atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

PubMed

Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

2012-07-20

Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

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

Rhizoma Dioscoreae extract protects against alveolar bone loss by regulating the cell cycle: A predictive study based on the protein‑protein interaction network.

PubMed

Zhang, Zhi-Guo; Song, Chang-Heng; Zhang, Fang-Zhen; Chen, Yan-Jing; Xiang, Li-Hua; Xiao, Gary Guishan; Ju, Da-Hong

2016-06-01

Rhizoma Dioscoreae extract (RDE) exhibits a protective effect on alveolar bone loss in ovariectomized (OVX) rats. The aim of this study was to predict the pathways or targets that are regulated by RDE, by re‑assessing our previously reported data and conducting a protein‑protein interaction (PPI) network analysis. In total, 383 differentially expressed genes (≥3‑fold) between alveolar bone samples from the RDE and OVX group rats were identified, and a PPI network was constructed based on these genes. Furthermore, four molecular clusters (A‑D) in the PPI network with the smallest P‑values were detected by molecular complex detection (MCODE) algorithm. Using Database for Annotation, Visualization and Integrated Discovery (DAVID) and Ingenuity Pathway Analysis (IPA) tools, two molecular clusters (A and B) were enriched for biological process in Gene Ontology (GO). Only cluster A was associated with biological pathways in the IPA database. GO and pathway analysis results showed that cluster A, associated with cell cycle regulation, was the most important molecular cluster in the PPI network. In addition, cyclin‑dependent kinase 1 (CDK1) may be a key molecule achieving the cell‑cycle‑regulatory function of cluster A. From the PPI network analysis, it was predicted that delayed cell cycle progression in excessive alveolar bone remodeling via downregulation of CDK1 may be another mechanism underling the anti‑osteopenic effect of RDE on alveolar bone.

OncoPPi-informed discovery of mitogen-activated protein kinase kinase 3 as a novel binding partner of c-Myc | Office of Cancer Genomics

Cancer.gov

Mitogen-activated protein kinase kinase 3 (MKK3) is a dual threonine/tyrosine protein kinase that regulates inflammation, proliferation and apoptosis through specific phosphorylation and activation of the p38 mitogen-activated protein kinase. However, the role of MKK3 beyond p38-signaling remains elusive. Recently, we reported a protein-protein interaction (PPI) network of cancer-associated genes, termed OncoPPi, as a resource for the scientific community to generate new biological models. Analysis of the OncoPPi connectivity identified MKK3 as one of the major hub proteins in the network.

A sampling framework for incorporating quantitative mass spectrometry data in protein interaction analysis.

PubMed

Tucker, George; Loh, Po-Ru; Berger, Bonnie

2013-10-04

Comprehensive protein-protein interaction (PPI) maps are a powerful resource for uncovering the molecular basis of genetic interactions and providing mechanistic insights. Over the past decade, high-throughput experimental techniques have been developed to generate PPI maps at proteome scale, first using yeast two-hybrid approaches and more recently via affinity purification combined with mass spectrometry (AP-MS). Unfortunately, data from both protocols are prone to both high false positive and false negative rates. To address these issues, many methods have been developed to post-process raw PPI data. However, with few exceptions, these methods only analyze binary experimental data (in which each potential interaction tested is deemed either observed or unobserved), neglecting quantitative information available from AP-MS such as spectral counts. We propose a novel method for incorporating quantitative information from AP-MS data into existing PPI inference methods that analyze binary interaction data. Our approach introduces a probabilistic framework that models the statistical noise inherent in observations of co-purifications. Using a sampling-based approach, we model the uncertainty of interactions with low spectral counts by generating an ensemble of possible alternative experimental outcomes. We then apply the existing method of choice to each alternative outcome and aggregate results over the ensemble. We validate our approach on three recent AP-MS data sets and demonstrate performance comparable to or better than state-of-the-art methods. Additionally, we provide an in-depth discussion comparing the theoretical bases of existing approaches and identify common aspects that may be key to their performance. Our sampling framework extends the existing body of work on PPI analysis using binary interaction data to apply to the richer quantitative data now commonly available through AP-MS assays. This framework is quite general, and many enhancements are likely possible. Fruitful future directions may include investigating more sophisticated schemes for converting spectral counts to probabilities and applying the framework to direct protein complex prediction methods.

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.

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.

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.

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.

Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets

PubMed Central

Vinayagam, Arunachalam; Gibson, Travis E.; Lee, Ho-Joon; Yilmazel, Bahar; Roesel, Charles; Hu, Yanhui; Kwon, Young; Sharma, Amitabh; Liu, Yang-Yu; Perrimon, Norbert; Barabási, Albert-László

2016-01-01

The protein–protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as “indispensable,” “neutral,” or “dispensable,” which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network’s control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets. PMID:27091990

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.

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.

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

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.

Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

PubMed Central

Chen, Ching-Tai; Peng, Hung-Pin; Jian, Jhih-Wei; Tsai, Keng-Chang; Chang, Jeng-Yih; Yang, Ei-Wen; Chen, Jun-Bo; Ho, Shinn-Ying; Hsu, Wen-Lian; Yang, An-Suei

2012-01-01

Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with the physicochemical complementarity features based on the non-covalent interaction data derived from protein interiors. PMID:22701576

HubAlign: an accurate and efficient method for global alignment of protein-protein interaction networks.

PubMed

Hashemifar, Somaye; Xu, Jinbo

2014-09-01

High-throughput experimental techniques have produced a large amount of protein-protein interaction (PPI) data. The study of PPI networks, such as comparative analysis, shall benefit the understanding of life process and diseases at the molecular level. One way of comparative analysis is to align PPI networks to identify conserved or species-specific subnetwork motifs. A few methods have been developed for global PPI network alignment, but it still remains challenging in terms of both accuracy and efficiency. This paper presents a novel global network alignment algorithm, denoted as HubAlign, that makes use of both network topology and sequence homology information, based upon the observation that topologically important proteins in a PPI network usually are much more conserved and thus, more likely to be aligned. HubAlign uses a minimum-degree heuristic algorithm to estimate the topological and functional importance of a protein from the global network topology information. Then HubAlign aligns topologically important proteins first and gradually extends the alignment to the whole network. Extensive tests indicate that HubAlign greatly outperforms several popular methods in terms of both accuracy and efficiency, especially in detecting functionally similar proteins. HubAlign is available freely for non-commercial purposes at http://ttic.uchicago.edu/∼hashemifar/software/HubAlign.zip. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

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 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

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.

In Silico Enhancing M. tuberculosis Protein Interaction Networks in STRING To Predict Drug-Resistance Pathways and Pharmacological Risks.

PubMed

Mei, Suyu

2018-05-04

Bacterial protein-protein interaction (PPI) networks are significant to reveal the machinery of signal transduction and drug resistance within bacterial cells. The database STRING has collected a large number of bacterial pathogen PPI networks, but most of the data are of low quality without being experimentally or computationally validated, thus restricting its further biomedical applications. We exploit the experimental data via four solutions to enhance the quality of M. tuberculosis H37Rv (MTB) PPI networks in STRING. Computational results show that the experimental data derived jointly by two-hybrid and copurification approaches are the most reliable to train an L 2 -regularized logistic regression model for MTB PPI network validation. On the basis of the validated MTB PPI networks, we further study the three problems via breadth-first graph search algorithm: (1) discovery of MTB drug-resistance pathways through searching for the paths between known drug-target genes and drug-resistance genes, (2) choosing potential cotarget genes via searching for the critical genes located on multiple pathways, and (3) choosing essential drug-target genes via analysis of network degree distribution. In addition, we further combine the validated MTB PPI networks with human PPI networks to analyze the potential pharmacological risks of known and candidate drug-target genes from the point of view of system pharmacology. The evidence from protein structure alignment demonstrates that the drugs that act on MTB target genes could also adversely act on human signaling pathways.

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.

Simple and efficient machine learning frameworks for identifying protein-protein interaction relevant articles and experimental methods used to study the interactions.

PubMed

Agarwal, Shashank; Liu, Feifan; Yu, Hong

2011-10-03

Protein-protein interaction (PPI) is an important biomedical phenomenon. Automatically detecting PPI-relevant articles and identifying methods that are used to study PPI are important text mining tasks. In this study, we have explored domain independent features to develop two open source machine learning frameworks. One performs binary classification to determine whether the given article is PPI relevant or not, named "Simple Classifier", and the other one maps the PPI relevant articles with corresponding interaction method nodes in a standardized PSI-MI (Proteomics Standards Initiative-Molecular Interactions) ontology, named "OntoNorm". We evaluated our system in the context of BioCreative challenge competition using the standardized data set. Our systems are amongst the top systems reported by the organizers, attaining 60.8% F1-score for identifying relevant documents, and 52.3% F1-score for mapping articles to interaction method ontology. Our results show that domain-independent machine learning frameworks can perform competitively well at the tasks of detecting PPI relevant articles and identifying the methods that were used to study the interaction in such articles. Simple Classifier is available at http://sourceforge.net/p/simpleclassify/home/ and OntoNorm at http://sourceforge.net/p/ontonorm/home/.

