan Shen Yin, Hunag Lian Wen Dan Tang and Gua Lou Xie Bai Ban Xia Tang ). In addition, these results delivered novel understandings of the molecular network mechanisms of IHD phenotype subtypes with PSCS complications, which would be both insightful for IHD precision medicine and the integration of disease and TCM syndrome diagnoses.

Integrated Modules Analysis to Explore the Molecular Mechanisms of Phlegm-Stasis Cementation Syndrome with Ischemic Heart Disease

PubMed Central

Xu, Wei-Ming; Yang, Kuo; Jiang, Li-Jie; Hu, Jing-Qing; Zhou, Xue-Zhong

2018-01-01

Background: Ischemic heart disease (IHD) has been the leading cause of death for several decades globally, IHD patients usually hold the symptoms of phlegm-stasis cementation syndrome (PSCS) as significant complications. However, the underlying molecular mechanisms of PSCS complicated with IHD have not yet been fully elucidated. Materials and Methods: Network medicine methods were utilized to elucidate the underlying molecular mechanisms of IHD phenotypes. Firstly, high-quality IHD-associated genes from both human curated disease-gene association database and biomedical literatures were integrated. Secondly, the IHD disease modules were obtained by dissecting the protein-protein interaction (PPI) topological modules in the String V9.1 database and the mapping of IHD-associated genes to the PPI topological modules. After that, molecular functional analyses (e.g., Gene Ontology and pathway enrichment analyses) for these IHD disease modules were conducted. Finally, the PSCS syndrome modules were identified by mapping the PSCS related symptom-genes to the IHD disease modules, which were further validated by both pharmacological and physiological evidences derived from published literatures. Results: The total of 1,056 high-quality IHD-associated genes were integrated and evaluated. In addition, eight IHD disease modules (the PPI sub-networks significantly relevant to IHD) were identified, in which two disease modules were relevant to PSCS syndrome (i.e., two PSCS syndrome modules). These two modules had enriched pathways on Toll-like receptor signaling pathway (hsa04620) and Renin-angiotensin system (hsa04614), with the molecular functions of angiotensin maturation (GO:0002003) and response to bacterium (GO:0009617), which had been validated by classical Chinese herbal formulas-related targets, IHD-related drug targets, and the phenotype features derived from human phenotype ontology (HPO) and published biomedical literatures. Conclusion: A network medicine-based approach was proposed to identify the underlying molecular modules of PSCS complicated with IHD, which could be used for interpreting the pharmacological mechanisms of well-established Chinese herbal formulas (e.g., Tao Hong Si Wu Tang, Dan Shen Yin, Hunag Lian Wen Dan Tang and Gua Lou Xie Bai Ban Xia Tang). In addition, these results delivered novel understandings of the molecular network mechanisms of IHD phenotype subtypes with PSCS complications, which would be both insightful for IHD precision medicine and the integration of disease and TCM syndrome diagnoses. PMID:29403392

FGF2 and FAM201A affect the development of osteonecrosis of the femoral head after femoral neck fracture.

PubMed

Huang, Gangyong; Zhao, Guanglei; Xia, Jun; Wei, Yibing; Chen, Feiyan; Chen, Jie; Shi, Jingsheng

2018-04-30

Osteonecrosis of the femoral head (ONFH) is a common orthopedic disease associated with high disability, and femoral neck fracture (FNF) is one of the most common reasons for traumatic ONFH. This study was designed to reveal the mechanisms underlying ONFH. Using fastx_toolkit and prinseq-lite tools, quality control was conducted for the sequencing data. The differentially expressed genes (DEGs, including both mRNAs and lncRNAs) between ONFH and FNF samples were identified using the edgeR package in R, and were then subjected to enrichment analysis using the BioCloud platform. Subsequently, protein-protein interaction (PPI) networks were constructed using Cytoscape software. After the target genes of DE-lncRNAs were predicted based on Spearman's rank correlation coefficient, lncRNA-gene coexpression network was visualized using the Cytoscape software. Furthermore, functional enrichment analysis was carried out for the target genes using the clusterprofiler package in R. Additionally, the key genes were detected by quantitative real-time polymerase chain reaction (qRT-PCR). A total of 2965 DEGs were identified from the ONFH samples, including 602 DE-lncRNAs (such as downregulated FAM201A). In the PPI networks, eight upregulated genes (including FGF2, IGF1, SOX9, and COL2A1) and 11 downregulated genes were among the top 20 genes according to all of the scores, such as degree centrality, closeness centrality, and betweenness centrality scores. Functional enrichment analysis showed that IGF1, SOX9, and COL2A1 were significantly enriched during skeletal system development. Moreover, qRT-PCR experiments detected the upregulation of FGF2 and downregulation of FAM201A in ONFH samples. FGF2 and FAM201A were correlated with the development of ONFH. Besides, IGF1, SOX9, and COL2A1 might also affect the pathogenesis of ONFH. Copyright © 2018. Published by Elsevier B.V.

Brand name and generic proton pump inhibitor prescriptions in the United States: insights from the national ambulatory medical care survey (2006-2010).

PubMed

Gawron, Andrew J; Feinglass, Joseph; Pandolfino, John E; Tan, Bruce K; Bove, Michiel J; Shintani-Smith, Stephanie

2015-01-01

Introduction. Proton pump inhibitors (PPI) are one of the most commonly prescribed medication classes with similar efficacy between brand name and generic PPI formulations. Aims. We determined demographic, clinical, and practice characteristics associated with brand name PPI prescriptions at ambulatory care visits in the United States. Methods. Observational cross sectional analysis using the National Ambulatory Medical Care Survey (NAMCS) of all adult (≥18 yrs of age) ambulatory care visits from 2006 to 2010. PPI prescriptions were identified by using the drug entry code as brand name only or generic available formulations. Descriptive statistics were reported in terms of unweighted patient visits and proportions of encounters with brand name PPI prescriptions. Global chi-square tests were used to compare visits with brand name PPI prescriptions versus generic PPI prescriptions for each measure. Poisson regression was used to determine the incidence rate ratio (IRR) for generic versus brand PPI prescribing. Results. A PPI was prescribed at 269.7 million adult ambulatory visits, based on 9,677 unweighted visits, of which 53% were brand name only prescriptions. In 2006, 76.0% of all PPI prescriptions had a brand name only formulation compared to 31.6% of PPI prescriptions in 2010. Visits by patients aged 25-44 years had the greatest proportion of brand name PPI formulations (57.9%). Academic medical centers and physician-owned practices had the greatest proportion of visits with brand name PPI prescriptions (58.9% and 55.6% of visits with a PPI prescription, resp.). There were no significant differences in terms of median income, patient insurance type, or metropolitan status when comparing the proportion of visits with brand name versus generic PPI prescriptions. Poisson regression results showed that practice ownership type was most strongly associated with the likelihood of receiving a brand name PPI over the entire study period. Compared to HMO visits, patient visits at academic medical centers (IRR 4.2, 95% CI 2.2-8.0), physician-owned practices (IRR 3.9, 95% CI 2.1-7.1), and community health centers (IRR 3.6, 95% CI 1.9-6.6) were all more likely to have brand name PPIs. Conclusion. PPI prescriptions with brand name only formulations are most strongly associated with physician practice type.

A novel one-class SVM based negative data sampling method for reconstructing proteome-wide HTLV-human protein interaction networks.

PubMed

Mei, Suyu; Zhu, Hao

2015-01-26

Protein-protein interaction (PPI) prediction is generally treated as a problem of binary classification wherein negative data sampling is still an open problem to be addressed. The commonly used random sampling is prone to yield less representative negative data with considerable false negatives. Meanwhile rational constraints are seldom exerted on model selection to reduce the risk of false positive predictions for most of the existing computational methods. In this work, we propose a novel negative data sampling method based on one-class SVM (support vector machine, SVM) to predict proteome-wide protein interactions between HTLV retrovirus and Homo sapiens, wherein one-class SVM is used to choose reliable and representative negative data, and two-class SVM is used to yield proteome-wide outcomes as predictive feedback for rational model selection. Computational results suggest that one-class SVM is more suited to be used as negative data sampling method than two-class PPI predictor, and the predictive feedback constrained model selection helps to yield a rational predictive model that reduces the risk of false positive predictions. Some predictions have been validated by the recent literature. Lastly, gene ontology based clustering of the predicted PPI networks is conducted to provide valuable cues for the pathogenesis of HTLV retrovirus.

Cost Effectiveness of Gastroprotection with Proton Pump Inhibitors in Older Low-Dose Acetylsalicylic Acid Users in the Netherlands.

PubMed

Chau, Sek Hung; Sluiter, Reinier L; Kievit, Wietske; Wensing, Michel; Teichert, Martina; Hugtenburg, Jacqueline G

2017-05-01

The present study aimed to assess the cost effectiveness of concomitant proton pump inhibitor (PPI) treatment in low-dose acetylsalicylic acid (LDASA) users at risk of upper gastrointestinal (UGI) adverse effects as compared with no PPI co-medication with attention to the age-dependent influence of PPI-induced adverse effects. We used a Markov model to compare the strategy of PPI co-medication with no PPI co-medication in older LDASA users at risk of UGI adverse effects. As PPIs reduce the risk of UGI bleeding and dyspepsia, these risk factors were modelled together with PPI adverse effects for LDASA users 60-69, 70-79 (base case) and 80 years and older. Incremental cost-utility ratios (ICURs) were calculated as cost per quality-adjusted life-year (QALY) gained per age category. Furthermore, a budget impact analysis assessed the expected changes in expenditure of the Dutch healthcare system following the adoption of PPI co-treatment in all LDASA users potentially at risk of UGI adverse effects. PPI co-treatment of 70- to 79-year-old LDASA users, as compared with no PPI, resulted in incremental costs of €100.51 at incremental effects of 0.007 QALYs with an ICUR of €14,671/QALY. ICURs for 60- to 69-year-old LDASA users were €13,264/QALY and €64,121/QALY for patients 80 years and older. Initiation of PPI co-treatment for all Dutch LDASA users of 60 years and older at risk of UGI adverse effects but not prescribed a PPI (19%) would have cost €1,280,478 in the first year (year 2013 values). PPI co-medication in LDASA users at risk of UGI adverse effects is generally cost effective. However, this strategy becomes less cost effective with higher age, particularly in patients aged 80 years and older, mainly due to the increased risks of PPI-induced adverse effects.

Esophageal motor dysfunction plays a key role in GERD with globus sensation--analysis of factors promoting resistance to PPI therapy.

PubMed

Tsutsui, Hideaki; Manabe, Noriaki; Uno, Masako; Imamura, Hiroshi; Kamada, Tomoari; Kusunoki, Hiroaki; Shiotani, Akiko; Hata, Jiro; Harada, Tamotsu; Haruma, Ken

2012-09-01

Patients with gastroesophageal reflux disease (GERD) also have various extra-esophageal symptoms. Laryngopharyngeal reflux disease (LPRD) is a subtype of GERD associated with globus sensation, but proton pump inhibitor (PPI) therapy achieves disappointing results. This study investigated esophageal motility in GERD patients with globus sensation who were resistant to PPI therapy. The subjects were 350 patients with globus sensation. All patients underwent both laryngoscopy and upper gastrointestinal endoscopy to exclude organic disease. After 4 weeks of treatment with rabeprazole sodium (20 mg daily), the patients were divided into PPI-responsive and PPI-resistant groups. Then we investigated esophageal motility in the PPI-resistant group by a multichannel intraluminal impedance and manometry study. A total of 119 patients (55.6%) were resistant to PPI therapy, among whom 57 patients (47.9%) had abnormal esophageal motility. They included 36 patients (66.4%) with ineffective esophageal motility, 9 patients (14.4%) with achalasia, 6 patients (9.6%) with diffuse esophageal spasm, 5 patients (8%) with nutcracker esophagus, and 1 patient (1.6%) with hypertensive lower esophageal sphincter. There were significant differences of upper esophageal sphincter pressure and esophageal body peristalsis between the patients with PPI-resistant LPRD and healthy controls matched for age and sex. Among patients with PPI-resistant LPRD, 47.9% had abnormal esophageal motility.

The electrochemical behavior of poly 1-pyrenemethyl methacrylate binder and its effect on the interfacial chemistry of a silicon electrode

NASA Astrophysics Data System (ADS)

Haregewoin, Atetegeb Meazah; Terborg, Lydia; Zhang, Liang; Jurng, Sunhyung; Lucht, Brett L.; Guo, Jinghua; Ross, Philip N.; Kostecki, Robert

2018-02-01

The physico-chemical properties of poly (1-pyrenemethyl methacrylate) (PPy) are presented with respect to its use as a binder in a Si composite anode for Li-ion batteries. PPy thin-films on Si(100) wafer and Cu model electrodes are shown to exhibit superior adhesion as compared to conventional polyvinylidene difluoride (PVdF) binder. Electrochemical testing of the model bi-layer PPy/Si(100) electrodes in a standard organic carbonate electrolyte reveal higher electrolyte reduction current and an overall irreversible cathodic charge consumption during initial cycling versus the uncoated Si electrode. The PPy thin-film is also shown to impede lithiation of the underlying Si. XAS, AFM, TGA and ATR-FTIR analysis indicated that PPy binder is both chemically and electrochemically stable in the cycling potential range however significant swelling is observed due to a selective uptake of diethyl carbonate (DEC) from the electrolyte. The increased concentration of DEC and depletion of ethylene carbonate (EC) at the Si/PPy interface leads to continuous decomposition of the electrolyte and results in non-passivating behavior of the Si(100)/PPy electrode as compared to pristine silicon. Consequently, PPy binder improves the mechanical integrity of composite Si anodes but it influences mass transport at the Si(100)/PPy interface and alters electrochemical response of silicon during cycling in an adverse manner.

Heteroprotein Complex Formation of Bovine Lactoferrin and Pea Protein Isolate: A Multiscale Structural Analysis.

PubMed

Adal, Eda; Sadeghpour, Amin; Connell, Simon; Rappolt, Michael; Ibanoglu, Esra; Sarkar, Anwesha

2017-02-13

Associative electrostatic interactions between two oppositely charged globular proteins, lactoferrin (LF) and pea protein isolate (PPI), the latter being a mixture of vicilin, legumin, and convicilin, was studied with a specific PPI/LF molar ratio at room temperature. Structural aspects of the electrostatic complexes probed at different length scales were investigated as a function of pH by means of different complementary techniques, namely, with dynamic light scattering, small-angle X-ray scattering (SAXS), turbidity measurements, and atomic force microscopy (AFM). Irrespective of the applied techniques, the results consistently displayed that complexation between LF and PPI did occur. In an optimum narrow range of pH 5.0-5.8, a viscous liquid phase of complex coacervate was obtained upon mild centrifugation of the turbid LF-PPI mixture with a maximum R h , turbidity and the ζ-potential being close to zero observed at pH 5.4. In particular, the SAXS data demonstrated that the coacervates were densely assembled with a roughly spherical size distribution exhibiting a maximum extension of ∼80 nm at pH 5.4. Equally, AFM image analysis showed size distributions containing most frequent cluster sizes around 40-80 nm with spherical to elliptical shapes (axis aspect ratio ≤ 2) as well as less frequent elongated to chainlike structures. The most frequently observed compact complexes, we identify as mainly leading to LF-PPI coacervation, whereas for the less frequent chain-like aggregates, we hypothesize that additionally PPI-PPI facilitated complexes exist.

Stringent DDI-based Prediction of H. sapiens-M. tuberculosis H37Rv Protein-Protein Interactions

PubMed Central

2013-01-01

Background H. sapiens-M. tuberculosis H37Rv protein-protein interaction (PPI) data are very important information to illuminate the infection mechanism of M. tuberculosis H37Rv. But current H. sapiens-M. tuberculosis H37Rv PPI data are very scarce. This seriously limits the study of the interaction between this important pathogen and its host H. sapiens. Computational prediction of H. sapiens-M. tuberculosis H37Rv PPIs is an important strategy to fill in the gap. Domain-domain interaction (DDI) based prediction is one of the frequently used computational approaches in predicting both intra-species and inter-species PPIs. However, the performance of DDI-based host-pathogen PPI prediction has been rather limited. Results We develop a stringent DDI-based prediction approach with emphasis on (i) differences between the specific domain sequences on annotated regions of proteins under the same domain ID and (ii) calculation of the interaction strength of predicted PPIs based on the interacting residues in their interaction interfaces. We compare our stringent DDI-based approach to a conventional DDI-based approach for predicting PPIs based on gold standard intra-species PPIs and coherent informative Gene Ontology terms assessment. The assessment results show that our stringent DDI-based approach achieves much better performance in predicting PPIs than the conventional approach. Using our stringent DDI-based approach, we have predicted a small set of reliable H. sapiens-M. tuberculosis H37Rv PPIs which could be very useful for a variety of related studies. We also analyze the H. sapiens-M. tuberculosis H37Rv PPIs predicted by our stringent DDI-based approach using cellular compartment distribution analysis, functional category enrichment analysis and pathway enrichment analysis. The analyses support the validity of our prediction result. Also, based on an analysis of the H. sapiens-M. tuberculosis H37Rv PPI network predicted by our stringent DDI-based approach, we have discovered some important properties of domains involved in host-pathogen PPIs. We find that both host and pathogen proteins involved in host-pathogen PPIs tend to have more domains than proteins involved in intra-species PPIs, and these domains have more interaction partners than domains on proteins involved in intra-species PPI. Conclusions The stringent DDI-based prediction approach reported in this work provides a stringent strategy for predicting host-pathogen PPIs. It also performs better than a conventional DDI-based approach in predicting PPIs. We have predicted a small set of accurate H. sapiens-M. tuberculosis H37Rv PPIs which could be very useful for a variety of related studies. PMID:24564941

Factor Structure of the Psychopathic Personality Inventory (PPI): Findings from a Large Incarcerated Sample

PubMed Central

Neumann, Craig S.; Malterer, Melanie B.; Newman, Joseph P.

2010-01-01

Recent exploratory factor analysis (EFA) of the Psychopathic Personality Inventory (PPI; Lilienfeld, 1990) with a community sample suggested that the PPI subscales may be comprised of two higher-order factors (Benning et al., 2003). However, little research has examined the PPI structure in offenders. The current study attempted to replicate the Benning et al. two-factor solution using a large (N=1224) incarcerated male sample. Confirmatory factor analysis (CFA) of this model with the full sample resulted in poor model fit. Next, to identify a factor solution that would summarize the offender data, EFA was conducted using a split-half of the total sample, followed by an attempt to replicate the EFA solution via CFA with the other split-half sample. Using the recommendations of Prooijen and van der Kloot (2001) for recovering EFA solutions, model fit results provided some evidence that the EFA solution could be recovered via CFA. However, this model involved extensive cross-loadings of the subscales across three factors, suggesting item overlap across PPI subscales. In sum, the two-factor solution reported by Benning et al. (2003) was not a viable model for the current sample of offenders, and additional research is needed to elucidate the latent structure of the PPI. PMID:18557694

Viral-templated gold/polypyrrole nanopeapods for an ammonia gas sensor

NASA Astrophysics Data System (ADS)

Yan, Yiran; Zhang, Miluo; Moon, Chung Hee; Su, Heng-Chia; Myung, Nosang V.; Haberer, Elaine D.

2016-08-01

One-dimensional gold/polypyrrole (Au/PPy) nanopeapods were fabricated using a viral template: M13 bacteriophage. The genetically modified filamentous virus displayed gold-binding peptides along its length, allowing selective attachment of gold nanoparticles (Au NPs) under ambient conditions. A PPy shell was electropolymerized on the viral-templated Au NP chains forming nanopeapod structures. The PPy shell morphology and thickness were controlled through electrodeposition potential and time, resulting in an ultra-thin conductive polymer shell of 17.4 ± 3.3 nm. A post-electrodeposition acid treatment was used to modify the electrical properties of these hybrid materials. The electrical resistance of the nanopeapods was monitored at each assembly step. Chemiresistive ammonia (NH3) gas sensors were developed from networks of the hybrid Au/PPy nanostructures. Room temperature sensing performance was evaluated from 5 to 50 ppmv and a mixture of reversible and irreversible chemiresistive behavior was observed. A sensitivity of 0.30%/ppmv was found for NH3 concentrations of 10 ppmv or less, and a lowest detection limit (LDL) of 0.007 ppmv was calculated. Furthermore, acid-treated devices exhibited an enhanced sensitivity of 1.26%/ppmv within the same concentration range and a calculated LDL of 0.005 ppmv.

The modified iron avidity index: a promising phenotypic predictor in HFE-related haemochromatosis.

PubMed

Verhaegh, Pauline L M; Moris, Wenke; Koek, Ger H; van Deursen, Cees Th B M

2016-10-01

Phenotypes of the HFE-related haemochromatosis vary considerably, making it hard to predict the course of iron accumulation. The aim of this retrospective study was to determine if the Iron Avidity Index (IAI) is a good phenotypic predictor of the number of phlebotomies needed per year during maintenance treatment (NPDMT) in patients with homozygous p.C282Y hereditary haemochromatosis (HH). Patients with HH homozygous for p.C282Y, on maintenance treatment for at least 1 year were included. The IAI (ferritin level at diagnosis/age at diagnosis) was calculated. Ninety-five patients were included in the analysis. Linear regression analysis showed the confounding effect of sex on the relationship between IAI and NPDMT. A modified IAI, adjusted for sex, was calculated. As proton pump inhibitor (PPI) use was independently associated with NPDMT, the group was split in PPI- and non-PPI-users. A positive correlation between the modified IAI and the NPDMT was shown in both groups (PPI r = 0.367, P = 0.023; non-PPI r = 0.453, P < 0.001). An ROC was computed to measure the accuracy of the modified IAI to predict who needed 0-2 vs. ≥3 maintenance treatments per year. The AUROC in the PPI and non-PPI group were respectively 0.576 (0.368-0.784) and 0.752 (0.606-0.899). The modified IAI is a fairly good predictor in non-PPI-using homozygous C282Y HH patients, to differentiate who needs ≥3 maintenance phlebotomies per year. Therefore, this index might help to select patients that benefit from an alternative less frequent therapy, e.g. erythrocytapheresis. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

PubMed Central

Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

2010-01-01

The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

Using Bioinformatics Approach to Explore the Pharmacological Mechanisms of Multiple Ingredients in Shuang-Huang-Lian

PubMed Central

Zhang, Bai-xia; Li, Jian; Gu, Hao; Li, Qiang; Zhang, Qi; Zhang, Tian-jiao; Wang, Yun; Cai, Cheng-ke

2015-01-01

Due to the proved clinical efficacy, Shuang-Huang-Lian (SHL) has developed a variety of dosage forms. However, the in-depth research on targets and pharmacological mechanisms of SHL preparations was scarce. In the presented study, the bioinformatics approaches were adopted to integrate relevant data and biological information. As a result, a PPI network was built and the common topological parameters were characterized. The results suggested that the PPI network of SHL exhibited a scale-free property and modular architecture. The drug target network of SHL was structured with 21 functional modules. According to certain modules and pharmacological effects distribution, an antitumor effect and potential drug targets were predicted. A biological network which contained 26 subnetworks was constructed to elucidate the antipneumonia mechanism of SHL. We also extracted the subnetwork to explicitly display the pathway where one effective component acts on the pneumonia related targets. In conclusions, a bioinformatics approach was established for exploring the drug targets, pharmacological activity distribution, effective components of SHL, and its mechanism of antipneumonia. Above all, we identified the effective components and disclosed the mechanism of SHL from the view of system. PMID:26495421

Esomeprazole use is independently associated with significant reduction of BMD: 1-year prospective comparative safety study of four proton pump inhibitors.

PubMed

Bahtiri, Elton; Islami, Hilmi; Hoxha, Rexhep; Qorraj-Bytyqi, Hasime; Rexhepi, Sylejman; Hoti, Kreshnik; Thaçi, Kujtim; Thaçi, Shpetim; Karakulak, Çağla

2016-09-01

Because of the efficacy of proton pump inhibitors (PPIs), their the use is increasing dramatically. The risk of adverse effects of short-term PPI therapy is low, but there are important safety concerns for potential adverse effects of prolonged PPI therapy. Findings from studies assessing the association between PPI use and bone mineral density (BMD) and/or fracture risk are contradictory. The aim of this study was to prospectively assess potential association of PPI treatment with the 12-month change in BMD of the lumbar spine, femur neck, and total hip. The study was performed in 200 PPI users and 50 PPI nonusers. Lumbar spine (L1-L4), femur neck, and total hip BMD were measured by dual-energy X-ray absorptiometry at the baseline and at 12 months. A total of 209 subjects completed the entire 12 months of the study and were included in the final analysis. A Wilcoxon signed-rank test showed that at 12 months PPI use was associated with statistically significant reductions in femur neck and total hip T scores (Z = -2.764, p = 0.005 and Z = -3.281, p = 0.001, respectively). A multiple linear regression analysis showed that only esomeprazole added significantly to the prediction of total lumbar spine and femur neck T scores (p = 0.048 and p = 0.037, respectively). Compared with the baseline, 12 months of PPI treatment resulted in lower femur neck and total hip BMD T scores. Among the four PPIs studied, esomeprazole was independently associated with significant reduction of BMD, whereas omeprazole had no effects on BMD. Considering the widespread use of PPIs, BMD screening should be considered in the case of prolonged PPI use.

LENS: web-based lens for enrichment and network studies of human proteins

PubMed Central

2015-01-01

Background Network analysis is a common approach for the study of genetic view of diseases and biological pathways. Typically, when a set of genes are identified to be of interest in relation to a disease, say through a genome wide association study (GWAS) or a different gene expression study, these genes are typically analyzed in the context of their protein-protein interaction (PPI) networks. Further analysis is carried out to compute the enrichment of known pathways and disease-associations in the network. Having tools for such analysis at the fingertips of biologists without the requirement for computer programming or curation of data would accelerate the characterization of genes of interest. Currently available tools do not integrate network and enrichment analysis and their visualizations, and most of them present results in formats not most conducive to human cognition. Results We developed the tool Lens for Enrichment and Network Studies of human proteins (LENS) that performs network and pathway and diseases enrichment analyses on genes of interest to users. The tool creates a visualization of the network, provides easy to read statistics on network connectivity, and displays Venn diagrams with statistical significance values of the network's association with drugs, diseases, pathways, and GWASs. We used the tool to analyze gene sets related to craniofacial development, autism, and schizophrenia. Conclusion LENS is a web-based tool that does not require and download or plugins to use. The tool is free and does not require login for use, and is available at http://severus.dbmi.pitt.edu/LENS. PMID:26680011

VANLO - Interactive visual exploration of aligned biological networks

PubMed Central

Brasch, Steffen; Linsen, Lars; Fuellen, Georg

2009-01-01

Background Protein-protein interaction (PPI) is fundamental to many biological processes. In the course of evolution, biological networks such as protein-protein interaction networks have developed. Biological networks of different species can be aligned by finding instances (e.g. proteins) with the same common ancestor in the evolutionary process, so-called orthologs. For a better understanding of the evolution of biological networks, such aligned networks have to be explored. Visualization can play a key role in making the various relationships transparent. Results We present a novel visualization system for aligned biological networks in 3D space that naturally embeds existing 2D layouts. In addition to displaying the intra-network connectivities, we also provide insight into how the individual networks relate to each other by placing aligned entities on top of each other in separate layers. We optimize the layout of the entire alignment graph in a global fashion that takes into account inter- as well as intra-network relationships. The layout algorithm includes a step of merging aligned networks into one graph, laying out the graph with respect to application-specific requirements, splitting the merged graph again into individual networks, and displaying the network alignment in layers. In addition to representing the data in a static way, we also provide different interaction techniques to explore the data with respect to application-specific tasks. Conclusion Our system provides an intuitive global understanding of aligned PPI networks and it allows the investigation of key biological questions. We evaluate our system by applying it to real-world examples documenting how our system can be used to investigate the data with respect to these key questions. Our tool VANLO (Visualization of Aligned Networks with Layout Optimization) can be accessed at . PMID:19821976

Screening of potential genes contributing to the macrocycle drug resistance of C. albicans via microarray analysis

PubMed Central

Yang, Jing; Zhang, Wei; Sun, Jian; Xi, Zhiqin; Qiao, Zusha; Zhang, Jinyu; Wang, Yan; Ji, Ying; Feng, Wenli

2017-01-01

The aim of the present study was to investigate the potential genes involved in drug resistance of Candida albicans (C. albicans) by performing microarray analysis. The gene expression profile of GSE65396 was downloaded from the Gene Expression Omnibus, including a control, 15-min and 45-min macrocyclic compound RF59-treated group with three repeats for each. Following preprocessing using RAM, the differentially expressed genes (DEGs) were screened using the Limma package. Subsequently, the Kyoto Encyclopedia of Genes and Genomes pathways of these genes were analyzed using the Database for Annotation, Visualization and Integrated Discovery. Based on interactions estimated by the Search Tool for Retrieval of Interacting Gene, the protein-protein interaction (PPI) network was visualized using Cytoscape. Subnetwork analysis was performed using ReactomeFI. A total of 154 upregulated and 27 downregulated DEGs were identified in the 15-min treated group, compared with the control, and 235 upregulated and 233 downregulated DEGs were identified in the 45-min treated group, compared with the control. The upregulated DEGs were significantly enriched in the ribosome pathway. Based on the PPI network, PRP5, RCL1, NOP13, NOP4 and MRT4 were the top five nodes in the 15-min treated comparison. GIS2, URA3, NOP58, ELP3 and PLP7 were the top five nodes in the 45-min treated comparison, and its subnetwork was significantly enriched in the ribosome pathway. The macrocyclic compound RF59 had a notable effect on the ribosome and its associated pathways of C. albicans. RCL1, NOP4, MRT4, GIS2 and NOP58 may be important in RF59-resistance. PMID:28944888

Cost effectiveness in Canada of a multidrug prepackaged regimen (Hp-PAC)+ for Helicobacter pylori eradication.

PubMed

Agro, K; Blackhouse, G; Goeree, R; Willan, A R; Huang, J Q; Hunt, R H; O'Brien, B J

2001-01-01

To assess the cost effectiveness of a multidrug prepackaged regimen for Helicobacter pylori, the Hp-PAC (lansoprazole 30mg, clarithromycin 500 mg, amoxicillin 1 g, all twice daily), relative to alternative pharmacological strategies in the management of confirmed duodenal ulcer over a 1-year period from 2 perspectives: (i) a strict healthcare payer perspective (Ontario Ministry of Health) excluding the patient copayment; and (ii) a healthcare payer perspective including the patient copayment. A decision-analytical model was developed to estimate expected per patient costs [1998 Canadian dollars ($ Can)], weeks without ulcer and symptomatic ulcer recurrences for the Hp-PAC compared with: proton pump inhibitor (PPI)-clarithromycin-amoxicillin (PPI-CA), PPI-clarithromycin-metronidazole (PPI-CM), PPI-amoxicillin-metronidazole (PPI-AM) and ranitidine-bismuthmetronidazole-tetracycline (RAN-BMT). All PPI-based regimens had higher expected costs but better outcomes relative to RAN-BMT. From a strict healthcare payer perspective, PPI-CM ($Can 209) yielded lower expected costs than PPI-CA ($Can 221) and slightly lower costs than Hp-PAC ($Can 211). However, these 3 regimens all shared identical outcomes (51.2 weeks without ulcer). When the current Ontario, Canada, $Can 2 patient copayment was added to the dispensing fee, Hp-PAC yielded lower costs ($Can 214) than PPI-CM ($Can 216). From a strict healthcare payer perspective, Hp-PAC is weakly dominated by PPI-CM with an incremental cost effectiveness (relative to RAN-BMT) of $Can 5.77 per ulcer week averted. When the patient copayment is added to this perspective, Hp-PAC weakly dominates PPI-CM ($Can 5 per ulcer week averted). Regardless of perspective, Hp-PAC and PPI-CM differed by only $Can 2 per patient over 1 year and the expected time without ulcer was 51.2 weeks for both. More data on the clinical and statistical differences in H. pylori eradication with Hp-PAC and PPI-CM would be useful. This analysis does not in clude the possible advantage of Hp-PAC in terms of compliance and antibacterial resistance.

The Indications, Applications, and Risks of Proton Pump Inhibitors.

PubMed

Mössner, Joachim

2016-07-11

Proton pump inhibitors (PPI) are the most effective drugs for inhibiting gastric acid secretion. They have been in clinical use for more than 25 years, In 2014, 3.475 billion daily defined doses (DDD) of PPI were prescribed in Germany. This high number alone calls for a critical analysis of the spectrum of indications for PPI and their potential adverse effects. This review is based on pertinent publications retrieved by a selective search in the PubMed and Cochrane Library databases, with particular emphasis on randomized, prospective multicenter trials, cohort studies, case-control studies, and meta-analyses. The inhibition of gastric acid secretion with PPI is successfully used for the treatment of gastroesophageal reflux disease and of gastric and duodenal ulcers, for the secondary prevention of gastroduodenal lesions that have arisen under treatment with nonsteroidal anti-inflammatory drugs and acetylsalicylic acid, and for the prevention of recurrent hemorrhage from ulcers after successful endoscopic hemostasis. PPI are given along with practically all antibiotic regimens for the eradication of Helicobacter pylori infection. The number of prescriptions for PPI has risen linearly over the past 25 years. As there has been no broadening of indications, one may well ask whether the current, extensive use of PPI is justified. There is evidence that patients taking PPI are at greater risk for fractures. Moreover, the vitamin B12 level should be checked occasionally in all patients taking PPI. PPI are among the more effective drugs for the treatment of diseases associated with gastric acid. In view of their cost and potential adverse effects, they should only be prescribed for scientifically validated indications.

Esophageal Motility and Rikkunshito Treatment for Proton Pump Inhibitor-Refractory Nonerosive Reflux Disease: A Prospective, Uncontrolled, Open-Label Pilot Study Trial.

PubMed

Odaka, Takeo; Yamato, Shigeru; Yokosuka, Osamu

2017-01-01

Only a few reports focused on esophageal motility in patients with proton pump inhibitor (PPI)-refractory nonerosive reflux disease (NERD) and there has been no established strategy for treatment. To clarify the characteristics of esophageal motility in patients with PPI-refractory NERD, we evaluated esophageal function using combined multichannel intraluminal impedance and esophageal manometry (MII-EM). In addition, we evaluated the efficacy of rikkunshito (RKT), which is a gastrointestinal prokinetic agent. Thirty patients with NERD were enrolled and underwent MII-EM. After 8 weeks of RKT (7.5 g/d) treatment, MII-EM was repeated on patients with PPI-refractory NERD. Symptoms were assessed by the Gastrointestinal Symptom Rating Scale. In patients with PPI-refractory NERD, measures of complete bolus transit, peristaltic contractions, and residual pressure of the lower esophageal sphincter during swallowing deviated from the standard values and esophageal clearance was found to be deteriorated. RKT significantly improved the peristaltic contractions ( P < 0.05), the complete bolus transit ( P < 0.01), and the residual pressure of lower esophageal sphincter ( P < 0.05) in these patients. The overall score ( P < 0.01) and the subscale scores of acid reflux syndrome ( P < 0.05), abdominal pain ( P < 0.05), and indigestion syndrome ( P < 0.01) in the Gastrointestinal Symptom Rating Scale were significantly improved by the 8-week RKT treatment. In the pilot study, patients with PPI-refractory NERD had disorders of esophageal and lower esophageal sphincter motility that were improved by RKT. Further studies examining esophageal motor activity of RKT in PPI-refractory NERD are required. University hospital Medical Information Network (UMIN) Clinical Trial Registry identifier: UMIN000003092.

A novel strategy of integrated microarray analysis identifies CENPA, CDK1 and CDC20 as a cluster of diagnostic biomarkers in lung adenocarcinoma.

PubMed

Liu, Wan-Ting; Wang, Yang; Zhang, Jing; Ye, Fei; Huang, Xiao-Hui; Li, Bin; He, Qing-Yu

2018-07-01

Lung adenocarcinoma (LAC) is the most lethal cancer and the leading cause of cancer-related death worldwide. The identification of meaningful clusters of co-expressed genes or representative biomarkers may help improve the accuracy of LAC diagnoses. Public databases, such as the Gene Expression Omnibus (GEO), provide rich resources of valuable information for clinics, however, the integration of multiple microarray datasets from various platforms and institutes remained a challenge. To determine potential indicators of LAC, we performed genome-wide relative significance (GWRS), genome-wide global significance (GWGS) and support vector machine (SVM) analyses progressively to identify robust gene biomarker signatures from 5 different microarray datasets that included 330 samples. The top 200 genes with robust signatures were selected for integrative analysis according to "guilt-by-association" methods, including protein-protein interaction (PPI) analysis and gene co-expression analysis. Of these 200 genes, only 10 genes showed both intensive PPI network and high gene co-expression correlation (r > 0.8). IPA analysis of this regulatory networks suggested that the cell cycle process is a crucial determinant of LAC. CENPA, as well as two linked hub genes CDK1 and CDC20, are determined to be potential indicators of LAC. Immunohistochemical staining showed that CENPA, CDK1 and CDC20 were highly expressed in LAC cancer tissue with co-expression patterns. A Cox regression model indicated that LAC patients with CENPA + /CDK1 + and CENPA + /CDC20 + were high-risk groups in terms of overall survival. In conclusion, our integrated microarray analysis demonstrated that CENPA, CDK1 and CDC20 might serve as novel cluster of prognostic biomarkers for LAC, and the cooperative unit of three genes provides a technically simple approach for identification of LAC patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Sensorimotor Gating in Depressed and Euthymic Patients with Bipolar Disorder: Analysis on Prepulse Inhibition of Acoustic Startle Response Stratified by Gender and State.

PubMed

Matsuo, Junko; Ota, Miho; Hidese, Shinsuke; Teraishi, Toshiya; Hori, Hiroaki; Ishida, Ikki; Hiraishi, Moeko; Kunugi, Hiroshi

2018-01-01

Prepulse inhibition (PPI) of the acoustic startle reflex is an operational measure of sensorimotor gating. The findings on PPI deficits in bipolar disorder (BD) are inconsistent among studies due to various confounding factors such as gender. This study aimed to assess sensorimotor gating deficits in patients with BD stratified by gender and state (depressed/euthymic), and to explore related clinical variables. Subjects were 106 non-manic BD patients (26 BD I and 80 BD II; 63 with depression and 43 euthymic) and 232 age-, gender-, and ethnicity-matched (Japanese) healthy controls. Depression severity was assessed using the Hamilton Depression Rating Scale-21. The electromyographic activity of the orbicularis oculi muscle was measured by a computerized startle reflex test unit. Startle magnitude, habituation, and PPI were compared among the three clinical groups: depressed BD, euthymic BD, and healthy controls. In a second analysis, patients were divided into four groups using the quartile PPI levels of controls of each gender, and a ratio of the low-PPI group (<1st quartile of controls) was compared. Effects of psychosis and medication status were examined by the Mann-Whitney U test. Clinical correlates such as medication dosage and depression severity with startle measurements were examined by Spearman's correlation. Male patients with depression, but not euthymic male patients, showed significantly lower PPI at a prepulse of 86 dB and 120 ms lead interval than did male controls. More than half of the male patients with depression showed low-PPI. In contrast, PPI in female patients did not differ from that in female controls in either the depressed or euthymic state. Female patients with active psychosis showed significantly lower PPI than those without psychosis. Female patients on typical antipsychotics had significantly lower PPI, than those without such medication. PPI showed a significant positive correlation with lamotrigine dosage in male patients and lithium dosage in female patients. These findings suggest that sensorimotor gating is impaired in male BD patients with depression. However, we obtained no evidence for such abnormalities in female BD patients except for those with current psychosis. The observed associations between medication and startle measurements warrant further investigation.

Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer

PubMed Central

Makondi, Precious Takondwa; Lee, Chia-Hwa; Huang, Chien-Yu; Chu, Chi-Ming; Chang, Yu-Jia

2018-01-01

Bevacizumab combined with cytotoxic chemotherapy is the backbone of metastatic colorectal cancer (mCRC) therapy; however, its treatment efficacy is hampered by therapeutic resistance. Therefore, understanding the mechanisms underlying bevacizumab resistance is crucial to increasing the therapeutic efficacy of bevacizumab. The Gene Expression Omnibus (GEO) database (dataset, GSE86525) was used to identify the key genes and pathways involved in bevacizumab-resistant mCRC. The GEO2R web tool was used to identify differentially expressed genes (DEGs). Functional and pathway enrichment analyses of the DEGs were performed using the Database for Annotation, Visualization, and Integrated Discovery(DAVID). Protein–protein interaction (PPI) networks were established using the Search Tool for the Retrieval of Interacting Genes/Proteins database(STRING) and visualized using Cytoscape software. A total of 124 DEGs were obtained, 57 of which upregulated and 67 were downregulated. PPI network analysis showed that seven upregulated genes and nine downregulated genes exhibited high PPI degrees. In the functional enrichment, the DEGs were mainly enriched in negative regulation of phosphate metabolic process and positive regulation of cell cycle process gene ontologies (GOs); the enriched pathways were the phosphoinositide 3-kinase-serine/threonine kinase signaling pathway, bladder cancer, and microRNAs in cancer. Cyclin-dependent kinase inhibitor 1A(CDKN1A), toll-like receptor 4 (TLR4), CD19 molecule (CD19), breast cancer 1, early onset (BRCA1), platelet-derived growth factor subunit A (PDGFA), and matrix metallopeptidase 1 (MMP1) were the DEGs involved in the pathways and the PPIs. The clinical validation of the DEGs in mCRC (TNM clinical stages 3 and 4) revealed that high PDGFA expression levels were associated with poor overall survival, whereas high BRCA1 and MMP1 expression levels were associated with favorable progress free survival(PFS). The identified genes and pathways can be potential targets and predictors of therapeutic resistance and prognosis in bevacizumab-treated patients with mCRC. PMID:29342159

Appropriate proton pump inhibitors use in elderly outpatients according to recommendations.

PubMed

Schonheit, Claire; Le Petitcorps, Hélène; Pautas, Éric

2016-12-01

Proton pump inhibitors (PPI) are widely prescribed, particularly in elderly patients, and their side effects are underestimated. Recommendations of the french health authorities, some specific to the elderly, specify their indications. The main objective of this descriptive and prospective study was to assess in elderly patients the adequacy of PPI prescriptions to these recommendations and to the marketing authorization. Analysis of all patients hospitalized in an acute geriatric unit over a period of 2 years for which the drug prescription on admission included a PPI. For the 125 patients included (mean age 84 years), the PPI treatment period exceeded one year in 68% of cases and 49.6% of PPI prescriptions were not consistent with the recommendations; not recommended indications are mainly prevention of gastroduodenal lesions in case of antiplatelet, VKA or corticosteroid treatment (24%), anemia (12%) or epigastric pain (8.5%) without prior endoscopic exploration. Only 50.4% of patients treated with PPI had an upper gastro-intestinal endoscopy, which should be systematically performed in patients over 65 years according to the recommendations. Our study confirms the low appropriateness of PPI prescriptions, particularly in elderly patients. This can be explained by controversial issues or by difficulties in adapting these recommendations in geriatric practice.

Nitrogen-doped carbon nanofibers derived from polypyrrole coated bacterial cellulose as high-performance electrode materials for supercapacitors and Li-ion batteries

DOE PAGES

Lei, Wen; Han, Lili; Xuan, Cuijuan; ...

2016-05-24

Here, nitrogen-doped carbon nanofiber (NDCN) was synthesized via carbonization of polypyrrole (PPy) coated bacterial cellulose (BC) composites, where BC serves as templates as well as precursor, and PPy serves as the nitrogen source. The synthesized NDCN was employed as electrode for both supercapacitors and Li-ion batteries. The large surface area exposed to electrolyte resulting from the 3D carbon networks leads to sufficient electrode/electrolyte interface and creates shorter transport paths of electrolyte ions and Li + ion. Besides, the three types of N dopants in NDCN improve the electronic conductivity, as well as superior electrochemical performance.

An all-solid-state yarn supercapacitor using cotton yarn electrodes coated with polypyrrole nanotubes.

PubMed

Wei, Chengzhuo; Xu, Qi; Chen, Zeqi; Rao, Weida; Fan, Lingling; Yuan, Ye; Bai, Zikui; Xu, Jie

2017-08-01

A novel all-solid-state yarn supercapacitor (YSC) has been fabricated by using the cotton yarns coated with polypyrrole (PPy) nanotubes. The interconnected network structure of PPy can increase the surface area as well as the electrode/electrolyte interface area, thus resulting in improved electrochemical performance. For the proposed YSC, a high areal-specific capacitance of 74.0mFcm -2 and a desirable energy density of 7.5μWhcm -2 are achieved. The flexibility of the YSC demonstrates that it is suitable for the integration as flexible power sources in wearable electronic textiles. Copyright © 2017 Elsevier Ltd. All rights reserved.

BIPS: BIANA Interolog Prediction Server. A tool for protein-protein interaction inference.

PubMed

Garcia-Garcia, Javier; Schleker, Sylvia; Klein-Seetharaman, Judith; Oliva, Baldo

2012-07-01

Protein-protein interactions (PPIs) play a crucial role in biology, and high-throughput experiments have greatly increased the coverage of known interactions. Still, identification of complete inter- and intraspecies interactomes is far from being complete. Experimental data can be complemented by the prediction of PPIs within an organism or between two organisms based on the known interactions of the orthologous genes of other organisms (interologs). Here, we present the BIANA (Biologic Interactions and Network Analysis) Interolog Prediction Server (BIPS), which offers a web-based interface to facilitate PPI predictions based on interolog information. BIPS benefits from the capabilities of the framework BIANA to integrate the several PPI-related databases. Additional metadata can be used to improve the reliability of the predicted interactions. Sensitivity and specificity of the server have been calculated using known PPIs from different interactomes using a leave-one-out approach. The specificity is between 72 and 98%, whereas sensitivity varies between 1 and 59%, depending on the sequence identity cut-off used to calculate similarities between sequences. BIPS is freely accessible at http://sbi.imim.es/BIPS.php.

Predicting overlapping protein complexes from weighted protein interaction graphs by gradually expanding dense neighborhoods.

PubMed

Dimitrakopoulos, Christos; Theofilatos, Konstantinos; Pegkas, Andreas; Likothanassis, Spiros; Mavroudi, Seferina

2016-07-01

Proteins are vital biological molecules driving many fundamental cellular processes. They rarely act alone, but form interacting groups called protein complexes. The study of protein complexes is a key goal in systems biology. Recently, large protein-protein interaction (PPI) datasets have been published and a plethora of computational methods that provide new ideas for the prediction of protein complexes have been implemented. However, most of the methods suffer from two major limitations: First, they do not account for proteins participating in multiple functions and second, they are unable to handle weighted PPI graphs. Moreover, the problem remains open as existing algorithms and tools are insufficient in terms of predictive metrics. In the present paper, we propose gradually expanding neighborhoods with adjustment (GENA), a new algorithm that gradually expands neighborhoods in a graph starting from highly informative "seed" nodes. GENA considers proteins as multifunctional molecules allowing them to participate in more than one protein complex. In addition, GENA accepts weighted PPI graphs by using a weighted evaluation function for each cluster. In experiments with datasets from Saccharomyces cerevisiae and human, GENA outperformed Markov clustering, restricted neighborhood search and clustering with overlapping neighborhood expansion, three state-of-the-art methods for computationally predicting protein complexes. Seven PPI networks and seven evaluation datasets were used in total. GENA outperformed existing methods in 16 out of 18 experiments achieving an average improvement of 5.5% when the maximum matching ratio metric was used. Our method was able to discover functionally homogeneous protein clusters and uncover important network modules in a Parkinson expression dataset. When used on the human networks, around 47% of the detected clusters were enriched in gene ontology (GO) terms with depth higher than five in the GO hierarchy. In the present manuscript, we introduce a new method for the computational prediction of protein complexes by making the realistic assumption that proteins participate in multiple protein complexes and cellular functions. Our method can detect accurate and functionally homogeneous clusters. Copyright © 2016 Elsevier B.V. All rights reserved.

Deficient prepulse inhibition in schizophrenia in a multi-site cohort: Internal replication and extension.

PubMed

Swerdlow, Neal R; Light, Gregory A; Thomas, Michael L; Sprock, Joyce; Calkins, Monica E; Green, Michael F; Greenwood, Tiffany A; Gur, Raquel E; Gur, Ruben C; Lazzeroni, Laura C; Nuechterlein, Keith H; Radant, Allen D; Seidman, Larry J; Siever, Larry J; Silverman, Jeremy M; Stone, William S; Sugar, Catherine A; Tsuang, Debby W; Tsuang, Ming T; Turetsky, Bruce I; Braff, David L

2017-05-23

The Consortium on the Genetics of Schizophrenia (COGS) collected case-control endophenotype and genetic information from 2457 patients and healthy subjects (HS) across 5 test sites over 3.5 years. Analysis of the first "wave" (W1) of 1400 subjects identified prepulse inhibition (PPI) deficits in patients vs. HS. Data from the second COGS "wave" (W2), and the combined W(1+2), were used to assess: 1) the replicability of PPI deficits in this design; 2) the impact of response criteria on PPI deficits; and 3) PPI in a large cohort of antipsychotic-free patients. PPI in W2 HS (n=315) and schizophrenia patients (n=326) was compared to findings from W1; planned analyses assessed the impact of diagnosis, "wave" (1 vs. 2), and startle magnitude criteria. Combining waves allowed us to assess PPI in 120 antipsychotic-free patients, including many in the early course of illness. ANOVA of all W(1+2) subjects revealed robust PPI deficits in patients across "waves" (p<0.0004). Strict response criteria excluded almost 39% of all subjects, disproportionately impacting specific subgroups; ANOVA in this smaller cohort confirmed no significant effect of "wave" or "wave x diagnosis" interaction, and a significant effect of diagnosis (p<0.002). Antipsychotic-free, early-illness patients had particularly robust PPI deficits. Schizophrenia-linked PPI deficits were replicable across two multi-site "waves" of subjects collected over 3.5years. Strict response criteria disproportionately excluded older, male, non-Caucasian patients with low-normal hearing acuity. These findings set the stage for genetic analyses of PPI using the combined COGS wave 1 and 2 cohorts. Copyright © 2017 Elsevier B.V. All rights reserved.