Intermolecular interactions and aggregation of fac-tris(2-phenylpyridinato-C2,N)iridium(III) in nonpolar solvents.

PubMed

Takayasu, Satoshi; Suzuki, Takayoshi; Shinozaki, Kazuteru

2013-08-15

The intermolecular interaction and aggregation of the neutral complex fac-tris(2-phenylpyridinato-C(2),N)iridium(III) (fac-Ir(ppy)3) in solution was investigated. Intermolecular interactions were found to effectively decrease the luminescence lifetime via self-quenching with increasing fac-Ir(ppy)3 concentrations. A Stern-Volmer plot for quenching in acetonitrile was linear, due to bimolecular self-quenching, but curved in toluene as the result of excimer formation. (1)H NMR spectra demonstrated a monomer-aggregate equilibrium which resulted in spectral shifts depending on solvent polarity. X-ray crystallography provided structural information concerning the aggregate, which is based on a tetramer consisting of two Δ-fac-Ir(ppy)3-Λ-fac-Ir(ppy)3 pairs. Offset π-π stacking of ppy ligands and electrostatic dipole-dipole interactions between complex molecules play an important role in the formation of these molecular pairs.

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.

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.

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.

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

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.

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.

Evolution versus "intelligent design": comparing the topology of protein-protein interaction networks to the Internet.

PubMed

Yang, Q; Siganos, G; Faloutsos, M; Lonardi, S

2006-01-01

Recent research efforts have made available genome-wide, high-throughput protein-protein interaction (PPI) maps for several model organisms. This has enabled the systematic analysis of PPI networks, which has become one of the primary challenges for the system biology community. In this study, we attempt to understand better the topological structure of PPI networks by comparing them against man-made communication networks, and more specifically, the Internet. Our comparative study is based on a comprehensive set of graph metrics. Our results exhibit an interesting dichotomy. On the one hand, both networks share several macroscopic properties such as scale-free and small-world properties. On the other hand, the two networks exhibit significant topological differences, such as the cliqueishness of the highest degree nodes. We attribute these differences to the distinct design principles and constraints that both networks are assumed to satisfy. We speculate that the evolutionary constraints that favor the survivability and diversification are behind the building process of PPI networks, whereas the leading force in shaping the Internet topology is a decentralized optimization process geared towards efficient node communication.

Inferring the Brassica rapa Interactome Using Protein–Protein Interaction Data from Arabidopsis thaliana

PubMed Central

Yang, Jianhua; Osman, Kim; Iqbal, Mudassar; Stekel, Dov J.; Luo, Zewei; Armstrong, Susan J.; Franklin, F. Chris H.

2013-01-01

Following successful completion of the Brassica rapa sequencing project, the next step is to investigate functions of individual genes/proteins. For Arabidopsis thaliana, large amounts of protein–protein interaction (PPI) data are available from the major PPI databases (DBs). It is known that Brassica crop species are closely related to A. thaliana. This provides an opportunity to infer the B. rapa interactome using PPI data available from A. thaliana. In this paper, we present an inferred B. rapa interactome that is based on the A. thaliana PPI data from two resources: (i) A. thaliana PPI data from three major DBs, BioGRID, IntAct, and TAIR. (ii) ortholog-based A. thaliana PPI predictions. Linking between B. rapa and A. thaliana was accomplished in three complementary ways: (i) ortholog predictions, (ii) identification of gene duplication based on synteny and collinearity, and (iii) BLAST sequence similarity search. A complementary approach was also applied, which used known/predicted domain–domain interaction data. Specifically, since the two species are closely related, we used PPI data from A. thaliana to predict interacting domains that might be conserved between the two species. The predicted interactome was investigated for the component that contains known A. thaliana meiotic proteins to demonstrate its usability. PMID:23293649

The Functional Networks of Prepulse Inhibition: Neuronal Connectivity Analysis Based on FDG-PET in Awake and Unrestrained Rats.

PubMed

Rohleder, Cathrin; Wiedermann, Dirk; Neumaier, Bernd; Drzezga, Alexander; Timmermann, Lars; Graf, Rudolf; Leweke, F Markus; Endepols, Heike

2016-01-01

Prepulse inhibition (PPI) is a neuropsychological process during which a weak sensory stimulus ("prepulse") attenuates the motor response ("startle reaction") to a subsequent strong startling stimulus. It is measured as a surrogate marker of sensorimotor gating in patients suffering from neuropsychological diseases such as schizophrenia, as well as in corresponding animal models. A variety of studies has shown that PPI of the acoustical startle reaction comprises three brain circuitries for: (i) startle mediation, (ii) PPI mediation, and (iii) modulation of PPI mediation. While anatomical connections and information flow in the startle and PPI mediation pathways are well known, spatial and temporal interactions of the numerous regions involved in PPI modulation are incompletely understood. We therefore combined [(18)F]fluoro-2-deoxyglucose positron-emission-tomography (FDG-PET) with PPI and resting state control paradigms in awake rats. A battery of subtractive, correlative as well as seed-based functional connectivity analyses revealed a default mode-like network (DMN) active during resting state only. Furthermore, two functional networks were observed during PPI: Metabolic activity in the lateral circuitry was positively correlated with PPI effectiveness and involved the auditory system and emotional regions. The medial network was negatively correlated with PPI effectiveness, i.e., associated with startle, and recruited a spatial/cognitive network. Our study provides evidence for two distinct neuronal networks, whose continuous interplay determines PPI effectiveness in rats, probably by either protecting the prepulse or facilitating startle processing. Discovering similar networks affected in neuropsychological disorders may help to better understand mechanisms of sensorimotor gating deficits and provide new perspectives for therapeutic strategies.

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

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

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

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/ .

Impact of Proton Pump Inhibitor Therapy on the Efficacy of Clopidogrel in the CAPRIE and CREDO Trials

PubMed Central

Dunn, Steven P.; Steinhubl, Steven R.; Bauer, Deborah; Charnigo, Richard J.; Berger, Peter B.; Topol, Eric J.

2013-01-01

Background Proton pump inhibitors (PPIs) may interfere with the metabolic activation of clopidogrel via inhibition of cytochrome P450 2C19, but the clinical implications remain unclear. Methods and Results The impact of PPI use on the 1‐year primary end point (ischemic stroke, myocardial infarction [MI], or vascular death) in the Clopidogrel versus Aspirin in Patients at Risk of Ischemic Events (CAPRIE) trial and the 28‐day (all‐cause death, MI, or urgent target vessel revascularization) and 1‐year (all‐cause death, MI, or stroke) primary end points in the Clopidogrel for Reduction of Events During Observation (CREDO) trial were examined. Clopidogrel appeared to elevate risk for the primary end point in CAPRIE among PPI users (estimated hazard ratio [EHR] 2.66, 95% CI 0.94 to 7.50) while lowering it for non‐PPI users (EHR 0.90, 95% CI 0.83 to 0.99, interaction P=0.047). Moreover, PPI use was associated with worse outcomes in patients receiving clopidogrel (EHR 2.39, 95% CI 1.74 to 3.28) but not aspirin (EHR 1.04, 95% CI 0.70 to 1.57, interaction P=0.001). Clopidogrel did not significantly alter risk for the 1‐year primary end point in CREDO among PPI users (EHR 0.82, 95% CI 0.48 to 1.40) while lowering it for non‐PPI users (EHR 0.71, 95% CI 0.52 to 0.98, interaction P=0.682). Also, PPI use was associated with worse outcomes in both patients receiving clopidogrel (EHR 1.67, 95% CI 1.06 to 2.64) and those receiving placebo (EHR 1.56, 95% CI 1.06 to 2.30, interaction P=0.811). Conclusions In CREDO, the efficacy of clopidogrel was not significantly affected by PPI use. However, in CAPRIE, clopidogrel was beneficial to non‐PPI users while apparently harmful to PPI users. Whether this negative interaction is clinically important for patients receiving clopidogrel without aspirin needs further study. PMID:23525436

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.

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

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

Clopidogrel and proton pump inhibitor (PPI) interaction: separate intake and a non-omeprazole PPI the solution?

PubMed

Kenngott, S; Olze, R; Kollmer, M; Bottheim, H; Laner, A; Holinski-Feder, E; Gross, M

2010-05-18

Dual therapy with aspirin and clopidogrel increases the risk of gastrointestinal bleeding. Therefore, co-therapy with a proton pump inhibitor (PPI) is recommended by most guidelines. However, there are warnings against combining PPIs with clopidogrel because of their interactions with cytochrome P450 isoenzyme 2C19 (CYP2C19). The effects of the combined or separate intake of 20 mg of omeprazole and 75 mg of clopidogrel on the clopidogrel-induced inhibition of platelet aggregation were measured in four healthy subjects whose CYP2C19 exon sequences were determined. The effects of co-therapy with 10 mg of rabeprazole were also examined. Two subjects showed the wild-type CYP2C19 sequence. The concurrent intake of omeprazole had no effect on clopidogrel-induced platelet inhibition in these subjects. Two subjects were heterozygous for the *2 allele, with predicted reduced CYP2C19 activity. One of them was a clopidogrel non-responder. In the second heterozygous subject, omeprazole co-therapy reduced the clopidogrel anti-platelet effect when taken simultaneously or separately. However, the simultaneous intake of rabeprazole did not reduce the clopidogrel effect. The clopidogrel-PPI interaction does not seem to be a PPI class effect. Rabeprazole did not affect the clopidogrel effect in a subject with a clear omeprazole-clopidogrel interaction. The separate intake of PPI and clopidogrel may not be sufficient to prevent their interaction.

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 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.

Combining active learning and semi-supervised learning techniques to extract protein interaction sentences.

PubMed

Song, Min; Yu, Hwanjo; Han, Wook-Shin

2011-11-24

Protein-protein interaction (PPI) extraction has been a focal point of many biomedical research and database curation tools. Both Active Learning and Semi-supervised SVMs have recently been applied to extract PPI automatically. In this paper, we explore combining the AL with the SSL to improve the performance of the PPI task. We propose a novel PPI extraction technique called PPISpotter by combining Deterministic Annealing-based SSL and an AL technique to extract protein-protein interaction. In addition, we extract a comprehensive set of features from MEDLINE records by Natural Language Processing (NLP) techniques, which further improve the SVM classifiers. In our feature selection technique, syntactic, semantic, and lexical properties of text are incorporated into feature selection that boosts the system performance significantly. By conducting experiments with three different PPI corpuses, we show that PPISpotter is superior to the other techniques incorporated into semi-supervised SVMs such as Random Sampling, Clustering, and Transductive SVMs by precision, recall, and F-measure. Our system is a novel, state-of-the-art technique for efficiently extracting protein-protein interaction pairs.

HomPPI: a class of sequence homology based protein-protein interface prediction methods

PubMed Central

2011-01-01

Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i) NPS-HomPPI (Non partner-specific HomPPI), which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii) PS-HomPPI (Partner-specific HomPPI), which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC) of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of both the query and the target can be reliably identified. The HomPPI web server is available at http://homppi.cs.iastate.edu/. Conclusions Sequence homology-based methods offer a class of computationally efficient and reliable approaches for predicting the protein-protein interface residues that participate in either obligate or transient interactions. For query proteins involved in transient interactions, the reliability of interface residue prediction can be improved by exploiting knowledge of putative interaction partners. PMID:21682895

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.

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.

A novel non-contact radar sensor for affective and interactive analysis.

PubMed

Lin, Hong-Dun; Lee, Yen-Shien; Shih, Hsiang-Lan; Chuang, Bor-Nian

2013-01-01

Currently, many physiological signal sensing techniques have been applied for affective analysis in Human-Computer Interaction applications. Most known maturely developed sensing methods (EEG/ECG/EMG/Temperature/BP etc. al.) replied on contact way to obtain desired physiological information for further data analysis. However, those methods might cause some inconvenient and uncomfortable problems, and not easy to be used for affective analysis in interactive performing. To improve this issue, a novel technology based on low power radar technology (Nanosecond Pulse Near-field Sensing, NPNS) with 300 MHz radio-frequency was proposed to detect humans' pulse signal by the non-contact way for heartbeat signal extraction. In this paper, a modified nonlinear HRV calculated algorithm was also developed and applied on analyzing affective status using extracted Peak-to-Peak Interval (PPI) information from detected pulse signal. The proposed new affective analysis method is designed to continuously collect the humans' physiological signal, and validated in a preliminary experiment with sound, light and motion interactive performance. As a result, the mean bias between PPI (from NPNS) and RRI (from ECG) shows less than 1ms, and the correlation is over than 0.88, respectively.

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

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

A scalable double-barcode sequencing platform for characterization of dynamic protein-protein interactions.

PubMed

Schlecht, Ulrich; Liu, Zhimin; Blundell, Jamie R; St Onge, Robert P; Levy, Sasha F

2017-05-25

Several large-scale efforts have systematically catalogued protein-protein interactions (PPIs) of a cell in a single environment. However, little is known about how the protein interactome changes across environmental perturbations. Current technologies, which assay one PPI at a time, are too low throughput to make it practical to study protein interactome dynamics. Here, we develop a highly parallel protein-protein interaction sequencing (PPiSeq) platform that uses a novel double barcoding system in conjunction with the dihydrofolate reductase protein-fragment complementation assay in Saccharomyces cerevisiae. PPiSeq detects PPIs at a rate that is on par with current assays and, in contrast with current methods, quantitatively scores PPIs with enough accuracy and sensitivity to detect changes across environments. Both PPI scoring and the bulk of strain construction can be performed with cell pools, making the assay scalable and easily reproduced across environments. PPiSeq is therefore a powerful new tool for large-scale investigations of dynamic PPIs.

[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.

Imbalance in chemical space: How to facilitate the identification of protein-protein interaction inhibitors.

PubMed

Kuenemann, Mélaine A; Labbé, Céline M; Cerdan, Adrien H; Sperandio, Olivier

2016-04-01

Protein-protein interactions (PPIs) play vital roles in life and provide new opportunities for therapeutic interventions. In this large data analysis, 3,300 inhibitors of PPIs (iPPIs) were compared to 17 reference datasets of collectively ~566,000 compounds (including natural compounds, existing drugs, active compounds on conventional targets, etc.) using a chemoinformatics approach. Using this procedure, we showed that comparable classes of PPI targets can be formed using either the similarity of their ligands or the shared properties of their binding cavities, constituting a proof-of-concept that not only can binding pockets be used to group PPI targets, but that these pockets certainly condition the properties of their corresponding ligands. These results demonstrate that matching regions in both chemical space and target space can be found. Such identified classes of targets could lead to the design of PPI-class-specific chemical libraries and therefore facilitate the development of iPPIs to the stage of drug candidates.

Clopidogrel and proton pump inhibitor (PPI) interaction: separate intake and a non-omeprazole PPI the solution?

PubMed Central

2010-01-01

Background Dual therapy with aspirin and clopidogrel increases the risk of gastrointestinal bleeding. Therefore, co-therapy with a proton pump inhibitor (PPI) is recommended by most guidelines. However, there are warnings against combining PPIs with clopidogrel because of their interactions with cytochrome P450 isoenzyme 2C19 (CYP2C19). Methods The effects of the combined or separate intake of 20 mg of omeprazole and 75 mg of clopidogrel on the clopidogrel-induced inhibition of platelet aggregation were measured in four healthy subjects whose CYP2C19 exon sequences were determined. The effects of co-therapy with 10 mg of rabeprazole were also examined. Results Two subjects showed the wild-type CYP2C19 sequence. The concurrent intake of omeprazole had no effect on clopidogrel-induced platelet inhibition in these subjects. Two subjects were heterozygous for the *2 allele, with predicted reduced CYP2C19 activity. One of them was a clopidogrel non-responder. In the second heterozygous subject, omeprazole co-therapy reduced the clopidogrel anti-platelet effect when taken simultaneously or separately. However, the simultaneous intake of rabeprazole did not reduce the clopidogrel effect. Conclusion The clopidogrel-PPI interaction does not seem to be a PPI class effect. Rabeprazole did not affect the clopidogrel effect in a subject with a clear omeprazole-clopidogrel interaction. The separate intake of PPI and clopidogrel may not be sufficient to prevent their interaction. PMID:20562062

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

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.

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.

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 .

Emory University: High-Throughput Protein-Protein Interaction Analysis for Hippo Pathway Profiling | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory University used high-throughput protein-protein interaction (PPI) mapping for Hippo signaling pathway profiling to rapidly unveil promising PPIs as potential therapeutic targets and advance functional understanding of signaling circuitry in cells. Read the abstract.

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.

Evaluating patient and public involvement in health research: from theoretical model to practical workshop.

PubMed

Gibson, Andy; Welsman, Jo; Britten, Nicky

2017-10-01

There is a growing literature on evaluating aspects of patient and public involvement (PPI). We have suggested that at the core of successful PPI is the dynamic interaction of different forms of knowledge, notably lay and professional. We have developed a four-dimensional theoretical framework for understanding these interactions. We explore the practical utility of the theoretical framework as a tool for mapping and evaluating the experience of PPI in health services research. We conducted three workshops with different PPI groups in which participants were invited to map their PPI experiences on wall charts representing the four dimensions of our framework. The language used to describe the four dimensions was modified to make it more accessible to lay audiences. Participants were given sticky notes to indicate their own positions on the different dimensions and to write explanatory comments if they wished. Participants' responses were then discussed and analysed as a group. The three groups were distinctive in their mapped responses suggesting different experiences in relation to having a strong or weak voice in their organization, having few or many ways of getting involved, addressing organizational or public concerns and believing that the organization was willing to change or not. The framework has practical utility for mapping and evaluating PPI interactions and is sensitive to differences in PPI experiences within and between different organizations. The workshops enabled participants to reflect collaboratively on their experiences with a view to improving PPI experiences and planning for the future. © 2017 The Authors Health Expectations published by John Wiley & Sons Ltd.