Fabp7 Maps to a Quantitative Trait Locus for a Schizophrenia Endophenotype

PubMed Central

Watanabe, Akiko; Toyota, Tomoko; Owada, Yuji; Hayashi, Takeshi; Iwayama, Yoshimi; Matsumata, Miho; Ishitsuka, Yuichi; Nakaya, Akihiro; Maekawa, Motoko; Ohnishi, Tetsuo; Arai, Ryoichi; Sakurai, Katsuyasu; Yamada, Kazuo; Kondo, Hisatake; Hashimoto, Kenji; Osumi, Noriko; Yoshikawa, Takeo

2007-01-01

Deficits in prepulse inhibition (PPI) are a biological marker for schizophrenia. To unravel the mechanisms that control PPI, we performed quantitative trait loci (QTL) analysis on 1,010 F2 mice derived by crossing C57BL/6 (B6) animals that show high PPI with C3H/He (C3) animals that show low PPI. We detected six major loci for PPI, six for the acoustic startle response, and four for latency to response peak, some of which were sex-dependent. A promising candidate on the Chromosome 10-QTL was Fabp7 (fatty acid binding protein 7, brain), a gene with functional links to the N-methyl-D-aspartic acid (NMDA) receptor and expression in astrocytes. Fabp7-deficient mice showed decreased PPI and a shortened startle response latency, typical of the QTL's proposed effects. A quantitative complementation test supported Fabp7 as a potential PPI-QTL gene, particularly in male mice. Disruption of Fabp7 attenuated neurogenesis in vivo. Human FABP7 showed altered expression in schizophrenic brains and genetic association with schizophrenia, which were both evident in males when samples were divided by sex. These results suggest that FABP7 plays a novel and crucial role, linking the NMDA, neurodevelopmental, and glial theories of schizophrenia pathology and the PPI endophenotype, with larger or overt effects in males. We also discuss the results from the perspective of fetal programming. PMID:18001149

Preparation of sulfonated graphene/polypyrrole solid-phase microextraction coating by in situ electrochemical polymerization for analysis of trace terpenes.

PubMed

Zhang, Chengjiang; Zhang, Zhuomin; Li, Gongke

2014-06-13

In this study, a novel sulfonated graphene/polypyrrole (SG/PPy) solid-phase microextraction (SPME) coating was prepared and fabricated on a stainless-steel wire by a one-step in situ electrochemical polymerization method. Crucial preparation conditions were optimized as polymerization time of 15min and SG doping amount of 1.5mg/mL. SG/PPy coating showed excellent thermal stability and mechanical durability with a long lifespan of more than 200 stable replicate extractions. SG/PPy coating demonstrated higher extraction selectivity and capacity to volatile terpenes than commonly-used commercial coatings. Finally, SG/PPy coating was practically applied for the analysis of volatile components from star anise and fennel samples. The majority of volatile components identified were terpenes, which suggested the ultra-high extraction selectivity of SG/PPy coating to terpenes during real analytical projects. Four typical volatile terpenes were further quantified to be 0.2-27.4μg/g from star anise samples with good recoveries of 76.4-97.8% and 0.1-1.6μg/g from fennel samples with good recoveries of 80.0-93.1%, respectively. Copyright © 2014 Elsevier B.V. All rights reserved.

Application of Machine Learning Approaches for Protein-protein Interactions Prediction.

PubMed

Zhang, Mengying; Su, Qiang; Lu, Yi; Zhao, Manman; Niu, Bing

2017-01-01

Proteomics endeavors to study the structures, functions and interactions of proteins. Information of the protein-protein interactions (PPIs) helps to improve our knowledge of the functions and the 3D structures of proteins. Thus determining the PPIs is essential for the study of the proteomics. In this review, in order to study the application of machine learning in predicting PPI, some machine learning approaches such as support vector machine (SVM), artificial neural networks (ANNs) and random forest (RF) were selected, and the examples of its applications in PPIs were listed. SVM and RF are two commonly used methods. Nowadays, more researchers predict PPIs by combining more than two methods. This review presents the application of machine learning approaches in predicting PPI. Many examples of success in identification and prediction in the area of PPI prediction have been discussed, and the PPIs research is still in progress. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Proton pump inhibitors affect the gut microbiome

PubMed Central

Imhann, Floris; Bonder, Marc Jan; Vich Vila, Arnau; Fu, Jingyuan; Mujagic, Zlatan; Vork, Lisa; Tigchelaar, Ettje F; Jankipersadsing, Soesma A; Cenit, Maria Carmen; Harmsen, Hermie J M; Dijkstra, Gerard; Franke, Lude; Xavier, Ramnik J; Jonkers, Daisy; Wijmenga, Cisca; Weersma, Rinse K; Zhernakova, Alexandra

2016-01-01

Background and aims Proton pump inhibitors (PPIs) are among the top 10 most widely used drugs in the world. PPI use has been associated with an increased risk of enteric infections, most notably Clostridium difficile. The gut microbiome plays an important role in enteric infections, by resisting or promoting colonisation by pathogens. In this study, we investigated the influence of PPI use on the gut microbiome. Methods The gut microbiome composition of 1815 individuals, spanning three cohorts, was assessed by tag sequencing of the 16S rRNA gene. The difference in microbiota composition in PPI users versus non-users was analysed separately in each cohort, followed by a meta-analysis. Results 211 of the participants were using PPIs at the moment of stool sampling. PPI use is associated with a significant decrease in Shannon's diversity and with changes in 20% of the bacterial taxa (false discovery rate <0.05). Multiple oral bacteria were over-represented in the faecal microbiome of PPI-users, including the genus Rothia (p=9.8×10−38). In PPI users we observed a significant increase in bacteria: genera Enterococcus, Streptococcus, Staphylococcus and the potentially pathogenic species Escherichia coli. Conclusions The differences between PPI users and non-users observed in this study are consistently associated with changes towards a less healthy gut microbiome. These differences are in line with known changes that predispose to C. difficile infections and can potentially explain the increased risk of enteric infections in PPI users. On a population level, the effects of PPI are more prominent than the effects of antibiotics or other commonly used drugs. PMID:26657899

The relationship between proton pump inhibitor use and longitudinal change in bone mineral density: a population-based study [corrected] from the Canadian Multicentre Osteoporosis Study (CaMos).

PubMed

Targownik, Laura E; Leslie, William D; Davison, K Shawn; Goltzman, David; Jamal, Sophie A; Kreiger, Nancy; Josse, Robert G; Kaiser, Stephanie M; Kovacs, Christopher S; Prior, Jerilynn C; Zhou, Wei

2012-09-01

Proton pump inhibitor (PPI) use has been identified as a risk factor for hip and vertebral fractures. Evidence supporting a relationship between PPI use and osteoporosis remains scant. Demonstrating that PPIs are associated with accelerated bone mineral density (BMD) loss would provide supportive evidence for a mechanism through which PPIs could increase fracture risk. We used the Canadian Multicentre Osteoporosis Study data set, which enrolled a population-based sample of Canadians who underwent BMD testing of the femoral neck, total hip, and lumbar spine (L1-L4) at baseline, and then again at 5 and 10 years. Participants also reported drug use and exposure to risk factors for osteoporosis and fracture. Multivariate linear regression was used to determine the independent association of PPI exposure and baseline BMD, and on change in BMD at 5 and 10 years. In all, 8,340 subjects were included in the baseline analysis, with 4,512 (55%) undergoing year 10 BMD testing. After adjusting for potential confounders, PPI use was associated with significantly lower baseline BMD at the femoral neck and total hip. PPI use was not associated with a significant acceleration in covariate-adjusted BMD loss at any measurement site after 5 and 10 years of follow-up. PPI users had lower BMD at baseline than PPI non-users, but PPI use over 10 years did not appear to be associated with accelerated BMD loss. The reasons for discordant findings between PPI use at baseline and during follow-up require further study.

Electrodeposition of Polypyrrole and Reduced Graphene Oxide onto Carbon Bundle Fibre as Electrode for Supercapacitor.

PubMed

Abdul Bashid, Hamra Assyaima; Lim, Hong Ngee; Kamaruzaman, Sazlinda; Abdul Rashid, Suraya; Yunus, Robiah; Huang, Nay Ming; Yin, Chun Yang; Rahman, Mohammad Mahbubur; Altarawneh, Mohammednoor; Jiang, Zhong Tao; Alagarsamy, Pandikumar

2017-12-01

A nanocomposite comprising of polypyrrole and reduced graphene oxide was electrodeposited onto a carbon bundle fibre (CBF) through a two-step approach (CBF/PPy-rGO-2). The CBF/PPy-rGO-2 had a highly porous structure compared to a nanocomposite of polypyrrole and reduced graphene oxide that was electrodeposited onto a CBF in a one-step approach (CBF/PPy-rGO), as observed through a field emission scanning electron microscope. An X-ray photoelectron spectroscopic analysis revealed the presence of hydrogen bond between the oxide functional groups of rGO and the amine groups of PPy in PPy-rGO-2 nanocomposite. The fabricated CBF/PPy-rGO-2 nanocomposite material was used as an electrode material in a symmetrical solid-state supercapacitor, and the device yielded a specific capacitance, energy density and power density of 96.16 F g - 1 , 13.35 Wh kg - 1 and of 322.85 W kg - 1 , respectively. Moreover, the CBF/PPy-rGO-2 showed the capacitance retention of 71% after 500 consecutive charge/discharge cycles at a current density of 1 A g - 1 . The existence of a high degree of porosity in CBF/PPy-rGO-2 significantly improved the conductivity and facilitated the ionic penetration. The CBF/PPy-rGO-2-based symmetrical solid-state supercapacitor device demonstrated outstanding pliability because the cyclic voltammetric curves remained the same upon bending at various angles. Carbon bundle fibre modified with porous polypyrrole/reduced graphene oxide nanocomposite for flexible miniature solid-state supercapacitor.

Designing focused chemical libraries enriched in protein-protein interaction inhibitors using machine-learning methods.

PubMed

Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O; Sperandio, Olivier

2010-03-05

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is freely available on request from our CDithem platform website, www.CDithem.com.

Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods

PubMed Central

Reynès, Christelle; Host, Hélène; Camproux, Anne-Claude; Laconde, Guillaume; Leroux, Florence; Mazars, Anne; Deprez, Benoit; Fahraeus, Robin; Villoutreix, Bruno O.; Sperandio, Olivier

2010-01-01

Protein-protein interactions (PPIs) may represent one of the next major classes of therapeutic targets. So far, only a minute fraction of the estimated 650,000 PPIs that comprise the human interactome are known with a tiny number of complexes being drugged. Such intricate biological systems cannot be cost-efficiently tackled using conventional high-throughput screening methods. Rather, time has come for designing new strategies that will maximize the chance for hit identification through a rationalization of the PPI inhibitor chemical space and the design of PPI-focused compound libraries (global or target-specific). Here, we train machine-learning-based models, mainly decision trees, using a dataset of known PPI inhibitors and of regular drugs in order to determine a global physico-chemical profile for putative PPI inhibitors. This statistical analysis unravels two important molecular descriptors for PPI inhibitors characterizing specific molecular shapes and the presence of a privileged number of aromatic bonds. The best model has been transposed into a computer program, PPI-HitProfiler, that can output from any drug-like compound collection a focused chemical library enriched in putative PPI inhibitors. Our PPI inhibitor profiler is challenged on the experimental screening results of 11 different PPIs among which the p53/MDM2 interaction screened within our own CDithem platform, that in addition to the validation of our concept led to the identification of 4 novel p53/MDM2 inhibitors. Collectively, our tool shows a robust behavior on the 11 experimental datasets by correctly profiling 70% of the experimentally identified hits while removing 52% of the inactive compounds from the initial compound collections. We strongly believe that this new tool can be used as a global PPI inhibitor profiler prior to screening assays to reduce the size of the compound collections to be experimentally screened while keeping most of the true PPI inhibitors. PPI-HitProfiler is freely available on request from our CDithem platform website, www.CDithem.com. PMID:20221258

Self-Supported Crack-Free Conducting Polymer Films with Stabilized Wrinkling Patterns and Their Applications

PubMed Central

Xie, Jixun; Han, Xue; Ji, Haipeng; Wang, Juanjuan; Zhao, Jingxin; Lu, Conghua

2016-01-01

Self-supported conducting polymer films with controlled microarchitectures are highly attractive from fundamental and applied points of view. Here a versatile strategy is demonstrated to fabricate thin free-standing crack-free polyaniline (PANI)-based films with stable wrinkling patterns. It is based on oxidization polymerization of pyrrole inside a pre-wrinkled PANI film, in which the wrinkled PANI film is used both as a template and oxidizing agent for the first time. The subsequently grown polypyrrole (PPy) and the formation of interpenetrated PANI/PPy networks play a decisive role in enhancing the film integrity and the stability of wrinkles. This enhancing effect is attributed to the modification of internal stresses by the interpenetrated PANI/PPy microstructures. Consequently, a crack-free film with stable controlled wrinkles such as the wavelength, orientation and spatial location has been achieved. Moreover, the wrinkling PANI/PPy film can be removed from the initially deposited substrate to become free-standing. It can be further transferred onto target substrates to fabricate hierarchical patterns and functional devices such as flexible electrodes, gas sensors, and surface-enhanced Raman scattering substrates. This simple universal enhancing strategy has been extended to fabrication of other PANI-based composite systems with crack-free film integrity and stabilized surface patterns, irrespective of pattern types and film geometries. PMID:27827459

Ten-day high-dose proton pump inhibitor triple therapy versus sequential therapy for Helicobacter pylori eradication.

PubMed

Auesomwang, Chonticha; Maneerattanaporn, Monthira; Chey, William D; Kiratisin, Pattarachai; Leelakusolwong, Somchai; Tanwandee, Tawesak

2018-05-27

Eradication rates of Helicobacter pylori following standard triple therapy are declining worldwide, but high-dose proton-pump inhibitor-based triple therapy (HD-PPI-TT) and sequential therapy (ST) have demonstrated higher cure rates. We aimed to compare the efficacy and tolerability of HD-PPI-TT and ST in H. pylori-associated functional dyspepsia (HP-FD). One hundred and twenty HP-FD patients were randomized to receive 10-day HD-PPI-TT (60 mg lansoprazole/500 mg clarithromycin/1 g amoxicillin, each administered twice daily for 10 days) or 10-day ST (30 mg lansoprazole/1 g amoxicillin, each administered twice daily for 5 days followed by 30 mg lansoprazole/500 mg clarithromycin/400 mg metronidazole, each administered twice daily for 5 days). H. pylori status was determined in post-treatment week 4 by 14 C-urea breath test. Eradication and antibiotic resistance rates, dyspeptic symptoms, drug compliance, and adverse effects were compared. Intention-to-treat (ITT) eradication rates were similar in the ST and HD-PPI-TT groups (85% vs. 80%; P=0.47). However, the eradication rate was significantly higher following ST compared with HD-PPI-TT in per protocol (PP) analysis (94.4% vs. 81.4%; P=0.035). ST achieved higher cure rates than HD-PPI-TT in clarithromycin-resistant H. pylori strains (100% vs. 33.3%; P=0.02). Treatment compliance was similar in the HD-PPI-TT and ST groups, although nausea and dizziness were more common in the ST group. ST achieved better H. pylori eradication than HD-PPI-TT in patients with FD. However, the eradication rate for ST fell from 94.4% in PP to 85% in ITT analysis. Adverse effects might result in poorer compliance and compromise actual ST efficacy. (ClinicalTrials.gov: NCT01888237). This article is protected by copyright. All rights reserved.

The effect of dose and type of proton pump inhibitor use on risk of fractures and osteoporosis treatment in older Australian women: A prospective cohort study.

PubMed

van der Hoorn, Mariëlle M C; Tett, Susan E; de Vries, Oscar J; Dobson, Annette J; Peeters, G M E E Geeske

2015-12-01

Proton pump inhibitors (PPIs) are among the most prescribed medications worldwide, however, there is growing concern regarding potential negative effects on bone health. The aim was to examine the effect of dose and type of PPI use on subsequent use of osteoporosis medication and fractures in older Australian women. Data were included from 4432 participants (born 1921-26) in the 2002 survey of the Australian Longitudinal Study on Women's Health. Medication data were from the national pharmaceutical administrative database (2003-2012, inclusive). Fractures were sourced from linked hospital datasets available for four major States of Australia. Competing risk regression models used PPI exposure as a time-dependent covariate and either time to first osteoporosis medication prescription or fracture as the outcome, with death as a competing risk. Of the 2328 PPI users and 2104 PPI non-users, 827 (36%) and 550 (26%) became users of osteoporosis medication, respectively. PPI use was associated with an increased risk of subsequent use of osteoporosis medication (adjusted sub-hazard ratio [SHR]=1.28; 95% confidence interval [CI]=1.13-1.44) and subsequent fracture (SHR=1.29, CI=1.08-1.55). Analysis with PPI categorized according to defined daily dose (DDD), showed some evidence for a dose-response effect (osteoporosis medication: <400 DDD: SHR=1.23, CI=1.06-1.42 and ≥400 DDD: SHR=1.39, CI=1.17-1.65, compared with non-users; SHRs were in the same range for fractures). Esomeprazole was the most common PPI prescribed (22.9%). Analysis by type of PPI use showed an increased subsequent risk for: (1) use of osteoporosis medication for rabeprazole (SHR=1.51, CI=1.08-2.10) and esomeprazole (SHR=1.48, CI=1.17-1.88); and (2) fractures for rabeprazole (SHR=2.06, CI=1.37-3.10). Users of multiple types of PPI also had increased risks for use of osteoporosis medication and fractures. An appropriate benefit/risk assessment should be made when prescribing PPIs, especially for esomeprazole and rabeprazole, as osteoporosis and fracture risks were increased in this cohort of elderly females subsequent to PPI prescription. Copyright © 2015 Elsevier Inc. All rights reserved.

Convergent roles of de novo mutations and common variants in schizophrenia in tissue-specific and spatiotemporal co-expression network.

PubMed

Jia, Peilin; Chen, Xiangning; Fanous, Ayman H; Zhao, Zhongming

2018-05-24

Genetic components susceptible to complex disease such as schizophrenia include a wide spectrum of variants, including common variants (CVs) and de novo mutations (DNMs). Although CVs and DNMs differ by origin, it remains elusive whether and how they interact at the gene, pathway, and network levels that leads to the disease. In this work, we characterized the genes harboring schizophrenia-associated CVs (CVgenes) and the genes harboring DNMs (DNMgenes) using measures from network, tissue-specific expression profile, and spatiotemporal brain expression profile. We developed an algorithm to link the DNMgenes and CVgenes in spatiotemporal brain co-expression networks. DNMgenes tended to have central roles in the human protein-protein interaction (PPI) network, evidenced in their high degree and high betweenness values. DNMgenes and CVgenes connected with each other significantly more often than with other genes in the networks. However, only CVgenes remained significantly connected after adjusting for their degree. In our gene co-expression PPI network, we found DNMgenes and CVgenes connected in a tissue-specific fashion, and such a pattern was similar to that in GTEx brain but not in other GTEx tissues. Importantly, DNMgene-CVgene subnetworks were enriched with pathways of chromatin remodeling, MHC protein complex binding, and neurotransmitter activities. In summary, our results unveiled that both DNMgenes and CVgenes contributed to a core set of biologically important pathways and networks, and their interactions may attribute to the risk for schizophrenia. Our results also suggested a stronger biological effect of DNMgenes than CVgenes in schizophrenia.

Impact of constitutional isomers of (BMes(2))phenylpyridine on structure, stability, phosphorescence, and Lewis acidity of mononuclear and dinuclear Pt(II) complexes.

PubMed

Rao, Ying-Li; Wang, Suning

2009-08-17

The impact of two constitutional isomers, 2-(4-BMes(2)-Ph)-pyridine (p-B-ppy, 1) and 5-BMes(2)-2-ph-pyridine (p-ppy-B, 2), as N,C-chelate ligands on the structures, stabilities, electronic and photophysical properties, and Lewis acidities of Pt(II) complexes has been investigated. Six Pt(II) complexes, Pt(p-B-ppy)Ph(DMSO) (1a), Pt(p-B-ppy)Ph(py) (1b), [Pt(p-B-ppy)Ph](2)(4,4'-bipy) (1c), Pt(p-ppy-B)Ph(DMSO) (2a), Pt(p-ppy-B)Ph(py) (2b), and [Pt(p-ppy-B)Ph](2)(4,4'-bipy) (2c), have been synthesized and fully characterized. The structures of 1a, 1c, 2a, and 2c were established by single-crystal X-ray diffraction analysis. All complexes adopt a cis geometry with the phenyl ligand being cis to the phenyl ring of the ppy chelate. The dinuclear complexes 2a and 2c were found to exist in two isomeric forms in solution, syn and anti, with respect to the relative orientation of the two BMes(2) groups in the molecule. While all complexes are stable in solution under ambient air, compound 2a was found to react with H(2)O slowly in solution and form complex 2a-OH, where one of the mesityl groups on the boron center was replaced by an OH group. This instability of 2a is attributed to an internal dimethylsulfoxide-directed hydrolysis process via hydrogen bonds. The electron-accepting ability of the free ligands and the complexes were examined by cyclic voltammetry, establishing that, for p-ppy-B, Pt(II) chelation enhances the electron-accepting ability while, for p-B-ppy, Pt(II) chelation has little impact. All Pt(II) complexes display oxygen-sensitive phosphorescence in solution at ambient temperature, dominated by B-ppy or ppy-B centered pi --> pi* transitions. The Lewis acidity of the complexes was examined by fluoride titration experiments using UV-vis, phosphorescence, and NMR spectroscopic methods, establishing that the p-ppy-B complexes have similar and strong binding constants while the p-B-ppy complexes have a much lower affinity toward F(-), compared to the free ligands. In the dinuclear complexes, weak electronic communication between the two Pt(II) units is evident in 1c but absent in 2c, attributable to the different steric interactions in the two molecules.

Global De Novo Protein-Protein Interactome Elucidates Interactions of Drought-Responsive Proteins in Horse Gram (Macrotyloma uniflorum).

PubMed

Bhardwaj, Jyoti; Gangwar, Indu; Panzade, Ganesh; Shankar, Ravi; Yadav, Sudesh Kumar

2016-06-03

Inspired by the availability of de novo transcriptome of horse gram (Macrotyloma uniflorum) and recent developments in systems biology studies, the first ever global protein-protein interactome (PPI) map was constructed for this highly drought-tolerant legume. Large-scale studies of PPIs and the constructed database would provide rationale behind the interplay at cascading translational levels for drought stress-adaptive mechanisms in horse gram. Using a bidirectional approach (interolog and domain-based), a high-confidence interactome map and database for horse gram was constructed. Available transcriptomic information for shoot and root tissues of a sensitive (M-191; genotype 1) and a drought-tolerant (M-249; genotype 2) genotype of horse gram was utilized to draw comparative PPI subnetworks under drought stress. High-confidence 6804 interactions were predicted among 1812 proteins covering about one-fourth of the horse gram proteome. The highest number of interactions (33.86%) in horse gram interactome matched with Arabidopsis PPI data. The top five hub nodes mostly included ubiquitin and heat-shock-related proteins. Higher numbers of PPIs were found to be responsive in shoot tissue (416) and root tissue (2228) of genotype 2 compared with shoot tissue (136) and root tissue (579) of genotype 1. Characterization of PPIs using gene ontology analysis revealed that kinase and transferase activities involved in signal transduction, cellular processes, nucleocytoplasmic transport, protein ubiquitination, and localization of molecules were most responsive to drought stress. Hence, these could be framed in stress adaptive mechanisms of horse gram. Being the first legume global PPI map, it would provide new insights into gene and protein regulatory networks for drought stress tolerance mechanisms in horse gram. Information compiled in the form of database (MauPIR) will provide the much needed high-confidence systems biology information for horse gram genes, proteins, and involved processes. This information would ease the effort and increase the efficacy for similar studies on other legumes. Public access is available at http://14.139.59.221/MauPIR/ .

Comparative analysis and assessment of M. tuberculosis H37Rv protein-protein interaction datasets

PubMed Central

2011-01-01

Background M. tuberculosis is a formidable bacterial pathogen. There is thus an increasing demand on understanding the function and relationship of proteins in various strains of M. tuberculosis. Protein-protein interactions (PPIs) data are crucial for this kind of knowledge. However, the quality of the main available M. tuberculosis PPI datasets is unclear. This hampers the effectiveness of research works that rely on these PPI datasets. Here, we analyze the two main available M. tuberculosis H37Rv PPI datasets. The first dataset is the high-throughput B2H PPI dataset from Wang et al’s recent paper in Journal of Proteome Research. The second dataset is from STRING database, version 8.3, comprising entirely of H37Rv PPIs predicted using various methods. We find that these two datasets have a surprisingly low level of agreement. We postulate the following causes for this low level of agreement: (i) the H37Rv B2H PPI dataset is of low quality; (ii) the H37Rv STRING PPI dataset is of low quality; and/or (iii) the H37Rv STRING PPIs are predictions of other forms of functional associations rather than direct physical interactions. Results To test the quality of these two datasets, we evaluate them based on correlated gene expression profiles, coherent informative GO term annotations, and conservation in other organisms. We observe a significantly greater portion of PPIs in the H37Rv STRING PPI dataset (with score ≥ 770) having correlated gene expression profiles and coherent informative GO term annotations in both interaction partners than that in the H37Rv B2H PPI dataset. Predicted H37Rv interologs derived from non-M. tuberculosis experimental PPIs are much more similar to the H37Rv STRING functional associations dataset (with score ≥ 770) than the H37Rv B2H PPI dataset. H37Rv predicted physical interologs from IntAct also show extremely low similarity with the H37Rv B2H PPI dataset; and this similarity level is much lower than that between the S. aureus MRSA252 predicted physical interologs from IntAct and S. aureus MRSA252 pull-down PPIs. Comparative analysis with several representative two-hybrid PPI datasets in other species further confirms that the H37Rv B2H PPI dataset is of low quality. Next, to test the possibility that the H37Rv STRING PPIs are not purely direct physical interactions, we compare M. tuberculosis H37Rv protein pairs that catalyze adjacent steps in enzymatic reactions to B2H PPIs and predicted PPIs in STRING, which shows it has much lower similarities with the B2H PPIs than with STRING PPIs. This result strongly suggests that the H37Rv STRING PPIs more likely correspond to indirect relationships between protein pairs than to B2H PPIs. For more precise support, we turn to S. cerevisiae for its comprehensively studied interactome. We compare S. cerevisiae predicted PPIs in STRING to three independent protein relationship datasets which respectively comprise PPIs reported in Y2H assays, protein pairs reported to be in the same protein complexes, and protein pairs that catalyze successive reaction steps in enzymatic reactions. Our analysis reveals that S. cerevisiae predicted STRING PPIs have much higher similarity to the latter two types of protein pairs than to two-hybrid PPIs. As H37Rv STRING PPIs are predicted using similar methods as S. cerevisiae predicted STRING PPIs, this suggests that these H37Rv STRING PPIs are more likely to correspond to the latter two types of protein pairs rather than to two-hybrid PPIs as well. Conclusions The H37Rv B2H PPI dataset has low quality. It should not be used as the gold standard to assess the quality of other (possibly predicted) H37Rv PPI datasets. The H37Rv STRING PPI dataset also has low quality; nevertheless, a subset consisting of STRING PPIs with score ≥770 has satisfactory quality. However, these STRING “PPIs” should be interpreted as functional associations, which include a substantial portion of indirect protein interactions, rather than direct physical interactions. These two factors cause the strikingly low similarity between these two main H37Rv PPI datasets. The results and conclusions from this comparative analysis provide valuable guidance in using these M. tuberculosis H37Rv PPI datasets in subsequent studies for a wide range of purposes. PMID:22369691

Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets.

PubMed

Ho, Hsiang; Milenković, Tijana; Memisević, Vesna; Aruri, Jayavani; Przulj, Natasa; Ganesan, Anand K

2010-06-15

RNA-mediated interference (RNAi)-based functional genomics is a systems-level approach to identify novel genes that control biological phenotypes. Existing computational approaches can identify individual genes from RNAi datasets that regulate a given biological process. However, currently available methods cannot identify which RNAi screen "hits" are novel components of well-characterized biological pathways known to regulate the interrogated phenotype. In this study, we describe a method to identify genes from RNAi datasets that are novel components of known biological pathways. We experimentally validate our approach in the context of a recently completed RNAi screen to identify novel regulators of melanogenesis. In this study, we utilize a PPI network topology-based approach to identify targets within our RNAi dataset that may be components of known melanogenesis regulatory pathways. Our computational approach identifies a set of screen targets that cluster topologically in a human PPI network with the known pigment regulator Endothelin receptor type B (EDNRB). Validation studies reveal that these genes impact pigment production and EDNRB signaling in pigmented melanoma cells (MNT-1) and normal melanocytes. We present an approach that identifies novel components of well-characterized biological pathways from functional genomics datasets that could not have been identified by existing statistical and computational approaches.

Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets

PubMed Central

2010-01-01

Background RNA-mediated interference (RNAi)-based functional genomics is a systems-level approach to identify novel genes that control biological phenotypes. Existing computational approaches can identify individual genes from RNAi datasets that regulate a given biological process. However, currently available methods cannot identify which RNAi screen "hits" are novel components of well-characterized biological pathways known to regulate the interrogated phenotype. In this study, we describe a method to identify genes from RNAi datasets that are novel components of known biological pathways. We experimentally validate our approach in the context of a recently completed RNAi screen to identify novel regulators of melanogenesis. Results In this study, we utilize a PPI network topology-based approach to identify targets within our RNAi dataset that may be components of known melanogenesis regulatory pathways. Our computational approach identifies a set of screen targets that cluster topologically in a human PPI network with the known pigment regulator Endothelin receptor type B (EDNRB). Validation studies reveal that these genes impact pigment production and EDNRB signaling in pigmented melanoma cells (MNT-1) and normal melanocytes. Conclusions We present an approach that identifies novel components of well-characterized biological pathways from functional genomics datasets that could not have been identified by existing statistical and computational approaches. PMID:20550706

The association between the use of proton pump inhibitors and the risk of hypomagnesemia: a systematic review and meta-analysis.

PubMed

Park, Chan Hyuk; Kim, Eun Hye; Roh, Yun Ho; Kim, Ha Yan; Lee, Sang Kil

2014-01-01

Although many case reports have described patients with proton pump inhibitor (PPI)-induced hypomagnesemia, the impact of PPI use on hypomagnesemia has not been fully clarified through comparative studies. We aimed to evaluate the association between the use of PPI and the risk of developing hypomagnesemia by conducting a systematic review with meta-analysis. We conducted a systematic search of MEDLINE, EMBASE, and the Cochrane Library using the primary keywords "proton pump," "dexlansoprazole," "esomeprazole," "ilaprazole," "lansoprazole," "omeprazole," "pantoprazole," "rabeprazole," "hypomagnesemia," "hypomagnesaemia," and "magnesium." Studies were included if they evaluated the association between PPI use and hypomagnesemia and reported relative risks or odds ratios or provided data for their estimation. Pooled odds ratios with 95% confidence intervals were calculated using the random effects model. Statistical heterogeneity was assessed with Cochran's Q test and I2 statistics. Nine studies including 115,455 patients were analyzed. The median Newcastle-Ottawa quality score for the included studies was seven (range, 6-9). Among patients taking PPIs, the median proportion of patients with hypomagnesemia was 27.1% (range, 11.3-55.2%) across all included studies. Among patients not taking PPIs, the median proportion of patients with hypomagnesemia was 18.4% (range, 4.3-52.7%). On meta-analysis, pooled odds ratio for PPI use was found to be 1.775 (95% confidence interval 1.077-2.924). Significant heterogeneity was identified using Cochran's Q test (df = 7, P<0.001, I2 = 98.0%). PPI use may increase the risk of hypomagnesemia. However, significant heterogeneity among the included studies prevented us from reaching a definitive conclusion.

Resonant structure, formation and stability of the planetary system HD155358

NASA Astrophysics Data System (ADS)

Silburt, Ari; Rein, Hanno

2017-08-01

Two Jovian-sized planets are orbiting the star HD155358 near exact mean motion resonance (MMR) commensurability. In this work, we re-analyse the radial velocity (RV) data previously collected by Robertson et al. Using a Bayesian framework, we construct two models - one that includes and the other that excludes gravitational planet-planet interactions (PPIs). We find that the orbital parameters from our PPI and no planet-planet interaction (noPPI) models differ by up to 2σ, with our noPPI model being statistically consistent with previous results. In addition, our new PPI model strongly favours the planets being in MMR, while our noPPI model strongly disfavours MMR. We conduct a stability analysis by drawing samples from our PPI model's posterior distribution and simulating them for 109 yr, finding that our best-fitting values land firmly in a stable region of parameter space. We explore a series of formation models that migrate the planets into their observed MMR. We then use these models to directly fit to the observed RV data, where each model is uniquely parametrized by only three constants describing its migration history. Using a Bayesian framework, we find that a number of migration models fit the RV data surprisingly well, with some migration parameters being ruled out. Our analysis shows that PPIs are important to take into account when modelling observations of multiplanetary systems. The additional information that one can gain from interacting models can help constrain planet migration parameters.

Electrodeposition of zinc hydroxysulfate nanosheets and reduction to zinc metal microdendrites on polypyrrole films.

PubMed

Andreoli, Enrico; Rooney, Denise A; Redington, Wynette; Gunning, Robert; Breslin, Carmel B

2012-01-01

Nanothin sheets made of zinc sulfate hydroxide hydrate, ZnSO4[Zn(OH)2]3 x 5H2O, are easily and quickly prepared using an innovative electrochemical route onto polypyrrole-polystyrene sulfonate (PPy-PSS) films. The sheets are characterized using a range of experimental techniques. The deposits are formed on the film surface with instantaneous nucleation to grow into a network of entangled nanosheets. The effect of the experimental conditions on the deposition is reported. Interestingly, the formation of the nanosheets is observed on PPy-PSS films only, and not on films doped with other sulfate/sulfonate dopants. The zinc nanosheets can be easily electrochemically reduced to metallic zinc microdentrites.

A Novel Algorithm for Detecting Protein Complexes with the Breadth First Search

PubMed Central

Tang, Xiwei; Wang, Jianxin; Li, Min; He, Yiming; Pan, Yi

2014-01-01

Most biological processes are carried out by protein complexes. A substantial number of false positives of the protein-protein interaction (PPI) data can compromise the utility of the datasets for complexes reconstruction. In order to reduce the impact of such discrepancies, a number of data integration and affinity scoring schemes have been devised. The methods encode the reliabilities (confidence) of physical interactions between pairs of proteins. The challenge now is to identify novel and meaningful protein complexes from the weighted PPI network. To address this problem, a novel protein complex mining algorithm ClusterBFS (Cluster with Breadth-First Search) is proposed. Based on the weighted density, ClusterBFS detects protein complexes of the weighted network by the breadth first search algorithm, which originates from a given seed protein used as starting-point. The experimental results show that ClusterBFS performs significantly better than the other computational approaches in terms of the identification of protein complexes. PMID:24818139

Cellulose-coupled graphene/polypyrrole composite electrodes containing conducting networks built by carbon fibers as wearable supercapacitors with excellent foldability and tailorability

NASA Astrophysics Data System (ADS)

Lyu, Shaoyi; Chang, Huanjun; Fu, Feng; Hu, La; Huang, Jingda; Wang, Siqun

2016-09-01

A paper-based wearable supercapacitor with excellent foldability and tailorability is fabricated from a chopped carbon fiber (CCF)-reinforced cellulose paper electrode material by coating with reduced graphene oxide (RGO) and polypyrrole (PPy) via in situ polymerization. The CCFs not only form an interpenetrating conducting network that acts as highly conductive electron transfer highways for the RGO/PPy layer in the paper electrode, but also endow the resulting electrode with an excellent areal capacitance of 363 mF cm-2 and a volumetric energy density of 0.28 mW h cm-3. Further, the CCFs give the electrode remarkable mechanical robustness, guaranteeing foldability and tailorability, with only slight loss of capacitance after repeated folding 600 times. Even after being subjected to severe cut-in fracture, the capacitance retention is up to 84%, indicating outstanding damage tolerance. The present study reveals a promising candidate for flexible wearable energy storage devices that are required to function in harsh environments.

Neural networks for link prediction in realistic biomedical graphs: a multi-dimensional evaluation of graph embedding-based approaches.

PubMed

Crichton, Gamal; Guo, Yufan; Pyysalo, Sampo; Korhonen, Anna

2018-05-21

Link prediction in biomedical graphs has several important applications including predicting Drug-Target Interactions (DTI), Protein-Protein Interaction (PPI) prediction and Literature-Based Discovery (LBD). It can be done using a classifier to output the probability of link formation between nodes. Recently several works have used neural networks to create node representations which allow rich inputs to neural classifiers. Preliminary works were done on this and report promising results. However they did not use realistic settings like time-slicing, evaluate performances with comprehensive metrics or explain when or why neural network methods outperform. We investigated how inputs from four node representation algorithms affect performance of a neural link predictor on random- and time-sliced biomedical graphs of real-world sizes (∼ 6 million edges) containing information relevant to DTI, PPI and LBD. We compared the performance of the neural link predictor to those of established baselines and report performance across five metrics. In random- and time-sliced experiments when the neural network methods were able to learn good node representations and there was a negligible amount of disconnected nodes, those approaches outperformed the baselines. In the smallest graph (∼ 15,000 edges) and in larger graphs with approximately 14% disconnected nodes, baselines such as Common Neighbours proved a justifiable choice for link prediction. At low recall levels (∼ 0.3) the approaches were mostly equal, but at higher recall levels across all nodes and average performance at individual nodes, neural network approaches were superior. Analysis showed that neural network methods performed well on links between nodes with no previous common neighbours; potentially the most interesting links. Additionally, while neural network methods benefit from large amounts of data, they require considerable amounts of computational resources to utilise them. Our results indicate that when there is enough data for the neural network methods to use and there are a negligible amount of disconnected nodes, those approaches outperform the baselines. At low recall levels the approaches are mostly equal but at higher recall levels and average performance at individual nodes, neural network approaches are superior. Performance at nodes without common neighbours which indicate more unexpected and perhaps more useful links account for this.

Integrated network analysis reveals potentially novel molecular mechanisms and therapeutic targets of refractory epilepsies

PubMed Central

Liu, Guangming; Wang, Yiwei; Zhao, Pengyao; Zhu, Yizhun; Yang, Xiaohan; Zheng, Tiezheng; Zhou, Xuezhong; Jin, Weilin; Sun, Changkai

2017-01-01

Epilepsy is a complex neurological disorder and a significant health problem. The pathogenesis of epilepsy remains obscure in a significant number of patients and the current treatment options are not adequate in about a third of individuals which were known as refractory epilepsies (RE). Network medicine provides an effective approach for studying the molecular mechanisms underlying complex diseases. Here we integrated 1876 disease-gene associations of RE and located those genes to human protein-protein interaction (PPI) network to obtain 42 significant RE-associated disease modules. The functional analysis of these disease modules showed novel molecular pathological mechanisms of RE, such as the novel enriched pathways (e.g., “presynaptic nicotinic acetylcholine receptors”, “signaling by insulin receptor”). Further analysis on the relationships between current drug targets and the RE-related disease genes showed the rational mechanisms of most antiepileptic drugs. In addition, we detected ten potential novel drug targets (e.g., KCNA1, KCNA4-6, KCNC3, KCND2, KCNMA1, CAMK2G, CACNB4 and GRM1) located in three RE related disease modules, which might provide novel insights into the new drug discovery for RE therapy. PMID:28388656

Finding trans-regulatory genes and protein complexes modulating meiotic recombination hotspots of human, mouse and yeast.

PubMed

Wu, Min; Kwoh, Chee-Keong; Li, Xiaoli; Zheng, Jie

2014-09-11

The regulatory mechanism of recombination is one of the most fundamental problems in genomics, with wide applications in genome wide association studies (GWAS), birth-defect diseases, molecular evolution, cancer research, etc. Recombination events cluster into short genomic regions called "recombination hotspots". Recently, a zinc finger protein PRDM9 was reported to regulate recombination hotspots in human and mouse genomes. In addition, a 13-mer motif contained in the binding sites of PRDM9 is found to be enriched in human hotspots. However, this 13-mer motif only covers a fraction of hotspots, indicating that PRDM9 is not the only regulator of recombination hotspots. Therefore, the challenge of discovering other regulators of recombination hotspots becomes significant. Furthermore, recombination is a complex process. Hence, multiple proteins acting as machinery, rather than individual proteins, are more likely to carry out this process in a precise and stable manner. Therefore, the extension of the prediction of individual trans-regulators to protein complexes is also highly desired. In this paper, we introduce a pipeline to identify genes and protein complexes associated with recombination hotspots. First, we prioritize proteins associated with hotspots based on their preference of binding to hotspots and coldspots. Second, using the above identified genes as seeds, we apply the Random Walk with Restart algorithm (RWR) to propagate their influences to other proteins in protein-protein interaction (PPI) networks. Hence, many proteins without DNA-binding information will also be assigned a score to implicate their roles in recombination hotspots. Third, we construct sub-PPI networks induced by top genes ranked by RWR for various species (e.g., yeast, human and mouse) and detect protein complexes in those sub-PPI networks. The GO term analysis show that our prioritizing methods and the RWR algorithm are capable of identifying novel genes associated with recombination hotspots. The trans-regulators predicted by our pipeline are enriched with epigenetic functions (e.g., histone modifications), demonstrating the epigenetic regulatory mechanisms of recombination hotspots. The identified protein complexes also provide us with candidates to further investigate the molecular machineries for recombination hotspots. Moreover, the experimental data and results are available on our web site http://www.ntu.edu.sg/home/zhengjie/data/RecombinationHotspot/NetPipe/.

Transoral Incisionless Fundoplication Effective in Eliminating GERD Symptoms in Partial Responders to Proton Pump Inhibitor Therapy at 6 Months

PubMed Central

Barnes, William E.; Simoni, Gilbert; Shughoury, Ahmad B.; Mavrelis, Peter G.; Raza, Mamoon; Heise, Jeffrey A.; Turgeon, Daniel G.; Fox, Mark A.

2015-01-01

Background. Incomplete control of troublesome regurgitation and extraesophageal manifestations of chronic gastroesophageal reflux disease (GERD) is a known limitation of proton pump inhibitor (PPI) therapy. This multicenter randomized study compared the efficacy of transoral incisionless fundoplication (TIF) against PPIs in controlling these symptoms in patients with small hiatal hernias. Methods. Between June and August 2012, 63 patients were randomized at 7 US community hospitals. Patients in the PPI group were placed on maximum standard dose (MSD). Patients in the TIF group underwent esophagogastric fundoplication using the EsophyX2 device. Primary outcome was elimination of daily troublesome regurgitation or extraesophageal symptoms. Secondary outcomes were normalization of esophageal acid exposure (EAE), PPI usage and healing of esophagitis. Results. Of 63 randomized patients (40 TIF and 23 PPI), 3 were lost to follow-up leaving 39 TIF and 21 PPI patients for analysis. At 6-month follow-up, troublesome regurgitation was eliminated in 97% of TIF patients versus 50% of PPI patients, relative risk (RR) = 1.9, 95% confidence interval (CI) = 1.2-3.11 (P = .006). Globally, 62% of TIF patients experienced elimination of regurgitation and extraesophageal symptoms versus 5% of PPI patients, RR = 12.9, 95% CI = 1.9-88.9 (P = .009). EAE was normalized in 54% of TIF patients (off PPIs) versus 52% of PPI patients (on MSD), RR = 1.0, 95% CI = 0.6-1.7 (P = .914). Ninety percent of TIF patients were off PPIs. Conclusion. At 6-month follow-up, TIF was more effective than MSD PPI therapy in eliminating troublesome regurgitation and extraesophageal symptoms of GERD. PMID:24756976

Proton pump inhibitors affect the gut microbiome.

PubMed

Imhann, Floris; Bonder, Marc Jan; Vich Vila, Arnau; Fu, Jingyuan; Mujagic, Zlatan; Vork, Lisa; Tigchelaar, Ettje F; Jankipersadsing, Soesma A; Cenit, Maria Carmen; Harmsen, Hermie J M; Dijkstra, Gerard; Franke, Lude; Xavier, Ramnik J; Jonkers, Daisy; Wijmenga, Cisca; Weersma, Rinse K; Zhernakova, Alexandra

2016-05-01

Proton pump inhibitors (PPIs) are among the top 10 most widely used drugs in the world. PPI use has been associated with an increased risk of enteric infections, most notably Clostridium difficile. The gut microbiome plays an important role in enteric infections, by resisting or promoting colonisation by pathogens. In this study, we investigated the influence of PPI use on the gut microbiome. The gut microbiome composition of 1815 individuals, spanning three cohorts, was assessed by tag sequencing of the 16S rRNA gene. The difference in microbiota composition in PPI users versus non-users was analysed separately in each cohort, followed by a meta-analysis. 211 of the participants were using PPIs at the moment of stool sampling. PPI use is associated with a significant decrease in Shannon's diversity and with changes in 20% of the bacterial taxa (false discovery rate <0.05). Multiple oral bacteria were over-represented in the faecal microbiome of PPI-users, including the genus Rothia (p=9.8×10(-38)). In PPI users we observed a significant increase in bacteria: genera Enterococcus, Streptococcus, Staphylococcus and the potentially pathogenic species Escherichia coli. The differences between PPI users and non-users observed in this study are consistently associated with changes towards a less healthy gut microbiome. These differences are in line with known changes that predispose to C. difficile infections and can potentially explain the increased risk of enteric infections in PPI users. On a population level, the effects of PPI are more prominent than the effects of antibiotics or other commonly used drugs. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Use of proton pump inhibitors among older Australians: national quality improvement programmes have led to sustained practice change.

PubMed

Pratt, Nicole L; Kalisch Ellett, Lisa M; Sluggett, Janet K; Gadzhanova, Svetla V; Ramsay, Emmae N; Kerr, Mhairi; LeBlanc, Vanessa T; Barratt, John D; Roughead, Elizabeth E

2017-02-01

To evaluate the impact of national multifaceted initiatives to improve use of proton pump inhibitors (PPIs) on the use of PPIs among older Australians. Interrupted time series analysis using administrative health claims data from the Australian Government Department of Veterans' Affairs (DVA). Australia. All veterans and dependents who received PPIs between January 2003 and December 2013. National, multifaceted interventions to improve PPI use were conducted by the Australian Government Department of Veterans' Affairs Veterans' MATES programme and Australia's NPS MedicineWise in April 2004, June 2006, May 2009 and August 2012. Trends in monthly rate of use of any PPI among the veteran population, and the monthly rate of use of low strength PPIs among all veterans dispensed a PPI. Interventions in 2004, 2006, 2009 and 2012 slowed the rate of increase in PPI use significantly, with the 2012 intervention resulting in a sustained 0.04% decrease in PPI use each month. The combined effect of all four interventions was a 20.9% (95% CI 7.8-33.9%) relative decrease in PPI use 12 months after the final intervention. The four interventions also resulted in a 42.2% (95% CI 19.9-64.5%) relative increase in low strength PPI use 12 months after the final intervention. National multifaceted programmes targeting clinicians and consumers were effective in reducing overall PPI use and increasing use of low strength PPIs. Interventions to improve PPI use should incorporate regular repetition of key messages to sustain practice change. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Detection of protein complex from protein-protein interaction network using Markov clustering

NASA Astrophysics Data System (ADS)

Ochieng, P. J.; Kusuma, W. A.; Haryanto, T.

2017-05-01

Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks.

Potential molecular mechanisms of overgrazing-induced dwarfism in sheepgrass (Leymus chinensis) analyzed using proteomic data.