Application of the fragment molecular orbital method analysis to fragment-based drug discovery of BET (bromodomain and extra-terminal proteins) inhibitors.

PubMed

Ozawa, Motoyasu; Ozawa, Tomonaga; Ueda, Kazuyoshi

2017-06-01

The molecular interactions of inhibitors of bromodomains (BRDs) were investigated. BRDs are protein interaction modules that recognizing ε-N-acetyl-lysine (εAc-Lys) motifs found in histone tails and are promising protein-protein interaction (PPI) targets. First, we analyzed a peptide ligand containing εAc-Lys to evaluate native PPIs. We then analyzed tetrahydroquinazoline-6-yl-benzensulfonamide derivatives found by fragment-based drug design (FBDD) and examined their interactions with the protein compared with the peptide ligand in terms of the inter-fragment interaction energy. In addition, we analyzed benzodiazepine derivatives that are high-affinity ligands for BRDs and examined differences in the CH/π interactions of the amino acid residues. We further surveyed changes in the charges of the amino acid residues among individual ligands, performed pair interaction energy decomposition analysis and estimated the water profile within the ligand binding site. Thus, useful insights for drug design were provided. Through these analyses and considerations, we show that the FMO method is a useful drug design tool to evaluate the process of FBDD and to explore PPI inhibitors. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Proton pump inhibitors and potential interactions with clopidogrel: an update.

PubMed

Gerson, Lauren B

2013-06-01

Clopidogrel, an antiplatelet agent, is increasingly prescribed for patients with recent stroke, myocardial infarction, acute coronary syndrome, and/or patients post-coronary stent insertion to prevent recurrent cardiovascular events. Since clopidogrel can increase the risk of gastrointestinal hemorrhage, co-administration of proton pump inhibitors (PPIs) has been recommended, particularly in patients at high risk. In 2009, the FDA issued warnings about potential interactions between clopidogrel and PPIs, given the fact that both drugs are metabolized via the cytochrome P450 pathway. Prior studies have demonstrated significant reduction in platelet inhibition when PPI therapy is administered to subjects on clopidogrel therapy. Two meta-analyses were published in 2010 and 2011, the first suggesting association of PPIs with adverse cardiovascular events when observational studies were examined, but noting that the results were limited by the presence of significant heterogeneity. The second meta-analysis did not find a significant increase in the risk of adverse primary events (which included all cause mortality, cardiovascular death, myocardial infarction, or stroke), and concluded that analysis of the data from two randomized controlled trials yielded a risk difference of zero. An updated literature search was performed to assess clinical studies describing interactions between PPIs and clopidogrel published from 2011-2012. The majority of these studies did not show significant interactions when primary cardiac outcomes were considered. More importantly, the newer data demonstrated that PPI usage independently was a risk factor for adverse CV outcomes, since most PPI users were older patients who were more likely to have concomitant co-morbid conditions. Two updated reviews also concluded that the presence of confounding factors likely explained differences in results between studies, and that there were no significant differences in effects on clopidogrel between individual proton pump inhibitors. Overall, clinicians can assure their patients that combination therapy is safe when indicated in a patient at high risk of GI bleeding, but they should also stop PPI therapy if it is not clinically indicated.

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.

Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks

PubMed Central

Zhang, Yihua; Li, Wan; Feng, Yuyan; Guo, Shanshan; Zhao, Xilei; Wang, Yahui; He, Yuehan; He, Weiming; Chen, Lina

2017-01-01

Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, which could be caused by many factors, including disturbances of metabolism and protein-protein interactions (PPIs). In this paper, a weighted COPD-related metabolic network and a weighted COPD-related PPI network were constructed base on COPD disease genes and functional information. Candidate genes in these weighted COPD-related networks were prioritized by making use of a gene prioritization method, respectively. Literature review and functional enrichment analysis of the top 100 genes in these two networks suggested the correlation of COPD and these genes. The performance of our gene prioritization method was superior to that of ToppGene and ToppNet for genes from the COPD-related metabolic network or the COPD-related PPI network after assessing using leave-one-out cross-validation, literature validation and functional enrichment analysis. The top-ranked genes prioritized from COPD-related metabolic and PPI networks could promote the better understanding about the molecular mechanism of this disease from different perspectives. The top 100 genes in COPD-related metabolic network or COPD-related PPI network might be potential markers for the diagnosis and treatment of COPD. PMID:29262568

Prioritizing chronic obstructive pulmonary disease (COPD) candidate genes in COPD-related networks.

PubMed

Zhang, Yihua; Li, Wan; Feng, Yuyan; Guo, Shanshan; Zhao, Xilei; Wang, Yahui; He, Yuehan; He, Weiming; Chen, Lina

2017-11-28

Chronic obstructive pulmonary disease (COPD) is a multi-factor disease, which could be caused by many factors, including disturbances of metabolism and protein-protein interactions (PPIs). In this paper, a weighted COPD-related metabolic network and a weighted COPD-related PPI network were constructed base on COPD disease genes and functional information. Candidate genes in these weighted COPD-related networks were prioritized by making use of a gene prioritization method, respectively. Literature review and functional enrichment analysis of the top 100 genes in these two networks suggested the correlation of COPD and these genes. The performance of our gene prioritization method was superior to that of ToppGene and ToppNet for genes from the COPD-related metabolic network or the COPD-related PPI network after assessing using leave-one-out cross-validation, literature validation and functional enrichment analysis. The top-ranked genes prioritized from COPD-related metabolic and PPI networks could promote the better understanding about the molecular mechanism of this disease from different perspectives. The top 100 genes in COPD-related metabolic network or COPD-related PPI network might be potential markers for the diagnosis and treatment of COPD.

AlphaSpace: Fragment-Centric Topographical Mapping To Target Protein–Protein Interaction Interfaces

PubMed Central

2016-01-01

Inhibition of protein–protein interactions (PPIs) is emerging as a promising therapeutic strategy despite the difficulty in targeting such interfaces with drug-like small molecules. PPIs generally feature large and flat binding surfaces as compared to typical drug targets. These features pose a challenge for structural characterization of the surface using geometry-based pocket-detection methods. An attractive mapping strategy—that builds on the principles of fragment-based drug discovery (FBDD)—is to detect the fragment-centric modularity at the protein surface and then characterize the large PPI interface as a set of localized, fragment-targetable interaction regions. Here, we introduce AlphaSpace, a computational analysis tool designed for fragment-centric topographical mapping (FCTM) of PPI interfaces. Our approach uses the alpha sphere construct, a geometric feature of a protein’s Voronoi diagram, to map out concave interaction space at the protein surface. We introduce two new features—alpha-atom and alpha-space—and the concept of the alpha-atom/alpha-space pair to rank pockets for fragment-targetability and to facilitate the evaluation of pocket/fragment complementarity. The resulting high-resolution interfacial map of targetable pocket space can be used to guide the rational design and optimization of small molecule or biomimetic PPI inhibitors. PMID:26225450

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

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.

Co-complex protein membership evaluation using Maximum Entropy on GO ontology and InterPro annotation.

PubMed

Armean, Irina M; Lilley, Kathryn S; Trotter, Matthew W B; Pilkington, Nicholas C V; Holden, Sean B

2018-06-01

Protein-protein interactions (PPI) play a crucial role in our understanding of protein function and biological processes. The standardization and recording of experimental findings is increasingly stored in ontologies, with the Gene Ontology (GO) being one of the most successful projects. Several PPI evaluation algorithms have been based on the application of probabilistic frameworks or machine learning algorithms to GO properties. Here, we introduce a new training set design and machine learning based approach that combines dependent heterogeneous protein annotations from the entire ontology to evaluate putative co-complex protein interactions determined by empirical studies. PPI annotations are built combinatorically using corresponding GO terms and InterPro annotation. We use a S.cerevisiae high-confidence complex dataset as a positive training set. A series of classifiers based on Maximum Entropy and support vector machines (SVMs), each with a composite counterpart algorithm, are trained on a series of training sets. These achieve a high performance area under the ROC curve of ≤0.97, outperforming go2ppi-a previously established prediction tool for protein-protein interactions (PPI) based on Gene Ontology (GO) annotations. https://github.com/ima23/maxent-ppi. sbh11@cl.cam.ac.uk. Supplementary data are available at Bioinformatics online.

GraphCrunch 2: Software tool for network modeling, alignment and clustering.

PubMed

Kuchaiev, Oleksii; Stevanović, Aleksandar; Hayes, Wayne; Pržulj, Nataša

2011-01-19

Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI) data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL") for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other existing tool. Finally, GraphCruch 2 implements an algorithm for clustering nodes within a network based solely on their topological similarities. Using GraphCrunch 2, we demonstrate that eukaryotic and viral PPI networks may belong to different graph model families and show that topology-based clustering can reveal important functional similarities between proteins within yeast and human PPI networks. GraphCrunch 2 is a software tool that implements the latest research on biological network analysis. It parallelizes computationally intensive tasks to fully utilize the potential of modern multi-core CPUs. It is open-source and freely available for research use. It runs under the Windows and Linux platforms.