PubMed

Ren, Weibo; Xie, Jihong; Hou, Xiangyang; Li, Xiliang; Guo, Huiqin; Hu, Ningning; Kong, Lingqi; Zhang, Jize; Chang, Chun; Wu, Zinian

2018-05-08

This study was designed to reveal potential molecular mechanisms of long-term overgrazing-induced dwarfism in sheepgrass (Leymus chinensis). An electrospray ionisation mass spectrometry system was used to generate proteomic data of dwarf sheepgrass from a long-term overgrazed rangeland and normal sheepgrass from a long-term enclosed rangeland. Differentially expressed proteins (DEPs) between dwarf and normal sheepgrass were identified, after which their potential functions and interactions with each other were predicted. The expression of key DEPs was confirmed by high-performance liquid chromatography mass spectrometry (HPLC-MS) using a multiple reaction monitoring method. Compared with normal sheepgrass, a total of 51 upregulated and 53 downregulated proteins were identified in dwarf sheepgrass. The amino acids biosynthesis pathway was differentially enriched between the two conditions presenting DEPs, such as SAT5_ARATH and DAPA_MAIZE. The protein-protein interaction (PPI) network revealed a possible interaction between RPOB2_LEPTE, A0A023H9M8_9STRA, ATPB_DIOEL, RBL_AMOTI and DNAK_GRATL. Four modules were also extracted from the PPI network. The HPLC-MS analysis confirmed the upregulation and downregulation of ATPB_DIOEL and DNAK_GRATL, respectively in dwarf samples compared with in the controls. The upregulated ATPB_DIOEL and downregulated DNAK_GRATL as well as proteins that interact with them, such as RPOB2_LEPTE, A0A023H9M8_9STRA and RBL_AMOTI, may be associated with the long-term overgrazing-induced dwarfism in sheepgrass.

Investigating multiple dysregulated pathways in rheumatoid arthritis based on pathway interaction network.

PubMed

Song, Xian-Dong; Song, Xian-Xu; Liu, Gui-Bo; Ren, Chun-Hui; Sun, Yuan-Bo; Liu, Ke-Xin; Liu, Bo; Liang, Shuang; Zhu, Zhu

2018-03-01

The traditional methods of identifying biomarkers in rheumatoid arthritis (RA) have focussed on the differentially expressed pathways or individual pathways, which however, neglect the interactions between pathways. To better understand the pathogenesis of RA, we aimed to identify dysregulated pathway sets using a pathway interaction network (PIN), which considered interactions among pathways. Firstly, RA-related gene expression profile data, protein-protein interactions (PPI) data and pathway data were taken up from the corresponding databases. Secondly, principal component analysis method was used to calculate the pathway activity of each of the pathway, and then a seed pathway was identified using data gleaned from the pathway activity. A PIN was then constructed based on the gene expression profile, pathway data, and PPI information. Finally, the dysregulated pathways were extracted from the PIN based on the seed pathway using the method of support vector machines and an area under the curve (AUC) index. The PIN comprised of a total of 854 pathways and 1064 pathway interactions. The greatest change in the activity score between RA and control samples was observed in the pathway of epigenetic regulation of gene expression, which was extracted and regarded as the seed pathway. Starting with this seed pathway, one maximum pathway set containing 10 dysregulated pathways was extracted from the PIN, having an AUC of 0.8249, and the result indicated that this pathway set could distinguish RA from the controls. These 10 dysregulated pathways might be potential biomarkers for RA diagnosis and treatment in the future.

Investigating dysregulated pathways in Staphylococcus aureus (SA) exposed macrophages based on pathway interaction network.

PubMed

Zhou, Wei; Zhang, Yan; Li, Yue-Hua; Wang, Shuang; Zhang, Jing-Jing; Zhang, Cui-Xia; Zhang, Zhi-Sheng

2017-02-01

This work aimed to identify dysregulated pathways for Staphylococcus aureus (SA) exposed macrophages based on pathway interaction network (PIN). The inference of dysregulated pathways was comprised of four steps: preparing gene expression data, protein-protein interaction (PPI) data and pathway data; constructing a PIN dependent on the data and Pearson correlation coefficient (PCC); selecting seed pathway from PIN by computing activity score for each pathway according to principal component analysis (PCA) method; and investigating dysregulated pathways in a minimum set of pathways (MSP) utilizing seed pathway and the area under the receiver operating characteristics curve (AUC) index implemented in support vector machines (SVM) model. A total of 20,545 genes, 449,833 interactions and 1189 pathways were obtained in the gene expression data, PPI data and pathway data, respectively. The PIN was consisted of 8388 interactions and 1189 nodes, and Respiratory electron transport, ATP synthesis by chemiosmotic coupling, and heat production by uncoupling proteins was identified as the seed pathway. Finally, 15 dysregulated pathways in MSP (AUC=0.999) were obtained for SA infected samples, such as Respiratory electron transport and DNA Replication. We have identified 15 dysregulated pathways for SA infected macrophages based on PIN. The findings might provide potential biomarkers for early detection and therapy of SA infection, and give insights to reveal the molecular mechanism underlying SA infections. However, how these dysregulated pathways worked together still needs to be studied. Copyright © 2016 Elsevier Ltd. All rights reserved.

Benchmarking pathway interaction network for colorectal cancer to identify dysregulated pathways.

PubMed

Wang, Q; Shi, C-J; Lv, S-H

2017-03-30

Different pathways act synergistically to participate in many biological processes. Thus, the purpose of our study was to extract dysregulated pathways to investigate the pathogenesis of colorectal cancer (CRC) based on the functional dependency among pathways. Protein-protein interaction (PPI) information and pathway data were retrieved from STRING and Reactome databases, respectively. After genes were aligned to the pathways, each pathway activity was calculated using the principal component analysis (PCA) method, and the seed pathway was discovered. Subsequently, we constructed the pathway interaction network (PIN), where each node represented a biological pathway based on gene expression profile, PPI data, as well as pathways. Dysregulated pathways were then selected from the PIN according to classification performance and seed pathway. A PIN including 11,960 interactions was constructed to identify dysregulated pathways. Interestingly, the interaction of mRNA splicing and mRNA splicing-major pathway had the highest score of 719.8167. Maximum change of the activity score between CRC and normal samples appeared in the pathway of DNA replication, which was selected as the seed pathway. Starting with this seed pathway, a pathway set containing 30 dysregulated pathways was obtained with an area under the curve score of 0.8598. The pathway of mRNA splicing, mRNA splicing-major pathway, and RNA polymerase I had the maximum genes of 107. Moreover, we found that these 30 pathways had crosstalks with each other. The results suggest that these dysregulated pathways might be used as biomarkers to diagnose CRC.

Oesophageal narrowing on barium oesophagram is more common in adult patients with eosinophilic oesophagitis than PPI-responsive oesophageal eosinophilia.

PubMed

Podboy, A; Katzka, D A; Enders, F; Larson, J J; Geno, D; Kryzer, L; Alexander, J

2016-06-01

To date there have been no clear features that aid in differentiating patients with eosinophilic oesophagitis (EoE) from PPI-responsive oesophageal eosinophilia (PPI-REE). However, barium swallow roentgenography is a more sensitive and specific measure to detect subtle fibrostenotic remodeling changes present in EoE. We aim to characterise any clinical, endoscopic, histiological or barium roentgenographic differences between EoE and PPI-REE. To characterise any clinical, endoscopic, histiological or barium roentgenographic differences between EoE and PPI-REE. We performed a retrospective cohort analysis on data collected from a tertiary referral centre population from 2010 to 2015. Data from 66 patients with EoE and 28 patients with PPI-REE were analysed. Cases were adults who met consensus guidelines for EOE, and had a barium swallow study within 6 months of the index endoscopy. Clinical, endoscopic, histiological and barium swallow findings were collected. Patients with EoE reported similar characteristics as PPI-REE patients, except EoE patients were younger (35.6 vs. 46.6 years; P = 0.011), had earlier symptom onset (29.0 vs. 38.0 years; P = 0.026), and smaller oesophageal diameters on barium swallow (19.5 mm vs. 20; P = 0.042). Patients with EoE were more likely to have distal strictures (EoE 77% vs. 25%; P = 0.02) and, importantly, a greater likelihood of small calibre oesophagus (51.5% vs. 17.9%; P = 0.002). Moreover, EoE patients had a higher probability of developing small calibre oesophagus after 20 years of symptoms (72.3% vs. 30.2%; P = 0.074) compared to PPI-REE patients. When compared with eosinophilic oesophagitis, PPI-REE patients demonstrate findings that suggest PPI-responsive oesophageal eosinophilia to be a later onset, less aggressive form of oesophageal stricturing disease than eosinophilic oesophagitis. © 2016 John Wiley & Sons Ltd.

Predictors of Need for Permanent Pacemaker Implantation and Conduction Abnormalities With a Novel Self-expanding Transcatheter Heart Valve.

PubMed

Pellegrini, Costanza; Husser, Oliver; Kim, Won-Keun; Holzamer, Andreas; Walther, Thomas; Rheude, Tobias; Mayr, Nicola Patrick; Trenkwalder, Teresa; Joner, Michael; Michel, Jonathan; Chaustre, Fabian; Kastrati, Adnan; Schunkert, Heribert; Burgdorf, Christof; Hilker, Michael; Möllmann, Helge; Hengstenberg, Christian

2018-03-15

The incidence of permanent pacemaker implantation (PPI) and new conduction abnormalities (CA) with the ACURATE neo (Symetis S.A., Eclubens, Switzerland) has not been studied in detail. We aimed to analyze their predictors, evaluating patient- and device-related factors, including implantation depth and device-to-annulus ratio (DAR). Two analyses of a multicenter population were performed: new PPI in pacemaker-naive patients (n = 283), and PPI/new-CA in patients without prior CA or pacemaker (n = 232). A new PPI was required in 9.9% of patients, who had a higher body mass index, higher rate of right bundle branch block and bradycardia. Neither implantation depth nor DAR differed in patients with PPI compared with those without. In the multivariable analysis neither DAR (OR, 1.010; 95%CI, 0.967-1.055; P = .7) nor implantation depth (OR, 0.972; 95%CI, 0.743-1.272; P = .8) predicted PPI. Only high body mass index, bradycardia and right bundle branch block persisted as independent predictors. PPI/new-onset CA occurred in 22.8% of patients and was associated with a higher logistic EuroSCORE. Neither implantation depth nor DAR differed in patients with PPI/new-CA vs those without (7.3 ± 1.9 vs 7.1 ± 1.5mm; P = .6 and 41.0 ± 7.9 vs 42.2 ± 10.1%; P = .4). The only predictor of PPI/new-CA was a higher logistic EuroSCORE (OR, 1.039; 95%CI, [1.008-1.071]; P = .013). New PPI and new-onset CA rates were low with the ACURATE neo. These were mainly influenced by patient characteristics and not by device-depending factors. Copyright © 2018 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.

Impact of New-Onset Left Bundle Branch Block and Periprocedural Permanent Pacemaker Implantation on Clinical Outcomes in Patients Undergoing Transcatheter Aortic Valve Replacement: A Systematic Review and Meta-Analysis.

PubMed

Regueiro, Ander; Abdul-Jawad Altisent, Omar; Del Trigo, María; Campelo-Parada, Francisco; Puri, Rishi; Urena, Marina; Philippon, François; Rodés-Cabau, Josep

2016-05-01

Available data on the clinical impact of new-onset left bundle branch block (LBBB) and permanent pacemaker implantation (PPI) after transcatheter aortic valve replacement (TAVR) remains controversial. We aimed to evaluate the impact of (1) periprocedural new-onset LBBB or PPI post-TAVR on cardiac mortality and all-cause 1-year mortality and (2) new-onset LBBB on the need for PPI at 1-year follow-up. We performed a systematic search from PubMed and EMBASE databases for studies reporting raw data on new-onset LBBB post-TAVR and the need for PPI or mortality at 1-year follow-up, or on 1-year mortality according to the need for periprocedural PPI post-TAVR. Data from 17 studies, including 4756 patients (8 studies) and 7032 patients (11 studies) for the evaluation of the impact of new-onset LBBB and periprocedural PPI post-TAVR were sourced, respectively (with 2 studies used for both outcomes). New-onset LBBB post-TAVR was associated with a higher risk of PPI (risk ratio [RR], 2.18; 95% confidence interval [CI], 1.28-3.70) and cardiac death (RR, 1.39; 95% CI, 1.04-1.86) during follow-up, as well with a tendency toward an increase in all-cause mortality (RR, 1.21; 95% CI, 0.98-1.50). Periprocedural PPI post-TAVR was not associated with any increased risk of all-cause mortality at 1 year (RR, 1.03; 95% CI, 0.9-1.18), yet a tendency toward a protective effect on cardiac death was observed (RR, 0.78; 95% CI, 0.60-1.03). New-onset LBBB post-TAVR is a marker of an increased risk of cardiac death and need for PPI at 1-year follow-up. The need for PPI early post-TAVR did not increase the risk of death. © 2016 American Heart Association, Inc.

Polymer-based adsorbent for heavy metals removal from aqueous solution

NASA Astrophysics Data System (ADS)

Mahmud, H. N. M. E.; Huq, A. K. O.; Yahya, R.

2017-06-01

A novel conducting polymer-based adsorbent, polypyrrole (PPy) fine powder has successfully been prepared as a new adsorbent and utilized in the adsorption of heavy metal ions like arsenic, zinc and cadmium ions from aqueous solution. PPy was chemically synthesized by using FeCl3.6H2O as an oxidant. The prepared PPy adsorbent was characterized by Brunauer-Emmet-Teller (BET) surface analysis, field emission scanning electron microscopy (FESEM) and attenuated total reflectance fourier transform infrared ATR-(FTIR) spectroscopy. The adsorption was conducted by varying different parameters such as, contact time, pH and adsorbent dosage. The concentrations of metal ions were measured by inductively coupled plasma mass spectroscopy (ICP-MS). The results show that PPy acts as an effective sorbent for the removal of arsenic, zinc and cadmium ions from aqueous solution. The as-prepared PPy fine powder is easy to prepare and appeared as an effective adsorbent for heavy metal ions particularly arsenic in wastewater treatment.

Polypyrrole-Grafted Coconut Shell Biological Carbon as a Potential Adsorbent for Methyl Tert-Butyl Ether Removal: Characterization and Adsorption Capability

PubMed Central

Li, Shanshan; Qian, Keke; Wang, Shan; Liang, Kaiqiang; Yan, Wei

2017-01-01

Methyl tert-butyl ether (MTBE) has been used as a common gasoline additive worldwide since the late twentieth century, and it has become the most frequently detected groundwater pollutant in many countries. This study aimed to synthesize a novel microbial carrier to improve its adsorptive capacity for MTBE and biofilm formation, compared to the traditional granular activated carbon (GAC). A polypyrrole (PPy)-modified GAC composite (PPy/GAC) was synthesized, and characterized by Fourier transform infrared spectroscopy (FT-IR) and Brunauer-Emmett-Teller (BET) surface area analysis. The adsorption behaviors of MTBE were well described by the pseudo-second-order and Langmuir isotherm models. Furthermore, three biofilm reactors were established with PPy/GAC, PPy, and GAC as the carriers, respectively, and the degradation of MTBE under continuous flow was investigated. Compared to the biofilm reactors with PPy or GAC (which both broke after a period of operation), the PPy/GAC biofilm column produced stable effluents under variable treatment conditions with a long-term effluent MTBE concentration <20 μg/L. Pseudomonas aeruginosa and Acinetobacter pittii may be the predominant bacteria responsible for MTBE degradation in these biofilm reactors. PMID:28125030

Functional Module Search in Protein Networks based on Semantic Similarity Improves the Analysis of Proteomics Data*

PubMed Central

Boyanova, Desislava; Nilla, Santosh; Klau, Gunnar W.; Dandekar, Thomas; Müller, Tobias; Dittrich, Marcus

2014-01-01

The continuously evolving field of proteomics produces increasing amounts of data while improving the quality of protein identifications. Albeit quantitative measurements are becoming more popular, many proteomic studies are still based on non-quantitative methods for protein identification. These studies result in potentially large sets of identified proteins, where the biological interpretation of proteins can be challenging. Systems biology develops innovative network-based methods, which allow an integrated analysis of these data. Here we present a novel approach, which combines prior knowledge of protein-protein interactions (PPI) with proteomics data using functional similarity measurements of interacting proteins. This integrated network analysis exactly identifies network modules with a maximal consistent functional similarity reflecting biological processes of the investigated cells. We validated our approach on small (H9N2 virus-infected gastric cells) and large (blood constituents) proteomic data sets. Using this novel algorithm, we identified characteristic functional modules in virus-infected cells, comprising key signaling proteins (e.g. the stress-related kinase RAF1) and demonstrate that this method allows a module-based functional characterization of cell types. Analysis of a large proteome data set of blood constituents resulted in clear separation of blood cells according to their developmental origin. A detailed investigation of the T-cell proteome further illustrates how the algorithm partitions large networks into functional subnetworks each representing specific cellular functions. These results demonstrate that the integrated network approach not only allows a detailed analysis of proteome networks but also yields a functional decomposition of complex proteomic data sets and thereby provides deeper insights into the underlying cellular processes of the investigated system. PMID:24807868

Highly biological active antibiofilm, anticancer and osteoblast adhesion efficacy from MWCNT/PPy/Pd nanocomposite

NASA Astrophysics Data System (ADS)

Murugesan, Balaji; Sonamuthu, Jegatheeswaran; Samayanan, Selvam; Arumugam, Sangili; Mahalingam, Sundrarajan

2018-03-01

Multifunctional biologically active materials have approached for antibiofilm, anticancer and osteoblast adhesion activities with significant biomedical applications, owing to this MWCNT modified with polypyrrole (PPy) matrix with the incorporation of palladium nanoparticles (NPs). The synthesized composite displays a tube-shaped morphology with highly dispersed crystalline Pd NPs, which are established through XRD, SEM, TEM and SAED studies. The pyridinic-N(∼402.7), pyrrolic sbnd N (∼400.8) peak in XPS spectra evidenced the interaction of PPy with Pd and MWCNT. Polymer stretching frequencies in FTIR and Raman spectroscopy proves successful formation of PPy and the Pd-N (1609 cm-1) interaction. In the stability aspect, it is up to 58.73% mass withstood at 800 °C in TGA analysis. The composite exhibits an efficient Anti-biofilm against a set of bacterial stain with planktonic cell growth. In vitro cytotoxicity of Vero and HeLa cell line assess the composites toxicity and anticancer activity up to 100 μg. The outcome of cell adhesions showed that human osteosarcoma cells (HOS) can adhere and to develop on the MWCNT/PPy/Pd composites. Furthermore, the proliferation of cells on MWCNT/PPy/Pd composites was also proved the biocompatibility of the composites against HOS cells. These results suggest that Pd-doped MWCNT/PPy composites are promising materials for biomedical applications.

Task modulated brain connectivity of the amygdala: a meta-analysis of psychophysiological interactions.

PubMed

Di, Xin; Huang, Jia; Biswal, Bharat B

2017-01-01

Understanding functional connectivity of the amygdala with other brain regions, especially task modulated connectivity, is a critical step toward understanding the role of the amygdala in emotional processes and the interactions between emotion and cognition. The present study performed coordinate-based meta-analysis on studies of task modulated connectivity of the amygdala which used psychophysiological interaction (PPI) analysis. We first analyzed 49 PPI studies on different types of tasks using activation likelihood estimation (ALE) meta-analysis. Widespread cortical and subcortical regions showed consistent task modulated connectivity with the amygdala, including the medial frontal cortex, bilateral insula, anterior cingulate, fusiform gyrus, parahippocampal gyrus, thalamus, and basal ganglia. These regions were in general overlapped with those showed coactivations with the amygdala, suggesting that these regions and amygdala are not only activated together, but also show different levels of interactions during tasks. Further analyses with subsets of PPI studies revealed task specific functional connectivities with the amygdala that were modulated by fear processing, face processing, and emotion regulation. These results suggest a dynamic modulation of connectivity upon task demands, and provide new insights on the functions of the amygdala in different affective and cognitive processes. The meta-analytic approach on PPI studies may offer a framework toward systematical examinations of task modulated connectivity.

Gut Microbiota Composition Before and After Use of Proton Pump Inhibitors.

PubMed

Hojo, Mariko; Asahara, Takashi; Nagahara, Akihito; Takeda, Tsutomu; Matsumoto, Kohei; Ueyama, Hiroya; Matsumoto, Kenshi; Asaoka, Daisuke; Takahashi, Takuya; Nomoto, Koji; Yamashiro, Yuichiro; Watanabe, Sumio

2018-05-24

Recently, problems associated with proton pump inhibitor (PPI) use have begun to surface. PPIs influence the gut microbiota; therefore, PPI use may increase the risk of enteric infections and cause bacterial translocation. In this study, we investigated fecal microbiota composition, fecal organic acid concentrations and pH, and gut bacteria in the blood of the same patients before and after PPI use. Twenty patients with reflux esophagitis based on endoscopic examination received 8 weeks of treatment with PPIs. To analyze fecal microbiota composition and gut bacteria in blood and organic acid concentrations, 16S and 23S rRNA-targeted quantitative RT-PCR and high-performance liquid chromatography were conducted. Lactobacillus species were significantly increased at both 4 and 8 weeks after PPI treatment compared with bacterial counts before treatment (P = 0.011 and P = 0.002, respectively). Among Lactobacillus spp., counts of the L. gasseri subgroup, L. fermentum, the L. reuteri subgroup, and the L. ruminis subgroup were significantly increased at 4 and 8 weeks after treatment compared with counts before treatment. Streptococcus species were also significantly increased at 4 and 8 weeks after PPI treatment compared with counts before treatment (P < 0.01 and P < 0.001, respectively). There was no significant difference in the total organic acid concentrations before and after PPI treatment. Detection rates of bacteria in blood before and after PPI treatment were 22 and 28%, respectively, with no significant differences. Our quantitative RT-PCR results showed that gut dysbiosis was caused by PPI use, corroborating previous results obtained by metagenomic analysis.

Proton pump inhibitor use for 12 months is not associated with changes in serum magnesium levels: a prospective open label comparative study.

PubMed

Bahtiri, Elton; Islami, Hilmi; Hoxha, Rexhep; Gashi, Afrim; Thaçi, Kujtim; Karakulak, Çağla; Thaçi, Shpetim; Qorraj Bytyqi, Hasime

2017-03-01

Proton pump inhibitors (PPIs) are a widely used class of drugs because of a generally acceptable safety profile. Among recently raised safety issues of the long-term use of PPIs is the increased risk of developing hypomagnesemia. As there have been very few prospective studies measuring serum magnesium levels before and after PPI therapy, we aimed to prospectively assess the potential association between PPI therapy for 12 months and the risk of hypomagnesemia as well as the incidence of new-onset hypomagnesemia during the study. In addition, the association of PPI therapy with the risk of hypocalcemia was assessed. The study included 250 patients with normal serum magnesium and total calcium levels, who underwent a long-term PPI treatment. Serum magnesium, total calcium, and parathormone (PTH) levels were measured at baseline and after 12 months. Of the 250 study participants, 209 completed 12 months of treatment and were included in the statistical analysis. The Wilcoxon signed rank test showed no statistically significant differences in serum magnesium levels between measurements at two different time points. However, there were statistically significant differences in serum total calcium and PTH levels in PPI users. Stable serum magnesium levels were demonstrated after 12 months and no association between PPI use and risk of hypomagnesemia was shown in the general population. Significant reductions of serum total calcium levels were demonstrated among PPI users; nevertheless, further research is required before recommending any serum calcium and PTH level monitoring in patients initiated on long-term PPI therapy.

A network analysis of the Chinese medicine Lianhua-Qingwen formula to identify its main effective components.

PubMed

Wang, Chun-Hua; Zhong, Yi; Zhang, Yan; Liu, Jin-Ping; Wang, Yue-Fei; Jia, Wei-Na; Wang, Guo-Cai; Li, Zheng; Zhu, Yan; Gao, Xiu-Mei

2016-02-01

Chinese medicine is known to treat complex diseases with multiple components and multiple targets. However, the main effective components and their related key targets and functions remain to be identified. Herein, a network analysis method was developed to identify the main effective components and key targets of a Chinese medicine, Lianhua-Qingwen Formula (LQF). The LQF is commonly used for the prevention and treatment of viral influenza in China. It is composed of 11 herbs, gypsum and menthol with 61 compounds being identified in our previous work. In this paper, these 61 candidate compounds were used to find their related targets and construct the predicted-target (PT) network. An influenza-related protein-protein interaction (PPI) network was constructed and integrated with the PT network. Then the compound-effective target (CET) network and compound-ineffective target network (CIT) were extracted, respectively. A novel approach was developed to identify effective components by comparing CET and CIT networks. As a result, 15 main effective components were identified along with 61 corresponding targets. 7 of these main effective components were further experimentally validated to have antivirus efficacy in vitro. The main effective component-target (MECT) network was further constructed with main effective components and their key targets. Gene Ontology (GO) analysis of the MECT network predicted key functions such as NO production being modulated by the LQF. Interestingly, five effective components were experimentally tested and exhibited inhibitory effects on NO production in the LPS induced RAW 264.7 cell. In summary, we have developed a novel approach to identify the main effective components in a Chinese medicine LQF and experimentally validated some of the predictions.

Highly efficient near ultraviolet organic light-emitting diode based on a meta-linked donor–acceptor molecule† †Electronic supplementary information (ESI) available: The details of the synthesis; the ground state and excited state geometries in PPI, TPA–PPI and mTPA–PPI; absorption and emission properties of PPI, TPA–PPI and mTPA–PPI in the gas phase; detailed absorption peak positions, emission peak positions and ηPL values of PPI and mTPA–PPI in different solvents; HOMO and LUMO of mTPA–PPI at ground state; NTO for the S0 → S1 absorption transition in PPI, TPA–PPI and mTPA–PPI; NTO for S0 → Sn electronic transition character in mTPA–PPI; lifetime measurement, radiative transition rates and non-radiative transition rates of PPI and mTPA–PPI in hexane and THF solutions; low-temperature fluorescence and phosphorescence spectra of PPI and mTPA–PPI; CV curves of PPI and mTPA–PPI, and schematic diagram of design principle of mTPA–PPI; TGA and DSC graphs of PPI and mTPA–PPI; current efficiency–current density–power efficiency curves and EL spectra at different driving voltages of PPI and mTPA–PPI devices. See DOI: 10.1039/c5sc01131k

PubMed Central

Liu, Haichao; Bai, Qing; Yao, Liang; Zhang, Haiyan; Xu, Hai; Zhang, Shitong; Li, Weijun; Gao, Yu; Li, Jinyu; Lu, Ping; Wang, Hongyan; Ma, Yuguang

2015-01-01

A novel near ultraviolet (NUV) emitter with a meta-linked donor–acceptor (D–A) structure between triphenylamine (TPA) and phenanthroimidazole (PPI), mTPA–PPI, was designed and synthesized. This molecular design is expected to resolve the conflict between the non-red-shifted emission and the introduction of a charge-transfer (CT) state in the D–A system, aiming at NUV organic light-emitting diodes (OLEDs) with high-efficiency and colour-purity. Theoretical calculations and photophysical experiments were implemented to verify the unique excited state properties of mTPA–PPI. The mTPA–PPI device exhibited excellent NUV electroluminescence (EL) performance with an emission peak at 404 nm, a full width at half maximum (FWHM) of only 47 nm corresponding to a CIE coordinate of (0.161, 0.049), and a maximum external quantum efficiency (EQE) of 3.33%, which is among the best results for NUV OLEDs. This work not only demonstrates the promising potential of mTPA–PPI in NUV OLEDs, but also provides a valuable strategy for the rational design of NUV materials by using the meta-linked D–A architecture. PMID:29218149

Highly compressible reduced graphene oxide/polypyrrole/MnO2 aerogel electrodes meeting the requirement of limiting space

NASA Astrophysics Data System (ADS)

Lv, Peng; Tang, Xun; Yuan, Jiajiao; Ji, Chenglong

2017-11-01

Highly compressible electrodes are in high demand in volume-restricted energy storage devices. Superelastic reduced graphene oxide (rGO) aerogel with attractive characteristics are proposed as the promising skeleton for compressible electrodes. Herein, a ternary aerogel was prepared by successively electrodepositing polypyrrole (PPy) and MnO2 into the superelastic rGO aerogel. In the rGO/PPy/MnO2 aerogel, rGO aerogel provides the continuously conductive network; MnO2 is mainly responsible for pseudo reactions; the middle PPy layer not only reduces the interface resistance between rGO and MnO2, but also further enhanced the mechanical strength of rGO backbone. The synergistic effect of the three components leads to excellent performances including high specific capacitance, reversible compressibility, and extreme durability. The gravimetric capacitance of the compressible rGO/PPy/MnO2 aerogel electrodes reaches 366 F g-1 and can retain 95.3% even under 95% compressive strain. And a volumetric capacitance of 138 F cm-3 is achieved, which is much higher than that of other rGO-based compressible electrodes. This volumetric capacitance value can be preserved by 85% after 3500 charge/discharge cycles with various compression conditions. This work will pave the way for advanced applications in the area of compressible energy-storage devices meeting the requirement of limiting space.

Proton Pump Inhibitor Use and the Risk of Chronic Kidney Disease.

PubMed

Lazarus, Benjamin; Chen, Yuan; Wilson, Francis P; Sang, Yingying; Chang, Alex R; Coresh, Josef; Grams, Morgan E

2016-02-01

Proton pump inhibitors (PPIs) are among the most commonly used drugs worldwide and have been linked to acute interstitial nephritis. Less is known about the association between PPI use and chronic kidney disease (CKD). To quantify the association between PPI use and incident CKD in a population-based cohort. In total, 10,482 participants in the Atherosclerosis Risk in Communities study with an estimated glomerular filtration rate of at least 60 mL/min/1.73 m(2) were followed from a baseline visit between February 1, 1996, and January 30, 1999, to December 31, 2011. The data was analyzed from May 2015 to October 2015. The findings were replicated in an administrative cohort of 248,751 patients with an estimated glomerular filtration rate of at least 60 mL/min/1.73 m(2) from the Geisinger Health System. Self-reported PPI use in the Atherosclerosis Risk in Communities study or an outpatient PPI prescription in the Geisinger Health System replication cohort. Histamine2 (H2) receptor antagonist use was considered a negative control and active comparator. Incident CKD was defined using diagnostic codes at hospital discharge or death in the Atherosclerosis Risk in Communities Study, and by a sustained outpatient estimated glomerular filtration rate of less than 60 mL/min/1.73 m(2) in the Geisinger Health System replication cohort. Among 10,482 participants in the Atherosclerosis Risk in Communities study, the mean (SD) age was 63.0 (5.6) years, and 43.9% were male. Compared with nonusers, PPI users were more often of white race, obese, and taking antihypertensive medication. Proton pump inhibitor use was associated with incident CKD in unadjusted analysis (hazard ratio [HR], 1.45; 95% CI, 1.11-1.90); in analysis adjusted for demographic, socioeconomic, and clinical variables (HR, 1.50; 95% CI, 1.14-1.96); and in analysis with PPI ever use modeled as a time-varying variable (adjusted HR, 1.35; 95% CI, 1.17-1.55). The association persisted when baseline PPI users were compared directly with H2 receptor antagonist users (adjusted HR, 1.39; 95% CI, 1.01-1.91) and with propensity score-matched nonusers (HR, 1.76; 95% CI, 1.13-2.74). In the Geisinger Health System replication cohort, PPI use was associated with CKD in all analyses, including a time-varying new-user design (adjusted HR, 1.24; 95% CI, 1.20-1.28). Twice-daily PPI dosing (adjusted HR, 1.46; 95% CI, 1.28-1.67) was associated with a higher risk than once-daily dosing (adjusted HR, 1.15; 95% CI, 1.09-1.21). Proton pump inhibitor use is associated with a higher risk of incident CKD. Future research should evaluate whether limiting PPI use reduces the incidence of CKD.

Multi-Dimensional Scaling based grouping of known complexes and intelligent protein complex detection.

PubMed

Rehman, Zia Ur; Idris, Adnan; Khan, Asifullah

2018-06-01

Protein-Protein Interactions (PPI) play a vital role in cellular processes and are formed because of thousands of interactions among proteins. Advancements in proteomics technologies have resulted in huge PPI datasets that need to be systematically analyzed. Protein complexes are the locally dense regions in PPI networks, which extend important role in metabolic pathways and gene regulation. In this work, a novel two-phase protein complex detection and grouping mechanism is proposed. In the first phase, topological and biological features are extracted for each complex, and prediction performance is investigated using Bagging based Ensemble classifier (PCD-BEns). Performance evaluation through cross validation shows improvement in comparison to CDIP, MCode, CFinder and PLSMC methods Second phase employs Multi-Dimensional Scaling (MDS) for the grouping of known complexes by exploring inter complex relations. It is experimentally observed that the combination of topological and biological features in the proposed approach has greatly enhanced prediction performance for protein complex detection, which may help to understand various biological processes, whereas application of MDS based exploration may assist in grouping potentially similar complexes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Involving the public in mental health and learning disability research: Can we, should we, do we?

PubMed

Paul, C; Holt, J

2017-10-01

WHAT IS KNOWN ON THE SUBJECT?: UK health policy is clear that researchers should involve the public throughout the research process. The public, including patients, carers and/or local citizens can bring a different and valuable perspective to the research process and improve the quality of research undertaken. Conducting health research is demanding with tight deadlines and scarce resources. This can make involving the public in research very challenging. WHAT THIS PAPER ADDS TO EXISTING KNOWLEDGE?: This is the first time the attitudes of researchers working in mental health and learning disability services towards PPI have been investigated. The principles of service user involvement in mental health and learning disability services may support PPI in research as a tool of collaboration and empowerment. This article extends our understanding of the cultural and attitudinal barriers to implementing PPI guidelines in mental health and learning disability services. WHAT ARE THE IMPLICATIONS FOR PRACTICE?: Researchers in mental health and learning disability services need to champion, share and publish effective involvement work. Structural barriers to PPI work should be addressed locally and successful strategies shared nationally and internationally. Where PPI guidelines are being developed, attention needs to be paid to cultural factors in the research community to win "hearts and minds" and support the effective integration of PPI across the whole research process. Introduction Patient and public involvement (PPI) is integral to UK health research guidance; however, implementation is inconsistent. There is little research into the attitudes of NHS health researchers towards PPI. Aim This study explored the attitude of researchers working in mental health and learning disability services in the UK towards PPI in health research. Method Using a qualitative methodology, semi-structured interviews were conducted with a purposive sample of eight researchers. A framework approach was used in the analysis to generate themes and core concepts. Results Participants valued the perspective PPI could bring to research, but frustration with tokenistic approaches to involvement work was also evident. Some cultural and attitudinal barriers to integrating PPI across the whole research process were identified. Discussion Despite clear guidelines and established service user involvement, challenges still exist in the integration of PPI in mental health and learning disability research in the UK. Implications for practice Guidelines on PPI may not be enough to prompt changes in research practice. Leaders and researchers need to support attitudinal and cultural changes where required, to ensure the full potential of PPI in mental health and learning disability services research is realized. Relevance statement Findings suggest that despite clear guidelines and a history of service user involvement, there are still challenges to the integration of PPI in mental health and learning disability research in the UK. For countries where PPI guidelines are being developed, attention needs to be paid to cultural factors in the research community to win "hearts and minds" and support the effective integration of PPI across the whole research process. © 2017 John Wiley & Sons Ltd.

IP-FCM measures physiologic protein-protein interactions modulated by signal transduction and small-molecule drug inhibition.

PubMed

Smith, Stephen E P; Bida, Anya T; Davis, Tessa R; Sicotte, Hugues; Patterson, Steven E; Gil, Diana; Schrum, Adam G

2012-01-01

Protein-protein interactions (PPI) mediate the formation of intermolecular networks that control biological signaling. For this reason, PPIs are of outstanding interest in pharmacology, as they display high specificity and may represent a vast pool of potentially druggable targets. However, the study of physiologic PPIs can be limited by conventional assays that often have large sample requirements and relatively low sensitivity. Here, we build on a novel method, immunoprecipitation detected by flow cytometry (IP-FCM), to assess PPI modulation during either signal transduction or pharmacologic inhibition by two different classes of small-molecule compounds. First, we showed that IP-FCM can detect statistically significant differences in samples possessing a defined PPI change as low as 10%. This sensitivity allowed IP-FCM to detect a PPI that increases transiently during T cell signaling, the antigen-inducible interaction between ZAP70 and the T cell antigen receptor (TCR)/CD3 complex. In contrast, IP-FCM detected no ZAP70 recruitment when T cells were stimulated with antigen in the presence of the src-family kinase inhibitor, PP2. Further, we tested whether IP-FCM possessed sufficient sensitivity to detect the effect of a second, rare class of compounds called SMIPPI (small-molecule inhibitor of PPI). We found that the first-generation non-optimized SMIPPI, Ro-26-4550, inhibited the IL-2:CD25 interaction detected by IP-FCM. This inhibition was detectable using either a recombinant CD25-Fc chimera or physiologic full-length CD25 captured from T cell lysates. Thus, we demonstrate that IP-FCM is a sensitive tool for measuring physiologic PPIs that are modulated by signal transduction and pharmacologic inhibition.

EgoNet: identification of human disease ego-network modules

PubMed Central

2014-01-01

Background Mining novel biomarkers from gene expression profiles for accurate disease classification is challenging due to small sample size and high noise in gene expression measurements. Several studies have proposed integrated analyses of microarray data and protein-protein interaction (PPI) networks to find diagnostic subnetwork markers. However, the neighborhood relationship among network member genes has not been fully considered by those methods, leaving many potential gene markers unidentified. The main idea of this study is to take full advantage of the biological observation that genes associated with the same or similar diseases commonly reside in the same neighborhood of molecular networks. Results We present EgoNet, a novel method based on egocentric network-analysis techniques, to exhaustively search and prioritize disease subnetworks and gene markers from a large-scale biological network. When applied to a triple-negative breast cancer (TNBC) microarray dataset, the top selected modules contain both known gene markers in TNBC and novel candidates, such as RAD51 and DOK1, which play a central role in their respective ego-networks by connecting many differentially expressed genes. Conclusions Our results suggest that EgoNet, which is based on the ego network concept, allows the identification of novel biomarkers and provides a deeper understanding of their roles in complex diseases. PMID:24773628

Network-Based Methods for Identifying Key Active Proteins in the Extracellular Electron Transfer Process in Shewanella oneidensis MR-1.

PubMed

Ding, Dewu; Sun, Xiao

2018-01-16

Shewanella oneidensis MR-1 can transfer electrons from the intracellular environment to the extracellular space of the cells to reduce the extracellular insoluble electron acceptors (Extracellular Electron Transfer, EET). Benefiting from this EET capability, Shewanella has been widely used in different areas, such as energy production, wastewater treatment, and bioremediation. Genome-wide proteomics data was used to determine the active proteins involved in activating the EET process. We identified 1012 proteins with decreased expression and 811 proteins with increased expression when the EET process changed from inactivation to activation. We then networked these proteins to construct the active protein networks, and identified the top 20 key active proteins by network centralization analysis, including metabolism- and energy-related proteins, signal and transcriptional regulatory proteins, translation-related proteins, and the EET-related proteins. We also constructed the integrated protein interaction and transcriptional regulatory networks for the active proteins, then found three exclusive active network motifs involved in activating the EET process-Bi-feedforward Loop, Regulatory Cascade with a Feedback, and Feedback with a Protein-Protein Interaction (PPI)-and identified the active proteins involved in these motifs. Both enrichment analysis and comparative analysis to the whole-genome data implicated the multiheme c -type cytochromes and multiple signal processing proteins involved in the process. Furthermore, the interactions of these motif-guided active proteins and the involved functional modules were discussed. Collectively, by using network-based methods, this work reported a proteome-wide search for the key active proteins that potentially activate the EET process.

Doping optimization of polypyrrole with toluenesulfonic acid using Box-Behnken design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Syed Draman, Sarifah Fauziah; Daik, Rusli; El-Sheikh, Said M.

A three-level Box-Behnken design was employed in doping optimization of polypyrrole with toluenesulfonic acid (TSA-doped PPy). The material was synthesized via chemical oxidative polymerization using pyrrole, toluenesulfonic acid (TSA) and ammonium persulfate (APS) as monomer, dopant and oxidant, respectively. The critical factors selected for this study were concentration of dopant, molar ratio between dopant to monomer (pyrrole) and concentration of oxidant. Obtaining adequate doping level of TSA-doped PPy is crucial because it affects the charge carriers for doped PPy and usually be responsible for electronic mobility along polymeric chain. Furthermore, the doping level also affects other properties such as electricalmore » and thermal conductivity. Doping level was calculated using elemental analysis. SEM images shows that the prepared TSA-doped PPy particles are spherical in shape with the diameters of about. The range of nanoparticles size is around 80-100 nm. The statistical analysis based on a Box–Behnken design showed that 0.01 mol of TSA, 1:1 mole ratio TSA to pyrrole and 0.25 M APS were the optimum conditions for sufficient doping level.« less

Item Response Theory Analysis of the Psychopathic Personality Inventory-Revised.

PubMed

Eichenbaum, Alexander E; Marcus, David K; French, Brian F

2017-06-01

This study examined item and scale functioning in the Psychopathic Personality Inventory-Revised (PPI-R) using an item response theory analysis. PPI-R protocols from 1,052 college student participants (348 male, 704 female) were analyzed. Analyses were conducted on the 131 self-report items comprising the PPI-R's eight content scales, using a graded response model. Scales collected a majority of their information about respondents possessing higher than average levels of the traits being measured. Each scale contained at least some items that evidenced limited ability to differentiate between respondents with differing levels of the trait being measured. Moreover, 80 items (61.1%) yielded significantly different responses between men and women presumably possessing similar levels of the trait being measured. Item performance was also influenced by the scoring format (directly scored vs. reverse-scored) of the items. Overall, the results suggest that the PPI-R, despite identifying psychopathic personality traits in individuals possessing high levels of those traits, may not identify these traits equally well for men and women, and scores are likely influenced by the scoring format of the individual item and scale.

In silico identification of essential proteins in Corynebacterium pseudotuberculosis based on protein-protein interaction networks.

PubMed

Folador, Edson Luiz; de Carvalho, Paulo Vinícius Sanches Daltro; Silva, Wanderson Marques; Ferreira, Rafaela Salgado; Silva, Artur; Gromiha, Michael; Ghosh, Preetam; Barh, Debmalya; Azevedo, Vasco; Röttger, Richard

2016-11-04

Corynebacterium pseudotuberculosis (Cp) is a gram-positive bacterium that is classified into equi and ovis serovars. The serovar ovis is the etiological agent of caseous lymphadenitis, a chronic infection affecting sheep and goats, causing economic losses due to carcass condemnation and decreased production of meat, wool, and milk. Current diagnosis or treatment protocols are not fully effective and, thus, require further research of Cp pathogenesis. Here, we mapped known protein-protein interactions (PPI) from various species to nine Cp strains to reconstruct parts of the potential Cp interactome and to identify potentially essential proteins serving as putative drug targets. On average, we predict 16,669 interactions for each of the nine strains (with 15,495 interactions shared among all strains). An in silico sanity check suggests that the potential networks were not formed by spurious interactions but have a strong biological bias. With the inferred Cp networks we identify 181 essential proteins, among which 41 are non-host homologous. The list of candidate interactions of the Cp strains lay the basis for developing novel hypotheses and designing according wet-lab studies. The non-host homologous essential proteins are attractive targets for therapeutic and diagnostic proposes. They allow for searching of small molecule inhibitors of binding interactions enabling modern drug discovery. Overall, the predicted Cp PPI networks form a valuable and versatile tool for researchers interested in Corynebacterium pseudotuberculosis.

Cerebrovascular Outcomes With Proton Pump Inhibitors and Thienopyridines: A Systematic Review and Meta-Analysis.

PubMed

Malhotra, Konark; Katsanos, Aristeidis H; Bilal, Mohammad; Ishfaq, Muhammad Fawad; Goyal, Nitin; Tsivgoulis, Georgios

2018-02-01

Pharmacokinetic and prior studies on thienopyridine and proton pump inhibitors (PPI) coadministration provide conflicting data for cardiovascular outcomes, whereas there is no established evidence on the association of concomitant use of PPI and thienopyridines with adverse cerebrovascular outcomes. We conducted a systematic review and meta-analysis of randomized controlled trials and cohort studies from inception to July 2017, reporting following outcomes among patients treated with thienopyridine and PPI versus thienopyridine alone (1) ischemic stroke, (2) combined ischemic or hemorrhagic stroke, (3) composite outcome of stroke, myocardial infarction (MI), and cardiovascular death, (4) MI, (5) all-cause mortality, and (6) major or minor bleeding events. After the unadjusted analyses of risk ratios, we performed additional analyses of studies reporting hazard ratios adjusted for potential confounders. We identified 22 studies (12 randomized controlled trials and 10 cohort studies) comprising 131 714 patients. Concomitant use of PPI with thienopyridines was associated with increased risk of ischemic stroke (risk ratio, 1.74; 95% confidence interval [CI], 1.41-2.16; P <0.001), composite stroke/MI/cardiovascular death (risk ratio, 1.14; 95% CI, 1.01-1.29; P =0.04), and MI (risk ratio, 1.19; 95% CI, 1.00-1.40; P =0.05). Likewise, in adjusted analyses concomitant use of PPI with thienopyridines was again associated with increased risk of stroke (hazard ratios adjusted, 1.30; 95% CI, 1.04-1.61; P =0.02), composite stroke/MI/cardiovascular death (hazard ratios adjusted, 1.23; 95% CI, 1.03-1.47; P =0.02), but not with MI (hazard ratios adjusted, 1.19; 95% CI, 0.93-1.52; P =0.16). Co-prescription of PPI and thienopyridines increases the risk of incident ischemic strokes and composite stroke/MI/cardiovascular death. Our findings corroborate the current guidelines for PPI deprescription and pharmacovigilance, especially in patients treated with thienopyridines. © 2018 American Heart Association, Inc.

Disease-aging network reveals significant roles of aging genes in connecting genetic diseases.

PubMed

Wang, Jiguang; Zhang, Shihua; Wang, Yong; Chen, Luonan; Zhang, Xiang-Sun

2009-09-01

One of the challenging problems in biology and medicine is exploring the underlying mechanisms of genetic diseases. Recent studies suggest that the relationship between genetic diseases and the aging process is important in understanding the molecular mechanisms of complex diseases. Although some intricate associations have been investigated for a long time, the studies are still in their early stages. In this paper, we construct a human disease-aging network to study the relationship among aging genes and genetic disease genes. Specifically, we integrate human protein-protein interactions (PPIs), disease-gene associations, aging-gene associations, and physiological system-based genetic disease classification information in a single graph-theoretic framework and find that (1) human disease genes are much closer to aging genes than expected by chance; and (2) diseases can be categorized into two types according to their relationships with aging. Type I diseases have their genes significantly close to aging genes, while type II diseases do not. Furthermore, we examine the topological characters of the disease-aging network from a systems perspective. Theoretical results reveal that the genes of type I diseases are in a central position of a PPI network while type II are not; (3) more importantly, we define an asymmetric closeness based on the PPI network to describe relationships between diseases, and find that aging genes make a significant contribution to associations among diseases, especially among type I diseases. In conclusion, the network-based study provides not only evidence for the intricate relationship between the aging process and genetic diseases, but also biological implications for prying into the nature of human diseases.

Hot spot-based design of small-molecule inhibitors for protein-protein interactions.

PubMed

Guo, Wenxing; Wisniewski, John A; Ji, Haitao

2014-06-01

Protein-protein interactions (PPIs) are important targets for the development of chemical probes and therapeutic agents. From the initial discovery of the existence of hot spots at PPI interfaces, it has been proposed that hot spots might provide the key for developing small-molecule PPI inhibitors. However, there has been no review on the ways in which the knowledge of hot spots can be used to achieve inhibitor design, nor critical examination of successful examples. This Digest discusses the characteristics of hot spots and the identification of druggable hot spot pockets. An analysis of four examples of hot spot-based design reveals the importance of this strategy in discovering potent and selective PPI inhibitors. A general procedure for hot spot-based design of PPI inhibitors is outlined. Copyright © 2014 Elsevier Ltd. All rights reserved.

Structure-Based Analysis Reveals Cancer Missense Mutations Target Protein Interaction Interfaces.

PubMed

Engin, H Billur; Kreisberg, Jason F; Carter, Hannah

2016-01-01

Recently it has been shown that cancer mutations selectively target protein-protein interactions. We hypothesized that mutations affecting distinct protein interactions involving established cancer genes could contribute to tumor heterogeneity, and that novel mechanistic insights might be gained into tumorigenesis by investigating protein interactions under positive selection in cancer. To identify protein interactions under positive selection in cancer, we mapped over 1.2 million nonsynonymous somatic cancer mutations onto 4,896 experimentally determined protein structures and analyzed their spatial distribution. In total, 20% of mutations on the surface of known cancer genes perturbed protein-protein interactions (PPIs), and this enrichment for PPI interfaces was observed for both tumor suppressors (Odds Ratio 1.28, P-value < 10(-4)) and oncogenes (Odds Ratio 1.17, P-value < 10(-3)). To study this further, we constructed a bipartite network representing structurally resolved PPIs from all available human complexes in the Protein Data Bank (2,864 proteins, 3,072 PPIs). Analysis of frequently mutated cancer genes within this network revealed that tumor-suppressors, but not oncogenes, are significantly enriched with functional mutations in homo-oligomerization regions (Odds Ratio 3.68, P-Value < 10(-8)). We present two important examples, TP53 and beta-2-microglobulin, for which the patterns of somatic mutations at interfaces provide insights into specifically perturbed biological circuits. In patients with TP53 mutations, patient survival correlated with the specific interactions that were perturbed. Moreover, we investigated mutations at the interface of protein-nucleotide interactions and observed an unexpected number of missense mutations but not silent mutations occurring within DNA and RNA binding sites. Finally, we provide a resource of 3,072 PPI interfaces ranked according to their mutation rates. Analysis of this list highlights 282 novel candidate cancer genes that encode proteins participating in interactions that are perturbed recurrently across tumors. In summary, mutation of specific protein interactions is an important contributor to tumor heterogeneity and may have important implications for clinical outcomes.

Identification of key genes and pathways associated with neuropathic pain in uninjured dorsal root ganglion by using bioinformatic analysis.

PubMed

Chen, Chao-Jin; Liu, De-Zhao; Yao, Wei-Feng; Gu, Yu; Huang, Fei; Hei, Zi-Qing; Li, Xiang

2017-01-01

Neuropathic pain is a complex chronic condition occurring post-nervous system damage. The transcriptional reprogramming of injured dorsal root ganglia (DRGs) drives neuropathic pain. However, few comparative analyses using high-throughput platforms have investigated uninjured DRG in neuropathic pain, and potential interactions among differentially expressed genes (DEGs) and pathways were not taken into consideration. The aim of this study was to identify changes in genes and pathways associated with neuropathic pain in uninjured L4 DRG after L5 spinal nerve ligation (SNL) by using bioinformatic analysis. The microarray profile GSE24982 was downloaded from the Gene Expression Omnibus database to identify DEGs between DRGs in SNL and sham rats. The prioritization for these DEGs was performed using the Toppgene database followed by gene ontology and pathway enrichment analyses. The relationships among DEGs from the protein interactive perspective were analyzed using protein-protein interaction (PPI) network and module analysis. Real-time polymerase chain reaction (PCR) and Western blotting were used to confirm the expression of DEGs in the rodent neuropathic pain model. A total of 206 DEGs that might play a role in neuropathic pain were identified in L4 DRG, of which 75 were upregulated and 131 were downregulated. The upregulated DEGs were enriched in biological processes related to transcription regulation and molecular functions such as DNA binding, cell cycle, and the FoxO signaling pathway. Ctnnb1 protein had the highest connectivity degrees in the PPI network. The in vivo studies also validated that mRNA and protein levels of Ctnnb1 were upregulated in both L4 and L5 DRGs. This study provides insight into the functional gene sets and pathways associated with neuropathic pain in L4 uninjured DRG after L5 SNL, which might promote our understanding of the molecular mechanisms underlying the development of neuropathic pain.

Effect of long-term proton pump inhibitor administration on gastric mucosal atrophy: A meta-analysis

PubMed Central

Li, Zhong; Wu, Cong; Li, Ling; Wang, Zhaoming; Xie, Haibin; He, Xiaozhou; Feng, Jin

2017-01-01

Background/Aims: Proton pump inhibitors (PPIs) are widely used for the treatment of acid-related gastrointestinal diseases. Recently, some studies have reported that PPIs can alter the gastric mucosal architecture; however, the relationship remains controversial. This meta-analysis study was designed to quantify the association between long-term PPI administration and gastric atrophy. Materials and Methods: A PubMed search was conducted to identify studies using the keywords proton pump inhibitors or PPI and gastric atrophy or atrophic gastritis; the timeframe of publication searched was up to May 2016. Heterogeneity among studies was tested with the Q test; odds ratios (OR) and 95% confidence intervals (CI) were calculated. P values were calculated by I2 tests and regarded as statistically significant when <0.05. Results: We identified 13 studies that included 1465 patients under long-term PPI therapy and 1603 controls, with a total gastric atrophy rate of 14.50%. There was a higher presence of gastric atrophy (15.84%; statistically significant) in PPI group compared to the control group (13.29%) (OR: 1.55, 95% CI: 1.00–2.41). Conclusions: The pooled data suggest that long-term PPI use is associated with increased rates of gastric atrophy. Large-scale multicenter studies should be conducted to further investigate the relationship between acid suppressants and precancerous diseases. PMID:28721975

Visible light photoelectrochemical aptasensor for adenosine detection based on CdS/PPy/g-C3N4 nanocomposites.

PubMed

Liu, Yixin; Ma, Hongmin; Zhang, Yong; Pang, Xuehui; Fan, Dawei; Wu, Dan; Wei, Qin

2016-12-15

In this work, a label-free photoelectrochemical (PEC) aptasensor was developed for adenosine detection based on CdS/PPy/g-C3N4 nanocomposites. The CdS/g-C3N4 heterojunction effectively prevented the photogenerated charges recombination of g-C3N4 and self-photocorrosion processes of CdS, improving photo-to-current conversion efficiency. The introduced polypyrrole (PPy) nanoparticles could lead to a more effective separation of photogenerated charges, thus resulting in a further increasing of photocurrent. The CdS/PPy/g-C3N4 was firstly employed as the photoactive materials for fabrication of aptasensor, and SH-aptamer was then adsorbed on the CdS/PPy/g-C3N4 modified electrodes through S-Cd bond. With increasing of adenosine concentration, the photocurrent decreased as the formation of SH-aptamer-adenosine bioaffinity complexes. Under optimal conditions, the PEC aptasensor had a sensitive response to adenosine in a linear range of 0.3nmolL(-1) to 200nmolL(-1) with a detection limit of 0.1nmolL(-1). Besides, the as-proposed aptasensor has also been applied in human serum samples analysis. The aptasensor exhibits high sensitivity and good stability, thus opening up a new promising PEC platform for some other small molecules analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

Efficacy and Safety of Proton Pump Inhibitors in the Long-Term Aspirin Users: A Meta-Analysis of Randomized Controlled Trials.

PubMed

Dahal, Khagendra; Sharma, Sharan P; Kaur, Jaspreet; Anderson, Billie J; Singh, Gurpinder

Long-term aspirin use in cardiovascular disease prevention may result in gastrointestinal bleeding. Although proton pump inhibitors (PPI) have been shown to reduce the risks of peptic ulcers and dyspeptic symptoms in long-term aspirin users in the randomized controlled trials, there are safety concerns about the long-term use of PPI. What is the safety and efficacy of PPI in patients using aspirin in long term for prevention of cardiovascular diseases and stroke? We searched MEDLINE, EMBASE, CENTRAL, CINAHL, ProQuest, and relevant references from inception through February 2015, and used random-effects model for meta-analysis. A total of 10 publications from 9 studies (n = 6382) were included in the meta-analysis. Compared with control, PPI reduced the risks of peptic ulcers [risk ratio (RR): 0.19; 95% confidence interval: 0.13-0.26; P < 0.00001], gastric ulcers [0.24 (0.16-0.35); P < 0.00001], duodenal ulcers [0.12 (0.05-0.29); P < 0.00001], bleeding ulcers [0.22 (0.10-0.51); P = 0.0004], and erosive esophagitis [0.14 (0.07-0.28); P < 0.00001]. PPI increased the resolution of epigastric pain [1.13 (1.03-1.25); P = 0.01], heartburn [1.24 (1.18-1.31); P < 0.00001], and regurgitation [1.26 (1.13-1.40); P < 0.0001], but did not increase the risks of all-cause mortality [1.72 (0.61-4.87); P = 0.31], cardiovascular mortality [1.80 (0.59-5.44); P = 0.30], nonfatal myocardial infarction/ischemia [0.56 (0.22-1.41); P = 0.22], ischemic stroke/transient ischemic attack [1.09 (0.34-3.53); P = 0.89] and other adverse events. The PPI seems to be effective in preventing peptic ulcers and erosive esophagitis and in resolution of dyspeptic symptoms without increasing adverse events, cardiac risks or mortality in long-term aspirin users.

A cost-effectiveness analysis of celecoxib compared with diclofenac in the treatment of pain in osteoarthritis (OA) within the Swedish health system using an adaptation of the NICE OA model.

PubMed

Brereton, Nicholas; Pennington, Becky; Ekelund, Mats; Akehurst, Ronald

2014-09-01

Celecoxib for the treatment of pain resulting from osteoarthritis (OA) was reviewed by the Tandvårds- och läkemedelsförmånsverket-Dental and Pharmaceutical Benefits Board (TLV) in Sweden in late 2010. This study aimed to evaluate the incremental cost-effectiveness ratio (ICER) of celecoxib plus a proton pump inhibitor (PPI) compared to diclofenac plus a PPI in a Swedish setting. The National Institute for Health and Care Excellence (NICE) in the UK developed a health economic model as part of their 2008 assessment of treatments for OA. In this analysis, the model was reconstructed and adapted to a Swedish perspective. Drug costs were updated using the TLV database. Adverse event costs were calculated using the regional price list of Southern Sweden and the standard treatment guidelines from the county council of Stockholm. Costs for treating cardiovascular (CV) events were taken from the Swedish DRG codes and the literature. Over a patient's lifetime treatment with celecoxib plus a PPI was associated with a quality-adjusted life year (QALY) gain of 0.006 per patient when compared to diclofenac plus a PPI. There was an increase in discounted costs of 529 kr per patient, which resulted in an incremental cost-effectiveness ratio (ICER) of 82,313 kr ($12,141). Sensitivity analysis showed that treatment was more cost effective in patients with an increased risk of bleeding or gastrointestinal (GI) complications. The results suggest that celecoxib plus a PPI is a cost effective treatment for OA when compared to diclofenac plus a PPI. Treatment is shown to be more cost effective in Sweden for patients with a high risk of bleeding or GI complications. It was in this population that the TLV gave a positive recommendation. There are known limitations on efficacy in the original NICE model.

The Association between the Use of Proton Pump Inhibitors and the Risk of Hypomagnesemia: A Systematic Review and Meta-Analysis

PubMed Central

Park, Chan Hyuk; Kim, Eun Hye; Roh, Yun Ho; Kim, Ha Yan; Lee, Sang Kil

2014-01-01

Background Although many case reports have described patients with proton pump inhibitor (PPI)-induced hypomagnesemia, the impact of PPI use on hypomagnesemia has not been fully clarified through comparative studies. We aimed to evaluate the association between the use of PPI and the risk of developing hypomagnesemia by conducting a systematic review with meta-analysis. Methods We conducted a systematic search of MEDLINE, EMBASE, and the Cochrane Library using the primary keywords “proton pump,” “dexlansoprazole,” “esomeprazole,” “ilaprazole,” “lansoprazole,” “omeprazole,” “pantoprazole,” “rabeprazole,” “hypomagnesemia,” “hypomagnesaemia,” and “magnesium.” Studies were included if they evaluated the association between PPI use and hypomagnesemia and reported relative risks or odds ratios or provided data for their estimation. Pooled odds ratios with 95% confidence intervals were calculated using the random effects model. Statistical heterogeneity was assessed with Cochran’s Q test and I 2 statistics. Results Nine studies including 115,455 patients were analyzed. The median Newcastle-Ottawa quality score for the included studies was seven (range, 6–9). Among patients taking PPIs, the median proportion of patients with hypomagnesemia was 27.1% (range, 11.3–55.2%) across all included studies. Among patients not taking PPIs, the median proportion of patients with hypomagnesemia was 18.4% (range, 4.3–52.7%). On meta-analysis, pooled odds ratio for PPI use was found to be 1.775 (95% confidence interval 1.077–2.924). Significant heterogeneity was identified using Cochran’s Q test (df = 7, P<0.001, I 2 = 98.0%). Conclusions PPI use may increase the risk of hypomagnesemia. However, significant heterogeneity among the included studies prevented us from reaching a definitive conclusion. PMID:25394217

Integrated analysis of long noncoding RNA and mRNA expression profile in children with obesity by microarray analysis.

PubMed

Liu, Yuesheng; Ji, Yuqiang; Li, Min; Wang, Min; Yi, Xiaoqing; Yin, Chunyan; Wang, Sisi; Zhang, Meizhen; Zhao, Zhao; Xiao, Yanfeng

2018-06-08

Long noncoding RNAs (lncRNAs) have an important role in adipose tissue function and energy metabolism homeostasis, and abnormalities may lead to obesity. To investigate whether lncRNAs are involved in childhood obesity, we investigated the differential expression profile of lncRNAs in obese children compared with non-obese children. A total number of 1268 differentially expressed lncRNAs and 1085 differentially expressed mRNAs were identified. Gene Ontology (GO) and pathway analysis revealed that these lncRNAs were involved in varied biological processes, including the inflammatory response, lipid metabolic process, osteoclast differentiation and fatty acid metabolism. In addition, the lncRNA-mRNA co-expression network and the protein-protein interaction (PPI) network were constructed to identify hub regulatory lncRNAs and genes based on the microarray expression profiles. This study for the first time identifies an expression profile of differentially expressed lncRNAs in obese children and indicated hub lncRNA RP11-20G13.3 attenuated adipogenesis of preadipocytes, which is conducive to the search for new diagnostic and therapeutic strategies of childhood obesity.

The Arabidopsis ppi1 Mutant Is Specifically Defective in the Expression, Chloroplast Import, and Accumulation of Photosynthetic ProteinsW⃞

PubMed Central

Kubis, Sybille; Baldwin, Amy; Patel, Ramesh; Razzaq, Azam; Dupree, Paul; Lilley, Kathryn; Kurth, Joachim; Leister, Dario; Jarvis, Paul

2003-01-01

The import of nucleus-encoded proteins into chloroplasts is mediated by translocon complexes in the envelope membranes. A component of the translocon in the outer envelope membrane, Toc34, is encoded in Arabidopsis by two homologous genes, atTOC33 and atTOC34. Whereas atTOC34 displays relatively uniform expression throughout development, atTOC33 is strongly upregulated in rapidly growing, photosynthetic tissues. To understand the reason for the existence of these two related genes, we characterized the atTOC33 knockout mutant ppi1. Immunoblotting and proteomics revealed that components of the photosynthetic apparatus are deficient in ppi1 chloroplasts and that nonphotosynthetic chloroplast proteins are unchanged or enriched slightly. Furthermore, DNA array analysis of 3292 transcripts revealed that photosynthetic genes are moderately, but specifically, downregulated in ppi1. Proteome differences in ppi1 could be correlated with protein import rates: ppi1 chloroplasts imported the ribulose-1,5-bisphosphate carboxylase/oxygenase small subunit and 33-kD oxygen-evolving complex precursors at significantly reduced rates, but the import of a 50S ribosomal subunit precursor was largely unaffected. The ppi1 import defect occurred at the level of preprotein binding, which is consistent with a role for atToc33 during preprotein recognition. The data suggest that atToc33 is involved preferentially in the import of photosynthetic proteins and, by extension, that atToc34 is involved in the import of nonphotosynthetic chloroplast proteins. PMID:12897258

What do pharmaceutical industry professionals in Europe believe about involving patients and the public in research and development of medicines? A qualitative interview study

PubMed Central

Parsons, Suzanne; Starling, Bella; Mullan-Jensen, Christine; Warner, Kay; Wever, Kim

2016-01-01

Objectives To explore European-based pharmaceutical industry professionals’ beliefs about patient and public involvement (PPI) in medicines research and development (R&D). Setting Pharmaceutical companies in the UK, Poland and Spain. Participants 21 pharmaceutical industry professionals, four based in the UK, five with pan-European roles, four based in Spain and eight based in Poland. Method Qualitative interview study (telephone and face-to-face, semistructured interviews). All interviews were audio taped, translated (where appropriate) and transcribed for analysis using the Framework approach. Results 21 pharmaceutical industry professionals participated. Key themes were: beliefs about (1) whether patients and the public should be involved in medicines R&D; (2) the barriers and facilitators to PPI in medicines R&D and (3) how the current relationships between the pharmaceutical industry, patient organisations and patients influence PPI in medicines R&D. Conclusions Although interviewees appeared positive about PPI, many were uncertain about when, how and which patients to involve. Patients and the public's lack of knowledge and interest in medicines R&D, and the pharmaceutical industry's lack of knowledge, interest and receptivity to PPI were believed to be key challenges to increasing PPI. Interviewees also believed that relationships between the pharmaceutical industry, patient organisations, patients and the public needed to change to facilitate PPI in medicines R&D. Existing pharmaceutical industry codes of practice and negative media reporting of the pharmaceutical industry were also seen as negative influences on these relationships. PMID:26743701

The extent, quality and impact of patient and public involvement in primary care research: a mixed methods study.

PubMed

Blackburn, Steven; McLachlan, Sarah; Jowett, Sue; Kinghorn, Philip; Gill, Paramjit; Higginbottom, Adele; Rhodes, Carol; Stevenson, Fiona; Jinks, Clare

2018-01-01

In the UK, more patients go to primary care than other parts of the health service. Therefore it is important for research into primary care to include the insights and views of people who receive these services. To explore the extent, quality and impact of patient and public involvement (PPI) in primary care research, we examined documents of 200 projects and surveyed 191 researchers.We found that about half of studies included PPI to develop research ideas and during the study itself. Common activities included designing study materials, advising on methods, and managing the research. Some studies did not undertake the PPI activities initially planned and funded for. PPI varied by study design, health condition and study population. We found pockets of good practice: having a PPI budget, supporting PPI contributors, and PPI informing recruitment issues. However, good practice was lacking in other areas. Few projects offered PPI contributors training, used PPI to develop information for participants about study progress and included PPI to advise on publishing findings.Researchers reported beneficial impacts of PPI. Most impact was reported when the approach to PPI included more indicators of good practice. The main cost of PPI for researchers was their time. Many reported difficulties providing information about PPI.In partnership with PPI contributors, we have used these findings to develop:a new Cost and Consequences Framework for PPI highlighting financial and non-financial costs, benefits and harms of PPIFifteen co-produced recommendations to improve the practice and delivery of PPI. Background: To improve the lives of patients in primary care requires the involvement of service users in primary care research. We aimed to explore the extent, quality and impact of patient and public involvement (PPI) in primary care research. Methods: We extracted information about PPI from grant applications, reports and an electronic survey of researchers of studies funded by the NIHR School for Primary Care Research (SPCR). We applied recognised quality indicators to assess the quality of PPI and assessed its impact on research. Results: We examined 200 grant applications and reports of 181 projects. PPI was evident in the development of 47 (24%) grant applications. 113 (57%) grant applications included plans for PPI during the study, mostly in study design, oversight, and dissemination. PPI during projects was reported for 83 (46%) projects, including designing study materials and managing the research. We identified inconsistencies between planned and reported PPI. PPI varied by study design, health condition and study population.Of 46 (24%) of 191 questionnaires completed, 15 reported PPI activity. Several projects showed best practice according to guidelines, in terms of having a PPI budget, supporting PPI contributors, and PPI informing recruitment issues. However few projects offered PPI contributors training, used PPI to develop information for participants about study progress, and had PPI in advising on dissemination.Beneficial impacts of PPI in designing studies and writing participant information was frequently reported. Less impact was reported on developing funding applications, managing or carrying out the research. The main cost of PPI for researchers was their time. Many researchers found it difficult to provide information about PPI activities.Our findings informed:a new Cost and Consequences Framework for PPI in primary care research highlighting financial and non-financial costs, plus the benefits and harms of PPIFifteen co-produced recommendations to improve PPI in research and within the SPCR. Conclusions: The extent, quality and impact of PPI in primary care research is inconsistent across research design and topics. Pockets of good practice were identified making a positive impact on research. The new Cost and Consequences Framework may help others assess the impact of PPI.

Polypyrrole electrodes doped with sulfanilic acid azochromotrop for electrochemical supercapacitors

NASA Astrophysics Data System (ADS)

Chen, S.; Zhitomirsky, I.

2013-12-01

In this work we demonstrate the feasibility of deposition of polypyrrole (PPy) films by electropolymerization on stainless steel substrates and fabrication of PPy powders by chemical polymerization using sulfanilic acid azochromotrop (SPADNS) as a new anionic dopant. The problem of low adhesion of PPy films to stainless steel substrates is addressed by the use of SPADNS, which exhibits chelating properties, promoting film formation. The use of fine particles, prepared by the chemical polymerization method, allows impregnation of Ni foams and fabrication of porous electrodes with high materials loading for electrochemical supercapacitors (ES). PPy films and Ni foam based PPy electrodes show capacitive behaviour in Na2SO4 electrolyte. The electron microscopy studies, impedance spectroscopy data and analysis of the SPADNS structure provide an insight into the factors, controlling capacitive behaviour. The Ni foam based electrodes offer advantages of improved capacitive behaviour at high materials loadings and good cycling stability. The area normalized and volume normalized specific capacitances are as high as 5.43 F cm-2 and 93.6 F cm-3, respectively, for materials loading of 35.4 mg cm-2. The capacitance retention of Ni foam based electrodes is 91.5% after 1000 cycles. The Ni foam based PPy electrodes are promising for application in ES.

Efficacy of Vonoprazan for Gastroesophageal Reflux Symptoms in Patients with Proton Pump Inhibitor-resistant Non-erosive Reflux Disease.

PubMed

Niikura, Ryota; Yamada, Atsuo; Hirata, Yoshihiro; Hayakawa, Yoku; Takahashi, Akihiro; Shinozaki, Tomohiro; Takeuchi, Yoshinori; Fujishiro, Mitsuhiro; Koike, Kazuhiko

2018-03-30

Objective Clinically, patients with proton pomp inhibitor (PPI)-resistant gastro-esophageal reflux disease (GERD) are very challenging to treat. The aim of this study was to determine the rates of symptom relief and adverse events among PPI-resistant GERD patients that changed their therapy from a PPI to vonoprazan. Methods Patients with severe gastroesophageal reflux symptoms (total GERD-Q score ≥8) without endoscopic findings of mucosal breaks who changed their medication from a PPI to vonoprazan during a 12-week period from 2015 to 2016 at 2 hospitals were selected. The primary outcome was the self-reported relief of gastroesophageal reflux symptoms. The odds ratio (OR) for the improvement of symptoms was calculated based on an exact binomial distribution using a matched-pair analysis. The secondary outcome was the GERD-Q score and adverse events. Results Twenty-six patients (6 men) with a mean age of 67.5 years were analyzed. After the therapy was changed from a PPI to vonoprazan, 18 patients (69.2%) reported an improvement, 6 (23.1%) reported no change, and 2 (7.7%) reported an exacerbation of symptoms. A change in therapy was significantly associated with improved self-reported symptoms (OR 9.0, p<0.001). The mean total GERD-Q score during vonoprazan treatment was significantly lower than that during PPI therapy (11.96 vs. 8.92). There were no significant differences in the incidence of adverse events between the therapies. Conclusion Changing the medication from a PPI to vonoprazan was significantly associated with an improvement in gastroesophageal reflux symptoms. Vonoprazan is one of the most promising treatment options for patients with PPI-resistant GERD.

Why Are Men Satisfied or Dissatisfied with Penile Implants? A Mixed Method Study on Satisfaction with Penile Prosthesis Implantation.

PubMed

Carvalheira, Ana; Santana, Rita; Pereira, Nuno M

2015-12-01

Studies have demonstrated high levels of satisfaction with penile prosthesis implantation (PPI). However, qualitative research exploring the experience of PPI through men's narratives is scarce. The main goals were to analyze (i) the level of sexual satisfaction (quantitatively), and (ii) the reasons for satisfaction and/or dissatisfaction with PPI (qualitatively). Participants were 47 men with erectile dysfunction who underwent surgery between 2003 and 2012, placed by a single surgeon. Structured telephone interviews were carried out. Satisfaction with PPI was a qualitative and quantitative measure assessed through the following four items: (i) "Would you repeat the PPI surgery?"; (ii) "Would you recommend the PPI surgery?"; (iii) "How satisfied are you with the PP?"; and (iv) "Could you explain the motives of your satisfaction/dissatisfaction?". The majority of men (79%) reported to be satisfied with PPI. Content analysis revealed four main themes for men's satisfaction with the PPI: (i) psychological factors were reported 54 times (n = 54) and included positive emotions, self-esteem, confidence, enhancement of male identity, major live change, and self-image; (ii) improvement of sexual function was reported 54 times (n = 54) and referred to achievement of vaginal penetration, increase of sexual desire, sexual satisfaction, penis size, and improvement of erectile function; (iii) relationship factors were reported 11 times (n = 11) and referred to relationship improvement and the possibility of giving pleasure to the partner; and (iv) improvement in urinary function (n = 3). The level of satisfaction with the implementation of penile prostheses is very high, therefore constituting a treatment for erectile dysfunction with a positive impact on the experience of men at sexual, psychological and relational level. © 2015 International Society for Sexual Medicine.

Recovery of biological motion perception and network plasticity after cerebellar tumor removal.

PubMed

Sokolov, Arseny A; Erb, Michael; Grodd, Wolfgang; Tatagiba, Marcos S; Frackowiak, Richard S J; Pavlova, Marina A

2014-10-01

Visual perception of body motion is vital for everyday activities such as social interaction, motor learning or car driving. Tumors to the left lateral cerebellum impair visual perception of body motion. However, compensatory potential after cerebellar damage and underlying neural mechanisms remain unknown. In the present study, visual sensitivity to point-light body motion was psychophysically assessed in patient SL with dysplastic gangliocytoma (Lhermitte-Duclos disease) to the left cerebellum before and after neurosurgery, and in a group of healthy matched controls. Brain activity during processing of body motion was assessed by functional magnetic resonance imaging (MRI). Alterations in underlying cerebro-cerebellar circuitry were studied by psychophysiological interaction (PPI) analysis. Visual sensitivity to body motion in patient SL before neurosurgery was substantially lower than in controls, with significant improvement after neurosurgery. Functional MRI in patient SL revealed a similar pattern of cerebellar activation during biological motion processing as in healthy participants, but located more medially, in the left cerebellar lobules III and IX. As in normalcy, PPI analysis showed cerebellar communication with a region in the superior temporal sulcus, but located more anteriorly. The findings demonstrate a potential for recovery of visual body motion processing after cerebellar damage, likely mediated by topographic shifts within the corresponding cerebro-cerebellar circuitry induced by cerebellar reorganization. The outcome is of importance for further understanding of cerebellar plasticity and neural circuits underpinning visual social cognition.

Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

PubMed

Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

2015-06-01

To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

Synthesis and property of novel MnO2@polypyrrole coaxial nanotubes as electrode material for supercapacitors

NASA Astrophysics Data System (ADS)

Yao, Wei; Zhou, Hui; Lu, Yun

2013-11-01

Novel MnO2@polypyrrole (PPy) coaxial nanotubes have been prepared via a simple and green approach without any surfactant and additional oxidant. Under the acidic condition, MnO2 nanotubes act as both template and oxidant to initiate the polymerization of pyrrole monomers on its fresh-activated surface. Fourier transform infrared spectra (FT-IR), X-ray diffraction patterns (XRD), thermo-gravimetric analysis data (TG) and X-ray photoelectron spectra (XPS) suggest the formation of composite structure of MnO2@PPy. Also, FESEM and TEM images intuitively confirm that the PPy shell is coated uniformly on the surface of MnO2 nanotubes. Adjusting the concentrations of sulfuric acid or adding oxidant can modulate the morphology of the products accordingly. Due to the synergic effect between MnO2 core and PPy shell, the MnO2@PPy coaxial nanotubes possess better rate capability, larger specific capacitance of 380 F g-1, doubling the specific capacitance of MnO2 nanotubes, and good capacitance retention of 90% for its initial capacitance after 1000 cycles.

Biomaterials functionalization using a novel peptide that selectively binds to a conducting polymer

NASA Astrophysics Data System (ADS)

Sanghvi, Archit B.; Miller, Kiley P.-H.; Belcher, Angela M.; Schmidt, Christine E.

2005-06-01

The goal in biomaterial surface modification is to retain a material's bulk properties while modifying only its surface to possess desired recognition and specificity. Here we develop a unique strategy for surface functionalization of an electrically conductive polymer, chlorine-doped polypyrrole (PPyCl), which has been widely researched for various electronic and biomedical applications. An M13 bacteriophage library was used to screen 109 different 12-mer peptide inserts against PPyCl. A binding phage (ϕT59) was isolated, and its binding stability and specificity to PPyCl was assessed using fluorescence microscopy and titer count analysis. The relative binding strength and mechanism of the corresponding 12-mer peptide and its variants was studied using atomic force microscopy and fluorescamine assays. Further, the T59 peptide was joined to a cell adhesive sequence and used to promote cell attachment on PPyCl. This strategy can be extended to immobilize a variety of molecules to PPyCl for numerous applications. In addition, phage display can be applied to other polymers to develop bioactive materials without altering their bulk properties.

Antihypertensive Properties of a Pea Protein Hydrolysate during Short- and Long-Term Oral Administration to Spontaneously Hypertensive Rats.

PubMed

Girgih, Abraham T; Nwachukwu, Ifeanyi D; Onuh, John O; Malomo, Sunday A; Aluko, Rotimi E

2016-05-01

This study investigated short-term (24 h) and long-term (5 wk) systolic blood pressure (SBP)-lowering effects in spontaneously hypertensive rats (SHR) of a 5 kDa membrane pea protein hydrolysate permeate (PPH-5) produced through thermoase hydrolysis of pea protein isolate (PPI). Amino acid analysis showed that the PPH-5 had lower contents of sulfur-containing amino acids than the PPI. Size-exclusion chromatography indicated mainly low molecular weight (<10 kDa) peptides in PPH-5 but not in the PPI. The PPH-5 had renin and angiotensin converting enzyme inhibition IC50 values of 0.57 and 0.10 mg/mL (P < 0.05), respectively, and consisted mainly of peptides with 2 to 6 amino acids. Mass spectrometry analysis revealed mainly hydrophilic tetrapeptide sequences. After a single oral administration (100 mg/kg body weight) to SHR, the unheated PPI showed weakest (P < 0.05) SBP-lowering effect with a -4 mm Hg maximum when compared to -25 mm Hg for heat-treated PPI and -36 mm Hg for PPH-5. Incorporation of the PPH-5 as 0.5% or 1% (w/w) casein substitute in the SHR diet produced maximum SBP reductions of -22 or -26 mm Hg (P < 0.05), respectively after 3 wk. In comparison, the unhydrolyzed PPI produced a maximum SBP reduction of -17 mm Hg also after 3 wk. Potency of the pea products decreased in the 4th and 5th wk, though SBP values of the treated rats were still lower than the untreated control. We conclude that the antihypertensive potency of PPH-5 may have been due to the presence of easily absorbed hydrophilic peptides. © 2016 Institute of Food Technologists®

Finding Correlation between Protein Protein Interaction Modules Using Semantic Web Techniques

NASA Astrophysics Data System (ADS)

Kargar, Mehdi; Moaven, Shahrouz; Abolhassani, Hassan

Many complex networks such as social networks and computer show modular structures, where edges between nodes are much denser within modules than between modules. It is strongly believed that cellular networks are also modular, reflecting the relative independence and coherence of different functional units in a cell. In this paper we used a human curated dataset. In this paper we consider each module in the PPI network as ontology. Using techniques in ontology alignment, we compare each pair of modules in the network. We want to see that is there a correlation between the structure of each module or they have totally different structures. Our results show that there is no correlation between proteins in a protein protein interaction network.

Dynamic Changes in Amygdala Psychophysiological Connectivity Reveal Distinct Neural Networks for Facial Expressions of Basic Emotions.

PubMed

Diano, Matteo; Tamietto, Marco; Celeghin, Alessia; Weiskrantz, Lawrence; Tatu, Mona-Karina; Bagnis, Arianna; Duca, Sergio; Geminiani, Giuliano; Cauda, Franco; Costa, Tommaso

2017-03-27

The quest to characterize the neural signature distinctive of different basic emotions has recently come under renewed scrutiny. Here we investigated whether facial expressions of different basic emotions modulate the functional connectivity of the amygdala with the rest of the brain. To this end, we presented seventeen healthy participants (8 females) with facial expressions of anger, disgust, fear, happiness, sadness and emotional neutrality and analyzed amygdala's psychophysiological interaction (PPI). In fact, PPI can reveal how inter-regional amygdala communications change dynamically depending on perception of various emotional expressions to recruit different brain networks, compared to the functional interactions it entertains during perception of neutral expressions. We found that for each emotion the amygdala recruited a distinctive and spatially distributed set of structures to interact with. These changes in amygdala connectional patters characterize the dynamic signature prototypical of individual emotion processing, and seemingly represent a neural mechanism that serves to implement the distinctive influence that each emotion exerts on perceptual, cognitive, and motor responses. Besides these differences, all emotions enhanced amygdala functional integration with premotor cortices compared to neutral faces. The present findings thus concur to reconceptualise the structure-function relation between brain-emotion from the traditional one-to-one mapping toward a network-based and dynamic perspective.

A Framework of Knowledge Integration and Discovery for Supporting Pharmacogenomics Target Predication of Adverse Drug Events: A Case Study of Drug-Induced Long QT Syndrome.

PubMed

Jiang, Guoqian; Wang, Chen; Zhu, Qian; Chute, Christopher G

2013-01-01

Knowledge-driven text mining is becoming an important research area for identifying pharmacogenomics target genes. However, few of such studies have been focused on the pharmacogenomics targets of adverse drug events (ADEs). The objective of the present study is to build a framework of knowledge integration and discovery that aims to support pharmacogenomics target predication of ADEs. We integrate a semantically annotated literature corpus Semantic MEDLINE with a semantically coded ADE knowledgebase known as ADEpedia using a semantic web based framework. We developed a knowledge discovery approach combining a network analysis of a protein-protein interaction (PPI) network and a gene functional classification approach. We performed a case study of drug-induced long QT syndrome for demonstrating the usefulness of the framework in predicting potential pharmacogenomics targets of ADEs.

Development and application of a recombination-based library versus library high- throughput yeast two-hybrid (RLL-Y2H) screening system.

PubMed

Yang, Fang; Lei, Yingying; Zhou, Meiling; Yao, Qili; Han, Yichao; Wu, Xiang; Zhong, Wanshun; Zhu, Chenghang; Xu, Weize; Tao, Ran; Chen, Xi; Lin, Da; Rahman, Khaista; Tyagi, Rohit; Habib, Zeshan; Xiao, Shaobo; Wang, Dang; Yu, Yang; Chen, Huanchun; Fu, Zhenfang; Cao, Gang

2018-02-16

Protein-protein interaction (PPI) network maintains proper function of all organisms. Simple high-throughput technologies are desperately needed to delineate the landscape of PPI networks. While recent state-of-the-art yeast two-hybrid (Y2H) systems improved screening efficiency, either individual colony isolation, library preparation arrays, gene barcoding or massive sequencing are still required. Here, we developed a recombination-based 'library vs library' Y2H system (RLL-Y2H), by which multi-library screening can be accomplished in a single pool without any individual treatment. This system is based on the phiC31 integrase-mediated integration between bait and prey plasmids. The integrated fragments were digested by MmeI and subjected to deep sequencing to decode the interaction matrix. We applied this system to decipher the trans-kingdom interactome between Mycobacterium tuberculosis and host cells and further identified Rv2427c interfering with the phagosome-lysosome fusion. This concept can also be applied to other systems to screen protein-RNA and protein-DNA interactions and delineate signaling landscape in cells.

Up-regulated expression of cartilage intermediate-layer protein and ANK in articular hyaline cartilage from patients with calcium pyrophosphate dihydrate crystal deposition disease.

PubMed

Hirose, Jun; Ryan, Lawrence M; Masuda, Ikuko

2002-12-01

Excess accumulation of extracellular inorganic pyrophosphate (ePPi) in aged human cartilage is crucial in calcium pyrophosphate dihydrate (CPPD) crystal formation in cartilage matrix. Two sources of ePPi are ePPi-generating ectoenzymes (NTPPPH) and extracellular transport of intracellular PPi by ANK. This study was undertaken to evaluate the role of NTPPPH and ANK in ePPi elaboration, by investigating expression of NTPPPH enzymes (cartilage intermediate-layer protein [CILP] and plasma cell membrane glycoprotein 1 [PC-1]) and ANK in human chondrocytes from osteoarthritic (OA) articular cartilage containing CPPD crystals and without crystals. Chondrocytes were harvested from knee cartilage at the time of arthroplasty (OA with CPPD crystals [CPPD], n = 8; OA without crystals [OA], n = 10). Normal adult human chondrocytes (n = 1) were used as a control. Chondrocytes were cultured with transforming growth factor beta1 (TGFbeta1), which stimulates ePPi elaboration, and/or insulin-like growth factor 1 (IGF-1), which inhibits ePPi elaboration. NTPPPH and ePPi were measured in the media at 48 hours. Media CILP, PC-1, and ANK were determined by dot-immunoblot analysis. Chondrocyte messenger RNA (mRNA) was extracted for reverse transcriptase-polymerase chain reaction to study expression of mRNA for CILP, PC-1, and ANK. NTPPPH and ANK mRNA and protein were also studied in fresh frozen cartilage. Basal ePPi elaboration and NTPPPH activity in conditioned media from CPPD chondrocytes were elevated compared with normal chondrocytes, and tended to be higher compared with OA chondrocytes. Basal expression of mRNA for CILP (chondrocytes) and ANK (cartilage) was higher in both CPPD chondrocytes and CPPD cartilage extract than in OA or normal samples. PC-1 mRNA was less abundant in CPPD chondrocytes and cartilage extract than in OA chondrocytes and extract, although the difference was not significant. CILP, PC-1, and ANK protein levels were similar in CPPD, OA, and normal chondrocytes or cartilage extracts. Both CILP and ANK mRNA expression and ePPi elaboration were stimulated by TGFbeta1 and inhibited by IGF-1 in chondrocytes from all sources. CILP and ANK mRNA expression correlates with chondrocyte ePPi accumulation around CPPD and OA chondrocytes, and all respond similarly to growth factor stimulation. These findings suggest that up-regulated CILP and ANK expression contributes to higher ePPi accumulation from CPPD crystal-forming cartilage.

Changes in connectivity of the posterior default network node during visual processing in mild cognitive impairment: staged decline between normal aging and Alzheimer's disease.

PubMed

Krajcovicova, Lenka; Barton, Marek; Elfmarkova-Nemcova, Nela; Mikl, Michal; Marecek, Radek; Rektorova, Irena

2017-12-01

Visual processing difficulties are often present in Alzheimer's disease (AD), even in its pre-dementia phase (i.e. in mild cognitive impairment, MCI). The default mode network (DMN) modulates the brain connectivity depending on the specific cognitive demand, including visual processes. The aim of the present study was to analyze specific changes in connectivity of the posterior DMN node (i.e. the posterior cingulate cortex and precuneus, PCC/P) associated with visual processing in 17 MCI patients and 15 AD patients as compared to 18 healthy controls (HC) using functional magnetic resonance imaging. We used psychophysiological interaction (PPI) analysis to detect specific alterations in PCC connectivity associated with visual processing while controlling for brain atrophy. In the HC group, we observed physiological changes in PCC connectivity in ventral visual stream areas and with PCC/P during the visual task, reflecting the successful involvement of these regions in visual processing. In the MCI group, the PCC connectivity changes were disturbed and remained significant only with the anterior precuneus. In between-group comparison, we observed significant PPI effects in the right superior temporal gyrus in both MCI and AD as compared to HC. This change in connectivity may reflect ineffective "compensatory" mechanism present in the early pre-dementia stages of AD or abnormal modulation of brain connectivity due to the disease pathology. With the disease progression, these changes become more evident but less efficient in terms of compensation. This approach can separate the MCI from HC with 77% sensitivity and 89% specificity.

Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise

PubMed Central

Correia, Catarina; Oliveira, Guiomar; Vicente, Astrid M.

2014-01-01

Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical “noise” that warrant further analysis for causal variants. PMID:25409314

Protein interaction networks reveal novel autism risk genes within GWAS statistical noise.

PubMed

Correia, Catarina; Oliveira, Guiomar; Vicente, Astrid M

2014-01-01

Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical "noise" that warrant further analysis for causal variants.

Assembling a protein-protein interaction map of the SSU processome from existing datasets.

PubMed

Lim, Young H; Charette, J Michael; Baserga, Susan J

2011-03-10

The small subunit (SSU) processome is a large ribonucleoprotein complex involved in small ribosomal subunit assembly. It consists of the U3 snoRNA and ∼72 proteins. While most of its components have been identified, the protein-protein interactions (PPIs) among them remain largely unknown, and thus the assembly, architecture and function of the SSU processome remains unclear. We queried PPI databases for SSU processome proteins to quantify the degree to which the three genome-wide high-throughput yeast two-hybrid (HT-Y2H) studies, the genome-wide protein fragment complementation assay (PCA) and the literature-curated (LC) datasets cover the SSU processome interactome. We find that coverage of the SSU processome PPI network is remarkably sparse. Two of the three HT-Y2H studies each account for four and six PPIs between only six of the 72 proteins, while the third study accounts for as little as one PPI and two proteins. The PCA dataset has the highest coverage among the genome-wide studies with 27 PPIs between 25 proteins. The LC dataset was the most extensive, accounting for 34 proteins and 38 PPIs, many of which were validated by independent methods, thereby further increasing their reliability. When the collected data were merged, we found that at least 70% of the predicted PPIs have yet to be determined and 26 proteins (36%) have no known partners. Since the SSU processome is conserved in all Eukaryotes, we also queried HT-Y2H datasets from six additional model organisms, but only four orthologues and three previously known interologous interactions were found. This provides a starting point for further work on SSU processome assembly, and spotlights the need for a more complete genome-wide Y2H analysis.

Assembling a Protein-Protein Interaction Map of the SSU Processome from Existing Datasets

PubMed Central

Baserga, Susan J.

2011-01-01

Background The small subunit (SSU) processome is a large ribonucleoprotein complex involved in small ribosomal subunit assembly. It consists of the U3 snoRNA and ∼72 proteins. While most of its components have been identified, the protein-protein interactions (PPIs) among them remain largely unknown, and thus the assembly, architecture and function of the SSU processome remains unclear. Methodology We queried PPI databases for SSU processome proteins to quantify the degree to which the three genome-wide high-throughput yeast two-hybrid (HT-Y2H) studies, the genome-wide protein fragment complementation assay (PCA) and the literature-curated (LC) datasets cover the SSU processome interactome. Conclusions We find that coverage of the SSU processome PPI network is remarkably sparse. Two of the three HT-Y2H studies each account for four and six PPIs between only six of the 72 proteins, while the third study accounts for as little as one PPI and two proteins. The PCA dataset has the highest coverage among the genome-wide studies with 27 PPIs between 25 proteins. The LC dataset was the most extensive, accounting for 34 proteins and 38 PPIs, many of which were validated by independent methods, thereby further increasing their reliability. When the collected data were merged, we found that at least 70% of the predicted PPIs have yet to be determined and 26 proteins (36%) have no known partners. Since the SSU processome is conserved in all Eukaryotes, we also queried HT-Y2H datasets from six additional model organisms, but only four orthologues and three previously known interologous interactions were found. This provides a starting point for further work on SSU processome assembly, and spotlights the need for a more complete genome-wide Y2H analysis. PMID:21423703

Comparison of the human gastric microbiota in hypochlorhydric states arising as a result of Helicobacter pylori-induced atrophic gastritis, autoimmune atrophic gastritis and proton pump inhibitor use

PubMed Central

Eccles, Richard; Duckworth, Carrie A.; Varro, Andrea

2017-01-01

Several conditions associated with reduced gastric acid secretion confer an altered risk of developing a gastric malignancy. Helicobacter pylori-induced atrophic gastritis predisposes to gastric adenocarcinoma, autoimmune atrophic gastritis is a precursor of type I gastric neuroendocrine tumours, whereas proton pump inhibitor (PPI) use does not affect stomach cancer risk. We hypothesised that each of these conditions was associated with specific alterations in the gastric microbiota and that this influenced subsequent tumour risk. 95 patients (in groups representing normal stomach, PPI treated, H. pylori gastritis, H. pylori-induced atrophic gastritis and autoimmune atrophic gastritis) were selected from a cohort of 1400. RNA extracted from gastric corpus biopsies was analysed using 16S rRNA sequencing (MiSeq). Samples from normal stomachs and patients treated with PPIs demonstrated similarly high microbial diversity. Patients with autoimmune atrophic gastritis also exhibited relatively high microbial diversity, but with samples dominated by Streptococcus. H. pylori colonisation was associated with decreased microbial diversity and reduced complexity of co-occurrence networks. H. pylori-induced atrophic gastritis resulted in lower bacterial abundances and diversity, whereas autoimmune atrophic gastritis resulted in greater bacterial abundance and equally high diversity compared to normal stomachs. Pathway analysis suggested that glucose-6-phospahte1-dehydrogenase and D-lactate dehydrogenase were over represented in H. pylori-induced atrophic gastritis versus autoimmune atrophic gastritis, and that both these groups showed increases in fumarate reductase. Autoimmune and H. pylori-induced atrophic gastritis were associated with different gastric microbial profiles. PPI treated patients showed relatively few alterations in the gastric microbiota compared to healthy subjects. PMID:29095917

Different effects of isolation-rearing and neonatal MK-801 treatment on attentional modulations of prepulse inhibition of startle in rats.

PubMed

Wu, Zhe-Meng; Ding, Yu; Jia, Hong-Xiao; Li, Liang

2016-09-01

Prepulse inhibition (PPI) is suppression of the startle reflex by a weaker sensory stimulus (prepulse) preceding the startling stimulus. In people with schizophrenia, impairment of attentional modulation of PPI, but not impairment of baseline PPI, is correlated with symptom severity. In rats, both fear conditioning of prepulse and perceptually spatial separation between the conditioned prepulse and a noise masker enhance PPI (the paradigms of attentional modulation of PPI). As a neurodevelopmental model of schizophrenia, isolation rearing impairs both baseline PPI and attentional modulations of PPI in rats. This study examined in Sprague-Dawley male rats whether neonatally blocking N-methyl-D-aspartate (NMDA) receptors specifically affects attentional modulations of PPI during adulthood. Both socially reared rats with neonatal exposure to the NMDA receptor antagonist MK-801 and isolation-reared rats exhibited augmented startle responses, but only isolation rearing impaired baseline PPI. Fear conditioning of the prepulse enhanced PPI in socially reared rats, but MK-801-treated rats lost the prepulse feature specificity. Perceptually spatial separation between the conditioned prepulse and a noise masker further enhanced PPI only in normally reared rats. Clozapine administration during adulthood generally weakened startle, enhanced baseline PPI in neonatally interrupted rats, and restored the fear conditioning-induced PPI enhancement in isolation-reared rats with a loss of the prepulse feature specificity. Clozapine administration also abolished both the perceptual separation-induced PPI enhancement in normally reared rats and the fear conditioning-induced PPI enhancement in MK-801-treated rats. Isolation rearing impairs both baseline PPI and attentional modulations of PPI, but neonatally disrupting NMDA receptor-mediated transmissions specifically impair attentional modulations of PPI. Clozapine has limited alleviating effects.

Prediction of protein-protein interaction network using a multi-objective optimization approach.

PubMed

Chowdhury, Archana; Rakshit, Pratyusha; Konar, Amit

2016-06-01

Protein-Protein Interactions (PPIs) are very important as they coordinate almost all cellular processes. This paper attempts to formulate PPI prediction problem in a multi-objective optimization framework. The scoring functions for the trial solution deal with simultaneous maximization of functional similarity, strength of the domain interaction profiles, and the number of common neighbors of the proteins predicted to be interacting. The above optimization problem is solved using the proposed Firefly Algorithm with Nondominated Sorting. Experiments undertaken reveal that the proposed PPI prediction technique outperforms existing methods, including gene ontology-based Relative Specific Similarity, multi-domain-based Domain Cohesion Coupling method, domain-based Random Decision Forest method, Bagging with REP Tree, and evolutionary/swarm algorithm-based approaches, with respect to sensitivity, specificity, and F1 score.

Peritoneal delivery of sodium pyrophosphate blocks the progression of pre-existing vascular calcification in uremic apolipoprotein-E knockout mice.

PubMed

de Oliveira, Rodrigo B; Louvet, Loïc; Riser, Bruce L; Barreto, Fellype C; Benchitrit, Joyce; Rezg, Raja; Poirot, Sabrina; Jorgetti, Vanda; Drüeke, Tilman B; Massy, Ziad A

2015-08-01

Chronic kidney disease (CKD) is generally associated with disturbances of mineral and bone metabolism. They contribute to the development of vascular calcification (VC), a strong, independent predictor of cardiovascular risk. Pyrophosphate (PPi), an endogenous inhibitor of hydroxyapatite formation, has been shown to slow the progression of VC in uremic animals. Since in patients with CKD treatment is usually initiated for already existing calcifications, we aimed to compare the efficacy of PPi therapy with that of the phosphate binder sevelamer, using a uremic apolipoprotein-E knockout mouse model with advanced VCs. After CKD creation or sham surgery, 12-week-old female mice were randomized to one sham group and four CKD groups (n = 18-19/group). Treatment was initiated 8 weeks after left nephrectomy allowing prior VC development. Uremic groups received either intraperitoneal PPi (high dose, 1.65 mg/kg or low dose, 0.33 mg/kg per day), oral sevelamer (3 % in diet), or placebo treatment for 8 weeks. Both intima and media calcifications worsened with time in placebo-treated CKD mice, based on both quantitative image analysis and biochemical measurements. Progression of calcification between 8 and 16 weeks was entirely halted by PPi treatment, as it was by sevelamer treatment. PPi did not induce consistent bone histomorphometry changes. Finally, the beneficial vascular action of PPi probably involved mechanisms different from that of sevelamer. Further studies are needed to gain more precise insight into underlying mechanisms and to see whether PPi administration may also be useful in patients with CKD and VC.

Learning to work together - lessons from a reflective analysis of a research project on public involvement.