PIPE: a protein–protein interaction passage extraction module for BioCreative challenge

PubMed Central

Chu, Chun-Han; Su, Yu-Chen; Chen, Chien Chin; Hsu, Wen-Lian

2016-01-01

Identifying the interactions between proteins mentioned in biomedical literatures is one of the frequently discussed topics of text mining in the life science field. In this article, we propose PIPE, an interaction pattern generation module used in the Collaborative Biocurator Assistant Task at BioCreative V (http://www.biocreative.org/) to capture frequent protein-protein interaction (PPI) patterns within text. We also present an interaction pattern tree (IPT) kernel method that integrates the PPI patterns with convolution tree kernel (CTK) to extract PPIs. Methods were evaluated on LLL, IEPA, HPRD50, AIMed and BioInfer corpora using cross-validation, cross-learning and cross-corpus evaluation. Empirical evaluations demonstrate that our method is effective and outperforms several well-known PPI extraction methods. Database URL: PMID:27524807

LocFuse: human protein-protein interaction prediction via classifier fusion using protein localization information.

PubMed

Zahiri, Javad; Mohammad-Noori, Morteza; Ebrahimpour, Reza; Saadat, Samaneh; Bozorgmehr, Joseph H; Goldberg, Tatyana; Masoudi-Nejad, Ali

2014-12-01

Protein-protein interaction (PPI) detection is one of the central goals of functional genomics and systems biology. Knowledge about the nature of PPIs can help fill the widening gap between sequence information and functional annotations. Although experimental methods have produced valuable PPI data, they also suffer from significant limitations. Computational PPI prediction methods have attracted tremendous attentions. Despite considerable efforts, PPI prediction is still in its infancy in complex multicellular organisms such as humans. Here, we propose a novel ensemble learning method, LocFuse, which is useful in human PPI prediction. This method uses eight different genomic and proteomic features along with four types of different classifiers. The prediction performance of this classifier selection method was found to be considerably better than methods employed hitherto. This confirms the complex nature of the PPI prediction problem and also the necessity of using biological information for classifier fusion. The LocFuse is available at: http://lbb.ut.ac.ir/Download/LBBsoft/LocFuse. The results revealed that if we divide proteome space according to the cellular localization of proteins, then the utility of some classifiers in PPI prediction can be improved. Therefore, to predict the interaction for any given protein pair, we can select the most accurate classifier with regard to the cellular localization information. Based on the results, we can say that the importance of different features for PPI prediction varies between differently localized proteins; however in general, our novel features, which were extracted from position-specific scoring matrices (PSSMs), are the most important ones and the Random Forest (RF) classifier performs best in most cases. LocFuse was developed with a user-friendly graphic interface and it is freely available for Linux, Mac OSX and MS Windows operating systems. Copyright © 2014 Elsevier Inc. All rights reserved.

Solubility and surface thermodynamics of conducting polymers by inverse gas chromatography. III: polypyrrole chloride.

PubMed

Duaij, Omar K; Alghamdi, Ali; Al-Saigh, Zeki Y

2013-05-24

Inverse gas chromatography, IGC, was applied to characterize conducting polypyrrole chloride (PPyCl) using twenty three solvents. IGC is able to reveal the change in the morphology, the strength of solvent-PPyCl interactions, thermodynamics parameters (χ12, Ω1(∞)), solvent and polymer solubility parameters, and molar heats of sorption, mixing and evaporation (ΔH1(s), ΔH1(∞), ΔH1(v)). The following solvents showed stronger interactions than others; yet, none of these solvents are good solvents for PPyCl: dodecane among the alkane family, tetrahydrofuran and methyl ethyl ketone among the oxy and keto group, dichloromethane among the chlorinated group up to 120°C and chloroform at 180°C, and toluene among the cyclic and aromatic group. Overall, the groups showed higher affinities to PPyCl are: acetates, oxy and cyclic, and chlorinated groups. Comprehensive solvents and PPyCl solubility parameters are obtained. The latter showed that PPyCl is not soluble in any solvent used. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

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.

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

All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning.

PubMed

Airola, Antti; Pyysalo, Sampo; Björne, Jari; Pahikkala, Tapio; Ginter, Filip; Salakoski, Tapio

2008-11-19

Automated extraction of protein-protein interactions (PPI) is an important and widely studied task in biomedical text mining. We propose a graph kernel based approach for this task. In contrast to earlier approaches to PPI extraction, the introduced all-paths graph kernel has the capability to make use of full, general dependency graphs representing the sentence structure. We evaluate the proposed method on five publicly available PPI corpora, providing the most comprehensive evaluation done for a machine learning based PPI-extraction system. We additionally perform a detailed evaluation of the effects of training and testing on different resources, providing insight into the challenges involved in applying a system beyond the data it was trained on. Our method is shown to achieve state-of-the-art performance with respect to comparable evaluations, with 56.4 F-score and 84.8 AUC on the AImed corpus. We show that the graph kernel approach performs on state-of-the-art level in PPI extraction, and note the possible extension to the task of extracting complex interactions. Cross-corpus results provide further insight into how the learning generalizes beyond individual corpora. Further, we identify several pitfalls that can make evaluations of PPI-extraction systems incomparable, or even invalid. These include incorrect cross-validation strategies and problems related to comparing F-score results achieved on different evaluation resources. Recommendations for avoiding these pitfalls are provided.

Large-Scale Validation of Mixed-Solvent Simulations to Assess Hotspots at Protein-Protein Interaction Interfaces.

PubMed

Ghanakota, Phani; van Vlijmen, Herman; Sherman, Woody; Beuming, Thijs

2018-04-23

The ability to target protein-protein interactions (PPIs) with small molecule inhibitors offers great promise in expanding the druggable target space and addressing a broad range of untreated diseases. However, due to their nature and function of interacting with protein partners, PPI interfaces tend to extend over large surfaces without the typical pockets of enzymes and receptors. These features present unique challenges for small molecule inhibitor design. As such, determining whether a particular PPI of interest could be pursued with a small molecule discovery strategy requires an understanding of the characteristics of the PPI interface and whether it has hotspots that can be leveraged by small molecules to achieve desired potency. Here, we assess the ability of mixed-solvent molecular dynamic (MSMD) simulations to detect hotspots at PPI interfaces. MSMD simulations using three cosolvents (acetonitrile, isopropanol, and pyrimidine) were performed on a large test set of 21 PPI targets that have been experimentally validated by small molecule inhibitors. We compare MSMD, which includes explicit solvent and full protein flexibility, to a simpler approach that does not include dynamics or explicit solvent (SiteMap) and find that MSMD simulations reveal additional information about the characteristics of these targets and the ability for small molecules to inhibit the PPI interface. In the few cases were MSMD simulations did not detect hotspots, we explore the shortcomings of this technique and propose future improvements. Finally, using Interleukin-2 as an example, we highlight the advantage of the MSMD approach for detecting transient cryptic druggable pockets that exists at PPI interfaces.

Emory University: Prediction of Protein-Protein Interactions by NanoLuc-Based Protein-Fragment Complementation Assay | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory has developed a new NanoLuc®-based protein-fragment complementation assay (NanoPCA) which allows the detection of novel protein-protein interactions (PPI). NanoPCA allows the study of PPI dynamics with reversible interactions.  Read the abstract. Experimental Approaches Read the detailed Experimetnal Approaches. 

Prediction of Protein-Protein Interactions by NanoLuc-Based Protein-Fragment Complementation Assay | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory has developed a new NanoLuc®-based protein-fragment complementation assay (NanoPCA) which allows the detection of novel protein-protein interactions (PPI). NanoPCA allows the study of PPI dynamics with reversible interactions.  Read the abstract. Experimental Approaches Read the detailed Experimetnal Approaches. 

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.

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.

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.

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.

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.

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.

A leap into the chemical space of protein-protein interaction inhibitors.

PubMed

Villoutreix, B O; Labbé, C M; Lagorce, D; Laconde, G; Sperandio, O

2012-01-01

Protein-protein interactions (PPI) are involved in vital cellular processes and are therefore associated to a growing number of diseases. But working with them as therapeutic targets comes with some major hurdles that require substantial mutations from our way to design drugs on historical targets such as enzymes and G-Protein Coupled Receptor (GPCR). Among the numerous ways we could improve our methodologies to maximize the potential of developing new chemical entities on PPI targets, is the fundamental question of what type of compounds should we use to identify the first hits and among which chemical space should we navigate to optimize them to the drug candidate stage. In this review article, we cover different aspects on PPI but with the aim to gain some insights into the specific nature of the chemical space of PPI inhibitors. We describe the work of different groups to highlight such properties and discuss their respective approach. We finally discuss a case study in which we describe the properties of a set of 115 PPI inhibitors that we compare to a reference set of 1730 enzyme inhibitors. This case study highlights interesting properties such as the unfortunate price that still needs to be paid by PPI inhibitors in terms of molecular weight, hydrophobicity, and aromaticity in order to reach a critical level of activity. But it also shows that not all PPI targets are equivalent, and that some PPI targets can demonstrate a better druggability by illustrating the better drug likeness of their associated inhibitors.