PubMed

Howe, A; Mathie, E; Munday, D; Cowe, M; Goodman, C; Keenan, J; Kendall, S; Poland, F; Staniszewska, S; Wilson, P

2017-01-01

Patient and public involvement (PPI) in research is very important, and funders and the NHS all expect this to happen. What this means in practice, and how to make it really successful, is therefore an important research question. This article analyses the experience of a research team using PPI, and makes recommendations on strengthening PPI in research. There were different PPI roles in our study - some people were part of the research team: some were on the advisory group; and there were patient groups who gave specific feedback on how to make research work better for their needs. We used minutes, other written documents, and structured individual and group reflections to learn from our own experiences over time. The main findings were:- for researchers and those in a PPI role to work in partnership, project structures must allow flexibility and responsiveness to different people's ideas and needs; a named link person can ensure support; PPI representatives need to feel fully included in the research; make clear what is expected for all roles; and ensure enough time and funding to allow meaningful involvement. Some roles brought more demands but also more rewards than others - highlighting that it is important that people giving up their time to help with research experience gains from doing so. Those contributing to PPI on a regular basis may want to learn new skills, rather than always doing the same things. Researchers and the public need to find ways to develop roles in PPI over time. We also found that, even for a team with expertise in PPI, there was a need both for understanding of different ways to contribute, and an evolving 'normalisation' of new ways of working together over time, which both enriched the process and the outputs. Background Patient and public involvement (PPI) is now an expectation of research funders, in the UK, but there is relatively little published literature on what this means in practice - nor is there much evaluative research about implementation and outputs. Policy literature endorses the need to include PPI representation at all stages of planning, performing and research dissemination, and recommends resource allocation to these roles; but details of how to make such inputs effective in practice are less common. While literature on power and participation informs the debate, there are relatively few published case studies of how this can play out through the lived experience of PPI in research; early findings highlight key issues around access to knowledge, resources, and interpersonal respect. This article describes the findings of a case study of PPI within a study about PPI in research. Methods The aim of the study was to look at how the PPI representatives' inputs had developed over time, key challenges and changes, and lessons learned. We used realist evaluation and normalisation process theory to frame and analyse the data, which was drawn from project documentation, minutes of meetings and workshops, field notes and observations made by PPI representatives and researchers; documented feedback after meetings and activities; and the structured feedback from two formal reflective meetings. Results Key findings included the need for named contacts who support, integrate and work with PPI contributors and researchers, to ensure partnership working is encouraged and supported to be as effective as possible. A structure for partnership working enabled this to be enacted systematically across all settings. Some individual tensions were nonetheless identified around different roles, with possible implications for clarifying expectations and deepening understandings of the different types of PPI contribution and of their importance. Even in a team with research expertise in PPI, the data showed that there were different phases and challenges to 'normalising' the PPI input to the project. Mutual commitment and flexibility, embedded through relationships across the team, led to inclusion and collaboration. Conclusion Work on developing relationships and teambuilding are as important for enabling partnership between PPI representatives and researchers as more practical components such as funding and information sharing. Early explicit exploration of the different roles and their contributions may assist effective participation and satisfaction.

Burden of gastro-oesophageal reflux disease in patients with persistent and intense symptoms despite proton pump inhibitor therapy: A post hoc analysis of the 2007 national health and wellness survey.

PubMed

Toghanian, Samira; Johnson, David A; Stålhammar, Nils-Olov; Zerbib, Frank

2011-10-01

Research on the negative impact of gastro-oesophageal reflux disease (GORD) on the health-related quality of life (HR-QOL) and resource utilization of patients with persistent and intense GORD symptoms despite proton pump inhibitor (PPI) therapy is lacking. The aim of this study was to describe the population of patients with GORD with persistent moderate-to-severe symptoms despite ongoing PPI therapy, and to compare their HR-QOL and healthcare resource use with patients with low GORD symptom load during ongoing PPI therapy. In this post hoc analysis of the 2007 National Health and Wellness Survey (NHWS), PPI-compliant (≥22 days with PPI use in the past month) European (France, Germany and the UK) and US respondents with physician-diagnosed GORD were stratified into those with persistent and intense GORD symptoms, those with low symptom load, or an intermediate group. 5672 PPI-compliant respondents were identified (persistent and intense symptoms, n = 1741; low symptom load, n = 1805; intermediate group, n = 2126). Respondents with persistent and intense symptoms had poorer HR-QOL than patients with a low symptom load, but none of the differences were statistically significant. Respondents with persistent and intense symptoms also reported lower work productivity (all countries; significant difference [p < 0.01] only in the US), greater activity impairment (all countries; significant difference [p < 0.01] only in the US) and more hours missed from work due to health problems (US, UK and Germany; significant difference [p < 0.01] only in the US). In the UK and US, respondents with persistent and intense symptoms reported significantly more visits to both primary-care physicians and specialists than respondents with a low symptom load (all p < 0.01). Additionally, US respondents with persistent and intense symptoms reported significantly more emergency room visits (p < 0.01). The 2007 NHWS gives support to the hypothesis that persistent and intense GORD symptoms despite PPI therapy have a significant and negative impact on both HR-QOL and healthcare resource utilization. These findings outline the need for new treatment options for symptomatic GORD patients taking PPI therapy.

Electrophoretic nanotechnology of graphene-carbon nanotube and graphene-polypyrrole nanofiber composites for electrochemical supercapacitors.

PubMed

Shi, Kaiyuan; Zhitomirsky, Igor

2013-10-01

Thin films of multiwalled carbon nanotubes (MWCNT), graphene and polypyrrole (PPy) nanofibers were prepared by cathodic electrophoretic deposition (EPD) from aqueous suspensions, containing safranin (SAF) as a new dispersant. The results of Fourier transform infrared spectroscopy, UV-Vis spectroscopy studies and sedimentation tests, coupled with deposition yield and electron microscopy data showed that SAF adsorbed on MWCNT, graphene and PPy, provided their dispersion and charging in the suspensions and allowed efficient EPD. The deposition yield can be controlled by the variation of SAF concentration in the suspensions and deposition time. The use of SAF as a co-dispersant for MWCNT, graphene and PPy, allowed controlled EPD of composite graphene-MWCNT and graphene-PPy films. The proposed approach for the deposition of PPy paves the way for EPD of neutral polymers using organic dyes as dispersing and charging agents. The composite films were investigated for application in electrochemical supercapacitors (ES). The graphene-MWCNT and graphene-PPy films showed significant increase in capacitance, decrease in resistance and increase in capacitance retention at high charge-discharge rates compared to the films of individual components. The analysis of electrochemical testing results and electron microscopy data provided an insight into the influence of composite microstructure on electrochemical performance. The composites, prepared by EPD are promising materials for electrodes of ES. Copyright © 2013 Elsevier Inc. All rights reserved.

Surface amplification of pencil graphite electrode with polypyrrole and reduced graphene oxide for fabrication of a guanine/adenine DNA based electrochemical biosensors for determination of didanosine anticancer drug

NASA Astrophysics Data System (ADS)

Karimi-Maleh, Hassan; Bananezhad, Asma; Ganjali, Mohammad R.; Norouzi, Parviz; Sadrnia, Abdolhossein

2018-05-01

Didanosine is nucleoside analog reverse transcriptase inhibitors with many side effects such as nausea and vomiting, stomach pain, tingling, burning and numbness and determination of this drug is very important in biological samples. This paper presents a DNA biosensor for determination of didanosine (DDI) in pharmaceutical samples. A pencil graphite electrode modified with conductive materials such as polypyrrole (PPy) and reduced graphene oxide (rGO) (PGE/PPy/rGO) was used for this goal. The double-stranded DNA was successfully immobilized on PGE/PPy/rGO. The PGE/PPy/rGO was characterized by microscopic and electrochemical methods. Then, the interaction of DDI with DNA was identified by decreases in the oxidation currents of guanine and adenine by differential pulse voltammetric (DPV) method. The dynamic range of DDI identified in the range of 0.02-50.0 μM and this electrode provided a low limit of detection (LOD = 8.0 nM) for DDI. The PGE/PPy/rGO loaded with ds-DNA was utilized for the measurement of DDI in real samples and obtained data were compared with HPLC method. The statistical tests such as F-test and t-test were used for confirming ability of PGE/PPy/rGO loaded with ds-DNA for analysis of DDI in real samples.

Directly administered antiretroviral therapy for HIV-infected drug users does not have an impact on antiretroviral resistance: results from a randomized controlled trial.

PubMed

Maru, Duncan Smith-Rohrberg; Kozal, Michael J; Bruce, R Douglas; Springer, Sandra A; Altice, Frederick L

2007-12-15

Directly administered antiretroviral therapy (DAART) is an effective intervention that improves clinical outcomes among HIV-infected drug users. Its effects on antiretroviral drug resistance, however, are unknown. We conducted a community-based, prospective, randomized controlled trial of DAART compared with self-administered therapy (SAT). We performed a modified intention-to-treat analysis among 115 subjects who provided serum samples for HIV genotypic resistance testing at baseline and at follow-up. The main outcomes measures included total genotypic sensitivity score, future drug options, number of new drug resistance mutations (DRMs), and number of new major International AIDS Society (IAS) mutations. The adjusted probability of developing at least 1 new DRM did not differ between the 2 arms (SAT: 0.41 per person-year [PPY], DAART: 0.49 PPY; adjusted relative risk [RR] = 1.04; P = 0.90), nor did the number of new mutations (SAT: 0.76 PPY, DAART: 0.83 PPY; adjusted RR = 0.99; P = 0.99) or the probability of developing new major IAS new drug mutations (SAT: 0.30 PPY, DAART: 0.33 PPY; adjusted RR = 1.12; P = 0.78). On measures of GSS and FDO, the 2 arms also did not differ. In this trial, DAART provided on-treatment virologic benefit for HIV-infected drug users without affecting the rate of development of antiretroviral medication resistance.

Polypyrrole-coated LiCoO2 nanocomposite with enhanced electrochemical properties at high voltage for lithium-ion batteries

NASA Astrophysics Data System (ADS)

Cao, Jingchao; Hu, Guorong; Peng, Zhongdong; Du, Ke; Cao, Yanbing

2015-05-01

A conducting polypyrrole thin film is successfully coated onto the surface of LiCoO2 by a simple chemical polymerization method. The structure and morphology of pristine LiCoO2 and PPy-coated LiCoO2 are investigated by the techniques of X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscope (TEM). Energy dispersive X-ray spectroscopy (EDXS), Fourier transform infrared spectrometry (FTIR) and thermogravimetric analysis (TGA) further demonstrate the existence of PPy. The electrochemical properties of the composites are investigated by galvanostatic charge-discharge test and AC impedance measurements, which show that the conductive PPy film on the surface significantly decrease the charge-transfer resistance of LiCoO2. The PPy-coated LiCoO2 exhibits a good electrochemical performance, showing initial discharge capacity of 182 mAh g-1 and retains 94.3% after 170 cycles. However, the retention of pristine LiCoO2 is only 83.5%. The rate capability results show that the reversible capacity retention (10C/0.2C) of LiCoO2 increases from 52.4% to 80.1% after being coated with PPy. The continuously coated thin PPy film is just like a capsule shell, which can protect the core (LiCoO2) from corrosion causing by the HF attacking and greatly reduce the dissolution of Co into electrolyte.

Identification of Hub Genes and Pathways in Zika Virus Infection Using RNA-Seq Data: A Network-Based Computational Approach.

PubMed

Brahma, Rahul; Gurumayum, Sanathoi; Naorem, Leimarembi Devi; Muthaiyan, Mathavan; Gopal, Jeyakodi; Venkatesan, Amouda

2018-05-01

Zika virus (ZIKV), a single-strand RNA flavivirus, is transmitted primarily through Aedes aegypti. The recent outbreaks in America and unexpected association between ZIKV infection and birth defects have triggered the global attention. This vouches to understand the molecular mechanisms of ZIKV infection to develop effective drug therapy. A systems-level understanding of biological process affected by ZIKV infection in fetal brain sample led us to identify the candidate genes for pharmaceutical intervention and potential biomarkers for diagnosis. To identify the key genes, transcriptomics data (RNA-Seq) with GSE93385 of ZIKV (Strain: MR766) infected human fetal neural stem cell are analyzed. In total, 1,084 differentially expressed genes (DEGs) are identified, that is, 471 upregulated and 613 downregulated genes. Further analysis such as the gene ontology term suggested that the downregulated genes are mostly enriched in defense response to virus, receptor binding, laminin binding, extracellular matrix, endoplasmic reticulum, and for upregulated DEGs: translation initiation, RNA binding, cytosol, and nucleosome are enriched. And through pathway analysis, systemic lupus erythematosus (SLE) is found to be the most enriched pathway. Protein-protein interaction (PPI) network is constructed to find the hub genes using STRING database. The seven key genes namely cyclin-dependent kinase 1 (CDK1), cyclin B1 (CCNB1), histone cluster 1 H2B family member K, (HIST1H2BK) histone cluster 1 H2B family member O (HIST1H2BO), and histone cluster 1 H2B family member B (HIST1H2BB), polo-like kinase 1 (PLK1), and cell division cycle 20 (CDC20) with highest degree are found to be hub genes using Centiscape, a Cytoscape plugin. The modules of PPI network using Molecular Complex Detection plugin are found significant in structural constituent of ribosome, defense response to virus, nucleosome, SLE, extracellular region, and regulation of gene silencing. Thus, identified key hub genes and pathways shed light on molecular mechanism that may contribute to the discovery of novel therapeutic targets and development of new strategies for the intervention of ZIKV disease.

A network biology-based approach to evaluating the effect of environmental contaminants on human interactome and diseases.

PubMed

Iida, M; Takemoto, K

2018-09-30

Environmental contaminant exposure can pose significant risks to human health. Therefore, evaluating the impact of this exposure is of great importance; however, it is often difficult because both the molecular mechanism of disease and the mode of action of the contaminants are complex. We used network biology techniques to quantitatively assess the impact of environmental contaminants on the human interactome and diseases with a particular focus on seven major contaminant categories: persistent organic pollutants (POPs), dioxins, polycyclic aromatic hydrocarbons (PAHs), pesticides, perfluorochemicals (PFCs), metals, and pharmaceutical and personal care products (PPCPs). We integrated publicly available data on toxicogenomics, the diseasome, protein-protein interactions (PPIs), and gene essentiality and found that a few contaminants were targeted to many genes, and a few genes were targeted by many contaminants. The contaminant targets were hub proteins in the human PPI network, whereas the target proteins in most categories did not contain abundant essential proteins. Generally, contaminant targets and disease-associated proteins were closely associated with the PPI network, and the closeness of the associations depended on the disease type and chemical category. Network biology techniques were used to identify environmental contaminants with broad effects on the human interactome and contaminant-sensitive biomarkers. Moreover, this method enabled us to quantify the relationship between environmental contaminants and human diseases, which was supported by epidemiological and experimental evidence. These methods and findings have facilitated the elucidation of the complex relationship between environmental exposure and adverse health outcomes. Copyright © 2018 Elsevier Inc. All rights reserved.

Identification of T1D susceptibility genes within the MHC region by combining protein interaction networks and SNP genotyping data

PubMed Central

Brorsson, C.; Hansen, N. T.; Lage, K.; Bergholdt, R.; Brunak, S.; Pociot, F.

2009-01-01

Aim To develop novel methods for identifying new genes that contribute to the risk of developing type 1 diabetes within the Major Histocompatibility Complex (MHC) region on chromosome 6, independently of the known linkage disequilibrium (LD) between human leucocyte antigen (HLA)-DRB1, -DQA1, -DQB1 genes. Methods We have developed a novel method that combines single nucleotide polymorphism (SNP) genotyping data with protein–protein interaction (ppi) networks to identify disease-associated network modules enriched for proteins encoded from the MHC region. Approximately 2500 SNPs located in the 4 Mb MHC region were analysed in 1000 affected offspring trios generated by the Type 1 Diabetes Genetics Consortium (T1DGC). The most associated SNP in each gene was chosen and genes were mapped to ppi networks for identification of interaction partners. The association testing and resulting interacting protein modules were statistically evaluated using permutation. Results A total of 151 genes could be mapped to nodes within the protein interaction network and their interaction partners were identified. Five protein interaction modules reached statistical significance using this approach. The identified proteins are well known in the pathogenesis of T1D, but the modules also contain additional candidates that have been implicated in β-cell development and diabetic complications. Conclusions The extensive LD within the MHC region makes it important to develop new methods for analysing genotyping data for identification of additional risk genes for T1D. Combining genetic data with knowledge about functional pathways provides new insight into mechanisms underlying T1D. PMID:19143816

SYSTEMS BIOLOGY ANALYSES OF GENE EXPRESSION AND GENOME WIDE ASSOCIATION STUDY DATA IN OBSTRUCTIVE SLEEP APNEA

PubMed Central

LIU, YU; PATEL, SANJAY; NIBBE, ROD; MAXWELL, SEAN; CHOWDHURY, SALIM A.; KOYUTURK, MEHMET; ZHU, XIAOFENG; LARKIN, EMMA K.; BUXBAUM, SARAH G; PUNJABI, NARESH M.; GHARIB, SINA A.; REDLINE, SUSAN; CHANCE, MARK R.

2015-01-01

The precise molecular etiology of obstructive sleep apnea (OSA) is unknown; however recent research indicates that several interconnected aberrant pathways and molecular abnormalities are contributors to OSA. Identifying the genes and pathways associated with OSA can help to expand our understanding of the risk factors for the disease as well as provide new avenues for potential treatment. Towards these goals, we have integrated relevant high dimensional data from various sources, such as genome-wide expression data (microarray), protein-protein interaction (PPI) data and results from genome-wide association studies (GWAS) in order to define sub-network elements that connect some of the known pathways related to the disease as well as define novel regulatory modules related to OSA. Two distinct approaches are applied to identify sub-networks significantly associated with OSA. In the first case we used a biased approach based on sixty genes/proteins with known associations with sleep disorders and/or metabolic disease to seed a search using commercial software to discover networks associated with disease followed by information theoretic (mutual information) scoring of the sub-networks. In the second case we used an unbiased approach and generated an interactome constructed from publicly available gene expression profiles and PPI databases, followed by scoring of the network with p-values from GWAS data derived from OSA patients to uncover sub-networks significant for the disease phenotype. A comparison of the approaches reveals a number of proteins that have been previously known to be associated with OSA or sleep. In addition, our results indicate a novel association of Phosphoinositide 3-kinase, the STAT family of proteins and its related pathways with OSA. PMID:21121029

Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding

PubMed Central

Cannistraci, Carlo Vittorio; Alanis-Lobato, Gregorio; Ravasi, Timothy

2013-01-01

Motivation: Most functions within the cell emerge thanks to protein–protein interactions (PPIs), yet experimental determination of PPIs is both expensive and time-consuming. PPI networks present significant levels of noise and incompleteness. Predicting interactions using only PPI-network topology (topological prediction) is difficult but essential when prior biological knowledge is absent or unreliable. Methods: Network embedding emphasizes the relations between network proteins embedded in a low-dimensional space, in which protein pairs that are closer to each other represent good candidate interactions. To achieve network denoising, which boosts prediction performance, we first applied minimum curvilinear embedding (MCE), and then adopted shortest path (SP) in the reduced space to assign likelihood scores to candidate interactions. Furthermore, we introduce (i) a new valid variation of MCE, named non-centred MCE (ncMCE); (ii) two automatic strategies for selecting the appropriate embedding dimension; and (iii) two new randomized procedures for evaluating predictions. Results: We compared our method against several unsupervised and supervisedly tuned embedding approaches and node neighbourhood techniques. Despite its computational simplicity, ncMCE-SP was the overall leader, outperforming the current methods in topological link prediction. Conclusion: Minimum curvilinearity is a valuable non-linear framework that we successfully applied to the embedding of protein networks for the unsupervised prediction of novel PPIs. The rationale for our approach is that biological and evolutionary information is imprinted in the non-linear patterns hidden behind the protein network topology, and can be exploited for predicting new protein links. The predicted PPIs represent good candidates for testing in high-throughput experiments or for exploitation in systems biology tools such as those used for network-based inference and prediction of disease-related functional modules. Availability: https://sites.google.com/site/carlovittoriocannistraci/home Contact: kalokagathos.agon@gmail.com or timothy.ravasi@kaust.edu.sa Supplementary information: Supplementary data are available at Bioinformatics online. PMID:23812985

Predicting protein complexes using a supervised learning method combined with local structural information.

PubMed

Dong, Yadong; Sun, Yongqi; Qin, Chao

2018-01-01

The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein interaction (PPI) networks even though many true complexes are not dense subgraphs. Supervised learning methods utilize the informative properties of known complexes; they often extract features from existing complexes and then use the features to train a classification model. The trained model is used to guide the search process for new complexes. However, insufficient extracted features, noise in the PPI data and the incompleteness of complex data make the classification model imprecise. Consequently, the classification model is not sufficient for guiding the detection of complexes. Therefore, we propose a new robust score function that combines the classification model with local structural information. Based on the score function, we provide a search method that works both forwards and backwards. The results from experiments on six benchmark PPI datasets and three protein complex datasets show that our approach can achieve better performance compared with the state-of-the-art supervised, semi-supervised and unsupervised methods for protein complex detection, occasionally significantly outperforming such methods.

Proton-pump inhibitors and risk of fractures: an update meta-analysis.

PubMed

Zhou, B; Huang, Y; Li, H; Sun, W; Liu, J

2016-01-01

To identify the relationship between proton-pump inhibitors (PPIs) and the risk of fracture, we conducted an update meta-analysis of observational studies. Results showed that PPI use was associated with a modestly increased risk of hip, spine, and any-site fracture. Many studies have investigated the association of proton-pump inhibitors (PPIs) with fracture risk, but the results have been inconsistent. To evaluate this question, we performed a meta-analysis of relevant observational studies. A systematic literature search up to February 2015 was performed in PubMed. We combined relative risks (RRs) for fractures using random-effects models and conducted subgroup and stratified analyses. Eighteen studies involving a total of 244,109 fracture cases were included in this meta-analysis. Pooled analysis showed that PPI use could moderately increase the risk of hip fracture [RR = 1.26, 95 % confidence intervals (CIs) 1.16–1.36]. There was statistically significant heterogeneity among studies (p < 0.001; I 2 = 71.9 %). After limiting to cohort studies, there was also a moderate increase in hip fracture risk without evidence of study heterogeneity. Pooling revealed that short-term use (<1 year) and longer use (>1 year) were similarly associated with increased risk of hip fracture. Furthermore, a moderately increased risk of spine (RR = 1.58, 95 % CI 1.38–1.82) and any-site fracture (RR = 1.33, 95 % CI 1.15–1.54) was also found among PPI users. In this update meta-analysis of observational studies, PPI use modestly increased the risk of hip, spine, and any-site fracture, but no evidence of duration effect in subgroup analysis.

Sex-Specific Brain Deficits in Auditory Processing in an Animal Model of Cocaine-Related Schizophrenic Disorders

PubMed Central

Broderick, Patricia A.; Rosenbaum, Taylor

2013-01-01

Cocaine is a psychostimulant in the pharmacological class of drugs called Local Anesthetics. Interestingly, cocaine is the only drug in this class that has a chemical formula comprised of a tropane ring and is, moreover, addictive. The correlation between tropane and addiction is well-studied. Another well-studied correlation is that between psychosis induced by cocaine and that psychosis endogenously present in the schizophrenic patient. Indeed, both of these psychoses exhibit much the same behavioral as well as neurochemical properties across species. Therefore, in order to study the link between schizophrenia and cocaine addiction, we used a behavioral paradigm called Acoustic Startle. We used this acoustic startle paradigm in female versus male Sprague-Dawley animals to discriminate possible sex differences in responses to startle. The startle method operates through auditory pathways in brain via a network of sensorimotor gating processes within auditory cortex, cochlear nuclei, inferior and superior colliculi, pontine reticular nuclei, in addition to mesocorticolimbic brain reward and nigrostriatal motor circuitries. This paper is the first to report sex differences to acoustic stimuli in Sprague-Dawley animals (Rattus norvegicus) although such gender responses to acoustic startle have been reported in humans (Swerdlow et al. 1997 [1]). The startle method monitors pre-pulse inhibition (PPI) as a measure of the loss of sensorimotor gating in the brain's neuronal auditory network; auditory deficiencies can lead to sensory overload and subsequently cognitive dysfunction. Cocaine addicts and schizophrenic patients as well as cocaine treated animals are reported to exhibit symptoms of defective PPI (Geyer et al., 2001 [2]). Key findings are: (a) Cocaine significantly reduced PPI in both sexes. (b) Females were significantly more sensitive than males; reduced PPI was greater in females than in males. (c) Physiological saline had no effect on startle in either sex. Thus, the data elucidate gender-specificity to the startle response in animals. Finally, preliminary studies show the effect of cocaine on acoustic startle in tandem with effects on estrous cycle. The data further suggest that hormones may play a role in these sex differences to acoustic startle reported herein. PMID:24961412

Controlled delivery of Gemcitabine Hydrochloride using mannosylated poly(propyleneimine) dendrimers

NASA Astrophysics Data System (ADS)

Soni, Namrata; Jain, Keerti; Gupta, Umesh; Jain, N. K.

2015-11-01

The aim of the present investigation was to deliver Gemcitabine Hydrochloride (GmcH), an anticancer bioactive, specifically to lung tumor cells using mannosylated 4.0G poly(propyleneimine) dendrimers (M-PPI). 4.0G poly(propyleneimine) (PPI) dendrimers was synthesized using ethylenediamine as core and conjugated with mannose by ring opening reactions, followed by Schiff's reaction in the presence of sodium acetate buffer (pH 4.0). Synthesized PPI dendrimers and mannose-conjugated dendrimers were characterized using IR, NMR spectroscopy, and scanning electron microscopy. GmcH was loaded into PPI and M-PPI dendrimers using equilibrium dialysis method to develop the formulations, GmcH-PPI and GmcH-M-PPI, respectively. The developed formulations were evaluated for drug loading, in vitro release kinetics, in vitro stability, hemolytic toxicity, cytotoxicity, pharmacokinetic, and biodistribution studies. The dendrimeric formulation of GmcH showed pH-sensitive release with faster release at acidic pH, i.e., pH 4.0 in comparison with physiological pH 7.4. M-PPI conjugate showed significant reduction in hemolytic toxicity as compared to plain 4.0G PPI dendrimers towards human erythrocytes. In the cytotoxicity studies with A-549 lung adenocarcinoma cell line, the GmcH-M-PPI formulation showed the lowest IC50 value. Further, the pharmacokinetic and tissue distribution studies of free drug GmcH, GmcH-PPI, and GmcH-M-PPI in albino rats of Sprague-Dawley strain suggested the mean residence time of GmcH-M-PPI conjugate to be significantly higher (24.85 h) than free GmcH and GmcH-PPI. Deposition of drug (396.1 ± 4.7 after 2 h) in lung was found to be significantly higher with GmcH-M-PPI formulation in comparison with Gmch and GmcH-PPI.

Optical band gap determination of calcium doped lanthanum manganite nano particle tailored with polypyrrole

NASA Astrophysics Data System (ADS)

Gopalakrishna, Smitha Mysore; Murugendrappa, Malalkere Veerappa

2018-05-01

In this paper we bring forth the effect of La0.7Ca0.3MnO3 (LCM) perovskite nano particle on the optical band gap in composition with conducting Polypyrrole (PPy) prepared by chemical oxidation method. The morphology and crystalline phase were determined by SEM, TEM and X-Ray diffraction studies. The Optical band gap studies were analyzed using the UV-VIS spectrometer scanned in the range 200 nm to 600 nm for pure PPy and PPy/LCM composites. There is a characteristic peak observed for the composites situated around 315 nm for pure PPy, PPy/LCM10 and PPy/LCM50. But for higher compositions of LCM weight percentage like 30%, 40% and 50% the peak shift slightly to higher wavelength side. The peak shifts to 320 nm, 325 nm and 335 nm respectively. The optical band gap increased for Pure PPy, PPy/LCM10 and PPy/LCM20 and found to decrease gradually for PPy/LCM30, PPy/LCM40 and PPy/LCM50. The studies suggest that LCM composition in the PPy chain has a role in modifying the wavelength and in turn its band gap. The study may find application in organic devices working at high frequency and voltage.

De Novo Synthesis and Functional Analysis of Polyphosphate-Loaded Poly(Ethylene) Glycol Hydrogel Nanoparticles Targeting Pyocyanin and Pyoverdin Production in Pseudomonas aeruginosa as a Model Intestinal Pathogen

PubMed Central

Yin, Yushu; Papavasiliou, Georgia; Zaborina, Olga Y.; Alverdy, John C.; Teymour, Fouad

2017-01-01

The human gastrointestinal tract is the primary site of colonization of multidrug resistant pathogens and the major source of life-threatening complications in critically ill and immunocompromised patients. Eradication measures using antibiotics carry further risk of antibiotic resistance. Furthermore, antibiotic treatment can adversely shift the intestinal microbiome toward domination by resistant pathogens. Therefore, approaches directed to prevent replacement of health promoting microbiota with resistant pathogens should be developed. The use of non-microbicidal drugs to create microenvironmental conditions that suppress virulence of pathogens is an attractive strategy to minimize the negative consequences of intestinal microbiome disruption. We have previously shown that phosphate is depleted in the intestinal tract following surgical injury, that this depletion is a major “cue” that triggers bacterial virulence, and that the maintenance of phosphate abundance prevents virulence expression. However, the use of inorganic phosphate may not be a suitable agent to deliver to the site of the host-pathogen interaction since it is readily adsorbed in small intestine. Here we propose a novel drug delivery approach that exploits the use of nanoparticles that allow for prolonged release of phosphates. We have synthesized phosphate (Pi) and polyphosphate (PPi) crosslinked poly (ethylene) glycol (PEG) hydrogel nanoparticles (NP-Pi and NP-PPi, respectively) that result in sustained delivery of Pi and PPi. NP-PPi demonstrated more prolonged release of PPi as compared to the release of Pi from NP-Pi. In vitro studies indicate that free PPi as well NP-PPi are effective compounds for suppressing pyoverdin and pyocyanin production, two global virulence systems of virulence of P. aeruginosa. These studies suggest that sustained release of polyphosphate from NP-PPi can be exploited as a target for virulence suppression of lethal pathogenic phenotypes in the gastrointestinal tract. PMID:27761766

Inhibition of 5a-reductase in the nucleus accumbens counters sensorimotor gating deficits induced by dopaminergic activation

PubMed Central

Devoto, Paola; Frau, Roberto; Bini, Valentina; Pillolla, Giuliano; Saba, Pierluigi; Flore, Giovanna; Corona, Marta; Marrosu, Francesco; Bortolato, Marco

2012-01-01

Summary Cogent evidence highlights a key role of neurosteroids and androgens in schizophrenia. We recently reported that inhibition of steroid 5α-reductase (5αR), the rate-limiting enzyme in neurosteroid synthesis and androgen metabolism, elicits antipsychotic-like effects in humans and animal models, without inducing extrapyramidal side effects. To elucidate the anatomical substrates mediating these effects, we investigated the contribution of peripheral and neural structures to the behavioral effects of the 5αR inhibitor finasteride (FIN) on the prepulse inhibition (PPI) of the acoustic startle reflex (ASR), a rat paradigm that dependably simulates the sensorimotor gating impairments observed in schizophrenia and other neuropsychiatric disorders. The potential effect of drug-induced ASR modifications on PPI was excluded by measuring this index both as percent (%PPI) and absolute values (ΔPPI). In both orchidectomized and sham-operated rats, FIN prevented the %PPI deficits induced by the dopamine (DA) receptor agonists apomorphine (APO, 0.25 mg/kg, SC) and d-amphetamine (AMPH, 2.5 mg/kg, SC), although the latter effect was not corroborated by ΔPPI analysis. Conversely, APO-induced PPI deficits were countered by FIN infusions in the brain ventricles (10 μg/1 μl) and in the nucleus accumbens (NAc) shell and core (0.5 μg/0.5 μl/side). No significant PPI-ameliorating effect was observed following FIN injections in other brain regions, including dorsal caudate, basolateral amygdala, ventral hippocampus and medial prefrontal cortex, although a statistical trend was observed for the latter region. The efflux of DA in NAc was increased by systemic, but not intracerebral FIN administration. Taken together, these findings suggest that the role of 5αR in gating regulation is based on post-synaptic mechanisms in the NAc, and is not directly related to alterations in DA efflux in this region. PMID:22029952

Role of miR-452-5p in the tumorigenesis of prostate cancer: A study based on the Cancer Genome Atl(TCGA), Gene Expression Omnibus (GEO), and bioinformatics analysis.

PubMed

Gao, Li; Zhang, Li-Jie; Li, Sheng-Hua; Wei, Li-Li; Luo, Bin; He, Rong-Quan; Xia, Shuang

2018-03-06

MiR-452-5p has been reported to be down-regulated in prostate cancer, affecting the development of this type of cancer. However, the molecular mechanism of miR-452-5p in prostate cancer remains unclear. Therefore, we investigated the network of target genes of miR-452-5p in prostate cancer using bioinformatics analyses. We first analyzed the expression profiles and prognostic value of miR-452-5p in prostate cancer tissues from a public database. Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), PANTHER pathway analyses, and a disease ontology (DG) analysis were performed to find the molecular functions of the target genes from GSE datasets and miRWalk. Finally, we validated hub genes from the protein-protein interaction (PPI) networks of the target genes in the Human Protein Atlas (HPA) database and Gene Expression Profiling Interactive Analysis (GEPIA). Narrowing down the optimal target genes was conducted by seeking the common parts of up-regulated genes from GEPIA, down-regulated genes from GSE datasets, and predicted genes in miRWalk. Based on mining of GEO and ArrayExpress microarray chips and miRNA-Seq data in the TCGA database, which includes 1007 prostate cancer samples and 387 non-cancer samples, miR-452-5p is shown to be down-regulated in prostate cancer. GO, KEGG, and PANTHER pathway analyses suggested that the target genes might participate in important biological processes, such as transforming growth factor beta signaling and the positive regulation of brown fat cell differentiation and mesenchymal cell differentiation, as well as the Ras signaling pathway and pathways regulating the pluripotency of stem cells and arrhythmogenic right ventricular cardiomyopathy (ARVC). Nine genes-GABBR, PNISR, NTSR1, DOCK1, EREG, SFRP1, PTGS2, LEF1, and BMP2-were defined as hub genes in the PPI network. Three genes-FAM174B, SLC30A4, and SLIT1-were jointly shared by GEPIA, the GSE datasets, and miRWalk. Down-regulated miR-452-5p might play an essential role in the tumorigenesis of prostate cancer. Copyright © 2018. Published by Elsevier GmbH.

Influence of pea protein aggregates on the structure and stability of pea protein/soybean polysaccharide complex emulsions.

PubMed

Yin, Baoru; Zhang, Rujing; Yao, Ping

2015-03-20

The applications of plant proteins in the food and beverage industry have been hampered by their precipitation in acidic solution. In this study, pea protein isolate (PPI) with poor dispersibility in acidic solution was used to form complexes with soybean soluble polysaccharide (SSPS), and the effects of PPI aggregates on the structure and stability of PPI/SSPS complex emulsions were investigated. Under acidic conditions, high pressure homogenization disrupts the PPI aggregates and the electrostatic attraction between PPI and SSPS facilitates the formation of dispersible PPI/SSPS complexes. The PPI/SSPS complex emulsions prepared from the PPI containing aggregates prove to possess similar droplet structure and similar stability compared with the PPI/SSPS emulsions produced from the PPI in which the aggregates have been previously removed by centrifugation. The oil droplets are protected by PPI/SSPS complex interfacial films and SSPS surfaces. The emulsions show long-term stability against pH and NaCl concentration changes. This study demonstrates that PPI aggregates can also be used to produce stable complex emulsions, which may promote the applications of plant proteins in the food and beverage industry.

PPCM: Combing multiple classifiers to improve protein-protein interaction prediction

DOE PAGES

Yao, Jianzhuang; Guo, Hong; Yang, Xiaohan

2015-08-01

Determining protein-protein interaction (PPI) in biological systems is of considerable importance, and prediction of PPI has become a popular research area. Although different classifiers have been developed for PPI prediction, no single classifier seems to be able to predict PPI with high confidence. We postulated that by combining individual classifiers the accuracy of PPI prediction could be improved. We developed a method called protein-protein interaction prediction classifiers merger (PPCM), and this method combines output from two PPI prediction tools, GO2PPI and Phyloprof, using Random Forests algorithm. The performance of PPCM was tested by area under the curve (AUC) using anmore » assembled Gold Standard database that contains both positive and negative PPI pairs. Our AUC test showed that PPCM significantly improved the PPI prediction accuracy over the corresponding individual classifiers. We found that additional classifiers incorporated into PPCM could lead to further improvement in the PPI prediction accuracy. Furthermore, cross species PPCM could achieve competitive and even better prediction accuracy compared to the single species PPCM. This study established a robust pipeline for PPI prediction by integrating multiple classifiers using Random Forests algorithm. Ultimately, this pipeline will be useful for predicting PPI in nonmodel species.« less

What do pharmaceutical industry professionals in Europe believe about involving patients and the public in research and development of medicines? A qualitative interview study.

PubMed

Parsons, Suzanne; Starling, Bella; Mullan-Jensen, Christine; Tham, Su-Gwan; Warner, Kay; Wever, Kim

2016-01-07

To explore European-based pharmaceutical industry professionals' beliefs about patient and public involvement (PPI) in medicines research and development (R&D). Pharmaceutical companies in the UK, Poland and Spain. 21 pharmaceutical industry professionals, four based in the UK, five with pan-European roles, four based in Spain and eight based in Poland. Qualitative interview study (telephone and face-to-face, semistructured interviews). All interviews were audio taped, translated (where appropriate) and transcribed for analysis using the Framework approach. 21 pharmaceutical industry professionals participated. Key themes were: beliefs about (1) whether patients and the public should be involved in medicines R&D; (2) the barriers and facilitators to PPI in medicines R&D and (3) how the current relationships between the pharmaceutical industry, patient organisations and patients influence PPI in medicines R&D. Although interviewees appeared positive about PPI, many were uncertain about when, how and which patients to involve. Patients and the public's lack of knowledge and interest in medicines R&D, and the pharmaceutical industry's lack of knowledge, interest and receptivity to PPI were believed to be key challenges to increasing PPI. Interviewees also believed that relationships between the pharmaceutical industry, patient organisations, patients and the public needed to change to facilitate PPI in medicines R&D. Existing pharmaceutical industry codes of practice and negative media reporting of the pharmaceutical industry were also seen as negative influences on these relationships. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Study for every other day administration of vonoprazan in maintenance treatment of erosive GERD: study protocol for a multicentre randomised cross-over study

PubMed Central

Kato, Mototsugu; Ito, Noriko; Demura, Mamiko; Kubo, Kimitoshi; Mabe, Katsuhiro; Harada, Naohiko

2018-01-01

Introduction The first drug selected for treatment of gastro-oesophageal reflux disease (GERD) and prevention of the recurrence is a proton pump inhibitor (PPI), but recently, a potassium-competitive acid blocker (P-CAB) was put on the market in Japan. Its onset of effect is faster than PPI, and it takes more than 2 days to recover acid secretion after the withdrawal period. Therefore, unlike PPI, the usefulness of every other day administration or discontinuous administration is expected. Methods and analysis This study is a prospective, multicentre, open-label, two-period randomised cross-over study to compare the efficacy and safety of PPI every other day administration and P-CAB every other day administration in 120 patients who receive erosive GERD maintenance therapy with PPI. Patients will be randomly allocated to receive 4 weeks P-CAB or PPI followed by 4 weeks cross over, where those on P-CAB will receive PPI and vice versa. The primary endpoint is proportion of asymptomatic patients. Secondary endpoints are suppressive effect of GERD symptoms, proportion of asymptomatic patients at each time point, safety and cost-saving effect of P-CAB every other day administration, compliance with every other day administration, and proportion of asymptomatic patients at the first month of study drug administration. Ethics and dissemination This study was approved by the National Hospital Organization Central Review Board for Clinical Trials (5 December 2017). Discussion If P-CAB every other day administration is established as one of GERD maintenance therapies, there is merit in both medical cost reduction and the safety to alleviate elevation in serum gastrin. Trial registration number UMIN000034701. PMID:29527318

PPI, paradoxes and Plato: who's sailing the ship?

PubMed

Ives, Jonathan; Damery, Sarah; Redwod, Sabi

2013-03-01

Over the last decade, patient and public involvement (PPI) has become a requisite in applied health research. Some funding bodies demand explicit evidence of PPI, while others have made a commitment to developing PPI in the projects they fund. Despite being commonplace, there remains a dearth of engagement with the ethical and theoretical underpinnings of PPI processes and practices. More specifically, while there is a small (but growing) body of literature examining the effectiveness and impact of PPI, there has been relatively little reflection on whether the concept/practice of PPI is internally coherent. Here, the authors unpick a 'paradox' within PPI, which highlights a tension between its moral and pragmatic motivations and its implementation. The authors argue that this 'professionalisation paradox' means we need to rethink the practice, and purpose, of PPI in research.

Weight ratio effects on morphology and electrocapacitive performance for the MoS2/polypyrrole electrodes

NASA Astrophysics Data System (ADS)

Tu, Chao-Chi; Peng, Pei-Wen; Lin, Lu-Yin

2018-06-01

MoS2 is one of the promising electroactive materials for charge-storage devices. The charges cannot only be stored in the intersheet of MoS2 and the intrasheet of individual atomic layers, but also can be accumulated by conducting the Faradaic reactions on the Mo center. To further enhance the electrocapacitive performance of MoS2, incorporating conducting polymers is one of the feasible ways to improve the connection between MoS2 nanosheets. At the same time, the growth of conducting polymers can also be controlled via incorporating MoS2 nanosheets in the synthesis to enhance the conductivity and increase the specific surface area of the conducting polymers. In this work, layered structures of MoS2 nanosheets are successfully synthesized via a simple hydrothermal method, and pyrrole monomers are oxidative polymerized in the MoS2 solution to prepare the nanocomposites with different ratios of MoS2 and polypyrrole (Ppy). The optimized MoS2/Ppy electrode shows a specific capacitance (CF) of 182.28 F/g, which is higher than those of the MoS2 (40.58 F/g) and Ppy (116.95 F/g) electrodes measured at the same scan rate of 10 mV/s. The excellent high-rate capacity and good cycling stability with 20% decay on the CF value comparing to the initial value after the 1000 times repeated charge/discharge process are also achieved for the optimized MoS2/Ppy electrode. The better performance for the MoS2/Ppy electrode is resulting from the larger surface area for charge accumulation and the enhanced interconnection networks for charge transportation. The results suggest that combining two materials with complementary properties as the electrocapacitive material is one of the attractive ways to realize efficient charge-storage devices with efficient electrochemical performances and good cycling lifes.

Corrosion Protection Properties of PPy-ND Composite Coating: Sonoelectrochemical Synthesis and Design of Experiment

NASA Astrophysics Data System (ADS)

Ashassi-Sorkhabi, H.; Bagheri, R.; Rezaei-Moghadam, B.

2016-02-01

In this research, the nanocomposite coatings comprising the polypyrrole-nanodiamond, PPy-ND, on St-12 steel electrodes were electro-synthesized using in situ polymerization process under ultrasonic irradiation. The corrosion protection performance and morphology characterization of prepared coatings were investigated by electrochemical methods and scanning electron microscopy, SEM, respectively. Also, the experimental design was employed to determine the best values considering the effective parameters such as the concentration of nanoparticles, the applied current density and synthesis time to achieve the most protective films. A response surface methodology, RSM, involving a central composite design, CCD, was applied to the modeling and optimization of the PPy-ND nanocomposite deposition. Pareto graphic analysis of the parameters indicated that the applied current density and some of the interactions were effective on the response. The electrochemical results proved that the embedment of diamond nanoparticle, DNP, improves the corrosion resistance of PPy coatings significantly. Therefore, desirable correlation exists between predicted data and experimental results.

Evaluation of poultry protein isolate as a food ingredient: physicochemical properties and sensory characteristics of marinated chicken breasts.

PubMed

Khiari, Zied; Omana, Dileep A; Pietrasik, Zeb; Betti, Mirko

2013-07-01

The possibilities of replacing soy protein isolate (SPI) and reducing the amount of phosphate in marinated chicken breasts using poultry protein isolate (PPI) were investigated. PPI, prepared from mechanically separated turkey meat through the pH-shift technology, was used as a marinade ingredient for chicken breasts at 2 different concentrations (1.0% and 1.5%, w/w on a dry weight basis). Product characteristics were compared to samples marinated with salt, phosphate, or SPI. All the 5 treatments were subjected to instrumental and sensory analyses. Tumbling yield, drip, and cooking losses as well as expressible moisture showed that PPI can be used as a substitute for SPI in brine. The sensory analysis revealed that there were no differences among treatments in terms of appearance, color, flavor, saltiness, juiciness, tenderness, and overall acceptability of the marinated chicken breasts. However, chicken breasts marinated with phosphate had significantly higher aroma acceptability scores than those treated with 1% PPI. © 2013 Institute of Food Technologists®

PPI layouts: BioJS components for the display of Protein-Protein Interactions.

PubMed

Salazar, Gustavo A; Meintjes, Ayton; Mulder, Nicola

2014-01-01

We present two web-based components for the display of Protein-Protein Interaction networks using different self-organizing layout methods: force-directed and circular. These components conform to the BioJS standard and can be rendered in an HTML5-compliant browser without the need for third-party plugins. We provide examples of interaction networks and how the components can be used to visualize them, and refer to a more complex tool that uses these components. http://github.com/biojs/biojs; http://dx.doi.org/10.5281/zenodo.7753.

Proton Pump Inhibitor-Responsive Oesophageal Eosinophilia: An Entity Challenging Current Diagnostic Criteria for Eosinophilic Oesophagitis

PubMed Central

Molina-Infante, Javier; Bredenoord, Albert J.; Cheng, Edaire; Dellon, Evan S.; Furuta, Glenn T.; Gupta, Sandeep K.; Hirano, Ikuo; Katzka, David A.; Moawad, Fouad J.; Rothenberg, Marc E.; Schoepfer, Alain; Spechler, Stuart; Wen, Ting; Straumann, Alex; Lucendo, Alfredo J.

2016-01-01

Consensus diagnostic recommendations to distinguish gastro-oesophageal reflux disease (GORD) from eosinophilic oesophagitis (EoE) by response to a trial of proton pump inhibitors (PPI) unexpectedly uncovered an entity called “PPI-responsive oesophageal eosinophilia” (PPI-REE). PPI-REE refers to patients with clinical and histologic features of EoE that remit with PPI treatment. Recent and evolving evidence, mostly from adults, shows that PPI-REE and EoE patients at baseline are clinically, endoscopically and histologically indistinguishable, and have significant overlap in terms of features of Th2 immune-mediated inflammation and gene expression. Furthermore, PPI therapy restores oesophageal mucosal integrity, reduces Th2 inflammation and reverses the abnormal gene expression signature in PPI-REE patients, similar to the effects of topical steroids in EoE patients. Additionally, recent series have reported that EoE patients responsive to diet/topical steroids may also achieve remission on PPI therapy. This mounting evidence supports the concept that PPI-REE represents a continuum of the same immunologic mechanisms that underlie EoE. Accordingly, it seems counterintuitive to differentiate PPI-REE from EoE based on a differential response to PPI therapy when their phenotypic, molecular, mechanistic, and therapeutic features cannot be reliably distinguished. For patients with symptoms and histologic features of EoE, it is reasonable to consider PPI therapy not as a diagnostic test, but as a therapeutic agent. Due to its safety profile, ease of administration and high response rates (up to 50%), PPI can be considered a first-line treatment, before diet and topical steroids. The reasons why some EoE patients respond to PPI, while others do not, remain to be elucidated. PMID:26685124

Preparation of Different Substitued Polypyridine Ligands, Ruthenium(II)-Bridged Complexes and Spectoscopıc Studies.

PubMed

Obali, Aslihan Yilmaz; Ucan, Halil Ismet

2016-09-01

Novel different substitued polypyridine ligands 4-((4-(1H-imidazo[4,5-f][1,10]phenanthroline-2-yl)phenoxy)methyl)benzaldehyde (BA-PPY), (E)-N-(4-((4-(1H-imidazo[4,5-f][1,10]phenanthroline-2-yl)phenoxy)methyl)benzylidene)-pyrene-4-amine (PR-PPY), (E)-N-(4-((4-(1H-imidazo[4,5-f][1,10] phenanthroline-2-yl)phenoxy)methyl)benzylidene)-1,10-phenanthroline-5amine (FN-PPY), 2-(4-(bromomethyl)phenyl)-1H-imidazo[4,5-f][1,10] phenanthroline (BR-PPY), 2-(4-(azidomethyl)phenyl)-1H-imidazo[4,5-f][1,10]phenanthroline (N3-PPY) and triazole containing polypyridine ligand 3,4-bis[(4-(metoxy)-1,2,3-triazole)1-methylphenyl)-1H-imidazo[4,5-f][1,10]phenanthroline)] benzaldehyde (BA-DIPPY) and Ruthenium(II) complexes were synthesized and characterized. Their photopysical properties were investigated. The complexes RuP(PR-PPY), RuB(PR-PPY, RuP(FN-PPY) and RuB(FN-PPY) exhibited a broad absorption bands at 485, 475, 476, and 453 nm, respectively, assignable to the spin-allowed MLCT (dπ-π*) transition. The emission maxima of the pyrene-appended polypyridine ligand PR-PPY was observed at λems = 616 nm and the phenanthroline-appended polypyridine ligand FN-PPY was observed at λems = 668 nm. And the emission maxima of the complexes RuP(PR-PPY), RuB(PR-PPY), RuP(FN-PPY) and RuB(FN-PPY) were observed at λems = 646, 646, 685 and 685 nm, respectively. As seen in fluorescence spectra, the fluorescence intensities of the ligands are higher than their metal complexes. This is because of quenching effect of Ruthenium(II) metal on chromophore groups.

Meta-Analysis of Medical Regimen Adherence Outcomes in Pediatric Solid Organ Transplantation*

PubMed Central

Dew, Mary Amanda; DeVito Dabbs, Annette; Myaskovsky, Larissa; Shyu, Susan; Shellmer, Diana A.; DiMartini, Andrea F.; Steel, Jennifer; Unruh, Mark; Switzer, Galen E.; Shapiro, Ron; Greenhouse, Joel B.

2009-01-01

Background Adherence to the medical regimen after pediatric organ transplantation is important for maximizing good clinical outcomes. However, the literature provides inconsistent evidence regarding prevalence and risk factors for nonadherence posttransplant. Methods A total of 61 studies (30 kidney, 18 liver, 8 heart, 2 lung/heart-lung, and 3 with mixed recipient samples) were included in a meta-analysis. Average rates of nonadherence to 6 areas of the regimen, and correlations of potential risk factors with nonadherence, were calculated. Results Across all types of transplantation, nonadherence to clinic appointments and tests was most prevalent, at 12.9 cases per 100 patients per year (PPY). The immunosuppression nonadherence rate was 6 cases per 100 PPY. Nonadherence to substance use restrictions, diet, exercise and other healthcare requirements ranged from 0.6 to 8 cases per 100 PPY. Only the rate of nonadherence to clinic appointments and tests varied by transplant type: heart recipients had the lowest rate (4.6 cases per 100 PPY vs. 12.7–18.8 cases per 100 PPY in other recipients). Older age of the child, family functioning (greater parental distress, lower family cohesion), and the child’s psychological status (poorer behavioral functioning, greater distress) were among the psychosocial characteristics significantly correlated with poorer adherence. These correlations were small to modest in size (r =.12–.18). Conclusions These nonadherence rates provide benchmarks for clinicians to use to estimate patient risk. The identified psychosocial correlates of nonadherence are potential targets for intervention. Future studies should focus on improving the prediction of nonadherence risk and on testing interventions to reduce risk. PMID:19741474

A risk PRODH haplotype affects sensorimotor gating, memory, schizotypy, and anxiety in healthy male subjects.

PubMed

Roussos, Panos; Giakoumaki, Stella G; Bitsios, Panos

2009-06-15

Significant associations have been shown for haplotypes comprising three PRODH single nucleotide polymorphisms (SNPs; 1945T/C, 1766A/G, 1852G/A) located in the 3' region of the gene, suggesting a role of these variants in the etiopathogenesis of schizophrenia. We assessed the relationship between these high-risk PRODH polymorphisms and schizophrenia-related endophenotypes in a large and highly homogeneous cohort of healthy males. Participants (n = 217) were tested in prepulse inhibition (PPI), verbal and working memory, trait anxiety and schizotypy. The QTPHASE from the UNPHASED package was used for the association analysis of each SNP or haplotype data. This procedure revealed significant phenotypic impact of the risk CGA haplotype. Subjects were then divided in two groups; levels of PPI, anxiety, and schizotypy, verbal and working memory were compared with analysis of variance. CGA carriers (n = 32) exhibited attenuated PPI (p < .001) and verbal memory (p < .001) and higher anxiety (p < .004) and schizotypy (p < .008) compared with the noncarriers (n = 185). There were no differences in baseline startle, demographics, and working memory. The main significant correlations were schizotypy x PPI [85-dB, 120-msec trials] in the carriers and schizotypy x anxiety in the entire group and the noncarriers but not the carriers group. Our results strongly support PPI as a valid schizophrenia endophenotype and highlight the importance of examining the role of risk haplotypes on multiple endophenotypes and have implications for understanding the continuum from normality to psychosis, transitional states, and the genetics of schizophrenia-related traits.

The gene for pancreatic polypeptide (PPY) and the anonymous marker D17S78 are within 45 kb of each other on chromosome 17q21

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chandrasekharappa, S.C.; King, S.E.; Lee, Y.H.

1994-05-15

A gene for early-onset breast and ovarian cancer (BRCA1) has been localized to a small region of chromosome 17q21. A combination of genetic linkage studies, radiation-reduced hybrid analysis, and physical mapping by FISH has identified several genes/markers that lie in this interval. Among these are the gene encoding pancreatic polypeptide (PPY) and a polymorphic marker at locus D17S78. Efforts to construct a physical map of this region by isolating a large number of yeast artificial chromosome (YAC) and cosmid clones demonstrate that PPY and D17S78 are present within the same cosmid clone, and therefore no farther than 45 kb apart.more » This observation takes on particular significance since it excludes a recently described BRCA1 candidate gene from the interval defined by meiotic mapping. Although PPY and D17S78 were found to be no farther than 45 kb apart, identification of a smaller fragment that hybridizes to both probes would indicate that these two are much closer. The probe p131 and the gene PPY were previously mapped to 17q21-q23 and to the proximal long arm of chromosome 17, respectively. The demonstration of the close proximity of these markers should allow them to be treated as a single locus in terms of long-range genomic mapping of this region, and the genomic clones isolated should serve as useful resources for the identification of the BRCA1 gene. Analysis of a large number of a familial and spordic breast and ovarian cancers has identified frequent loss of heterozygosity near the BRCA1 locus. A recent report has suggested the responsible interval lies just telomeric to PPY, and a suggested candidate gene (MCD) for BRCA1 was found to be somatically rearranged in two of several hundred sporadic breast tumors.« less

Identification of genes related to proliferative diabetic retinopathy through RWR algorithm based on protein-protein interaction network.

PubMed

Zhang, Jian; Suo, Yan; Liu, Min; Xu, Xun

2018-06-01

Proliferative diabetic retinopathy (PDR) is one of the most common complications of diabetes and can lead to blindness. Proteomic studies have provided insight into the pathogenesis of PDR and a series of PDR-related genes has been identified but are far from fully characterized because the experimental methods are expensive and time consuming. In our previous study, we successfully identified 35 candidate PDR-related genes through the shortest-path algorithm. In the current study, we developed a computational method using the random walk with restart (RWR) algorithm and the protein-protein interaction (PPI) network to identify potential PDR-related genes. After some possible genes were obtained by the RWR algorithm, a three-stage filtration strategy, which includes the permutation test, interaction test and enrichment test, was applied to exclude potential false positives caused by the structure of PPI network, the poor interaction strength, and the limited similarity on gene ontology (GO) terms and biological pathways. As a result, 36 candidate genes were discovered by the method which was different from the 35 genes reported in our previous study. A literature review showed that 21 of these 36 genes are supported by previous experiments. These findings suggest the robustness and complementary effects of both our efforts using different computational methods, thus providing an alternative method to study PDR pathogenesis. Copyright © 2017 Elsevier B.V. All rights reserved.

Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors.

PubMed

Sable, Rushikesh; Jois, Seetharama

2015-06-23

Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers.

Proton pump inhibitor-responsive esophageal eosinophilia: a historical perspective on a novel and evolving entity.

PubMed

Molina-Infante, Javier; Katzka, David A; Dellon, Evan S

2015-01-01

Eosinophilic esophagitis (EoE) is an emerging chronic esophageal disease, first described in 1993, with a steadily increasing incidence and prevalence in western countries. Over the 80's and early 90's, dense esophageal eosinophilia was mostly associated gastroesophageal reflux disease (GERD). For the next 15 years, EoE and GERD were rigidly considered separate entities: Esophageal eosinophilia with pathological acid exposure on pH monitoring or response to proton pump inhibitor (PPI) therapy was GERD, whereas normal pH monitoring or absence of response to PPIs was EoE. Updated guidelines in 2011 described a novel phenotype, proton pump inhibitor-responsive esophageal eosinophilia (PPI-REE), referring to patients who appear to have EoE clinically, but who achieve complete remission after PPI therapy. Currently, PPI-REE must be formally excluded before diagnosing EoE, since 30-40% of patients with suspected EoE are eventually diagnosed with PPI-REE.Interestingly, PPI-REE and EoE remain undistinguishable based on clinical, endoscopic, and histological findings, pH monitoring, and measurement of tissue markers and cytokines related to eosinophilic inflammation.This review article aims to revisit the relatively novel concept of PPI-REE from a historical perspective, given the strong belief that only GERD, as an acid peptic disorder, could respond to the acid suppressing ability of PPI therapy, is becoming outdated. Evolving evidence suggests that PPI-REE is genetically and phenotypically undistinguishable from EoE and PPI therapy alone can almost completely reverse allergic inflammation. As such, PPI-REE might constitute a subphenotype of EoE and PPI therapy may be the first therapeutic step and diet/ steroids may represent step up therapy. Possibly, the term PPI-REE will be soon replaced by PPI-responsive EoE. The mechanism as to why some patients respond to PPI therapy (PPI-REE) while others do not (EoE), remains to be elucidated.

The Provider Perception Inventory: Psychometrics of a Scale Designed to Measure Provider Stigma about HIV, Substance Abuse, and MSM Behavior

PubMed Central

Windsor, Liliane Cambraia; Benoit, Ellen; Ream, Geoffrey; Forenza, Brad

2012-01-01

Non-gay identified men who have sex with men and women (NGI MSMW) and who use alcohol and other drugs are a vulnerable, understudied, and undertreated population. Little is known about the stigma faced by this population or about the way that health service providers view and serve these stigmatized clients. The Provider Perception Inventory (PPI) is a 39-item scale that measures health services providers’ stigma about HIV/AIDS, substance use, and MSM behavior. The PPI is unique in that it was developed to include service provider stigma targeted at NGI MSMW individuals. PPI was developed through a mixed methods approach. Items were developed based on existing measures and findings from focus groups with 18 HIV and substance abuse treatment providers. Exploratory factor analysis using data from 212 health service providers yielded a two dimensional scale: 1) Individual Attitudes (19 items), and 2) Agency Environment (11 items). Structural equation model analysis supported the scale’s predictive validity (N=190 sufficiently complete cases). Overall findings indicate initial support for the psychometrics of the PPI as a measure of service provider stigma pertaining to the intersection of HIV/AIDS, substance use, and MSM behavior. Limitations and implications to future research are discussed. PMID:23082899

The provider perception inventory: psychometrics of a scale designed to measure provider stigma about HIV, substance abuse, and MSM behavior.

PubMed

Windsor, Liliane C; Benoit, Ellen; Ream, Geoffrey L; Forenza, Brad

2013-01-01

Nongay identified men who have sex with men and women (NGI MSMW) and who use alcohol and other drugs are a vulnerable, understudied, and undertreated population. Little is known about the stigma faced by this population or about the way that health service providers view and serve these stigmatized clients. The provider perception inventory (PPI) is a 39-item scale that measures health services providers' stigma about HIV/AIDS, substance use, and MSM behavior. The PPI is unique in that it was developed to include service provider stigma targeted at NGI MSMW individuals. PPI was developed through a mixed methods approach. Items were developed based on existing measures and findings from focus groups with 18 HIV and substance abuse treatment providers. Exploratory factor analysis using data from 212 health service providers yielded a two dimensional scale: (1) individual attitudes (19 items) and (2) agency environment (11 items). Structural equation modeling analysis supported the scale's predictive validity (N=190 sufficiently complete cases). Overall findings indicate initial support for the psychometrics of the PPI as a measure of service provider stigma pertaining to the intersection of HIV/AIDS, substance use, and MSM behavior. Limitations and implications to future research are discussed.

Nature and consequences of protein-protein interactions in high protein concentration solutions.

PubMed

Saluja, Atul; Kalonia, Devendra S

2008-06-24

High protein concentration solutions are becoming increasingly important in the pharmaceutical industry. The solution behavior of proteins at high concentrations can markedly differ from that predicted based on dilute solution analysis due to thermodynamic non-ideality in these solutions. The non-ideality observed in these systems is related to the protein-protein interactions (PPI). Different types of forces play a key role in determining the overall nature and extent of these PPI and their relative contributions are affected by solute and solvent properties. However, individual contributions of these forces to the solution properties of concentrated protein solutions are not fully understood. The role of PPI, driven by these intermolecular forces, in governing solution rheology and physical stability of high protein concentration solutions is discussed from the point of view of pharmaceutical product development. Investigation of protein self-association and aggregation in concentrated protein solutions is crucial for ensuring the safety and efficacy of the final product for the duration of the desired product shelf life. Understanding rheology of high concentration protein solutions is critical for addressing issues during product manufacture and administration of final formulation to the patient. To this end, analysis of solution viscoelastic character can also provide an insight into the nature of PPI affecting solution rheology.

Integrative analyses of leprosy susceptibility genes indicate a common autoimmune profile.

PubMed

Zhang, Deng-Feng; Wang, Dong; Li, Yu-Ye; Yao, Yong-Gang

2016-04-01

Leprosy is an ancient chronic infection in the skin and peripheral nerves caused by Mycobacterium leprae. The development of leprosy depends on genetic background and the immune status of the host. However, there is no systematic view focusing on the biological pathways, interaction networks and overall expression pattern of leprosy-related immune and genetic factors. To identify the hub genes in the center of leprosy genetic network and to provide an insight into immune and genetic factors contributing to leprosy. We retrieved all reported leprosy-related genes and performed integrative analyses covering gene expression profiling, pathway analysis, protein-protein interaction network, and evolutionary analyses. A list of 123 differentially expressed leprosy related genes, which were enriched in activation and regulation of immune response, was obtained in our analyses. Cross-disorder analysis showed that the list of leprosy susceptibility genes was largely shared by typical autoimmune diseases such as lupus erythematosus and arthritis, suggesting that similar pathways might be affected in leprosy and autoimmune diseases. Protein-protein interaction (PPI) and positive selection analyses revealed a co-evolution network of leprosy risk genes. Our analyses showed that leprosy associated genes constituted a co-evolution network and might undergo positive selection driven by M. leprae. We suggested that leprosy may be a kind of autoimmune disease and the development of leprosy is a matter of defect or over-activation of body immunity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

How perfect can protein interactomes be?

PubMed

Levy, Emmanuel D; Landry, Christian R; Michnick, Stephen W

2009-03-03

Any engineered device should certainly not contain nonfunctional components, for this would be a waste of energy and money. In contrast, evolutionary theory tells us that biological systems need not be optimized and may very well accumulate nonfunctional elements. Mutational and demographic processes contribute to the cluttering of eukaryotic genomes and transcriptional networks with "junk" DNA and spurious DNA binding sites. Here, we question whether such a notion should be applied to protein interactomes-that is, whether these protein interactomes are expected to contain a fraction of nonselected, nonfunctional protein-protein interactions (PPIs), which we term "noisy." We propose a simple relationship between the fraction of noisy interactions expected in a given organism and three parameters: (i) the number of mutations needed to create and destroy interactions, (ii) the size of the proteome, and (iii) the fitness cost of noisy interactions. All three parameters suggest that noisy PPIs are expected to exist. Their existence could help to explain why PPIs determined from large-scale studies often lack functional relationships between interacting proteins, why PPIs are poorly conserved across organisms, and why the PPI space appears to be immensely large. Finally, we propose experimental strategies to estimate the fraction of evolutionary noise in PPI networks.

Clinical value of miR-182-5p in lung squamous cell carcinoma: a study combining data from TCGA, GEO, and RT-qPCR validation.

PubMed

Luo, Jie; Shi, Ke; Yin, Shu-Ya; Tang, Rui-Xue; Chen, Wen-Jie; Huang, Lin-Zhen; Gan, Ting-Qing; Cai, Zheng-Wen; Chen, Gang

2018-04-10

MiR-182-5p, as a member of miRNA family, can be detected in lung cancer and plays an important role in lung cancer. To explore the clinical value of miR-182-5p in lung squamous cell carcinoma (LUSC) and to unveil the molecular mechanism of LUSC. The clinical value of miR-182-5p in LUSC was investigated by collecting and calculating data from The Cancer Genome Atlas (TCGA) database, the Gene Expression Omnibus (GEO) database, and real-time quantitative polymerase chain reaction (RT-qPCR). Twelve prediction platforms were used to predict the target genes of miR-182-5p. Protein-protein interaction (PPI) networks and gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to explore the molecular mechanism of LUSC. The expression of miR-182-5p was significantly over-expressed in LUSC than in non-cancerous tissues, as evidenced by various approaches, including the TCGA database, GEO microarrays, RT-qPCR, and a comprehensive meta-analysis of 501 LUSC cases and 148 non-cancerous cases. Furthermore, a total of 81 potential target genes were chosen from the union of predicted genes and the TCGA database. GO and KEGG analyses demonstrated that the target genes are involved in pathways related to biological processes. PPIs revealed the relationships between these genes, with EPAS1, PRKCE, NR3C1, and RHOB being located in the center of the PPI network. MiR-182-5p upregulation greatly contributes to LUSC and may serve as a biomarker in LUSC.

Abnormal DNA methylation may contribute to the progression of osteosarcoma.

PubMed

Chen, Xiao-Gang; Ma, Liang; Xu, Jia-Xin

2018-01-01

The identification of optimal methylation biomarkers to achieve maximum diagnostic ability remains a challenge. The present study aimed to elucidate the potential molecular mechanisms underlying osteosarcoma (OS) using DNA methylation analysis. Based on the GSE36002 dataset obtained from the Gene Expression Omnibus database, differentially methylated genes were extracted between patients with OS and controls using t‑tests. Subsequently, hierarchical clustering was performed to segregate the samples into two distinct clusters, OS and normal. Gene Ontology (GO) and pathway enrichment analyses for differentially methylated genes were performed using the Database for Annotation, Visualization and Integrated Discovery tool. A protein‑protein interaction (PPI) network was established, followed by hub gene identification. Using the cut‑off threshold of ≥0.2 average β‑value difference, 3,725 unique CpGs (2,862 genes) were identified to be differentially methylated between the OS and normal groups. Among these 2,862 genes, 510 genes were differentially hypermethylated and 2,352 were differentially hypomethylated. The differentially hypermethylated genes were primarily involved in 20 GO terms, and the top 3 terms were associated with potassium ion transport. For differentially hypomethylated genes, GO functions principally included passive transmembrane transporter activity, channel activity and metal ion transmembrane transporter activity. In addition, a total of 10 significant pathways were enriched by differentially hypomethylated genes; notably, neuroactive ligand‑receptor interaction was the most significant pathway. Based on a connectivity degree >90, 7 hub genes were selected from the PPI network, including neuromedin U (NMU; degree=103) and NMU receptor 1 (NMUR1; degree=103). Functional terms (potassium ion transport, transmembrane transporter activity, and neuroactive ligand‑receptor interaction) and hub genes (NMU and NMUR1) may serve as potential targets for the treatment and diagnosis of OS.

Value of the Gastroesophageal Reflux Disease Questionnaire (GerdQ) in predicting the proton pump inhibitor response in coronary artery disease patients with gastroesophageal reflux-related chest pain.

PubMed

He, S; Liu, Y; Chen, Y; Tang, Y; Xu, J; Tang, C

2016-05-01

Chest pain experienced by patients with coronary artery disease can be partly due to gastroesophageal reflux-induced chest pain (GERP). Empirical proton pump inhibitor (PPI) therapy has been recommended as an initial clinical approach for treating GERP. However, PPI use may lead to some health problems. The Gastroesophageal Reflux Disease Questionnaire (GerdQ) may represent a noninvasive and cost-effective approach for avoiding PPI misuse and for identifying the appropriate patients for the PPI trial test. The aim of this pilot study was to prospectively evaluate the association between GerdQ scores and PPI response in patients with coronary artery disease (CAD) and GERP to determine whether the GerdQ predicts the PPI response in patients with CAD and GERP and to further validate the clinical application value of the GerdQ. A total of 154 consecutive patients with potential GERP were recruited to complete a GerdQ with subsequent PPI therapy. Based on the PPI trial result, patients were divided into a PPI-positive response group and a PPI-negative response group. The difference in the GerdQ scores between the two groups was assessed. The receiver operating characteristic (ROC) curve of GerdQ score was drawn according to the PPI response as the gold standard. The ability of GerdQ to predict the PPI response was assessed. A total of 96 patients completed the entire study; 62 patients (64.6%) were assigned to the PPI-positive response group, and 34 patients (35.4%) to the PPI-negative response group. The GerdQ score of the PPI-positive response group (8.11 ± 3.315) was significantly higher than that of the PPI-negative response group (4.41 ± 2.743), and the difference was statistically significant (t = 5.863, P = 0.000). The ROC curve was drawn according to a PPI response assessment result with a score above 2 as the gold standard. The area under curve was 0.806. When the critical value of GerdQ score was 7.5, Youden index was up to 0.514, the diagnostic sensitivity was 0.661, and the diagnostic specificity was 0.853. A GerdQ score greater than 7.5 better predicts the response to the PPI trial therapy. There is a strong association between the GerdQ score and the response to PPI therapy. Higher GerdQ scores were predictive of a positive PPI response in CAD patients with GERP. The GerdQ may be a reasonable screening tool for GERP in patients with CAD who are prepared to accept PPI therapy. © 2015 International Society for Diseases of the Esophagus.

Modular biological function is most effectively captured by combining molecular interaction data types.

PubMed

Ames, Ryan M; Macpherson, Jamie I; Pinney, John W; Lovell, Simon C; Robertson, David L

2013-01-01

Large-scale molecular interaction data sets have the potential to provide a comprehensive, system-wide understanding of biological function. Although individual molecules can be promiscuous in terms of their contribution to function, molecular functions emerge from the specific interactions of molecules giving rise to modular organisation. As functions often derive from a range of mechanisms, we demonstrate that they are best studied using networks derived from different sources. Implementing a graph partitioning algorithm we identify subnetworks in yeast protein-protein interaction (PPI), genetic interaction and gene co-regulation networks. Among these subnetworks we identify cohesive subgraphs that we expect to represent functional modules in the different data types. We demonstrate significant overlap between the subgraphs generated from the different data types and show these overlaps can represent related functions as represented by the Gene Ontology (GO). Next, we investigate the correspondence between our subgraphs and the Gene Ontology. This revealed varying degrees of coverage of the biological process, molecular function and cellular component ontologies, dependent on the data type. For example, subgraphs from the PPI show enrichment for 84%, 58% and 93% of annotated GO terms, respectively. Integrating the interaction data into a combined network increases the coverage of GO. Furthermore, the different annotation types of GO are not predominantly associated with one of the interaction data types. Collectively our results demonstrate that successful capture of functional relationships by network data depends on both the specific biological function being characterised and the type of network data being used. We identify functions that require integrated information to be accurately represented, demonstrating the limitations of individual data types. Combining interaction subnetworks across data types is therefore essential for fully understanding the complex and emergent nature of biological function.

Papaloizou-Pringle instability suppression by the magnetorotational instability in relativistic accretion discs

NASA Astrophysics Data System (ADS)

Bugli, M.; Guilet, J.; Müller, E.; Del Zanna, L.; Bucciantini, N.; Montero, P. J.

2018-03-01

Geometrically thick tori with constant specific angular momentum have been widely used in the last decades to construct numerical models of accretion flows on to black holes. Such discs are prone to a global non-axisymmetric hydrodynamic instability, known as Papaloizou-Pringle instability (PPI), which can redistribute angular momentum and also lead to an emission of gravitational waves. It is, however, not clear yet how the development of the PPI is affected by the presence of a magnetic field and by the concurrent development of the magnetorotational instability (MRI). We present a numerical analysis using three-dimensional GRMHD simulations of the interplay between the PPI and the MRI considering, for the first time, an analytical magnetized equilibrium solution as initial condition. In the purely hydrodynamic case, the PPI selects as expected the large-scale m = 1 azimuthal mode as the fastest growing and non-linearly dominant mode. However, when the torus is threaded by a weak toroidal magnetic field, the development of the MRI leads to the suppression of large-scale modes and redistributes power across smaller scales. If the system starts with a significantly excited m = 1 mode, the PPI can be dominant in a transient phase, before being ultimately quenched by the MRI. Such dynamics may well be important in compact star mergers and tidal disruption events.

Effects of cobalt precursor on pyrolyzed carbon-supported cobalt-polypyrrole as electrocatalyst toward oxygen reduction reaction

PubMed Central

2013-01-01

A series of non-precious metal electrocatalysts, namely pyrolyzed carbon-supported cobalt-polypyrrole, Co-PPy-TsOH/C, are synthesized with various cobalt precursors, including cobalt acetate, cobalt nitrate, cobalt oxalate, and cobalt chloride. The catalytic performance towards oxygen reduction reaction (ORR) is comparatively investigated with electrochemical techniques of cyclic voltammogram, rotating disk electrode and rotating ring-disk electrode. The results are analyzed and discussed employing physiochemical techniques of X-ray diffraction, transmission electron microscopy, Raman spectroscopy, X-ray photoelectron spectroscopy, inductively coupled plasma, elemental analysis, and extended X-ray absorption fine structure. It shows that the cobalt precursor plays an essential role on the synthesis process as well as microstructure and performance of the Co-PPy-TsOH/C catalysts towards ORR. Among the studied Co-PPy-TsOH/C catalysts, that prepared with cobalt acetate exhibits the best ORR performance. The crystallite/particle size of cobalt and its distribution as well as the graphitization degree of carbon in the catalyst greatly affects the catalytic performance of Co-PPy-TsOH/C towards ORR. Metallic cobalt is the main component in the active site in Co-PPy-TsOH/C for catalyzing ORR, but some other elements such as nitrogen are probably involved, too. PMID:24229351

Efficacy of Proton Pump Inhibitors for Patients with Duodenal Ulcers: A Pairwise and Network Meta-Analysis of Randomized Controlled Trials

PubMed Central

Hu, Zhan-Hong; Shi, Ai-Ming; Hu, Duan-Min; Bao, Jun-Jie

2017-01-01

Background/Aim: To compare the efficacy and tolerance of different proton pump inhibitors (PPIs) in different doses for patients with duodenal ulcers. Materials and Methods: An electronic database was searched to collect all randomized clinical trials (RCTs), and a pairwise and network meta-analysis were performed. Results: A total of 24 RCTs involving 6188 patients were included. The network meta-analysis showed that there were no significant differences for the 4-week healing rate of duodenal ulcer treated with different PPI regimens except pantoprazle 40 mg/d versus lansoprazole 15 mg/d [Relative risk (RR) = 3.57; 95% confidence interval (CI) = 1.36–10.31)] and lansoprazole 30 mg/d versus lansoprazole 15 mg/d (RR = 2.45; 95% CI = 1.01–6.14). In comparison with H2 receptor antagonists (H2 RA), pantoprazole 40 mg/d and lansoprazole 30 mg/d significantly increase the healing rate (RR = 2.96; 95% CI = 1.78–5.14 and RR = 2.04; 95% CI = 1.13–3.53, respectively). There was no significant difference for the rate of adverse events between different regimens, including H2 RA for a duration of 4-week of follow up. Conclusion: There was no significant difference for the efficacy and tolerance between the ordinary doses of different PPIs with the exception of lansoprazle 15 mg/d. PMID:28139495

Delayed-type hypersensitivity reactions induced by proton pump inhibitors: A clinical and in vitro T-cell reactivity study.

PubMed

Lin, C-Y; Wang, C-W; Hui, C-Y R; Chang, Y-C; Yang, C-H; Cheng, C-Y; Chen, W-W; Ke, W-M; Chung, W-H

2018-01-01

Proton pump inhibitors (PPIs) have been known to induce type I hypersensitivity reactions. However, severe delayed-type hypersensitivity reactions (DHR) induced by PPI, such as Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), or drug rash with eosinophilia and systemic symptoms (DRESS), are rarely reported. We conducted a study of a large series of PPI-related DHR, followed up their tolerability to alternative anti-ulcer agents, and investigated the T-cell reactivity to PPI in PPI-related DHR patients. We retrospectively analyzed patients with PPI-related DHR from multiple medical centers in Taiwan during the study period January 2003 to April 2016. We analyzed the causative PPI, clinical manifestations, organ involvement, treatment, and complications. We also followed up the potential risk of cross-hypersensitivity or tolerability to other PPI after their hypersensitivity episodes. Drug lymphocyte activation test (LAT) was conducted by measuring granulysin and interferon-γ to confirm the causalities. There were 69 cases of PPI-related DHR, including SJS/TEN (n=27) and DRESS (n=10). The LAT by measuring granulysin showed a sensitivity of 59.3% and specificity of 96.4%. Esomeprazole was the most commonly involved in PPI-related DHR (51%). Thirteen patients allergic to one kind of PPI could tolerate other structurally different PPI without cross-hypersensitivity reactions, whereas three patients developed cross-hypersensitivity reactions to alternative structurally similar PPI. The cross-reactivity to structurally similar PPI was also observed in LAT assay. PPIs have the potential to induce life-threatening DHR. In patients when PPI is necessary for treatment, switching to structurally different alternatives should be considered. © 2017 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd.

A patient and public involvement (PPI) toolkit for meaningful and flexible involvement in clinical trials - a work in progress.

PubMed

Bagley, Heather J; Short, Hannah; Harman, Nicola L; Hickey, Helen R; Gamble, Carrol L; Woolfall, Kerry; Young, Bridget; Williamson, Paula R

2016-01-01

Funders of research are increasingly requiring researchers to involve patients and the public in their research. Patient and public involvement (PPI) in research can potentially help researchers make sure that the design of their research is relevant, that it is participant friendly and ethically sound. Using and sharing PPI resources can benefit those involved in undertaking PPI, but existing PPI resources are not used consistently and this can lead to duplication of effort. This paper describes how we are developing a toolkit to support clinical trials teams in a clinical trials unit. The toolkit will provide a key 'off the shelf' resource to support trial teams with limited resources, in undertaking PPI. Key activities in further developing and maintaining the toolkit are to: ● listen to the views and experience of both research teams and patient and public contributors who use the tools; ● modify the tools based on our experience of using them; ● identify the need for future tools; ● update the toolkit based on any newly identified resources that come to light; ● raise awareness of the toolkit and ● work in collaboration with others to either develop or test out PPI resources in order to reduce duplication of work in PPI. Background Patient and public involvement (PPI) in research is increasingly a funder requirement due to the potential benefits in the design of relevant, participant friendly, ethically sound research. The use and sharing of resources can benefit PPI, but available resources are not consistently used leading to duplication of effort. This paper describes a developing toolkit to support clinical trials teams to undertake effective and meaningful PPI. Methods The first phase in developing the toolkit was to describe which PPI activities should be considered in the pathway of a clinical trial and at what stage these activities should take place. This pathway was informed through review of the type and timing of PPI activities within trials coordinated by the Clinical Trials Research Centre and previously described areas of potential PPI impact in trials. In the second phase, key websites around PPI and identification of resources opportunistically, e.g. in conversation with other trialists or social media, were used to identify resources. Tools were developed where gaps existed. Results A flowchart was developed describing PPI activities that should be considered in the clinical trial pathway and the point at which these activities should happen. Three toolkit domains were identified: planning PPI; supporting PPI; recording and evaluating PPI. Four main activities and corresponding tools were identified under the planning for PPI: developing a plan; identifying patient and public contributors; allocating appropriate costs; and managing expectations. In supporting PPI, tools were developed to review participant information sheets. These tools, which require a summary of potential trial participant characteristics and circumstances help to clarify requirements and expectations of PPI review. For recording and evaluating PPI, the planned PPI interventions should be monitored in terms of impact, and a tool to monitor public contributor experience is in development. Conclusions This toolkit provides a developing 'off the shelf' resource to support trial teams with limited resources in undertaking PPI. Key activities in further developing and maintaining the toolkit are to: listen to the views and experience of both research teams and public contributors using the tools, to identify the need for future tools, to modify tools based on experience of their use; to update the toolkit based on any newly identified resources that come to light; to raise awareness of the toolkit and to work in collaboration with others to both develop and test out PPI resources in order to reduce duplication of work in PPI.

The role of emotion regulation in the relations between psychopathy factors and impulsive and premeditated aggression.

PubMed

Long, Katherine; Felton, Julia W; Lilienfeld, Scott O; Lejuez, Carl W

2014-10-01

Given the high rates of aggressive behavior among highly psychopathic individuals, much research has sought to clarify the nature of the relation between psychopathy and aggression. The present study examined relations between Fearless Dominance (PPI FD), Self-Centered Impulsivity (PPI SCI), and Coldheartedness (PPI CH) Factors of the Psychopathic Personality Inventory (PPI; Lilienfeld & Andrews, 1996) and aggression dimensions (premeditated and impulsive aggression) in a sample of substance users receiving inpatient treatment. At the univariate level, PPI FD traits were significantly and positively related to premeditated aggression, but were not significantly related to impulsive aggression. PPI SCI traits were positively related to both forms of aggression, whereas PPI CH was not significantly related to either aggression dimension. Emotion regulation difficulties, as measured by the Difficulties with Emotion Regulation Scale (DERS; Gratz & Roemer, 2004), were negatively related to PPI FD traits, positively related to PPI SCI traits, and negatively related to PPI CH traits. Both PPI SCI and PPI FD traits exerted significant indirect effects on impulsive aggression through the DERS. In contrast, the DERS did not mediate the relations between psychopathic traits and premeditated aggression. Results provide a more nuanced understanding of the psychopathy-aggression relations and suggest that difficulties with emotion regulation may be an important mediator of the relations between psychopathy factors and impulsive aggression. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

The Role of Emotion Regulation in the Relations between Psychopathy Factors and Impulsive and Premeditated Aggression

PubMed Central

Long, Katherine; Felton, Julia W.; Lilienfeld, Scott O.; Lejuez, Carl W.

2014-01-01

Given the high rates of aggressive behavior among highly psychopathic individuals, much research has sought to clarify the nature of the relation between psychopathy and aggression. The present study examined relations between Fearless Dominance (PPI FD), Self-Centered Impulsivity (PPI SCI), and Coldheartedness (PPI CH) Factors of the Psychopathic Personality Inventory (PPI; Lilienfeld & Andrews, 1996) and aggression dimensions (premeditated and impulsive aggression) in a sample of substance users receiving inpatient treatment. At the univariate level, PPI FD traits were significantly and positively related to premeditated aggression, but were not significantly related to impulsive aggression. PPI SCI traits were positively related to both forms of aggression, whereas PPI CH was not significantly related to either aggression dimension. Emotion regulation difficulties, as measured by the Difficulties with Emotion Regulation Scale (DERS; Gratz & Roemer, 2004), were negatively related to PPI FD traits, positively related to PPI SCI traits, and negatively related to PPI CH traits. Both PPI SCI and PPI FD traits exerted significant indirect effects on impulsive aggression through the DERS. In contrast, the DERS did not mediate the relations between psychopathic traits and premeditated aggression. Results provide a more nuanced understanding of the psychopathy-aggression relations and suggest that difficulties with emotion regulation may be an important mediator of the relations between psychopathy factors and impulsive aggression. PMID:25198433

A Combined Molecular Dynamics and Experimental Study of Doped Polypyrrole.

PubMed

Fonner, John M; Schmidt, Christine E; Ren, Pengyu

2010-10-01

Polypyrrole (PPy) is a biocompatible, electrically conductive polymer that has great potential for battery, sensor, and neural implant applications. Its amorphous structure and insolubility, however, limit the experimental techniques available to study its structure and properties at the atomic level. Previous theoretical studies of PPy in bulk are also scarce. Using ab initio calculations, we have constructed a molecular mechanics force field of chloride-doped PPy (PPyCl) and undoped PPy. This model has been designed to integrate into the OPLS force field, and parameters are available for the Gromacs and TINKER software packages. Molecular dynamics (MD) simulations of bulk PPy and PPyCl have been performed using this force field, and the effects of chain packing and electrostatic scaling on the bulk polymer density have been investigated. The density of flotation of PPyCl films has been measured experimentally. Amorphous X-ray diffraction of PPyCl was obtained and correlated with atomic structures sampled from MD simulations. The force field reported here is foundational for bridging the gap between experimental measurements and theoretical calculations for PPy based materials.

Visualization of protein interaction networks: problems and solutions

PubMed Central

2013-01-01

Background Visualization concerns the representation of data visually and is an important task in scientific research. Protein-protein interactions (PPI) are discovered using either wet lab techniques, such mass spectrometry, or in silico predictions tools, resulting in large collections of interactions stored in specialized databases. The set of all interactions of an organism forms a protein-protein interaction network (PIN) and is an important tool for studying the behaviour of the cell machinery. Since graphic representation of PINs may highlight important substructures, e.g. protein complexes, visualization is more and more used to study the underlying graph structure of PINs. Although graphs are well known data structures, there are different open problems regarding PINs visualization: the high number of nodes and connections, the heterogeneity of nodes (proteins) and edges (interactions), the possibility to annotate proteins and interactions with biological information extracted by ontologies (e.g. Gene Ontology) that enriches the PINs with semantic information, but complicates their visualization. Methods In these last years many software tools for the visualization of PINs have been developed. Initially thought for visualization only, some of them have been successively enriched with new functions for PPI data management and PIN analysis. The paper analyzes the main software tools for PINs visualization considering four main criteria: (i) technology, i.e. availability/license of the software and supported OS (Operating System) platforms; (ii) interoperability, i.e. ability to import/export networks in various formats, ability to export data in a graphic format, extensibility of the system, e.g. through plug-ins; (iii) visualization, i.e. supported layout and rendering algorithms and availability of parallel implementation; (iv) analysis, i.e. availability of network analysis functions, such as clustering or mining of the graph, and the possibility to interact with external databases. Results Currently, many tools are available and it is not easy for the users choosing one of them. Some tools offer sophisticated 2D and 3D network visualization making available many layout algorithms, others tools are more data-oriented and support integration of interaction data coming from different sources and data annotation. Finally, some specialistic tools are dedicated to the analysis of pathways and cellular processes and are oriented toward systems biology studies, where the dynamic aspects of the processes being studied are central. Conclusion A current trend is the deployment of open, extensible visualization tools (e.g. Cytoscape), that may be incrementally enriched by the interactomics community with novel and more powerful functions for PIN analysis, through the development of plug-ins. On the other hand, another emerging trend regards the efficient and parallel implementation of the visualization engine that may provide high interactivity and near real-time response time, as in NAViGaTOR. From a technological point of view, open-source, free and extensible tools, like Cytoscape, guarantee a long term sustainability due to the largeness of the developers and users communities, and provide a great flexibility since new functions are continuously added by the developer community through new plug-ins, but the emerging parallel, often closed-source tools like NAViGaTOR, can offer near real-time response time also in the analysis of very huge PINs. PMID:23368786

Chemical polymerization and characterization of surfactant directed of polypyrrole-tannin-CTAB nanocomposites

NASA Astrophysics Data System (ADS)

Abdi, Mahnaz M.; Azli, Nur Farhana Waheeda Mohd; Lim, Hong Ngee; Tahir, Paridah Md; Razalli, Rawaida Liyana; Hoong, Yeoh Beng

2017-12-01

In this research, Tannin (TA) from Acacia mangium tree was used to modify polypyrrole (PPy) composite with enhanced physical and structural properties. Composite nanostructure preparation was done in the presence of cationic surfactant, cetyltrimethylammonium bromide (CTAB) to improve surface area and electron transferring of resulting polymer. The Fourier Transform InfraRed (FT-IR) spectrum showed the characteristics peaks of functional group of PPy, TA, and CTAB in the resulting composite indicating the incorporation of TA and CTAB into PPy structure. The spherical structure was observed for PPy/TA prepared in the presence of CTAB with higher porosity compared with the PPy/TA. Cyclic voltammograms of modified SPE electrode using Ppy/TA/CTAB showed enhanced current response compared with the electrode modified by only PPy or PPy/TA.

Patient and public involvement in the early stages of clinical trial development: a systematic cohort investigation

PubMed Central

Gamble, Carrol; Dudley, Louise; Allam, Alison; Bell, Philip; Goodare, Heather; Hanley, Bec; Preston, Jennifer; Walker, Alison; Williamson, Paula; Young, Bridget

2014-01-01

Background Randomised controlled trials (RCTs) are considered particularly likely to benefit from patient and public involvement (PPI). Decisions made by professional researchers at the outset may go on to have a significant impact on the potential for PPI contributions. Objective To increase knowledge of PPI within the early development of RCTs by systematically describing the reported level, nature and acceptability of proposed PPI to the funders. Methods Documentation from the outline application process for all RCTs that received funding from the Health Technology Assessment (HTA) Programme 2006–2010 was requested. For each application, data were extracted on trial characteristics, references to PPI in the development of the outline application and funding Board feedback, and plans for PPI in the full application and after the trial was funded. Results 110 applications were eligible with outline applications available for 90 (82%). The cohort covered a wide range of interventions and conditions. 54% (49/90) provided some information about PPI. 26 (28.9%) indicated PPI within the development of the outline application itself; 32 (35.6%) planned involvement in the full application and 43 (48%) once the trial was funded. Recruitment at diagnosis and surgical interventions were less likely to describe PPI. Blinded trials and trials in which participants may receive placebo only, more frequently described PPI activity. The HTA commissioning Board feedback rarely referred to PPI. Conclusions Incorporation of PPI within the development of the outline application or specification of plans for future involvement was low. Funder requests for applicants to provide information on PPI and justification for its absence should be welcomed but further research is needed to identify the impact of this on its contributions to research. Comments on PPI by reviewers should be directional rather than state that an increase is required. Challenges facing applicants in initiating PPI prior to funding need to be addressed. PMID:25056972

Use of poultry protein isolate as a food ingredient: sensory and color characteristics of low-fat Turkey bologna.

PubMed

Omana, Dileep A; Pietrasik, Zeb; Betti, Mirko

2012-07-01

The potential of using poultry protein isolate (PPI) as a food ingredient to substitute either soy protein isolate (SPI) or meat protein in turkey bologna was investigated. PPI was prepared from mechanically separated turkey meat using pH-shift technology and the prepared PPI was added to turkey bologna at 2 different concentrations (1.5% and 2% dry weight basis). Product characteristics were compared with those prepared with the addition of 2% SPI, 11% meat protein (control-1), or 13% meat protein (control-2). All the 5 treatments were subjected to sensory analysis to evaluate aroma, appearance, color, flavor, saltiness, juiciness, firmness, and overall acceptability of the turkey bologna samples using 9-point hedonic scales. A turkey bologna control sample with 11% meat protein appeared to be softer compared to other treatments as revealed by texture profile analysis while purge loss during storage in a retail display case was significantly (P < 0.05) higher compared to other treatments. Lightness (L*) value of the products decreased during 4 wk of retail storage. A turkey bologna control sample with 13% meat protein appeared to be darker and more reddish compared to other treatments. Replacing meat protein with protein isolates caused increase in yellowish color of turkey bologna. Sensory analysis concluded that 1.5% PPI and 2% PPI could be used as substitute of SPI or lean meat and the treatments could be improved by increasing saltiness and decreasing firmness. The study revealed that with slight modifications in saltiness, turkey bologna can be prepared with the addition of poultry protein isolates as an acceptable substitute for soy protein isolate or meat protein. This will help to avoid usage of nonmeat ingredients (as SPI substitute) and to reduce the cost of production (as meat protein substitute) of low-fat turkey bologna. © 2012 Institute of Food Technologists®

Assessment of regional air quality by a concentration-dependent Pollution Permeation Index

PubMed Central

Liang, Chun-Sheng; Liu, Huan; He, Ke-Bin; Ma, Yong-Liang

2016-01-01

Although air quality monitoring networks have been greatly improved, interpreting their expanding data in both simple and efficient ways remains challenging. Therefore, needed are new analytical methods. We developed such a method based on the comparison of pollutant concentrations between target and circum areas (circum comparison for short), and tested its applications by assessing the air pollution in Jing-Jin-Ji, Yangtze River Delta, Pearl River Delta and Cheng-Yu, China during 2015. We found the circum comparison can instantly judge whether a city is a pollution permeation donor or a pollution permeation receptor by a Pollution Permeation Index (PPI). Furthermore, a PPI-related estimated concentration (original concentration plus halved average concentration difference) can be used to identify some overestimations and underestimations. Besides, it can help explain pollution process (e.g., Beijing’s PM2.5 maybe largely promoted by non-local SO2) though not aiming at it. Moreover, it is applicable to any region, easy-to-handle, and able to boost more new analytical methods. These advantages, despite its disadvantages in considering the whole process jointly influenced by complex physical and chemical factors, demonstrate that the PPI based circum comparison can be efficiently used in assessing air pollution by yielding instructive results, without the absolute need for complex operations. PMID:27731344

A novel highly selective and sensitive detection of serotonin based on Ag/polypyrrole/Cu2O nanocomposite modified glassy carbon electrode.

PubMed

Selvarajan, S; Suganthi, A; Rajarajan, M

2018-06-01

A silver/polypyrrole/copper oxide (Ag/PPy/Cu 2 O) ternary nanocomposite was prepared by sonochemical and oxidative polymerization simple way, in which Cu 2 O was decorated with Ag nanoparticles, and covered by polyprrole (PPy) layer. The as prepared materials was characterized by UV-vis-spectroscopy (UV-vis), FT-IR, X-ray diffraction (XRD), thermo-gravimetric analysis (TGA), scanning electron microscopy (SEM) with EDX, high resolution transmission electron microscopy (HR-TEM) and X-ray photoelectron spectroscopy (XPS). Sensing of serotonin (5HT) was evaluated electrocatalyst using polypyrrole/glassy carbon electrode (PPy/GCE), polypyrrole/copper oxide/glassy carbon electrode (PPy/Cu 2 O/GCE) and silver/polypyrrole/copper oxide/glassy carbon electrode (Ag/PPy/Cu 2 O/GCE). The Ag/PPy/Cu 2 O/GCE was electrochemically treated in 0.1MPBS solution through cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The peak current response increases linearly with 5-HT concentration from 0.01 to 250 µmol L -1 and the detection limit was found to be 0.0124 μmol L -1 . It exhibits high electrocatalytic activity, satisfactory repeatability, stability, fast response and good selectivity against potentially interfering species, which suggests its potential in the development of sensitive, selective, easy-operation and low-cost serotonin sensor for practical routine analyses. The proposed method is potential to expand the possible applied range of the nanocomposite material for detection of various concerned electro active substances. Copyright © 2018 Elsevier B.V. All rights reserved.

Quantitative determination and evaluation of Paris polyphylla var. yunnanensis with different harvesting times using UPLC-UV-MS and FT-IR spectroscopy in combination with partial least squares discriminant analysis.

PubMed

Yang, Yuan-Gui; Zhang, Ji; Zhao, Yan-Li; Zhang, Jin-Yu; Wang, Yuan-Zhong

2017-07-01

A rapid method was developed and validated by ultra-performance liquid chromatography-triple quadrupole mass spectroscopy with ultraviolet detection (UPLC-UV-MS) for simultaneous determination of paris saponin I, paris saponin II, paris saponin VI and paris saponin VII. Partial least squares discriminant analysis (PLS-DA) based on UPLC and Fourier transform infrared (FT-IR) spectroscopy was employed to evaluate Paris polyphylla var. yunnanensis (PPY) at different harvesting times. Quantitative determination implied that the various contents of bioactive compounds with different harvesting times may lead to different pharmacological effects; the average content of total saponins for PPY harvested at 8 years was higher than that from other samples. The PLS-DA of FT-IR spectra had a better performance than that of UPLC for discrimination of PPY from different harvesting times. Copyright © 2016 John Wiley & Sons, Ltd.

Elucidating the Construct Validity of the Psychopathic Personality Inventory Triarchic Scales.

PubMed

Sellbom, Martin; Wygant, Dustin B; Drislane, Laura E

2015-01-01

This study sought to replicate and extend Hall and colleagues' (2014) work on developing and validating scales from the Psychopathic Personality Inventory (PPI) to index the triarchic psychopathy constructs of boldness, meanness, and disinhibition. This study also extended Hall et al.'s initial findings by including the PPI Revised (PPI-R). A community sample (n = 240) weighted toward subclinical psychopathy traits and a male prison sample (n = 160) were used for this study. Results indicated that PPI-Boldness, PPI-Meanness, and PPI-Disinhibition converged with other psychopathy, personality, and behavioral criteria in ways conceptually expected from the perspective of the triarchic psychopathy model, including showing very strong convergent and discriminant validity with their Triarchic Psychopathy Measure counterparts. These findings further enhance the utility of the PPI and PPI-R in measuring these constructs.

Ultrasonic vocalizations, predictability and sensorimotor gating in the rat

PubMed Central

Webber, Emily S.; Mankin, David E.; McGraw, Justin J.; Beckwith, Travis J.; Cromwell, Howard C.

2013-01-01

Prepulse inhibition (PPI) is a measure of sensorimotor gating in diverse groups of animals including humans. Emotional states can influence PPI in humans both in typical subjects and in individuals with mental illness. Little is known about emotional regulation during PPI in rodents. We used ultrasonic vocalization recording to monitor emotional states in rats during PPI testing. We altered the predictability of the PPI trials to examine any alterations in gating and emotional regulation. We also examined PPI in animals selectively bred for high or low levels of 50 kHz USV emission. Rats emitted high levels of 22 kHz calls consistently throughout the PPI session. USVs were sensitive to prepulses during the PPI session similar to startle. USV rate was sensitive to predictability among the different levels tested and across repeated experiences. Startle and inhibition of startle were not affected by predictability in a similar manner. No significant differences for PPI or startle were found related the different levels of predictability; however, there was a reduction in USV signals and an enhancement of PPI after repeated exposure. Animals selectively bred to emit high levels of USVs emitted significantly higher levels of USVs during the PPI session and a reduced ASR compared to the low and random selective lines. Overall, the results support the idea that PPI tests in rodents induce high levels of negative affect and that manipulating emotional styles of the animals alters the negative impact of the gating session as well as the intensity of the startle response. PMID:23850353

Integrating participatory community mobilization processes to improve dengue prevention: an eco-bio-social scaling up of local success in Machala, Ecuador.