Impact of Proton Pump Inhibitor Use on the Comparative Effectiveness and Safety of Prasugrel Versus Clopidogrel: Insights From the Treatment With Adenosine Diphosphate Receptor Inhibitors: Longitudinal Assessment of Treatment Patterns and Events After Acute Coronary Syndrome (TRANSLATE-ACS) Study.

PubMed

Jackson, Larry R; Peterson, Eric D; McCoy, Lisa A; Ju, Christine; Zettler, Marjorie; Baker, Brian A; Messenger, John C; Faries, Douglas E; Effron, Mark B; Cohen, David J; Wang, Tracy Y

2016-10-21

Proton pump inhibitors (PPIs) reduce gastrointestinal bleeding events but may alter clopidogrel metabolism. We sought to understand the comparative effectiveness and safety of prasugrel versus clopidogrel in the context of proton pump inhibitor (PPI) use. Using data on 11 955 acute myocardial infarction (MI) patients treated with percutaneous coronary intervention at 233 hospitals and enrolled in the TRANSLATE-ACS study, we compared whether discharge PPI use altered the association of 1-year adjusted risks of major adverse cardiovascular events (MACE; death, MI, stroke, or unplanned revascularization) and Global Use of Strategies To Open Occluded Arteries (GUSTO) moderate/severe bleeding between prasugrel- and clopidogrel-treated patients. Overall, 17% of prasugrel-treated and 19% of clopidogrel-treated patients received a PPI at hospital discharge. At 1 year, patients discharged on a PPI versus no PPI had higher risks of MACE (adjusted hazard ratio [HR] 1.38, 95% confidence interval [CI] 1.21-1.58) and GUSTO moderate/severe bleeding (adjusted HR 1.55, 95% CI 1.15-2.09). Risk of MACE was similar between prasugrel and clopidogrel regardless of PPI use (adjusted HR 0.88, 95% CI 0.62-1.26 with PPI, adjusted HR 1.07, 95% CI 0.90-1.28 without PPI, interaction P=0.31). Comparative bleeding risk associated with prasugrel versus clopidogrel use differed based on PPI use but did not reach statistical significance (adjusted HR 0.73, 95% CI 0.36-1.48 with PPI, adjusted HR 1.34, 95% CI 0.79-2.27 without PPI, interaction P=0.17). PPIs did not significantly affect the MACE and bleeding risk associated with prasugrel use, relative to clopidogrel. URL: https://www.clinicaltrials.gov. Unique identifier: NCT01088503. © 2016 The Authors and Eli Lilly & Company. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

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.

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

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

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.

Striking differences in properties of geometric isomers of [Ir(tpy)(ppy)H](+): Experimental and computational studies on their hydricities, interaction with CO 2, and photochemistry

DOE PAGES

Garg, Komal; Fujita, Etsuko; Matsubara, Yasuo; ...

2015-11-16

Here, we prepared two geometric isomers of [Ir(tpy)(ppy)H] +, previously proposed as a key intermediate in the photochemical reduction of CO 2 to CO, and characterized their notably different ground- and excited-state interactions with CO 2 and their hydricities using experimental and computational methods. Only one isomer, C-trans-[Ir(tpy)(ppy)H] +, reacts with CO 2 to generate the formato complex in the ground state, consistent with its calculated hydricity. Under photocatalytic conditions in CH 3CN/TEOA, a common reactive C-trans-[Ir(tpy)(ppy)] 0 species, irrespective of the starting isomer or monodentate ligand (such as hydride or Cl), reacts with CO 2 and produces CO withmore » the same catalytic efficiency.« less

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.

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.

Computational analysis of protein-protein interfaces involving an alpha helix: insights for terphenyl-like molecules binding.

PubMed

Isvoran, Adriana; Craciun, Dana; Martiny, Virginie; Sperandio, Olivier; Miteva, Maria A

2013-06-14

Protein-Protein Interactions (PPIs) are key for many cellular processes. The characterization of PPI interfaces and the prediction of putative ligand binding sites and hot spot residues are essential to design efficient small-molecule modulators of PPI. Terphenyl and its derivatives are small organic molecules known to mimic one face of protein-binding alpha-helical peptides. In this work we focus on several PPIs mediated by alpha-helical peptides. We performed computational sequence- and structure-based analyses in order to evaluate several key physicochemical and surface properties of proteins known to interact with alpha-helical peptides and/or terphenyl and its derivatives. Sequence-based analysis revealed low sequence identity between some of the analyzed proteins binding alpha-helical peptides. Structure-based analysis was performed to calculate the volume, the fractal dimension roughness and the hydrophobicity of the binding regions. Besides the overall hydrophobic character of the binding pockets, some specificities were detected. We showed that the hydrophobicity is not uniformly distributed in different alpha-helix binding pockets that can help to identify key hydrophobic hot spots. The presence of hydrophobic cavities at the protein surface with a more complex shape than the entire protein surface seems to be an important property related to the ability of proteins to bind alpha-helical peptides and low molecular weight mimetics. Characterization of similarities and specificities of PPI binding sites can be helpful for further development of small molecules targeting alpha-helix binding proteins.

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.

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.

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.

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

Large-scale protein-protein interactions detection by integrating big biosensing data with computational model.

PubMed

You, Zhu-Hong; Li, Shuai; Gao, Xin; Luo, Xin; Ji, Zhen

2014-01-01

Protein-protein interactions are the basis of biological functions, and studying these interactions on a molecular level is of crucial importance for understanding the functionality of a living cell. During the past decade, biosensors have emerged as an important tool for the high-throughput identification of proteins and their interactions. However, the high-throughput experimental methods for identifying PPIs are both time-consuming and expensive. On the other hand, high-throughput PPI data are often associated with high false-positive and high false-negative rates. Targeting at these problems, we propose a method for PPI detection by integrating biosensor-based PPI data with a novel computational model. This method was developed based on the algorithm of extreme learning machine combined with a novel representation of protein sequence descriptor. When performed on the large-scale human protein interaction dataset, the proposed method achieved 84.8% prediction accuracy with 84.08% sensitivity at the specificity of 85.53%. We conducted more extensive experiments to compare the proposed method with the state-of-the-art techniques, support vector machine. The achieved results demonstrate that our approach is very promising for detecting new PPIs, and it can be a helpful supplement for biosensor-based PPI data detection.

"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.

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.

Correlative Förster Resonance Electron Transfer-Proximity Ligation Assay (FRET-PLA) Technique for Studying Interactions Involving Membrane Proteins.

PubMed

Ivanusic, Daniel; Denner, Joachim; Bannert, Norbert

2016-08-01

This unit provides a guide and detailed protocol for studying membrane protein-protein interactions (PPI) using the acceptor-sensitized Förster resonance electron transfer (FRET) method in combination with the proximity ligation assay (PLA). The protocol in this unit is focused on the preparation of FRET-PLA samples and the detection of correlative FRET/PLA signals as well as on the analysis of FRET-PLA data and interpretation of correlative results when using cyan fluorescent protein (CFP) as a FRET donor and yellow fluorescent protein (YFP) as a FRET acceptor. The correlative application of FRET and PLA combines two powerful tools for monitoring PPI, yielding results that are more reliable than with either technique alone. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

Interactions between gastro-oesophageal reflux disease and eosinophilic oesophagitis.

PubMed

Molina-Infante, Javier; van Rhijn, Bram D

2015-10-01

Gastro-oesophageal reflux disease (GORD) is the most common oesophageal disorder, whereas eosinophilic oesophagitis (EoE) is an emerging disease unresponsive to PPI therapy. Updated guidelines in 2011 described proton pump inhibitor-responsive esophageal eosinophilia (PPI-REE), a novel phenotype in EoE patients who were responsive to PPIs. This article aims to update the complex interplay between GORD, EoE and PPIs. Oesophageal mucosal integrity is diffusely impaired in EoE and PPI-REE patients. PPI-REE might occur with either normal or pathological pH monitoring. The genetic hallmark of EoE is overlapped in PPI-REE, but not in GORD. PPIs can partially restore epithelial integrity and reverse allergic inflammation gene expression in PPI-REE. Acid hypersensitivity in EoE patients may explain symptomatic but not histological response on PPIs. Unsolved issues with PPI-REE are whether oesophageal barrier impairment is the cause or the effect of oesophageal eosinophilia and whether PPIs primarily targets barrier integrity or oesophageal inflammation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Gas Sensitivity Study of Polypyrrole Decorated Graphene Oxide Thick Film

NASA Astrophysics Data System (ADS)

Patil, Pritam; Gaikwad, Ganesh; Patil, Devidas Ramrao; Naik, Jitendra

2016-04-01

Polypyrrole (PPy) and graphene oxide (GO) nanocomposites were prepared by in situ polymerization method. The synthesized nanocomposites were characterized for current-voltage characteristic, Fourier transform infrared spectroscopy, X-ray diffraction and field emission scanning electron microscopy, which gave the evidence of the strong interaction between PPy nanofibers and GO nanosheets. The PPy/GO nanocomposites were used for the sensing of H2S, LPG, CO2 and NH3 gases respectively at room temperature. It was observed that PPy/GO nanocomposites with different GO weight ratios (5, 10 and 20 %) had better selectivity and sensitivity towards NH3 at room temperature.

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

Docosahexaenoic acid triglyceride-based microemulsions with an added dendrimer - Structural considerations.

PubMed

Lidich, Nina; Francesca Ottaviani, M; Hoffman, Roy E; Aserin, Abraham; Garti, Nissim

2016-12-01

Omega fatty acids, mainly the triglyceride of docosahexaenoic acid (TG-DHA), are considered important nutraceuticals. These compounds are water-insoluble and their transport across membranes depends on their carriers. Dendrimers are known as drug carriers across cell membranes and also as permeation enhancers. The solubilization of TG-DHA and dendrimer into a microemulsion (ME) system serving as a carrier could be used for a targeted delivery in the future. The interactions between TG-DHA and second generation poly(propyleneimine) dendrimers (PPI-G2) and their effect on structural transitions of ME were explored along the water dilution line using electron paramagnetic resonance and pulsed-gradient spin-echo NMR along with other analytical techniques. The microviscosity, order parameter, and micropolarity of all studied systems decrease upon water dilution. Incorporation of TG-DHA reduces the microviscosity, order, and micropolarity, whereas PPI-G2 leads to an increase in these parameters. The effect of PPI-G2 is more pronounced at relative high contents (1 and 5wt%) where PPI-G2 interacts with the hydrophilic headgroups of the surfactants. In the macroscale, the effects of TG-DHA and PPI-G2 differ mostly in the bicontinuous region, where macroviscosity increases upon TG-DHA incorporation and decreases upon solubilization of 5wt% PPI-G2. From DSC measurements it was concluded that in the presence of TG-DHA the PPI-G2 is intercalated easily at the interface. Copyright © 2016 Elsevier Inc. All rights reserved.

A systematic molecular dynamics approach to the study of peptide Keap1-Nrf2 protein-protein interaction inhibitors and its application to p62 peptides.

PubMed

Lu, Meng-Chen; Yuan, Zhen-Wei; Jiang, Yong-Lin; Chen, Zhi-Yun; You, Qi-Dong; Jiang, Zheng-Yu

2016-04-01

Protein-protein interactions (PPIs) as drug targets have been gaining growing interest, though developing drug-like small molecule PPI inhibitors remains challenging. Peptide PPI inhibitors, which can provide informative data on the PPI interface, are good starting points to develop small molecule modulators. Computational methods combining molecular dynamics simulations and binding energy calculations could give both the structural and the energetic perspective of peptide PPI inhibitors. Herein, we set up a computational workflow to investigate Keap1-Nrf2 peptide PPI inhibitors and predict the activity of novel sequences. Furthermore, we applied this method to investigate p62 peptides as PPI inhibitors of Keap1-Nrf2 and explored the activity change induced by the phosphorylation of serine. Our results showed that because of the unfavorable solvation effects, the binding affinity of the phosphorylated p62 peptide is lower than the Nrf2 ETGE peptide. Our research results not only provide a useful method to investigate the Keap1-Nrf2 peptide inhibitors, but also give a good example to show how to incorporate computational methods into the study of peptide PPI inhibitors. Besides, applying this method to p62 peptides provides a detailed explanation for the expression of cytoprotective Nrf2 targets induced by p62 phosphorylation, which may benefit the further study of the crosstalk between the Keap1-Nrf2 pathway and p62-mediated selective autophagy.

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.

Inhibitors of protein-protein interactions (PPIs): an analysis of scaffold choices and buried surface area.

PubMed

Ran, Xu; Gestwicki, Jason E

2018-06-13

Protein-protein interactions (PPI) were once considered 'undruggable', but clinical successes, driven by advanced methods in drug discovery, have challenged that notion. Here, we review the last three years of literature on PPI inhibitors to understand what is working and why. From the 66 recently reported PPI inhibitors, we found that the average molecular weight was significantly greater than 500Da, but that this trend was driven, in large part, by the contribution of peptide-based compounds. Despite differences in average molecular weight, we found that compounds based on small molecules or peptides were almost equally likely to be potent inhibitors (K D <1μM). Finally, we found PPIs with buried surface area (BSA) less than 2000Å 2 were more likely to be inhibited by small molecules, while PPIs with larger BSA values were typically inhibited by peptides. PPIs with BSA values over 4000Å 2 seemed to create a particular challenge, especially for orthosteric small molecules. Thus, it seems important to choose the inhibitor scaffold based on the properties of the target interaction. Moreover, this survey suggests a (more nuanced) conclusion to the question of whether PPIs are good drug targets; namely, that some PPIs are readily 'druggable' given the right choice of scaffold, while others still seem to deserve the 'undruggable' moniker. Copyright © 2018 Elsevier Ltd. All rights reserved.

Synthesis and electromagnetic interference shielding of cellulose-derived carbon aerogels functionalized with α-Fe2O3 and polypyrrole.

PubMed

Wan, Caichao; Li, Jian

2017-04-01

Eco-friendly cellulose-derived carbon aerogels (CDCA) were employed as porous substrate to integrate with α-Fe 2 O 3 and polypyrrole (PPy) via pyrolysis and vapor-phase polymerization. The SEM and TEM observations present that the wrinkled PPy sheets and the α-Fe 2 O 3 nanoparticles were well dispersed in CDCA. The strong interactions (such as hydrogen bonding) between the substrate and the nanomaterials were demonstrated by the FTIR and XPS analysis. When utilized as electromagnetic interference (EMI) shielding materials, the α-Fe 2 O 3 /PPy/CDCA (FPCA) composite has the highest total shielding effectiveness (SE total ) of 39.4dB, about 2.0, 2.9, and 1.3 times that of the acid-treated CDCA (19.3dB), PPy (13.6dB), and α-Fe 2 O 3 /CDCA (29.3dB), respectively. Moreover, the shielding effectiveness due to absorption accounts for 78.2%-84.2% of SE total for FPCA, indicative of the absorption-dominant shielding mechanism contributing to alleviating secondary radiation. These features make the composite a useful alternative candidate for EMI shielding. Copyright © 2017 Elsevier Ltd. All rights reserved.

Kinase Substrate Sensor (KISS), a Mammalian In Situ Protein Interaction Sensor*

PubMed Central

Lievens, Sam; Gerlo, Sarah; Lemmens, Irma; De Clercq, Dries J. H.; Risseeuw, Martijn D. P.; Vanderroost, Nele; De Smet, Anne-Sophie; Ruyssinck, Elien; Chevet, Eric; Van Calenbergh, Serge; Tavernier, Jan

2014-01-01

Probably every cellular process is governed by protein-protein interaction (PPIs), which are often highly dynamic in nature being modulated by in- or external stimuli. Here we present KISS, for KInase Substrate Sensor, a mammalian two-hybrid approach designed to map intracellular PPIs and some of the dynamic features they exhibit. Benchmarking experiments indicate that in terms of sensitivity and specificity KISS is on par with other binary protein interaction technologies while being complementary with regard to the subset of PPIs it is able to detect. We used KISS to evaluate interactions between different types of proteins, including transmembrane proteins, expressed at their native subcellular location. In situ analysis of endoplasmic reticulum stress-induced clustering of the endoplasmic reticulum stress sensor ERN1 and ligand-dependent β-arrestin recruitment to GPCRs illustrated the method's potential to study functional PPI modulation in complex cellular processes. Exploring its use as a tool for in cell evaluation of pharmacological interference with PPIs, we showed that reported effects of known GPCR antagonists and PPI inhibitors are properly recapitulated. In a three-hybrid setup, KISS was able to map interactions between small molecules and proteins. Taken together, we established KISS as a sensitive approach for in situ analysis of protein interactions and their modulation in a changing cellular context or in response to pharmacological challenges. PMID:25154561

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

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

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.

An electrochemical aptasensor based on a TiO2/three-dimensional reduced graphene oxide/PPy nanocomposite for the sensitive detection of lysozyme.