PubMed

Mitchell-Foster, Kendra; Ayala, Efraín Beltrán; Breilh, Jaime; Spiegel, Jerry; Wilches, Ana Arichabala; Leon, Tania Ordóñez; Delgado, Jefferson Adrian

2015-02-01

This project investigates the effectiveness and feasibility of scaling-up an eco-bio-social approach for implementing an integrated community-based approach for dengue prevention in comparison with existing insecticide-based and emerging biolarvicide-based programs in an endemic setting in Machala, Ecuador. An integrated intervention strategy (IIS) for dengue prevention (an elementary school-based dengue education program, and clean patio and safe container program) was implemented in 10 intervention clusters from November 2012 to November 2013 using a randomized controlled cluster trial design (20 clusters: 10 intervention, 10 control; 100 households per cluster with 1986 total households). Current existing dengue prevention programs served as the control treatment in comparison clusters. Pupa per person index (PPI) is used as the main outcome measure. Particular attention was paid to social mobilization and empowerment with IIS. Overall, IIS was successful in reducing PPI levels in intervention communities versus control clusters, with intervention clusters in the six paired clusters that followed the study design experiencing a greater reduction of PPI compared to controls (2.2 OR, 95% CI: 1.2 to 4.7). Analysis of individual cases demonstrates that consideration for contexualizing programs and strategies to local neighborhoods can be very effective in reducing PPI for dengue transmission risk reduction. In the rapidly evolving political climate for dengue control in Ecuador, integration of successful social mobilization and empowerment strategies with existing and emerging biolarvicide-based government dengue prevention and control programs is promising in reducing PPI and dengue transmission risk in southern coastal communities like Machala. However, more profound analysis of social determination of health is called for to assess sustainability prospects. © The author 2015. The World Health Organization has granted Oxford University Press permission for the reproduction of this article.

The Association of Schizophrenia Risk -Amino Acid Oxidase Polymorphisms With Sensorimotor Gating, Working Memory and Personality in Healthy Males

PubMed Central

Roussos, Panos; Giakoumaki, Stella G; Adamaki, Eva; Anastasios, Georgakopoulos; Nikos, Robakis K; Bitsios, Panos

2011-01-01

There is evidence supporting a role for the -amino acid oxidase (DAO) locus in schizophrenia. This study aimed to determine the relationship of five single-nucleotide polymorphisms (SNPs) within the DAO gene identified as promising schizophrenia risk genes (rs4623951, rs2111902, rs3918346, rs3741775, and rs3825251) to acoustic startle, prepulse inhibition (PPI), working memory, and personality dimensions. A highly homogeneous study entry cohort (n=530) of healthy, young male army conscripts (n=703) originating from the Greek LOGOS project (Learning On Genetics Of Schizophrenia Spectrum) underwent PPI of the acoustic startle reflex, working memory, and personality assessment. The QTPHASE from the UNPHASED package was used for the association analysis of each SNP or haplotype data, with p-values corrected for multiple testing by running 10 000 permutations of the data. The rs4623951_T-rs3741775_G and rs4623951_T-rs2111902_T diplotypes were associated with reduced PPI and worse performance in working memory tasks and a personality pattern characterized by attenuated anxiety. Median stratification analysis of the risk diplotype group (ie, those individuals homozygous for the T and G alleles (TG+)) showed reduced PPI and working memory performance only in TG+ individuals with high trait anxiety. The rs4623951_T allele, which is the DAO polymorphism most strongly associated with schizophrenia, might tag a haplotype that affects PPI, cognition, and personality traits in general population. Our findings suggest an influence of the gene in the neural substrate mediating sensorimotor gating and working memory, especially when combined with high anxiety and further validate DAO as a candidate gene for schizophrenia and spectrum disorders. PMID:21471957

Use of histamine H2 receptor antagonists and outcomes in patients with heart failure: a nationwide population-based cohort study.

PubMed

Adelborg, Kasper; Sundbøll, Jens; Schmidt, Morten; Bøtker, Hans Erik; Weiss, Noel S; Pedersen, Lars; Sørensen, Henrik Toft

2018-01-01

Histamine H 2 receptor activation promotes cardiac fibrosis and apoptosis in mice. However, the potential effectiveness of histamine H 2 receptor antagonists (H2RAs) in humans with heart failure is largely unknown. We examined the association between H2RA initiation and all-cause mortality among patients with heart failure. Using Danish medical registries, we conducted a nationwide population-based active-comparator cohort study of new users of H2RAs and proton pump inhibitors (PPIs) after first-time hospitalization for heart failure during the period 1995-2014. Hazard ratios (HRs) for all-cause mortality and hospitalization due to worsening of heart failure, adjusting for age, sex, and time between heart failure diagnosis and initiation of PPI or H2RA therapy, index year, comorbidity, cardiac surgery, comedications, and socioeconomic status were computed based on Cox regression analysis. Our analysis included 42,902 PPI initiators (median age 78 years, 46% female) and 3,296 H2RA initiators (median age 76 years, 48% female). Mortality risk was lower among H2RA initiators than PPI initiators after 1 year (26% vs 31%) and 5 years (60% vs 66%). In multivariable analyses, the 1-year HR was 0.80 (95% CI, 0.74-0.86) and the 5-year HR was 0.85 (95% CI, 0.80-0.89). These findings were consistent after propensity score matching and for ischemic and nonischemic heart failure, as for sex and age groups. The rate of hospitalization due to worsening of heart failure was lower among H2RA initiators than PPI initiators. In patients with heart failure, H2RA initiation was associated with 15%-20% lower mortality than PPI initiation.

Integrating participatory community mobilization processes to improve dengue prevention: an eco-bio-social scaling up of local success in Machala, Ecuador

PubMed Central

Mitchell-Foster, Kendra; Ayala, Efraín Beltrán; Breilh, Jaime; Spiegel, Jerry; Wilches, Ana Arichabala; Leon, Tania Ordóñez; Delgado, Jefferson Adrian

2015-01-01

Background This project investigates the effectiveness and feasibility of scaling-up an eco-bio-social approach for implementing an integrated community-based approach for dengue prevention in comparison with existing insecticide-based and emerging biolarvicide-based programs in an endemic setting in Machala, Ecuador. Methods An integrated intervention strategy (IIS) for dengue prevention (an elementary school-based dengue education program, and clean patio and safe container program) was implemented in 10 intervention clusters from November 2012 to November 2013 using a randomized controlled cluster trial design (20 clusters: 10 intervention, 10 control; 100 households per cluster with 1986 total households). Current existing dengue prevention programs served as the control treatment in comparison clusters. Pupa per person index (PPI) is used as the main outcome measure. Particular attention was paid to social mobilization and empowerment with IIS. Results Overall, IIS was successful in reducing PPI levels in intervention communities versus control clusters, with intervention clusters in the six paired clusters that followed the study design experiencing a greater reduction of PPI compared to controls (2.2 OR, 95% CI: 1.2 to 4.7). Analysis of individual cases demonstrates that consideration for contexualizing programs and strategies to local neighborhoods can be very effective in reducing PPI for dengue transmission risk reduction. Conclusions In the rapidly evolving political climate for dengue control in Ecuador, integration of successful social mobilization and empowerment strategies with existing and emerging biolarvicide-based government dengue prevention and control programs is promising in reducing PPI and dengue transmission risk in southern coastal communities like Machala. However, more profound analysis of social determination of health is called for to assess sustainability prospects. PMID:25604763

Clinical, but not oesophageal pH-impedance, profiles predict response to proton pump inhibitors in gastro-oesophageal reflux disease.

PubMed

Zerbib, Frank; Belhocine, Kafia; Simon, Mireille; Capdepont, Maylis; Mion, François; Bruley des Varannes, Stanislas; Galmiche, Jean-Paul

2012-04-01

Approximately 30% of patients with gastro-oesophageal reflux disease (GORD) do not achieve adequate symptom control with proton pump inhibitors (PPIs). The aim of this study was to determine whether any symptom profile or reflux pattern was associated with refractoriness to PPI therapy. Patients with typical GORD symptoms (heartburn and/or regurgitation) were included and had 24 h pH-impedance monitoring off therapy. Patients were considered to be responders if they had fewer than 2 days of mild symptoms per week while receiving a standard or double dose of PPI treatment for at least 4 weeks. Both clinical and reflux parameters were taken into account for multivariate analysis (logistic regression). One hundred patients were included (median age 50 years, 42 male), 43 responders and 57 non-responders. Overall, multivariate analysis showed that the factors associated with the absence of response were absence of oesophagitis (p=0.050), body mass index (BMI) ≤25 kg/m(2) (p=0.002) and functional dyspepsia (FD) (p=0.001). In patients who reported symptoms during the recording (n=85), the factors associated with PPI failure were BMI ≤25 kg/m(2) (p=0.004), FD (p=0.009) and irritable bowel syndrome (p=0.045). In patients with documented GORD (n=67), the factors associated with PPI failure were absence of oesophagitis (p=0.040), FD (p=0.003), irritable bowel syndrome (p=0.012) and BMI ≤25 kg/m(2) (p=0.029). No reflux pattern demonstrated by 24 h pH-impedance monitoring is associated with response to PPIs in patients with GORD symptoms. In contrast, absence of oesophagitis, presence of functional digestive disorders and BMI ≤25 kg/m(2) are strongly associated with PPI failure.

Proton Pump Inhibitors Increase Risk for Hepatic Encephalopathy in Patients With Cirrhosis in A Population Study.

PubMed

Tsai, Chia-Fen; Chen, Mu-Hong; Wang, Yen-Po; Chu, Chi-Jen; Huang, Yi-Hsiang; Lin, Han-Chieh; Hou, Ming-Chih; Lee, Fa-Yauh; Su, Tung-Ping; Lu, Ching-Liang

2017-01-01

Hepatic encephalopathy (HE) is a serious complication of cirrhosis and is associated with gut dysbiosis. Proton pump inhibitors (PPIs), frequently prescribed to patients with cirrhosis, can contribute to small-bowel bacterial overgrowth. We investigated whether PPI predisposes patients with cirrhosis to HE using a large database of patients. We performed a case-control study nested within a sample of Taiwan National Health Insurance beneficiaries (n = 1,000,000), followed up longitudinally from 1998 through 2011. Patients with cirrhosis and an occurrence of HE (n = 1166) were selected as the case cohort and matched to patients without HE (1:1, controls) for sex, enrollment time, end point time, follow-up period, and advanced cirrhosis. Information on prescribed drugs, drug dosage, supply days, and numbers of dispensed pills was extracted from the Taiwan National Health Insurance database. PPI use was defined as more than 30 cumulative defined daily doses (cDDDs); PPI nonuse was defined as 30 cDDDs or fewer. We performed logistic regression analyses to estimate the association between PPI use and the occurrence of HE. Among patients with cirrhosis and an occurrence of HE, 38% (n = 445) had a history of PPI use before HE occurrence. We observed a relationship between dose of PPI taken and HE risk. The confounder-adjusted odd ratios were 1.41 (95% confidence interval [CI], 1.09-1.84), 1.51 (95% CI, 1.11-2.06), and 3.01 (95% CI, 1.78-5.10) for patients with 30-120 cDDDs, 120-365 cDDDs, and more than 365 cDDDs, respectively, compared with PPI nonusers. All categories of PPIs, except rabeprazole, were associated with an increased risk of HE. Based on an analysis of data from Taiwan National Health Insurance beneficiaries, we found that use of PPIs in patients with cirrhosis increases the risk for HE; risk increases with dose. It therefore is important for health care providers to carefully consider prolonged PPI use by patients with cirrhosis. Copyright © 2017. Published by Elsevier Inc.

Preparation of polypyrrole-embedded electrospun poly(lactic acid) nanofibrous scaffolds for nerve tissue engineering

PubMed Central

Zhou, Jun-feng; Wang, Yi-guo; Cheng, Liang; Wu, Zhao; Sun, Xiao-dan; Peng, Jiang

2016-01-01

Polypyrrole (PPy) is a biocompatible polymer with good conductivity. Studies combining PPy with electrospinning have been reported; however, the associated decrease in PPy conductivity has not yet been resolved. We embedded PPy into poly(lactic acid) (PLA) nanofibers via electrospinning and fabricated a PLA/PPy nanofibrous scaffold containing 15% PPy with sustained conductivity and aligned topography. There was good biocompatibility between the scaffold and human umbilical cord mesenchymal stem cells as well as Schwann cells. Additionally, the direction of cell elongation on the scaffold was parallel to the direction of fibers. Our findings suggest that the aligned PLA/PPy nanofibrous scaffold is a promising biomaterial for peripheral nerve regeneration. PMID:27904497

Potential Interference of Protein-Protein Interactions by Graphyne.

PubMed

Luan, Binquan; Huynh, Tien; Zhou, Ruhong

2016-03-10

Graphyne has attracted tremendous attention recently due to its many potentially superior properties relative to those of graphene. Although extensive efforts have been devoted to explore the applicability of graphyne as an alternative nanomaterial for state-of-the-art nanotechnology (including biomedical applications), knowledge regarding its possible adverse effects to biological cells is still lacking. Here, using large-scale all-atom molecular dynamics simulations, we investigate the potential toxicity of graphyne by interfering a protein-protein interaction (ppI). We found that graphyne could indeed disrupt the ppIs by cutting through the protein-protein interface and separating the protein complex into noncontacting ones, due to graphyne's dispersive and hydrophobic interaction with the hydrophobic residues residing at the dimer interface. Our results help to elucidate the mechanism of interaction between graphyne and ppI networks within a biological cell and provide insights for its hazard reduction.

Insight into the ionotropic gelation of chitosan using tripolyphosphate and pyrophosphate as cross-linkers.

PubMed

Sacco, Pasquale; Paoletti, Sergio; Cok, Michela; Asaro, Fioretta; Abrami, Michela; Grassi, Mario; Donati, Ivan

2016-11-01

Ionotropic gelation of chitosan by means of opposite charged ions represents an efficient alternative to covalent reticulation because of milder condition of use and, in general, higher biocompatibility of the resulting systems. In this work 90° light scattering (turbidimetry), circular dichroism (CD) and 1 H NMR measurements have been performed to study the interactions between the biopolymer and ionic cross-linkers tripolyphosphate (TPP) and pyrophosphate (PPi) in dilute solutions. Thereafter, a dialysis-based technique was exploited to fabricate tridimensional chitosan hydrogels based on both polyanions. Resulting matrices showed a different mechanical behavior because of their peculiar mesh-texture at micro/nano-scale: in the present contribution we demonstrate that TPP and PPi favor the formation of homogeneous and inhomogeneous systems, respectively. The different texture of networks could be exploited in future for the preparation of systems for the controlled release of molecules. Copyright © 2016 Elsevier B.V. All rights reserved.

Protein-protein interaction analysis of Alzheimer`s disease and NAFLD based on systems biology methods unhide common ancestor pathways.

PubMed

Karbalaei, Reza; Allahyari, Marzieh; Rezaei-Tavirani, Mostafa; Asadzadeh-Aghdaei, Hamid; Zali, Mohammad Reza

2018-01-01

Analysis reconstruction networks from two diseases, NAFLD and Alzheimer`s diseases and their relationship based on systems biology methods. NAFLD and Alzheimer`s diseases are two complex diseases, with progressive prevalence and high cost for countries. There are some reports on relation and same spreading pathways of these two diseases. In addition, they have some similar risk factors, exclusively lifestyle such as feeding, exercises and so on. Therefore, systems biology approach can help to discover their relationship. DisGeNET and STRING databases were sources of disease genes and constructing networks. Three plugins of Cytoscape software, including ClusterONE, ClueGO and CluePedia, were used to analyze and cluster networks and enrichment of pathways. An R package used to define best centrality method. Finally, based on degree and Betweenness, hubs and bottleneck nodes were defined. Common genes between NAFLD and Alzheimer`s disease were 190 genes that used construct a network with STRING database. The resulting network contained 182 nodes and 2591 edges and comprises from four clusters. Enrichment of these clusters separately lead to carbohydrate metabolism, long chain fatty acid and regulation of JAK-STAT and IL-17 signaling pathways, respectively. Also seven genes selected as hub-bottleneck include: IL6, AKT1, TP53, TNF, JUN, VEGFA and PPARG. Enrichment of these proteins and their first neighbors in network by OMIM database lead to diabetes and obesity as ancestors of NAFLD and AD. Systems biology methods, specifically PPI networks, can be useful for analyzing complicated related diseases. Finding Hub and bottleneck proteins should be the goal of drug designing and introducing disease markers.

Sensorimotor Gating in Neurotensin-1 Receptor Null Mice

PubMed Central

Feifel, D.; Pang, Z.; Shilling, P.D.; Melendez, G.; Schreiber, R.; Button, D.

2009-01-01

BACKGROUND Converging evidence has implicated endogenous neurotensin (NT) in the pathophysiology of brain processes relevant to schizophrenia. Prepulse inhibition of the startle reflex (PPI) is a measure of sensorimotor gating and considered to be of strong relevance to neuropsychiatric disorders associated with psychosis and cognitive dysfunction. Mice genetically engineered to not express NT display deficits in PPI that model the PPI deficits seen in schizophrenia patients. NT1 receptors have been most strongly implicated in mediating the psychosis relevant effects of NT such as attenuating PPI deficits. To investigate the role of NT1 receptors in the regulation of PPI, we measured baseline PPI in wildtype (WT) and NT1 knockout (KO) mice. We also tested the effects of amphetamine and dizocilpine, a dopamine agonist and NMDA antagonist, respectively, that reduce PPI as well as the NT1 selective receptor agonist, PD149163, known to increase PPI in rats. METHODS Baseline PPI and acoustic startle response were measured in WT and NT1 knockout KO mice. After baseline testing, mice were tested again after receiving intraperatoneal (IP) saline or one of three doses of amphetamine (1.0, 3.0 and 10.0 mg/kg), dizocilpine (0.3, 1.0 and 3.0 mg/kg) and PD149163 (0.5, 2.0 and 6.0 mg/kg) on separate test days. RESULTS Baseline PPI and acoustic startle response in NT1 KO mice were not significantly different from NT1 WT mice. WT and KO mice exhibited similar responses to the PPI-disrupting effects of dizocilpine and amphetamine. PD149163 significantly facilitated PPI (P < 0.004) and decreased the acoustic startle response (P < 0.001) in WT but not NT1 KO mice. CONCLUSIONS The data does not support the regulation of baseline PPI or the PPI disruptive effects of amphetamine or dizocilpine by endogenous NT acting at the NT1 receptor, although they support the antipsychotic potential of pharmacological activation of NT1 receptors by NT1 agonists. PMID:19596359

Identification of GRB2 and GAB1 Coexpression as an Unfavorable Prognostic Factor for Hepatocellular Carcinoma by a Combination of Expression Profile and Network Analysis

PubMed Central

Yang, Mei; Wang, Danhua; Yu, Lingxiang; Guo, Chaonan; Guo, Xiaodong; Lin, Na

2013-01-01

Aim To screen novel markers for hepatocellular carcinoma (HCC) by a combination of expression profile, interaction network analysis and clinical validation. Methods HCC significant molecules which are differentially expressed or had genetic variations in HCC tissues were obtained from five existing HCC related databases (OncoDB.HCC, HCC.net, dbHCCvar, EHCO and Liverome). Then, the protein-protein interaction (PPI) network of these molecules was constructed. Three topological features of the network ('Degree', 'Betweenness', and 'Closeness') and the k-core algorithm were used to screen candidate HCC markers which play crucial roles in tumorigenesis of HCC. Furthermore, the clinical significance of two candidate HCC markers growth factor receptor-bound 2 (GRB2) and GRB2-associated-binding protein 1 (GAB1) was validated. Results In total, 6179 HCC significant genes and 977 HCC significant proteins were collected from existing HCC related databases. After network analysis, 331 candidate HCC markers were identified. Especially, GAB1 has the highest k-coreness suggesting its central localization in HCC related network, and the interaction between GRB2 and GAB1 has the largest edge-betweenness implying it may be biologically important to the function of HCC related network. As the results of clinical validation, the expression levels of both GRB2 and GAB1 proteins were significantly higher in HCC tissues than those in their adjacent nonneoplastic tissues. More importantly, the combined GRB2 and GAB1 protein expression was significantly associated with aggressive tumor progression and poor prognosis in patients with HCC. Conclusion This study provided an integrative analysis by combining expression profile and interaction network analysis to identify a list of biologically significant HCC related markers and pathways. Further experimental validation indicated that the aberrant expression of GRB2 and GAB1 proteins may be strongly related to tumor progression and prognosis in patients with HCC. The overexpression of GRB2 in combination with upregulation of GAB1 may be an unfavorable prognostic factor for HCC. PMID:24391994

Proton Pump Inhibitors in Gastroesophageal Reflux Disease: Friend or Foe.

PubMed

Gyawali, C Prakash

2017-09-01

Proton pump inhibitor (PPI) use in gastroesophageal reflux disease (GERD) has been redefined, in light of recent advances highlighting GERD phenotypes that respond to PPIs, and fresh revelations of potential risks of long-term PPI therapy. Erosive esophagitis predicts excellent response to PPI therapy, but non-erosive reflux disease (NERD) with abnormal reflux parameters on ambulatory reflux monitoring also demonstrates a similar response. In contrast, response is suboptimal in the absence of abnormal reflux parameters. In this setting, if an alternate appropriate indication for PPI therapy does not coexist, risks may outweigh benefits of PPI therapy. Adverse events from long-term PPI therapy continue to be reported, most based on association rather than cause-and-effect. Appropriate indications need to be established before embarking on long-term PPI therapy. Future research will define true risks of long-term PPI therapy, and develop alternate management options for acid peptic diseases.

Facile Synthesis of SrCO3-Sr(OH)2/PPy Nanocomposite with Enhanced Photocatalytic Activity under Visible Light

PubMed Central

Márquez-Herrera, Alfredo; Ovando-Medina, Victor Manuel; Castillo-Reyes, Blanca Estela; Zapata-Torres, Martin; Meléndez-Lira, Miguel; González-Castañeda, Jaquelina

2016-01-01

Pyrrole monomer was chemically polymerized onto SrCO3-Sr(OH)2 powders to obtain SrCO3-Sr(OH)2/polypyrrole nanocomposite to be used as a candidate for photocatalytic degradation of methylene blue dye (MB). The material was characterized by Fourier transform infrared (FTIR) spectroscopy, UV/Vis spectroscopy, and X-ray diffraction (XRD). It was observed from transmission electronic microscopy (TEM) analysis that the reported synthesis route allows the production of SrCO3-Sr(OH)2 nanoparticles with particle size below 100 nm which were embedded within a semiconducting polypyrrole matrix (PPy). The SrCO3-Sr(OH)2 and SrCO3-Sr(OH)2/PPy nanocomposites were tested in the photodegradation of MB dye under visible light irradiation. Also, the effects of MB dye initial concentration and the catalyst load on photodegradation efficiency were studied and discussed. Under the same conditions, the efficiency of photodegradation of MB employing the SrCO3-Sr(OH)2/PPy nanocomposite increases as compared with that obtained employing the SrCO3-Sr(OH)2 nanocomposite. PMID:28787830

Patient and public involvement in the early stages of clinical trial development: a systematic cohort investigation.

PubMed

Gamble, Carrol; Dudley, Louise; Allam, Alison; Bell, Philip; Goodare, Heather; Hanley, Bec; Preston, Jennifer; Walker, Alison; Williamson, Paula; Young, Bridget

2014-07-23

Randomised controlled trials (RCTs) are considered particularly likely to benefit from patient and public involvement (PPI). Decisions made by professional researchers at the outset may go on to have a significant impact on the potential for PPI contributions. To increase knowledge of PPI within the early development of RCTs by systematically describing the reported level, nature and acceptability of proposed PPI to the funders. Documentation from the outline application process for all RCTs that received funding from the Health Technology Assessment (HTA) Programme 2006-2010 was requested. For each application, data were extracted on trial characteristics, references to PPI in the development of the outline application and funding Board feedback, and plans for PPI in the full application and after the trial was funded. 110 applications were eligible with outline applications available for 90 (82%). The cohort covered a wide range of interventions and conditions. 54% (49/90) provided some information about PPI. 26 (28.9%) indicated PPI within the development of the outline application itself; 32 (35.6%) planned involvement in the full application and 43 (48%) once the trial was funded. Recruitment at diagnosis and surgical interventions were less likely to describe PPI. Blinded trials and trials in which participants may receive placebo only, more frequently described PPI activity. The HTA commissioning Board feedback rarely referred to PPI. Incorporation of PPI within the development of the outline application or specification of plans for future involvement was low. Funder requests for applicants to provide information on PPI and justification for its absence should be welcomed but further research is needed to identify the impact of this on its contributions to research. Comments on PPI by reviewers should be directional rather than state that an increase is required. Challenges facing applicants in initiating PPI prior to funding need to be addressed. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions.

PubMed

Hayashi, Takanori; Matsuzaki, Yuri; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka

2018-05-08

Protein-protein interactions (PPIs) play several roles in living cells, and computational PPI prediction is a major focus of many researchers. The three-dimensional (3D) structure and binding surface are important for the design of PPI inhibitors. Therefore, rigid body protein-protein docking calculations for two protein structures are expected to allow elucidation of PPIs different from known complexes in terms of 3D structures because known PPI information is not explicitly required. We have developed rapid PPI prediction software based on protein-protein docking, called MEGADOCK. In order to fully utilize the benefits of computational PPI predictions, it is necessary to construct a comprehensive database to gather prediction results and their predicted 3D complex structures and to make them easily accessible. Although several databases exist that provide predicted PPIs, the previous databases do not contain a sufficient number of entries for the purpose of discovering novel PPIs. In this study, we constructed an integrated database of MEGADOCK PPI predictions, named MEGADOCK-Web. MEGADOCK-Web provides more than 10 times the number of PPI predictions than previous databases and enables users to conduct PPI predictions that cannot be found in conventional PPI prediction databases. In MEGADOCK-Web, there are 7528 protein chains and 28,331,628 predicted PPIs from all possible combinations of those proteins. Each protein structure is annotated with PDB ID, chain ID, UniProt AC, related KEGG pathway IDs, and known PPI pairs. Additionally, MEGADOCK-Web provides four powerful functions: 1) searching precalculated PPI predictions, 2) providing annotations for each predicted protein pair with an experimentally known PPI, 3) visualizing candidates that may interact with the query protein on biochemical pathways, and 4) visualizing predicted complex structures through a 3D molecular viewer. MEGADOCK-Web provides a huge amount of comprehensive PPI predictions based on docking calculations with biochemical pathways and enables users to easily and quickly assess PPI feasibilities by archiving PPI predictions. MEGADOCK-Web also promotes the discovery of new PPIs and protein functions and is freely available for use at http://www.bi.cs.titech.ac.jp/megadock-web/ .

PPI layouts: BioJS components for the display of Protein-Protein Interactions

PubMed Central

Salazar, Gustavo A.; Meintjes, Ayton; Mulder, Nicola

2014-01-01

Summary: We present two web-based components for the display of Protein-Protein Interaction networks using different self-organizing layout methods: force-directed and circular. These components conform to the BioJS standard and can be rendered in an HTML5-compliant browser without the need for third-party plugins. We provide examples of interaction networks and how the components can be used to visualize them, and refer to a more complex tool that uses these components. Availability: http://github.com/biojs/biojs; http://dx.doi.org/10.5281/zenodo.7753 PMID:25075288

Probing the Extent of Randomness in Protein Interaction Networks

DTIC Science & Technology

2008-07-11

other [54]. This characteristic is exemplified in Video S1, which contains a three-dimensional animation of the HT E . coli PPI network determined by...experiment using either yeast two-hybrid (Y2H) or tandem affinity purification (TAP) methodology: C. jejuni [18], E . coli (HT1) [12], E . coli (HT2...DCDWa C. jejuni [18] 1331 11664 0.095 0.095 2.91 2.85 E . coli (HT1) [12] 1289 5420 0.083 0.089 3.60 3.29 (HT2) [13] 3047 11477 0.064 0.085 3.37 3.27 C

Associations of Proton-Pump Inhibitors and H2 Receptor Antagonists with Chronic Kidney Disease: A Meta-Analysis.

PubMed

Wijarnpreecha, Karn; Thongprayoon, Charat; Chesdachai, Supavit; Panjawatanana, Panadeekarn; Ungprasert, Patompong; Cheungpasitporn, Wisit

2017-10-01

The aim of this meta-analysis was to assess the risks of chronic kidney disease (CKD) and/or end-stage kidney disease (ESRD) in patients who are taking proton-pump inhibitors (PPIs) and/or H2 receptor antagonists (H2RAs). Comprehensive literature review was conducted utilizing MEDLINE and EMBASE databases through April 2017 to identify all studies that investigated the risks of CKD or ESRD in patients taking PPIs/H2RAs versus those without PPIs/H2RAs. Pooled risk ratios (RR) and 95% confidence interval (CI) were calculated using a random-effect, generic inverse variance method of DerSimonian and Laird. The protocol for this study is registered with PROSPERO (International Prospective Register of Systematic Reviews; no. CRD42017067252). Five studies with 536,902 participants were patients were identified and included in the data analysis. When compared with non-PPIs users, the pooled risk ratio (RR) of CKD or ESRD in patients with PPI use was 1.33 (95% CI 1.18-1.51). Pre-specified subgroup analysis (stratified by CKD or ESRD status) demonstrated pooled RRs of 1.22 (95% CI 1.14-1.30) for association between PPI use and CKD and 1.88 (95% CI 1.71-2.06) for association between PPI use and ESRD, respectively. However, there was no association between the use of H2RAs and CKD with a pooled RR of 1.02 (95% CI 0.83-1.25). When compared with the use of H2RAs, the pooled RR of CKD in patients with PPI use was 1.29 (95% CI 1.22-1.36). Our study demonstrates statistically significant 1.3-fold increased risks of CKD and ESRD in patients using PPIs, but not in patients using H2RAs.

Ultrasonic vocalizations, predictability and sensorimotor gating in the rat.

PubMed

Webber, Emily S; Mankin, David E; McGraw, Justin J; Beckwith, Travis J; Cromwell, Howard C

2013-09-15

Prepulse inhibition (PPI) is a measure of sensorimotor gating in diverse groups of animals including humans. Emotional states can influence PPI in humans both in typical subjects and in individuals with mental illness. Little is known about emotional regulation during PPI in rodents. We used ultrasonic vocalization recording to monitor emotional states in rats during PPI testing. We altered the predictability of the PPI trials to examine any alterations in gating and emotional regulation. We also examined PPI in animals selectively bred for high or low levels of 50kHz USV emission. Rats emitted high levels of 22kHz calls consistently throughout the PPI session. USVs were sensitive to prepulses during the PPI session similar to startle. USV rate was sensitive to predictability among the different levels tested and across repeated experiences. Startle and inhibition of startle were not affected by predictability in a similar manner. No significant differences for PPI or startle were found related to the different levels of predictability; however, there was a reduction in USV signals and an enhancement of PPI after repeated exposure. Animals selectively bred to emit high levels of USVs emitted significantly higher levels of USVs during the PPI session and a reduced ASR compared to the low and random selective lines. Overall, the results support the idea that PPI tests in rodents induce high levels of negative affect and that manipulating emotional styles of the animals alters the negative impact of the gating session as well as the intensity of the startle response. Copyright © 2013 Elsevier B.V. All rights reserved.

Cannabidiol Affects MK-801-Induced Changes in the PPI Learned Response of Capuchin Monkeys (Sapajus spp.).

PubMed

Saletti, Patricia G; Maior, Rafael S; Barros, Marilia; Nishijo, Hisao; Tomaz, Carlos

2017-01-01

There are several lines of evidence indicating a possible therapeutic action of cannabidiol (CBD) in schizophrenia treatment. Studies with rodents have demonstrated that CBD reverses MK-801 effects in prepulse inhibition (PPI) disruption, which may indicate that CBD acts by improving sensorimotor gating deficits. In the present study, we investigated the effects of CBD on a PPI learned response of capuchin monkeys ( Sapajus spp.). A total of seven monkeys were employed in this study. In Experiment 1, we evaluated the CBD (doses of 15, 30, 60 mg/kg, i.p.) effects on PPI. In Experiment 2, the effects of sub-chronic MK-801 (0.02 mg/kg, i.m.) on PPI were challenged by a CBD pre-treatment. No changes in PPI response were observed after CBD-alone administration. However, MK-801 increased the PPI response of our animals. CBD pre-treatment blocked the PPI increase induced by MK-801. Our findings suggest that CBD's reversal of the MK-801 effects on PPI is unlikely to stem from a direct involvement on sensorimotor mechanisms, but may possibly reflect its anxiolytic properties.

Centralities in simplicial complexes. Applications to protein interaction networks.

PubMed

Estrada, Ernesto; Ross, Grant J

2018-02-07

Complex networks can be used to represent complex systems which originate in the real world. Here we study a transformation of these complex networks into simplicial complexes, where cliques represent the simplices of the complex. We extend the concept of node centrality to that of simplicial centrality and study several mathematical properties of degree, closeness, betweenness, eigenvector, Katz, and subgraph centrality for simplicial complexes. We study the degree distributions of these centralities at the different levels. We also compare and describe the differences between the centralities at the different levels. Using these centralities we study a method for detecting essential proteins in PPI networks of cells and explain the varying abilities of the centrality measures at the different levels in identifying these essential proteins. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ovarian Cancer Differential Interactome and Network Entropy Analysis Reveal New Candidate Biomarkers.

PubMed

Ayyildiz, Dilara; Gov, Esra; Sinha, Raghu; Arga, Kazim Yalcin

2017-05-01

Ovarian cancer is one of the most common cancers and has a high mortality rate due to insidious symptoms and lack of robust diagnostics. A hitherto understudied concept in cancer pathogenesis may offer new avenues for innovation in ovarian cancer biomarker development. Cancer cells are characterized by an increase in network entropy, and several studies have exploited this concept to identify disease-associated gene and protein modules. We report in this study the changes in protein-protein interactions (PPIs) in ovarian cancer within a differential network (interactome) analysis framework utilizing the entropy concept and gene expression data. A compendium of six transcriptome datasets that included 140 samples from laser microdissected epithelial cells of ovarian cancer patients and 51 samples from healthy population was obtained from Gene Expression Omnibus, and the high confidence human protein interactome (31,465 interactions among 10,681 proteins) was used. The uncertainties of the up- or downregulation of PPIs in ovarian cancer were estimated through an entropy formulation utilizing combined expression levels of genes, and the interacting protein pairs with minimum uncertainty were identified. We identified 105 proteins with differential PPI patterns scattered in 11 modules, each indicating significantly affected biological pathways in ovarian cancer such as DNA repair, cell proliferation-related mechanisms, nucleoplasmic translocation of estrogen receptor, extracellular matrix degradation, and inflammation response. In conclusion, we suggest several PPIs as biomarker candidates for ovarian cancer and discuss their future biological implications as potential molecular targets for pharmaceutical development as well. In addition, network entropy analysis is a concept that deserves greater research attention for diagnostic innovation in oncology and tumor pathogenesis.

Contractor Past Performance Information (PPI) in Source Selection: A Comparison Study of Public and Private Sector

DTIC Science & Technology

2005-03-17

private sector . However, along the way, Government and private sector industry have begun to disagree about how PPI is collected and how PPI is used. Industry prefers a passive system of collecting delivery and quality data during contract performance, while the Federal Government uses both a passive system (similar to industry) as well as an active system of pulling PPI during contract performance. Industry uses PPI to establish and maintain a preferred vendor list from which to solicit bids, quotes, or proposals, while government uses PPI to assess

Effects of the PPy layer thickness on Co-PPy composite films

NASA Astrophysics Data System (ADS)

Haciismailoglu, Murside

2015-11-01

Co-PPy composite films were electrodeposited on ITO substrate from two different solutions potentiostatically. Firstly, the PPy layers with the thicknesses changing from 20 to 5000 nm were produced on ITO. Then Co was electrodeposited on these PPy/ITO substrates with a charge density of 1000 mC cm-2. The electrochemical properties were investigated by the current density-time transients and the variation of the elapsed time for the Co deposition depending on the PPy layer thickness. X-ray photoelectron (XPS) spectra indicated the presence of both Co metal and its oxides on the surface. The weak reflections of the Co3O4, CoO and hcp Co were detected by the X-ray diffraction (XRD) technique. According to scanning electron microscopy (SEM) images, the thickness of the PPy layer strongly affects the Co nucleation. The composite films with the PPy layer thinner than 200 nm and thicker than 2000 nm have an isotropic magnetic behavior due to the symmetrical crystal field. The composite films with the PPy layer thicknesses between 200 and 2000 nm have an anisotropic magnetic behavior attributable to the deterioration of this symmetrical crystal field by the PPy bubbles on the surface. All films are hard magnetic material, since the coercivities are larger than 125 Oe.

Myopathy including polymyositis: a likely class adverse effect of proton pump inhibitors?

PubMed

Clark, David W J; Strandell, Johanna

2006-06-01

Polymyositis occurring in patients treated with omeprazole has been signalled as a possible adverse drug reaction (ADR) by the New Zealand Intensive Medicines Monitoring Programme (IMMP) and the WHO Collaborating Centre for International Drug Monitoring: the Uppsala Monitoring Centre (UMC). Polymyositis and other myopathies have also been reported in post-marketing data and in the medical literature in association with proton pump inhibitor (PPI) use. We wished to follow-up these signals and investigate the evidence of causality for the association of polymyositis and other myopathy with PPI use. Spontaneously reported ADRs from national monitoring centres are sent to the WHO ADR database (VigiBase). VigiBase was searched for case reports of the PPIs, omeprazole, pantoprazole, lansoprazole, esomeprazole and rabeprazole, with terms indicative of myopathy, and further information was elicited from the national centres to help establish causality. Literature sources were reviewed for the occurrence of the above terms in combination with PPIs. In total, there were 292 reports of various myopathies with PPIs, excluding 868 cases of 'myalgia'. In this analysis, 69 patients recovered when the drug was withdrawn and, in 15 patients, the reaction re-occurred when the drug was reinstated. In one-third of the 292 cases, the PPI was the single administered drug, and the PPI was the single suspected drug by the reporter in 57% of reports where concomitant medication was used. In this analysis, three index cases are documented. One involves the same patient taking three different PPIs (lansoprazole, esomeprazole and rabeprazole) at different time periods, with myalgia and muscle weakness occurring with all three drugs. In the two other index cases, myopathies with esomeprazole and omeprazole were reported with positive rechallenge, and causality was assessed as 'possible' and 'certain' by the reporting centres. In 27 cases myositis or polymyositis was reported. Other myopathies were reported, including 35 cases with rhabdomyolysis. In 9 of these cases, the PPI was withdrawn and the reaction abated. The PPI was reinstated in one patient, but the reaction did not re-occur. Time to onset was given in 17 of the rhabdomyolysis cases, rhabdomyolysis occurred with the first week in 9 cases, and in 3 cases the reaction occurred between 14 days to 3 months of treatment. In 12 of these patients, an HMG-CoA reductase inhibitor (statin) was taken concomitantly. Case reports from the WHO ADR database, including index cases involving four out of five PPIs, along with evidence of a possible mechanism, provide compelling evidence that there is a causal association between members of the PPI drug class and myopathy including polymyositis. Evidence was also obtained to support the view that PPI use may be associated with occurrence of other myopathies, including the serious reaction rhabdomyolysis.

Electromagnetic interference attenuation and shielding effect of quaternary Epoxy-PPy/Fe3O4-ZnO nanocomposite as a broad band microwave-absorber

NASA Astrophysics Data System (ADS)

Olad, Ali; Shakoori, Sahar

2018-07-01

An increase in the electromagnetic wave pollution generated from wireless telecommunication devices has devoted to a great request for exploiting microwave absorbing materials for themselves. The combination of inherently conducting polymers such as polypyrrole (PPy) with metal oxides has led to design ideal microwave absorbing materials which benefit both advantage effects of ICPs and metal oxide nanoparticles. Herein, the quaternary nanocomposite of Epoxy-PPy/Fe3O4-ZnO was prepared and tested for the absorption of X-band microwaves. Simultaneous application of metal oxides and conducting polypyrrole in the epoxy matrix was evaluated in order to increase the absorption intensity and broadness of microwaves in X-band region. The morphology, microstructure, and phase structure of Fe3O4, ZnO, and PPy, as well as quaternary nanocomposite were characterized and studied using FTIR, XRD, FESEM and TEM techniques. The presence of nanoparticles in the quaternary nanocomposite was confirmed by EDS. The magnetization of iron oxide was studied by VSM. The synergetic effect of iron oxide and zinc oxide nanoparticles in different weight ratios (Fe3O4/ZnO) on the electromagnetic wave absorption was evaluated. The electromagnetic parameters have been evaluated by the vector network analyzer in the frequency range of 8.2-12.4 GHz which is named as X-band region and is adequate for radar applications. The electromagnetic wave absorbing outcomes indicated that Epoxy-PPy/Fe3O4-ZnO quaternary nanocomposite has wide absorption area and high attenuation, which is believed to be due to dielectric loss properties related to the polypyrrole, magnetic loss factor of Fe3O4, and synergetic effects of components. The maximum reflection loss reached to -32.53 dB at 9.96 GHz with a nanocomposite thickness of 2 mm which is dedicated to the Epoxy-PPy/Fe3O4-ZnO with iron oxide to zinc oxide ratio of 2:1. The absorption bandwidth with the reflection loss lower than -10 dB (90% attenuation) was up to 4.2 GHz that covering a frequency range of 8.2-12.4 GHz. Results showed that absorber having %15 (w/w) polypyrrole/epoxy resin in Epoxy-PPy/Fe3O4-ZnO nanocomposite with iron oxide to zinc oxide ratio of 2:1 displays the best reflection loss properties. The loss curves illustrated the values of dielectric loss tangent and magnetic loss tangent of prepared nanocomposites which are in the range of 0.25-0.7 and -0.08 to 0.09 respectively. Therefore, microwave absorption mechanism is probably attributed to dielectric loss.

Healthcare resource utilization with ixazomib or placebo plus lenalidomide-dexamethasone in the randomized, double-blind, phase 3 TOURMALINE-MM1 study in relapsed/refractory multiple myeloma.

PubMed

Hari, Parameswaran; Lin, Huamao Mark; Zhu, Yanyan; Berg, Deborah; Richardson, Paul G; Moreau, Philippe

2018-05-29

The aim of this analysis was to assess healthcare resource utilization in the pivotal phase 3 TOURMALINE-MM1 study of the oral proteasome inhibitor ixazomib or placebo plus lenalidomide and dexamethasone (Rd) in relapsed and/or refractory multiple myeloma (RRMM). In this double-blind, placebo-controlled, randomized study (NCT01564537), 722 patients with RRMM following 1-3 prior lines of therapy received Rd plus ixazomib (ixazomib-Rd; n = 360) or matching placebo (placebo-Rd; n = 362) until disease progression or unacceptable toxicity. Healthcare resource utilization data were captured on Day 1 of each 28-day cycle, every 4 weeks during follow-up for progression-free survival, and every 12 weeks during subsequent follow-up, and included medical encounters (length of stay, inpatient, outpatient, and reason) and number of missing days from work or other activities for patients and caregivers. Exposure-adjusted rates of hospitalization were similar between the ixazomib-Rd and placebo-Rd arms, at 0.530 and 0.564 per patient year (ppy), respectively, as were outpatient visit rates (3.305 and 3.355 ppy). Mean length of hospitalization per patient was 10.0 and 10.8 days, respectively. In both arms, hospitalization and outpatient visit rates were higher in patients with two or three prior lines of treatment (ixazomib-Rd: 0.632 and 3.909 ppy; placebo-Rd: 0.774 and 3.539 ppy) compared with patients with one prior line (ixazomib-Rd: 0.460 and 2.888 ppy; placebo-Rd: 0.436 and 3.243 ppy). Patients and their caregivers who missed any work or other activity missed a median of 7 and 5 days in the ixazomib-Rd arm, respectively, vs 8 and 4 days with placebo-Rd. The study was not powered for a statistical comparison of healthcare resource utilization between treatment arms, nor did it capture costs associated with utilization of the identified healthcare resources. This pre-specified analysis demonstrated that the all-oral triplet regimen of ixazomib added to Rd did not increase healthcare resource utilization compared with placebo-Rd.

[Adherence with proton pump inhibitor therapy, by continuously taking nonsteroidal anti-inflammatory drugs].

PubMed

Pimanov, S I; Makarenko, E V; Dikareva, E A

2015-01-01

To estimate the impact of adherence with proton pump inhibitor (PPI) therapy on the incidence of nonsteroidal anti-inflammatory drug (NSAID)-induced gastropathy (NSAID gastropathy) in patients with rheumatoid arthritis (RA). PPI pharmacotherapy adherence was estimated using the Medication Adherence Questionnaire (MAQ) in 92 patients with RA, including 32 patients did not take a PPI and 60 used a PPI. The groups were matched for age, disease duration, and used NSAIDs. All those asked underwent video esophagogastroduodenoscopy. According to the data of MAQ survey, low, moderate, and high adherence subgroups could be identified among the patients treated with a PPI. NSAID gastropathy was detected in 43.8% of the patients taking no PPI, in 50% of those with low PPI treatment adherence, in 12.5% with moderate adherence, and in 4.5% with high adherence. In the patients with low adherence to PPI therapy, NSAID gastropathy was recorded 11 times more frequently than in those with high adherence (c2 = 7.77; p = 0.005). This condition occurred in 28.6% of the patients taking NSAID without preventively using a PPI in the absence of risk factors for NSAID gastropathy. Only 36.7% patients who had been recommended to use a PPI for the prevention of NSAID gastropathy strictly observed their doctor's directions. Low PPI pharmacotherapy adherence may serve as an additional risk factor for NSAID gastropathy in patients in whom preventive antisecretory therapy used in combination with NSAID is indicated.

Effects of proton pump inhibitors on lung cancer precise radiotherapy-induced radiation pneumonitis.

PubMed

Su, QiaoLi; Wang, Duoning; Yuan, Bo; Liu, Feng; Lei, Yi; Li, Shuangqing

2014-11-01

The objective of this study was to explore the effects of proton pump inhibitors (PPIs) on the development and prognosis of lung cancer precise radiotherapy-induced radiation pneumonitis. Clinical materials of 84 lung cancer patients who had radiation pneumonitis after precise radiotherapy were retrospectively analyzed, and the patients were divided into PPI group and control group, according to whether or not PPIs were applied. The development and prognosis of patients and the effects of different doses of PPI on patient condition from two groups were compared. There were 57 PPI cases in PPI group and 27 cases in control group. Basic characteristics of patients were not statistically different between the two groups; however, white blood cell count, oxygenation indexes, blood gas pH, and lung imaging index were significantly different (p < 0.05), indicating that radiation pneumonitis tended to be more severe in PPI group. As regards effects of PPI on prognosis of two groups, remission rate of radiation pneumonia in PPI group was significantly less than that of the control group. Among 57 cases in PPI group, there were 31 patients applied with PPI ≤ 1DDD and 31 patients applied with PPI > 1DDD. In comparison of the various parameters of patients, 7 days after being applied with different doses of PPI, there were no significant differences between the parameters of radiation pneumonitis. PPIs should be cautiously utilized to avoid the effects of lung cancer radiotherapy-induced radiation pneumonia.

NetGen: a novel network-based probabilistic generative model for gene set functional enrichment analysis.

PubMed

Sun, Duanchen; Liu, Yinliang; Zhang, Xiang-Sun; Wu, Ling-Yun

2017-09-21

High-throughput experimental techniques have been dramatically improved and widely applied in the past decades. However, biological interpretation of the high-throughput experimental results, such as differential expression gene sets derived from microarray or RNA-seq experiments, is still a challenging task. Gene Ontology (GO) is commonly used in the functional enrichment studies. The GO terms identified via current functional enrichment analysis tools often contain direct parent or descendant terms in the GO hierarchical structure. Highly redundant terms make users difficult to analyze the underlying biological processes. In this paper, a novel network-based probabilistic generative model, NetGen, was proposed to perform the functional enrichment analysis. An additional protein-protein interaction (PPI) network was explicitly used to assist the identification of significantly enriched GO terms. NetGen achieved a superior performance than the existing methods in the simulation studies. The effectiveness of NetGen was explored further on four real datasets. Notably, several GO terms which were not directly linked with the active gene list for each disease were identified. These terms were closely related to the corresponding diseases when accessed to the curated literatures. NetGen has been implemented in the R package CopTea publicly available at GitHub ( http://github.com/wulingyun/CopTea/ ). Our procedure leads to a more reasonable and interpretable result of the functional enrichment analysis. As a novel term combination-based functional enrichment analysis method, NetGen is complementary to current individual term-based methods, and can help to explore the underlying pathogenesis of complex diseases.

MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform.

PubMed

Gupta, Surya; De Puysseleyr, Veronic; Van der Heyden, José; Maddelein, Davy; Lemmens, Irma; Lievens, Sam; Degroeve, Sven; Tavernier, Jan; Martens, Lennart

2017-05-01

Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments. MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT. jan.tavernier@vib-ugent.be or lennart.martens@vib-ugent.be. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

Mechanisms of CCl4-induced liver fibrosis with combined transcriptomic and proteomic analysis.

PubMed

Dong, Shu; Chen, Qi-Long; Song, Ya-Nan; Sun, Yang; Wei, Bin; Li, Xiao-Yan; Hu, Yi-Yang; Liu, Ping; Su, Shi-Bing

2016-01-01

The classic toxicity of carbon tetrachloride (CCl4) is to induce liver lesion and liver fibrosis. Liver fibrosis is a consequence of chronic liver lesion, which can progress into liver cirrhosis even hepatocarcinoma. However, the toxicological mechanisms of CCl4-induced liver fibrosis remain not fully understood. We combined transcriptomic and proteomic analysis and biological network technology, predicted toxicological targets and regulatory networks of CCl4 in liver fibrosis. Wistar rats were treated with CCl4 for 9 weeks. Histopathological changes, hydroxyproline (Hyp) contents, serum ALT and AST in the CCl4-treated group were significantly higher than that of CCl4-untreated group. CCl4-treated and -untreated liver tissues were examined by microarray and iTRAQ. The results showed that 3535 genes (fold change ≥ 1.5, P < 0.05) and 1412 proteins (fold change ≥ 1.2, P < 0.05) were differentially expressed. Moreover, the integrative analysis of transcriptomics and proteomics data showed 523 overlapped proteins, enriched in 182 GO terms including oxidation reduction, response to oxidative stress, inflammatory response, extracellular matrix organization, etc. Furthermore, KEGG pathway analysis showed that 36 pathways including retinol metabolism, PPAR signaling pathway, glycolysis/gluconeogenesis, arachidonic acid metabolism, metabolism of xenobiotics by cytochrome P450 and drug metabolism. Network of protein-protein interaction (PPI) and key function with their related targets were performed and the degree of network was calculated with Cytoscape. The expression of key targets such as CYP4A3, ALDH2 and ALDH7A1 decreased after CCl4 treatment. Therefore, the toxicological mechanisms of CCl4-induced liver fibrosis may be related with multi biological process, pathway and targets which may provide potential protection reaction mechanism for CCl4 detoxication in the liver.

The effects of the preferential 5-HT2A agonist psilocybin on prepulse inhibition of startle in healthy human volunteers depend on interstimulus interval.

PubMed

Vollenweider, Franz X; Csomor, Philipp A; Knappe, Bernhard; Geyer, Mark A; Quednow, Boris B

2007-09-01

Schizophrenia patients exhibit impairments in prepulse inhibition (PPI) of the startle response. Hallucinogenic 5-HT(2A) receptor agonists are used for animal models of schizophrenia because they mimic some symptoms of schizophrenia in humans and induce PPI deficits in animals. Nevertheless, one report indicates that the 5-HT(2A) receptor agonist psilocybin increases PPI in healthy humans. Hence, we investigated these inconsistent results by assessing the dose-dependent effects of psilocybin on PPI in healthy humans. Sixteen subjects each received placebo or 115, 215, and 315 microg/kg of psilocybin at 4-week intervals in a randomized and counterbalanced order. PPI at 30-, 60-, 120-, 240-, and 2000-ms interstimulus intervals (ISIs) was measured 90 and 165 min after drug intake, coinciding with the peak and post-peak effects of psilocybin. The effects of psilocybin on psychopathological core dimensions and sustained attention were assessed by the Altered States of Consciousness Rating Scale (5D-ASC) and the Frankfurt Attention Inventory (FAIR). Psilocybin dose-dependently reduced PPI at short (30 ms), had no effect at medium (60 ms), and increased PPI at long (120-2000 ms) ISIs, without affecting startle reactivity or habituation. Psilocybin dose-dependently impaired sustained attention and increased all 5D-ASC scores with exception of Auditory Alterations. Moreover, psilocybin-induced impairments in sustained attention performance were positively correlated with reduced PPI at the 30 ms ISI and not with the concomitant increases in PPI observed at long ISIs. These results confirm the psilocybin-induced increase in PPI at long ISIs and reveal that psilocybin also produces a decrease in PPI at short ISIs that is correlated with impaired attention and consistent with deficient PPI in schizophrenia.

Electrically controlled drug release from nanostructured polypyrrole coated on titanium

NASA Astrophysics Data System (ADS)

Sirivisoot, Sirinrath; Pareta, Rajesh; Webster, Thomas J.

2011-02-01

Previous studies have demonstrated that multi-walled carbon nanotubes grown out of anodized nanotubular titanium (MWNT-Ti) can be used as a sensing electrode for various biomedical applications; such sensors detected the redox reactions of certain molecules, specifically proteins deposited by osteoblasts during extracellular matrix bone formation. Since it is known that polypyrrole (PPy) can release drugs upon electrical stimulation, in this study antibiotics (penicillin/streptomycin, P/S) or an anti-inflammatory drug (dexamethasone, Dex), termed PPy[P/S] or PPy[Dex], respectively, were electrodeposited in PPy on titanium. The objective of the present study was to determine if such drugs can be released from PPy on demand and (by applying a voltage) control cellular behavior important for orthopedic applications. Results showed that PPy films possessed nanometer-scale roughness as analyzed by atomic force microscopy. X-ray photoelectron spectroscopy confirmed the presence of P/S and Dex encapsulated within the PPy films. Results from cyclic voltammetry showed that 80% of the drugs were released on demand when sweep voltages were applied for five cycles at a scan rate of 0.1 V s - 1. Furthermore, osteoblast (bone-forming cells) and fibroblast (fibrous tissue-forming cells) adhesion were determined on the PPy films. Results showed that PPy[Dex] enhanced osteoblast adhesion after 4 h of culture compared to plain Ti. PPy-Ti (with or without anionic drug doping) inhibited fibroblast adhesion compared to plain Ti. These in vitro results confirmed that electrodeposited PPy[P/S] and PPy[Dex] can release drugs on demand to potentially fight bacterial infection, reduce inflammation, promote bone growth or reduce fibroblast functions, further implicating the use of such materials as implant sensors.

Reflux parameters as modified by laparoscopic fundoplication in 40 patients with heartburn/regurgitation persisting despite PPI therapy: a study using impedance-pH monitoring.

PubMed

Frazzoni, Marzio; Conigliaro, Rita; Melotti, Gianluigi

2011-04-01

Patients with typical reflux symptoms (heartburn/regurgitation) persisting despite proton pump inhibitor (PPI) therapy are not uncommon. Impedance-pH monitoring detects gastroesophageal reflux at all pH levels and may establish if ongoing symptoms on PPI therapy are associated with acid/nonacid reflux. Laparoscopic fundoplication is a therapeutic option in such patients but reflux parameters on PPI therapy and after intervention and their relationship with symptom persistence/remission have been scarcely studied. The aim of this study was to assess reflux parameters and their relationship with symptoms before and after laparoscopic fundoplication, on and off PPI therapy, respectively, in patients with PPI-unresponsive heartburn/regurgitation and with a positive symptom-reflux association and/or abnormal reflux parameters detected on PPI therapy. Impedance-pH monitoring was performed on high-dose PPI therapy and 3 months after laparoscopic fundoplication, off PPI therapy, in 40 patients with PPI-unresponsive heartburn/regurgitation. Symptoms were scored by a validated questionnaire. Esophageal acid exposure time as well as the number of total and proximal reflux events and of acid and weakly acidic refluxes decreased significantly after surgery: normal values were found in 100, 77, 95, 92 and 65% of cases, respectively. Weakly alkaline refluxes increased significantly postoperatively but neither before nor after intervention were associated with symptoms. All patients reported total/subtotal remission of heartburn/regurgitation 3 months after surgery. Laparoscopic fundoplication improves acid and weakly acidic reflux parameters when compared with PPI therapy. This improvement justifies the very high post-surgical symptom remission rate that we observed. Prolonged follow-up is warranted but our findings strongly support the surgical option in PPI failures.

Sensitivity of the mouse to changes in azimuthal sound location: Angular separation, spectral composition, and sound level

PubMed Central

Allen, Paul D.; Ison, James R.

2010-01-01

Auditory spatial acuity was measured in mice using prepulse inhibition (PPI) of the acoustic startle reflex (ASR) as the indicator response for stimulus detection. The prepulse was a “speaker swap” (SSwap), shifting a noise between two speakers located along the azimuth. Their angular separation, and the spectral composition and sound level of the noise were varied, as was the interstimulus interval (ISI) between SSwap and ASR elicitation. In Experiment 1 a 180° SSwap of wide band noise (WBN) was compared with WBN Onset and Offset. SSwap and WBN Onset had near equal effects, but less than Offset. In Experiment 2 WBN SSwap was measured with speaker separations of 15°, 22.5°, 45°, and 90°. Asymptotic level and the growth rate of PPI increased with increased separation from 15° to 90°, but even the 15° SSwap provided significant PPI for the mean performance of the group. SSwap in Experiment 3 used octave band noise (2–4, 4–8, 8–16, or 16–32 kHz) and separations of 7.5° to 180°. SSwap was most effective for the highest frequencies, with no significant PPI for SSwap below 8–16 kHz, or for separations of 7.5°. In Experiment 4 SSwap had WBN sound levels from 40 to 78 dB SPL, and separations of 22.5°, 45°, 90° and 180°: PPI increased with level, this effect varying with ISI and angular separation. These experiments extend the prior findings on sound localization in mice, and the dependence of PPI on ISI adds a reaction-time-like dimension to this behavioral analysis. PMID:20364886

Proton pump inhibitor use may not prevent high-grade dysplasia and oesophageal adenocarcinoma in Barrett's oesophagus: a nationwide study of 9883 patients.

PubMed

Hvid-Jensen, F; Pedersen, L; Funch-Jensen, P; Drewes, A M

2014-05-01

Proton pump inhibitors (PPI) may potentially modify and decrease the risk for development of oesophageal adenocarcinoma in Barrett's oesophagus (BO). To investigate if the intensity and adherence of PPI use among all patients with BO in Denmark affected the risk of oesophageal adenocarcinoma. We performed a nationwide case-control study in Denmark among 9883 patients with a new diagnosis of BO. All incident oesophageal adenocarcinomas and high-grade dysplasias were identified, and risk ratios were estimated on the basis of prior use of PPIs. Sex- and age-matched BO patients without dysplasia or malignancies in a 10:1 ratio were used for comparison. Conditional logistic regression was used for analysis, adjusting for low-grade dysplasia, gender and medication. We identified 140 cases with incident oesophageal adenocarcinomas and/or high-grade dysplasia, with a median follow-up time of 10.2 years. The relative risk of oesophageal adenocarcinoma or high-grade dysplasia was 2.2 (0.7-6.7) and 3.4 (95% CI: 1.1-10.5) in long-term low- and high-adherence PPI users respectively. No cancer-protective effects from PPI's were seen. In fact, high-adherence and long-term use of PPI were associated with a significantly increased risk of adenocarcinoma or high-grade dysplasia. This could partly be due to confounding by indication or a true negative effect from PPIs. Until the results from future studies hopefully can elucidate the association further, continuous PPI therapy should be directed at symptom control and additional modalities considered as aid or replacement. © 2014 John Wiley & Sons Ltd.

Multiplex detection of protein-protein interactions using a next generation luciferase reporter.

PubMed

Verhoef, Lisette G G C; Mattioli, Michela; Ricci, Fernanda; Li, Yao-Cheng; Wade, Mark

2016-02-01

Cell-based assays of protein-protein interactions (PPIs) using split reporter proteins can be used to identify PPI agonists and antagonists. Generally, such assays measure one PPI at a time, and thus counterscreens for on-target activity must be run in parallel or at a subsequent stage; this increases both the cost and time during screening. Split luciferase systems offer advantages over those that use split fluorescent proteins (FPs). This is since split luciferase offers a greater signal:noise ratio and, unlike split FPs, the PPI can be reversed upon small molecule treatment. While multiplexed PPI assays using luciferase have been reported, they suffer from low signal:noise and require fairly complex spectral deconvolution during analysis. Furthermore, the luciferase enzymes used are large, which limits the range of PPIs that can be interrogated due to steric hindrance from the split luciferase fragments. Here, we report a multiplexed PPI assay based on split luciferases from Photinus pyralis (firefly luciferase, FLUC) and the deep-sea shrimp, Oplophorus gracilirostris (NanoLuc, NLUC). Specifically, we show that the binding of the p53 tumor suppressor to its two major negative regulators, MDM2 and MDM4, can be simultaneously measured within the same sample, without the requirement for complex filters or deconvolution. We provide chemical and genetic validation of this system using MDM2-targeted small molecules and mutagenesis, respectively. Combined with the superior signal:noise and smaller size of split NanoLuc, this multiplexed PPI assay format can be exploited to study the induction or disruption of pairwise interactions that are prominent in many cell signaling pathways. Copyright © 2015 Elsevier B.V. All rights reserved.

Effects of administration of a proton pump inhibitor before endoscopic submucosal dissection for differentiated early gastric cancer with ulcer.

PubMed

Myung, Yu Sik; Hong, Su Jin; Han, Jae Pil; Park, Kyung Woo; Ko, Bong Min; Lee, Moon Sung

2017-01-01

In ulcerative early gastric cancer, improvement and exacerbation of ulceration repeat as a malignant cycle. Moreover, early gastric cancer combined with ulcer is associated with a low curative resection rate and high risk of adverse events. The aim of this study was to investigate the ulcer healing rate and clinical outcomes with the administration of a proton pump inhibitor before endoscopic submucosal dissection for differentiated early gastric cancer with ulcer. A total of 136 patients with differentiated early gastric cancer with ulcer who met the expanded indications for endoscopic submucosal dissection were reviewed between June 2005 and June 2014. Eighty-one patients were given PPI before endoscopic submucosal dissection and 55 patients were not given PPI. The complete ulcer healing rate was significantly different between the two groups (59.3 % vs. 23.6 %, P < 0.001). The procedure time was 38.1 ± 35.7 and 50.8 ± 50.2 min (P = 0.047). However, no significant differences were detected in the en bloc resection rate, complete resection rate, and adverse events including bleeding and perforation. Multivariate analysis showed that administration of PPI (OR = 10.83, P < 0.001) and mucosal invasion (OR = 24.43, P < 0.001) were independent factors that predicted complete healing of ulceration. The calculated accuracy for whether complete healing of the ulcer after PPI administration can differentiate mucosal from submucosal invasion was 75.3 %. Administration of PPI before ESD in differentiated EGC meeting the expanded criteria is effective to heal the ulcer lesion and reduce the mean procedure time. Complete healing of the ulcer after PPI administration suggests mucosal cancer.

An ensemble framework for clustering protein-protein interaction networks.

PubMed

Asur, Sitaram; Ucar, Duygu; Parthasarathy, Srinivasan

2007-07-01

Protein-Protein Interaction (PPI) networks are believed to be important sources of information related to biological processes and complex metabolic functions of the cell. The presence of biologically relevant functional modules in these networks has been theorized by many researchers. However, the application of traditional clustering algorithms for extracting these modules has not been successful, largely due to the presence of noisy false positive interactions as well as specific topological challenges in the network. In this article, we propose an ensemble clustering framework to address this problem. For base clustering, we introduce two topology-based distance metrics to counteract the effects of noise. We develop a PCA-based consensus clustering technique, designed to reduce the dimensionality of the consensus problem and yield informative clusters. We also develop a soft consensus clustering variant to assign multifaceted proteins to multiple functional groups. We conduct an empirical evaluation of different consensus techniques using topology-based, information theoretic and domain-specific validation metrics and show that our approaches can provide significant benefits over other state-of-the-art approaches. Our analysis of the consensus clusters obtained demonstrates that ensemble clustering can (a) produce improved biologically significant functional groupings; and (b) facilitate soft clustering by discovering multiple functional associations for proteins. Supplementary data are available at Bioinformatics online.

Brain networks involved in tactile speed classification of moving dot patterns: the effects of speed and dot periodicity

PubMed Central

Yang, Jiajia; Kitada, Ryo; Kochiyama, Takanori; Yu, Yinghua; Makita, Kai; Araki, Yuta; Wu, Jinglong; Sadato, Norihiro

2017-01-01

Humans are able to judge the speed of an object’s motion by touch. Research has suggested that tactile judgment of speed is influenced by physical properties of the moving object, though the neural mechanisms underlying this process remain poorly understood. In the present study, functional magnetic resonance imaging was used to investigate brain networks that may be involved in tactile speed classification and how such networks may be affected by an object’s texture. Participants were asked to classify the speed of 2-D raised dot patterns passing under their right middle finger. Activity in the parietal operculum, insula, and inferior and superior frontal gyri was positively related to the motion speed of dot patterns. Activity in the postcentral gyrus and superior parietal lobule was sensitive to dot periodicity. Psycho-physiological interaction (PPI) analysis revealed that dot periodicity modulated functional connectivity between the parietal operculum (related to speed) and postcentral gyrus (related to dot periodicity). These results suggest that texture-sensitive activity in the primary somatosensory cortex and superior parietal lobule influences brain networks associated with tactually-extracted motion speed. Such effects may be related to the influence of surface texture on tactile speed judgment. PMID:28145505

Frequency of reporting on patient and public involvement (PPI) in research studies published in a general medical journal: a descriptive study.

PubMed

Price, Amy; Schroter, Sara; Snow, Rosamund; Hicks, Melissa; Harmston, Rebecca; Staniszewska, Sophie; Parker, Sam; Richards, Tessa

2018-03-23

While documented plans for patient and public involvement (PPI) in research are required in many grant applications, little is known about how frequently PPI occurs in practice. Low levels of reported PPI may mask actual activity due to limited PPI reporting requirements. This research analysed the frequency and types of reported PPI in the presence and absence of a journal requirement to include this information. A before and after comparison of PPI reported in research papers published in The BMJ before and 1 year after the introduction of a journal policy requiring authors to report if and how they involved patients and the public within their papers. Between 1 June 2013 and 31 May 2014, The BMJ published 189 research papers and 1 (0.5%) reported PPI activity. From 1 June 2015 to 31 May 2016, following the introduction of the policy, The BMJ published 152 research papers of which 16 (11%) reported PPI activity. Patients contributed to grant applications in addition to designing studies through to coauthorship and participation in study dissemination. Patient contributors were often not fully acknowledged; 6 of 17 (35%) papers acknowledged their contributions and 2 (12%) included them as coauthors. Infrequent reporting of PPI activity does not appear to be purely due to a failure of documentation. Reporting of PPI activity increased after the introduction of The BMJ 's policy, but activity both before and after was low and reporting was inconsistent in quality. Journals, funders and research institutions should collaborate to move us from the current situation where PPI is an optional extra to one where PPI is fully embedded in practice throughout the research process. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A Fast Response Ammonia Sensor Based on Coaxial PPy-PAN Nanofiber Yarn.

PubMed

Liu, Penghong; Wu, Shaohua; Zhang, Yue; Zhang, Hongnan; Qin, Xiaohong

2016-06-23

Highly orientated polypyrrole (PPy)-coated polyacrylonitrile (PAN) (PPy-PAN) nanofiber yarn was prepared with an electrospinning technique and in-situ chemical polymerization. The morphology and chemical structure of PPy-PAN nanofiber yarn was characterized by scanning electron microscopy (SEM), field emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), and fourier transform infrared spectroscopy (FTIR), which indicated that the PPy as the shell layer was homogeneously and uniformly polymerized on the surface of PAN nanofiber. The effects of different concentration of doping acid on the responses of PPy-PAN nanofiber yarn sensor were investigated. The electrical responses of the gas sensor based on the PPy-PAN nanofiber yarn to ammonia were investigated at room temperature. The nanoyarn sensor composed of uniaxially aligned PPy-PAN nanofibers with a one-dimensional structure exhibited a transient response, and the response time was less than 1 s. The excellent sensing properties mentioned above give rise to good potential application prospects in the field of ammonia sensor.

Asfotase-α improves bone growth, mineralization and strength in mouse models of neurofibromatosis type-1

PubMed Central

de la Croix Ndong, Jean; Makowski, Alexander James; Uppuganti, Sasidhar; Vignaux, Guillaume; Ono, Koichiro; Perrien, Daniel S.; Joubert, Simon; Baglio, Serena R.; Granchi, Donatella; Stevenson, David A.; Rios, Jonathan J.; Nyman, Jeffry S.; Elefteriou, Florent

2014-01-01

Mineralization of the skeleton depends on the balance between levels of pyrophosphate (PPi), an inhibitor of hydroxyapatite formation, and phosphate generated from PPi breakdown by alkaline phosphatase (ALP). We report here that ablation of Nf1, encoding the RAS/GTPase–activating protein neurofibromin, in bone–forming cells leads to supraphysiologic PPi accumulation, caused by a chronic ERK–dependent increase in genes promoting PPi synthesis and extracellular transport, namely Enpp1 and Ank. It also prevents BMP2–induced osteoprogenitor differentiation and, consequently, expression of ALP and PPi breakdown, further contributing to PPi accumulation. The short stature, impaired bone mineralization and strength in mice lacking Nf1 in osteochondroprogenitors or osteoblasts could be corrected by enzyme therapy aimed at reducing PPi concentration. These results establish neurofibromin as an essential regulator of bone mineralization, suggest that altered PPi homeostasis contributes to the skeletal dysplasiae associated with neurofibromatosis type-1 (NF1), and that some of the NF1 skeletal conditions might be preventable pharmacologically. PMID:24997609

Dielectric and electric modulus study of PPy/TiO2/CNT/SLS composite with temperature

NASA Astrophysics Data System (ADS)

Tiwari, D. C.; Atri, Priyanka; Sharma, Rishi

2013-02-01

Here we report the preparation and electrical characterization of nanocomposite of PPy/TiO2/CNT/SLS synthesized by in situ oxidative polymerization of pyrrole in the presence of TiO2 nanofibers, CNT and surfactant sodium lauryl sulfate. The surface morphology and elemental analysis is studied by SEM and EDAX. Dielectric and modulas studies were carried out in frequency range of 1 KHz to 2 MHz which provides quantitative description of grain and grain boundary effect in nanocomposite material.

The Proton Pump Inhibitor Non-Responder: A Clinical Conundrum

PubMed Central

Hussain, Zilla H; Henderson, Emily E; Maradey-Romerao, Carla; George, Nina; Fass, Ronnie; Lacy, Brian E

2015-01-01

Gastroesophageal reflux disease (GERD) is a highly prevalent chronic condition where in stomach contents reflux into the esophagus causing symptoms, esophageal injury, and subsequent complications. Proton pump inhibitors (PPI) remain the mainstay of therapy for acid suppression. Despite their efficacy, significant proportions of GERD patients are either partial or non-responders to PPI therapy. Patients should be assessed for mechanisms that can lead to PPI failure and may require further evaluation to investigate for alternative causes. This monograph will outline a diagnostic approach to the PPI non-responder, review mechanisms associated with PPI failure, and discuss therapeutic options for those who fail to respond to PPI therapy. PMID:26270485

Counselors' Perspectives of Positive Psychology for the Treatment of Addiction: A Mixed Methods Pilot Study.

PubMed

Krentzman, Amy R; Barker, Stacey L

2016-01-01

Little is known about the use of positive psychology interventions (PPI) in addictions treatment. Questionnaires and interviews with alcohol and substance use disorder counselors explored theories of how PPIs might work, the degree to which they are used, and downsides. Results suggested that positive and pathology-based themes were attended in equal proportion, that substance abuse treatment should help clients develop a good life in recovery; that counselors already use PPI; and that PPI might counter negative cognitions and affect. Reservations for using PPI included relying on PPI exclusively and employing PPI indiscriminately without regard to client characteristics.

Counselors’ Perspectives of Positive Psychology for the Treatment of Addiction: A Mixed Methods Pilot Study

PubMed Central

Krentzman, Amy R.; Barker, Stacey L.

2016-01-01

Little is known about the use of positive psychology interventions (PPI) in addictions treatment. Questionnaires and interviews with alcohol and substance use disorder counselors explored theories of how PPIs might work, the degree to which they are used, and downsides. Results suggested that positive and pathology-based themes were attended in equal proportion, that substance abuse treatment should help clients develop a good life in recovery; that counselors already use PPI; and that PPI might counter negative cognitions and affect. Reservations for using PPI included relying on PPI exclusively and employing PPI indiscriminately without regard to client characteristics. PMID:27980355

Characterization of recombinant PPi-dependent 6-phosphofructokinases from Methylosinus trichosporium OB3b and Methylobacterium nodulans ORS 2060.

PubMed

Rozova, O N; Khmelenina, V N; Trotsenko, Y A

2012-03-01

The properties of the purified recombinant PPi-dependent 6-phosphofructokinases (PPi-PFKs) from the methanotroph Methylosinus trichosporium OB3b and rhizospheric phytosymbiont Methylobacterium nodulans ORS 2060 were determined. The dependence of activities of PPi-PFK-His(6)-tag from Ms. trichosporium OB3b (6 × 45 kDa) and PPi-PFK from Mb. nodulans ORS 2060 (4 × 43 kDa) on the concentrations of substrates of forward and reverse reactions conformed to Michaelis-Menten kinetics. Besides fructose-6-phosphate, the enzymes also phosphorylated sedoheptulose-7-phosphate. ADP or AMP (1 mM each) inhibited activity of the Ms. trichosporium PPi-PFK but did not affect the activity of the Mb. nodulans enzyme. Preference of PPi-PFKs to fructose-1,6-bisphosphate implied a predominant function of the enzymes in hexose phosphate synthesis in these bacteria. PPi-PFKs from the methylotrophs have low similarity of translated amino acid sequences (17% identity) and belong to different phylogenetic subgroups of type II 6-phosphofructokinases. The relationship of PPi-PFKs with microaerophilic character of Ms. trichosporium OB3b and adaptation of Mb. nodulans ORS 2060 to anaerobic phase of phytosymbiosis are discussed.

Proton Pump Inhibitors and Risk of Rhabdomyolysis.

PubMed

Duncan, Scott J; Howden, Colin W

2017-01-01

Proton pump inhibitors (PPIs) have been associated with a variety of adverse events, although the level of evidence for many of these is weak at best. Recently, one national regulatory authority has mandated a change to the labeling of one PPI based on reports of possible associated rhabdomyolysis. Thus, in this review we summarize the available evidence linking PPI use with rhabdomyolysis. The level of evidence is insufficient to establish a causal relationship and is largely based on sporadic case reports. In general, patients with suspected PPI-associated rhabdomyolysis have not been re-challenged with a PPI after recovery. The mechanism whereby PPIs might have been associated with rhabdomyolysis is unclear but possibly related to interaction with concomitantly administered drugs such as HMG-CoA reductase inhibitors (statins). For patients with rhabdomyolysis, a careful search must be made for possible etiological factors. In patients who recover from an episode of possible PPI-related rhabdomyolysis but do not have a genuine requirement for PPI treatment, the PPI should not be re-introduced. For those with a definite indication for ongoing PPI treatment, the PPI can be re-introduced but should preferably not be administered with a statin.

APID interactomes: providing proteome-based interactomes with controlled quality for multiple species and derived networks

PubMed Central

Alonso-López, Diego; Gutiérrez, Miguel A.; Lopes, Katia P.; Prieto, Carlos; Santamaría, Rodrigo; De Las Rivas, Javier

2016-01-01

APID (Agile Protein Interactomes DataServer) is an interactive web server that provides unified generation and delivery of protein interactomes mapped to their respective proteomes. This resource is a new, fully redesigned server that includes a comprehensive collection of protein interactomes for more than 400 organisms (25 of which include more than 500 interactions) produced by the integration of only experimentally validated protein–protein physical interactions. For each protein–protein interaction (PPI) the server includes currently reported information about its experimental validation to allow selection and filtering at different quality levels. As a whole, it provides easy access to the interactomes from specific species and includes a global uniform compendium of 90,379 distinct proteins and 678,441 singular interactions. APID integrates and unifies PPIs from major primary databases of molecular interactions, from other specific repositories and also from experimentally resolved 3D structures of protein complexes where more than two proteins were identified. For this purpose, a collection of 8,388 structures were analyzed to identify specific PPIs. APID also includes a new graph tool (based on Cytoscape.js) for visualization and interactive analyses of PPI networks. The server does not require registration and it is freely available for use at http://apid.dep.usal.es. PMID:27131791

Three-dimensional graphene-polypyrrole hybrid electrochemical actuator

NASA Astrophysics Data System (ADS)

Liu, Jia; Wang, Zhi; Zhao, Yang; Cheng, Huhu; Hu, Chuangang; Jiang, Lan; Qu, Liangti

2012-11-01

The advancement of mechanical actuators benefits from the development of new structural materials with prominent properties. A novel three-dimensional (3D) hydrothermally converted graphene and polypyrrole (G-PPy) hybrid electrochemical actuator is presented, which is prepared via a convenient hydrothermal process, followed by in situ electropolymerization of pyrrole. The 3D pore-interconnected G-PPy pillar exhibits strong actuation responses superior to pure graphene and PPy film. In response to the low potentials of +/-0.8 V, the saturated strain of 3D G-PPy pillar can reach a record of 2.5%, which is more than 10 times higher than that of carbon nanotube film and about 3 times that of unitary graphene film under an applied potential of +/-1.2 V. Also, the 3D G-PPy actuator exhibits high actuation durability with high operating load as demonstrated by an 11 day continuous measurement. Finally, a proof-of-concept application of 3D G-PPy as smart filler for on/off switch is also demonstrated, which indicates the great potential of the 3D G-PPy structure developed in this study for advanced actuator systems.The advancement of mechanical actuators benefits from the development of new structural materials with prominent properties. A novel three-dimensional (3D) hydrothermally converted graphene and polypyrrole (G-PPy) hybrid electrochemical actuator is presented, which is prepared via a convenient hydrothermal process, followed by in situ electropolymerization of pyrrole. The 3D pore-interconnected G-PPy pillar exhibits strong actuation responses superior to pure graphene and PPy film. In response to the low potentials of +/-0.8 V, the saturated strain of 3D G-PPy pillar can reach a record of 2.5%, which is more than 10 times higher than that of carbon nanotube film and about 3 times that of unitary graphene film under an applied potential of +/-1.2 V. Also, the 3D G-PPy actuator exhibits high actuation durability with high operating load as demonstrated by an 11 day continuous measurement. Finally, a proof-of-concept application of 3D G-PPy as smart filler for on/off switch is also demonstrated, which indicates the great potential of the 3D G-PPy structure developed in this study for advanced actuator systems. Electronic supplementary information (ESI) available: Experimental setup for fabrication of G-PPy hybrid structure, and movie showing the on/off response of G-PPy filler. See DOI: 10.1039/c2nr32699j

PPi-dependent phosphofructotransferase (phosphofructokinase) activity in the mollicutes (mycoplasma) Acholeplasma laidlawii.

PubMed Central

Pollack, J D; Williams, M V

1986-01-01

A PPi-dependent phosphofructotransferase (PPi-fructose 6-phosphate 1-phosphotransferase, EC 2.7.1.90) which catalyzes the conversion of fructose 6 phosphate (F-6-P) to fructose 1,6-bisphosphate (F-1, 6-P2) was isolated from a cytoplasmic fraction of Acholeplasma laidlawii B-PG9 and partially purified (430-fold). PPi was required as the phosphate donor. ATP, dATP, CTP, dCTP, GTP, dGTP, UTP, dUTP, ITP, TTP, ADP, or Pi could not substitute for PPi. The PPi-dependent reaction (2.0 mM PPi) was not altered in the presence of any of these nucleotides (2.0 mM) or in the presence of smaller (less than or equal to 300 microM) amounts of fructose 2,6-bisphosphate, (NH4)2SO4, AMP, citrate, GDP, or phosphoenolpyruvate. Mg2+ and a pH of 7.4 were required for maximum activity. The partially purified enzyme in sucrose density gradient experiments had an approximate molecular weight of 74,000 and a sedimentation coefficient of 6.7. A second form of the enzyme (molecular weight, 37,000) was detected, although in relatively smaller amounts, by using Blue Sepharose matrix when performing electrophoresis experiments. The back reaction, F-1, 6-P2 to F-6-P, required Pi; arsenate could substitute for Pi, but not PPi or any other nucleotide tested. The computer-derived kinetic constants (+/- standard deviation) for the reaction in the PPi-driven direction of F-1, 6-P2 were as follows: v, 38.9 +/- 0.48 mM min-1; Ka(PPi), 0.11 +/- 0.04 mM; Kb(F-6-P), 0.65 +/- 0.15 mM; and Kia(PPi), 0.39 +/- 0.11 mM. A. laidlawii B-PG9 required PPi not only for the PPi-phosphofructotransferase reaction which we describe but also for purine nucleoside kinase activity. a dependency unknown in any other organism. In A. laidlawii B-PG9, the PPi requirement may be met by reactions in this organism already known to synthesize PPi (e.g., dUTPase and purine nucleobase phosphoribosyltransferases). In almost all other cells, the conversion of F-6-P to F-1,6-P2 is ATP dependent, and the reaction is generally considered to be the rate-limiting step of glycolysis. The ability of A. laidlawii B-PG9 and one other acholeplasma to use PPi instead of ATP as an energy source may offer these cytochrome-deficient organisms some metabolic advantage and may represent a conserved metabolic remnant of an earlier evolutionary process. PMID:3001032

A Pyrophosphate Based Energy Generating Module

DTIC Science & Technology

2008-12-01

OMB control number. 1. REPORT DATE DEC 2008 2 . REPORT TYPE N/A 3 . DATES COVERED - 4. TITLE AND SUBTITLE A Pyrophosphate Based Energy...for each substrate (PPi, PEP, and AMP) using double reciprocal Lineweaver-Burk plots of saturation data. 10| 2 10| 3 10|4 10|5 10|6 10|7 10-11 10- 10...Partitioning 1 2 3 4 Bilayer - + + + α-Hemolysin - - + + Upper Reservoir +PPi, +PEP +PPi, +PEP +PPi, +PEP +PPi, +PEP, +Luc Lower Reservoir +AMP

Association of Proton Pump Inhibitor (PPI) Use with Energy Intake, Physical Activity, and Weight Gain

PubMed Central

Czwornog, Jennifer L.; Austin, Gregory L.

2015-01-01

Studies suggest proton pump inhibitor (PPI) use impacts body weight regulation, though the effect of PPIs on energy intake, energy extraction, and energy expenditure is unknown. We used data on 3073 eligible adults from the National Health and Nutrition Examination Survey (NHANES). Medication use, energy intake, diet composition, and physical activity were extracted from NHANES. Multivariate regression models included confounding variables. Daily energy intake was similar between PPI users and non-users (p = 0.41). Diet composition was similar between the two groups, except that PPI users consumed a slightly greater proportion of calories from fat (34.5% vs. 33.2%; p = 0.02). PPI users rated themselves as being as physically active as their age/gender-matched peers and reported similar frequencies of walking or biking. However, PPI users were less likely to have participated in muscle-strengthening activities (OR: 0.53; 95% CI: 0.30–0.95). PPI users reported similar sedentary behaviors to non-users. Male PPI users had an increase in weight (of 1.52 ± 0.59 kg; p = 0.021) over the previous year compared to non-users, while female PPI users had a non-significant increase in weight. The potential mechanisms for PPI-associated weight gain are unclear as we did not find evidence for significant differences in energy intake or markers of energy expenditure. PMID:26492268

Asymmetric Dimethylarginine versus Proton Pump Inhibitors Usage in Patients with Stable Coronary Artery Disease: A Cross-Sectional Study.

PubMed

Kruszelnicka, Olga; Świerszcz, Jolanta; Bednarek, Jacek; Chyrchel, Bernadeta; Surdacki, Andrzej; Nessler, Jadwiga

2016-04-15

A recent experimental study suggested that proton pump inhibitors (PPI), widely used to prevent gastroduodenal complications of dual antiplatelet therapy, may increase the accumulation of the endogenous nitric oxide synthesis antagonist asymmetric dimethylarginine (ADMA), an adverse outcome predictor. Our aim was to assess the effect of PPI usage on circulating ADMA in coronary artery disease (CAD). Plasma ADMA levels were compared according to PPI use for ≥1 month prior to admission in 128 previously described non-diabetic men with stable CAD who were free of heart failure or other coexistent diseases. Patients on PPI tended to be older and with insignificantly lower estimated glomerular filtration rate (GFR). PPI use was not associated with any effect on plasma ADMA (0.51 ± 0.11 (SD) vs. 0.50 ± 0.10 µmol/L for those with PPI (n = 53) and without PPI (n = 75), respectively; p = 0.7). Additionally, plasma ADMA did not differ between PPI users and non-users stratified by a history of current smoking, CAD severity or extent. The adjustment for patients' age and GFR did not substantially change the results. Thus, PPI usage does not appear to affect circulating ADMA in non-diabetic men with stable CAD. Whether novel mechanisms of adverse PPI effects on the vasculature can be translated into clinical conditions, requires further studies.

Proton Pump Inhibitor Use and Magnesium Concentrations in Hemodialysis Patients: A Cross-Sectional Study

PubMed Central

Nakashima, Akio; Ohkido, Ichiro; Yokoyama, Keitaro; Mafune, Aki; Urashima, Mitsuyoshi; Yokoo, Takashi

2015-01-01

Magnesium concentration is a proven predictor of mortality in hemodialysis patients. Recent reports have indicated that proton pump inhibitor (PPI) use affects serum magnesium levels, however few studies have investigated the relationship between PPI use and magnesium levels in hemodialysis patients. This study aimed to clarify the association between PPI use and serum magnesium levels in hemodialysis patients. We designed this cross sectional study and included 1189 hemodialysis patients in stable condition. Associations between PPI and magnesium-related factors, as well as other possible confounders, were evaluated using a multiple regression model. We defined hypomagnesemia as a value < 2.0 mg/dL, and created comparable logistic regression models to assess the association between PPI use and hypomagnesemia. PPI use is associated with a significantly lower mean serum magnesium level than histamine 2 (H2) receptor antagonists or no acid-suppressive medications (mean [SD] PPI: 2.52 [0.45] mg/dL; H2 receptor antagonist: 2.68 [0.41] mg/dL; no acid suppressive medications: 2.68 [0.46] mg/dL; P = 0.001). Hypomagnesemia remained significantly associated with PPI (adjusted OR, OR: 2.05; 95% CI: 1.14–3.69; P = 0.017). PPI use is associated with an increased risk of hypomagnesemia in hemodialysis patients. Future prospective studies are needed to explore magnesium replacement in PPI users on hemodialysis. PMID:26618538

Effects of smoking on the acoustic startle response and prepulse inhibition in smokers with and without posttraumatic stress disorder.

PubMed

Vrana, Scott R; Calhoun, Patrick S; McClernon, F Joseph; Dennis, Michelle F; Lee, Sherman T; Beckham, Jean C

2013-12-01

Cigarette smokers smoke in part because nicotine helps regulate attention. Prepulse inhibition (PPI) of the startle reflex is a measure of early attentional gating that is reduced in abstinent smokers and in groups with attention regulation difficulties. Attention difficulties are found in people with posttraumatic stress disorder (PTSD). The aim of this study is to assess whether smoking and abstinence differentially affect the startle response and PPI in smokers with and without PTSD. Startle response and PPI (prepulses at 60, 120, or 240 ms) were measured in smokers with (N = 39) and without (N = 61) PTSD, while smoking and again while abstinent. Participants with PTSD produced both larger magnitude and faster latency startle responses than controls. Across groups, PPI was greater when smoking than when abstinent. The PTSD and control group exhibited different patterns of PPI across prepulse intervals when smoking and when abstinent. Older age was associated with reduced PPI, but only when abstinent from smoking. The effects of PTSD on startle magnitude and of smoking on PPI replicate earlier studies. The different pattern of PPI exhibited in PTSD and control groups across prepulse intervals, while smoking and abstinent suggests that previous research on smoking and PPI has been limited by not including longer prepulse intervals, and that nicotine may affect the time course as well as increasing the level of PPI. The reduced PPI among older participants during abstinence suggests that nicotine may play a role in maintaining attention in older smokers, which may motivate continued smoking in older individuals.

Analysis of molecular pathways in pancreatic ductal adenocarcinomas with a bioinformatics approach.

PubMed

Wang, Yan; Li, Yan

2015-01-01

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer death worldwide. Our study aimed to reveal molecular mechanisms. Microarray data of GSE15471 (including 39 matching pairs of pancreatic tumor tissues and patient-matched normal tissues) was downloaded from Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) in PDAC tissues compared with normal tissues by limma package in R language. Then GO and KEGG pathway enrichment analyses were conducted with online DAVID. In addition, principal component analysis was performed and a protein-protein interaction network was constructed to study relationships between the DEGs through database STRING. A total of 532 DEGs were identified in the 38 PDAC tissues compared with 33 normal tissues. The results of principal component analysis of the top 20 DEGs could differentiate the PDAC tissues from normal tissues directly. In the PPI network, 8 of the 20 DEGs were all key genes of the collagen family. Additionally, FN1 (fibronectin 1) was also a hub node in the network. The genes of the collagen family as well as FN1 were significantly enriched in complement and coagulation cascades, ECM-receptor interaction and focal adhesion pathways. Our results suggest that genes of collagen family and FN1 may play an important role in PDAC progression. Meanwhile, these DEGs and enriched pathways, such as complement and coagulation cascades, ECM-receptor interaction and focal adhesion may be important molecular mechanisms involved in the development and progression of PDAC.

Functional and molecular characterization of a glycosomal PPi-dependent enzyme in trypanosomatids: Pyruvate, phosphate dikinase

PubMed Central

Bringaud, Frederic; Baltz, Dominique; Baltz, Theo

1998-01-01

Trypanosomatids are parasitic protists that have an ATP-dependent glycolysis with no indication of PPi-dependent metabolism. Most of the glycolysis takes place in peroxisome-like organelles, the glycosomes. We characterized in Trypanosoma brucei a single-copy gene encoding a PPi-dependent enzyme, pyruvate, phosphate dikinase (PPDK), which was expressed functionally in Escherichia coli. Specific antibodies detected a 100-kDa protein in procyclic forms but not in mammalian forms of T. brucei, indicating a differential expression. Glycosomal localization of PPDK was determined by immunofluorescence analysis and was confirmed by Western blot analysis on glycosomal fractions by using anti-PPDK antibodies. Expression and localization of recombinant PPDKs in procyclic forms of T. brucei showed that the AKL motif at the C-terminal extremity of PPDK is necessary for glycosomal targeting. PPDK was detected in every trypanosomatid tested—Trypanosoma congolense, Trypanosoma vivax, Trypanosoma cruzi, Phytomonas, Crithidia and Leishmania—with a good correlation between amount of protein and enzymatic activity. The precise role of PPDK in trypanosomatid carbohydrate metabolism remains to be clarified. PMID:9653123

Dye-doped nanostructure polypyrrole film for electrochemically switching solid-phase microextraction of Ni(II) and ICP-OES analysis of waste water.

PubMed

Shamaeli, Ehsan; Alizadeh, Naader

2012-01-01

A nanostructure fiber based on conducting polypyrrole synthesized by an electrochemical method has been developed, and used for electrochemically switching solid-phase microextraction (ES-SPME). The ES-SPME was prepared by the doping of eriochrome blue in polypyrrole (PPy-ECB) and used for selectively extracting the Ni(II) cation in the presence of some transition and heavy metal ions. The cation-exchange behavior of electrochemically prepared polypyrrole on stainless-steel with and without eriochrome blue (ECB) dye was characterized using ICP-OES analysis. The effects of the scan rate for electrochemical synthesis, uptake and the release potential on the extraction behavior of the PPy-ECB conductive fiber were studied. Uptake and release time profiles show that the process of electrically switched cation exchange could be completed within 250 s. The results of the present study point concerning the possibility of developing a selective extraction process for Ni(II) from waste water was explored using such a nanostructured PPy-ECB film through an electrically switched cation exchange. 2012 © The Japan Society for Analytical Chemistry

Predicting Functions of Proteins in Mouse Based on Weighted Protein-Protein Interaction Network and Protein Hybrid Properties

PubMed Central

Shi, Xiaohe; Lu, Wen-Cong; Cai, Yu-Dong; Chou, Kuo-Chen

2011-01-01

Background With the huge amount of uncharacterized protein sequences generated in the post-genomic age, it is highly desirable to develop effective computational methods for quickly and accurately predicting their functions. The information thus obtained would be very useful for both basic research and drug development in a timely manner. Methodology/Principal Findings Although many efforts have been made in this regard, most of them were based on either sequence similarity or protein-protein interaction (PPI) information. However, the former often fails to work if a query protein has no or very little sequence similarity to any function-known proteins, while the latter had similar problem if the relevant PPI information is not available. In view of this, a new approach is proposed by hybridizing the PPI information and the biochemical/physicochemical features of protein sequences. The overall first-order success rates by the new predictor for the functions of mouse proteins on training set and test set were 69.1% and 70.2%, respectively, and the success rate covered by the results of the top-4 order from a total of 24 orders was 65.2%. Conclusions/Significance The results indicate that the new approach is quite promising that may open a new avenue or direction for addressing the difficult and complicated problem. PMID:21283518

Protein-protein interaction networks (PPI) and complex diseases

PubMed Central

Safari-Alighiarloo, Nahid; Taghizadeh, Mohammad; Rezaei-Tavirani, Mostafa; Goliaei, Bahram

2014-01-01

The physical interaction of proteins which lead to compiling them into large densely connected networks is a noticeable subject to investigation. Protein interaction networks are useful because of making basic scientific abstraction and improving biological and biomedical applications. Based on principle roles of proteins in biological function, their interactions determine molecular and cellular mechanisms, which control healthy and diseased states in organisms. Therefore, such networks facilitate the understanding of pathogenic (and physiologic) mechanisms that trigger the onset and progression of diseases. Consequently, this knowledge can be translated into effective diagnostic and therapeutic strategies. Furthermore, the results of several studies have proved that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer and autoimmune disorders. Based on such relationship, a novel paradigm is suggested in order to confirm that the protein interaction networks can be the target of therapy for treatment of complex multi-genic diseases rather than individual molecules with disrespect the network. PMID:25436094

Sensorimotor gating impairments induced by MK-801 treatment may be reduced by tolerance effect and by familiarization in monkeys

PubMed Central

Saletti, Patricia G.; Maior, Rafael S.; Hori, Etsuro; Nishijo, Hisao; Tomaz, Carlos

2015-01-01

Dizocilpine (MK-801) is a non-competitive NMDA antagonist that induces schizophreniclike effects. It is therefore widely used in experimental models of schizophrenia including prepulse inhibition (PPI) impairments in rodents. Nevertheless, MK-801 has never been tested in monkeys on a PPI paradigm. In order to evaluate MK-801 effects on monkeys’ PPI, we tested eight capuchin monkeys (Sapajus spp.) using three different doses of MK-801 (0.01; 0.02; 0.03 mg/kg). Results show PPI impairment in acute administration of the highest dose (0.03 mg/kg). PPI impairment induced by MK-801 was reversed by re-exposure to the PPI test throughout treatment trials, in contrast with rodent studies. These results indicate that tolerance effect and familiarization with PPI test may reduce the sensorimotor gating deficits induced by MK-801 in monkeys, suggesting a drug-training interaction. PMID:26441660

Computational prediction of protein interactions related to the invasion of erythrocytes by malarial parasites.

PubMed

Liu, Xuewu; Huang, Yuxiao; Liang, Jiao; Zhang, Shuai; Li, Yinghui; Wang, Jun; Shen, Yan; Xu, Zhikai; Zhao, Ya

2014-11-30

The invasion of red blood cells (RBCs) by malarial parasites is an essential step in the life cycle of Plasmodium falciparum. Human-parasite surface protein interactions play a critical role in this process. Although several interactions between human and parasite proteins have been discovered, the mechanism related to invasion remains poorly understood because numerous human-parasite protein interactions have not yet been identified. High-throughput screening experiments are not feasible for malarial parasites due to difficulty in expressing the parasite proteins. Here, we performed computational prediction of the PPIs involved in malaria parasite invasion to elucidate the mechanism by which invasion occurs. In this study, an expectation maximization algorithm was used to estimate the probabilities of domain-domain interactions (DDIs). Estimates of DDI probabilities were then used to infer PPI probabilities. We found that our prediction performance was better than that based on the information of D. melanogaster alone when information related to the six species was used. Prediction performance was assessed using protein interaction data from S. cerevisiae, indicating that the predicted results were reliable. We then used the estimates of DDI probabilities to infer interactions between 490 parasite and 3,787 human membrane proteins. A small-scale dataset was used to illustrate the usability of our method in predicting interactions between human and parasite proteins. The positive predictive value (PPV) was lower than that observed in S. cerevisiae. We integrated gene expression data to improve prediction accuracy and to reduce false positives. We identified 80 membrane proteins highly expressed in the schizont stage by fast Fourier transform method. Approximately 221 erythrocyte membrane proteins were identified using published mass spectral datasets. A network consisting of 205 interactions was predicted. Results of network analysis suggest that SNARE proteins of parasites and APP of humans may function in the invasion of RBCs by parasites. We predicted a small-scale PPI network that may be involved in parasite invasion of RBCs by integrating DDI information and expression profiles. Experimental studies should be conducted to validate the predicted interactions. The predicted PPIs help elucidate the mechanism of parasite invasion and provide directions for future experimental investigations.