PubMed

Wang, Minghua; Zhai, Shuyong; Ye, Zihan; He, Linghao; Peng, Donglai; Feng, Xiaozhong; Yang, Yanqin; Fang, Shaoming; Zhang, Hongzhong; Zhang, Zhihong

2015-04-14

A sensitive aptasensor based on a nanocomposite of hollow titanium dioxide nanoball, three-dimensional reduced graphene oxide, and polypyrrole (TiO2/3D-rGO/PPy) was developed for lysozyme detection. A lysozyme aptamer was easily immobilized onto the TiO2/3D-rGO/PPy nanocomposite matrix by assembling the aptamer onto graphene through simple π-stacking interactions and electrostatic interactions between PPy molecular chains and aptamer strands. In the presence of lysozyme, the aptamer on the adsorbent layer catches the target on the electrode interface, which generates a barrier for electrons and inhibits electron transfer, subsequently resulting in decreased electrochemically differential pulse voltammetric signals of a gold electrode modified with TiO2/3D-rGO/PPy. Using this strategy, a low limit of detection of 0.085 ng mL(-1) (5.5 pM) for detecting lysozyme was observed within the detection range of 0.1-50 ng mL(-1) (0.007-3.5 nM). The aptasensor also presents high specificity for lysozyme, which is unaffected by the coexistence of other proteins. Such an aptasensor opens a rapid, selective, and sensitive route to lysozyme detection. This finding indicates that the TiO2/3D-rGO/PPy nanocomposite could be used as an electrochemical biosensor for detecting proteins in the biomedical field.

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.

Assessment of drug-drug interaction potential between ceritinib and proton pump inhibitors in healthy subjects and in patients with ALK-positive non-small cell lung cancer.

PubMed

Lau, Yvonne Y; Gu, Wen; Lin, Tiffany; Viraswami-Appanna, Kalyanee; Cai, Can; Scott, Jeffrey W; Shi, Michael

2017-06-01

The impact of proton pump inhibitors (PPIs) on the pharmacokinetics (PK) and efficacy of ceritinib was evaluated. A healthy subject drug-drug interaction (DDI) study was conducted to assess the effect of esomeprazole on the PK of a single 750 mg dose of ceritinib. To further investigate the impact of PPIs on the PK and efficacy of ceritinib in ALK-positive cancer patients, two subgroup analyses were performed. Analysis 1 evaluated ceritinib steady-state trough concentration (C trough,ss ) and overall response rate (ORR) by concomitant use of PPIs in patients from the ASCEND-1, -2, and -3 studies; analysis 2 evaluated ceritinib single-dose and steady-state AUC 0-24h and C max by concomitant PPI use in patients from ASCEND-1 using a definition of PPI usage similar to that used in the healthy subject study. In the healthy subject study, co-administration of a single 750 mg dose of ceritinib with esomeprazole 40 mg for 6 days decreased ceritinib AUC 0-∞ by 76% and C max by 79%. However, based on subgroup analysis 1, patients had similar C trough,ss and ORR regardless of concomitant PPI usage. Based on analysis 2, co-administration of a single 750 mg ceritinib dose with PPIs for 6 days in patients suggested less effect on ceritinib exposure than that observed in healthy subjects as AUC 0-24h decreased by 30% and C max decreased by 25%. No clinically meaningful effect on steady-state exposure was observed after daily dosing. Long-term administration of ceritinib with PPIs does not adversely affect the PK and efficacy of ceritinib in ALK-positive cancer patients.

Targeting protein-protein interactions in hematologic malignancies: still a challenge or a great opportunity for future therapies?

PubMed Central

Cierpicki, Tomasz; Grembecka, Jolanta

2015-01-01

Summary Over the past several years, there has been an increasing research effort focused on inhibition of protein-protein interactions (PPIs) to develop novel therapeutic approaches for cancer, including hematologic malignancies. These efforts have led to development of small molecule inhibitors of PPIs, some of which already advanced to the stage of clinical trials while others are at different stages of pre-clinical optimization, emphasizing PPIs as an emerging and attractive class of drug targets. Here, we review several examples of recently developed inhibitors of protein-protein interactions highly relevant to hematologic cancers. We address the existing skepticism about feasibility of targeting PPIs and emphasize potential therapeutic benefit from blocking PPIs in hematologic malignancies. We then use these examples to discuss the approaches for successful identification of PPI inhibitors and provide analysis of the protein-protein interfaces, with the goal to address ‘druggability’ of new PPIs relevant to hematology. We discuss lessons learned to improve the success of targeting new protein-protein interactions and evaluate prospects and limits of the research in this field. We conclude that not all PPIs are equally tractable for blocking by small molecules, and detailed analysis of PPI interfaces is critical for selection of those with the highest chance of success. Together, our analysis uncovers patterns that should help to advance drug discovery in hematologic malignancies by successful targeting of new protein-protein interactions. PMID:25510283

Influence of the Acidic Beverage Cola on the Absorption of Erlotinib in Patients With Non-Small-Cell Lung Cancer.

PubMed

van Leeuwen, Roelof W F; Peric, Robert; Hussaarts, Koen G A M; Kienhuis, Emma; IJzerman, Nikki S; de Bruijn, Peter; van der Leest, Cor; Codrington, Henk; Kloover, Jeroen S; van der Holt, Bronno; Aerts, Joachim G; van Gelder, Teun; Mathijssen, Ron H J

2016-04-20

Erlotinib depends on stomach pH for its bioavailability. When erlotinib is taken concurrently with a proton pump inhibitor (PPI), stomach pH increases, which results in a clinically relevant decrease of erlotinib bioavailability. We hypothesized that this drug-drug interaction is reversed by taking erlotinib with the acidic beverage cola. The effects of cola on erlotinib bioavailability in patients not treated with a PPI were also studied. In this randomized, cross-over, pharmacokinetic study in patients with non-small-cell lung cancer, we studied intrapatient differences in absorption (area under the plasma concentration time curve [AUC0-12h]) after a 7-day period of concomitant treatment with erlotinib, with or without esomeprazole, with either cola or water. At the 7th and 14th day, patients were hospitalized for 1 day for pharmacokinetic sampling. Twenty-eight evaluable patients were included in the analysis. In patients treated with erlotinib and esomeprazole with cola, the mean AUC0-12h increased 39% (range, -12% to 136%; P = .004), whereas in patients not treated with the PPI, the mean AUC0-12h was only slightly higher (9%; range, -10% to +30%; P = .03) after erlotinib intake with cola. Cola intake led to a clinically relevant and statistically significant increase in the bioavailability of erlotinib during esomeprazole treatment. In patients not treated with the PPI, the effects of cola were marginal. These findings can be used to optimize the management of drug-drug interactions between PPIs and erlotinib. © 2016 by American Society of Clinical Oncology.

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.

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.

Facile Synthesis of Conductive Polypyrrole Wrinkle Topographies on Polydimethylsiloxane via a Swelling-Deswelling Process and Their Potential Uses in Tissue Engineering.

PubMed

Aufan, M Rifqi; Sumi, Yang; Kim, Semin; Lee, Jae Young

2015-10-28

Electrically conducting biomaterials have gained great attention in various biomedical studies especially to influence cell and tissue responses. In addition, wrinkling can present a unique topography that can modulate cell-material interactions. In this study, we developed a simple method to create wrinkle topographies of conductive polypyrrole (wPPy) on soft polydimethylsiloxane surfaces via a swelling-deswelling process during and after PPy polymerization and by varying the thickness of the PPy top layers. As a result, various features of wPPy in the range of the nano- and microscales were successfully obtained. In vitro cell culture studies with NIH 3T3 fibroblasts and PC12 neuronal cells indicated that the conductive wrinkle topographies promote cell adhesion and neurite outgrowth of PC12 cells. Our studies help to elucidate the design of the surface coating and patterning of conducting polymers, which will enable us to simultaneously provide topographical and electrical signals to improve cell-surface interactions for potential tissue-engineering applications.

Enhancement of p-Type Dye-Sensitized Solar Cell Performance by Supramolecular Assembly of Electron Donor and Acceptor

PubMed Central

Tian, Haining; Oscarsson, Johan; Gabrielsson, Erik; Eriksson, Susanna K.; Lindblad, Rebecka; Xu, Bo; Hao, Yan; Boschloo, Gerrit; Johansson, Erik M. J.; Gardner, James M.; Hagfeldt, Anders; Rensmo, Håkan; Sun, Licheng

2014-01-01

Supramolecular interactions based on porphyrin and fullerene derivatives were successfully adopted to improve the photovoltaic performance of p-type dye-sensitized solar cells (DSCs). Photoelectron spectroscopy (PES) measurements suggest a change in binding configuration of ZnTCPP after co-sensitization with C60PPy, which could be ascribed to supramolecular interaction between ZnTCPP and C60PPy. The performance of the ZnTCPP/C60PPy-based p-type DSC has been increased by a factor of 4 in comparison with the DSC with the ZnTCPP alone. At 560 nm, the IPCE value of DSCs based on ZnTCPP/C60PPy was a factor of 10 greater than that generated by ZnTCPP-based DSCs. The influence of different electrolytes on charge extraction and electron lifetime was investigated and showed that the enhanced Voc from the Co2+/3+(dtbp)3-based device is due to the positive EF shift of NiO. PMID:24603319

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/.

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.

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

Guidance of neurite outgrowth on aligned electrospun polypyrrole/poly(styrene-beta-isobutylene-beta-styrene) fiber platforms.

PubMed

Liu, Xiao; Chen, Jun; Gilmore, Kerry J; Higgins, Michael J; Liu, Yong; Wallace, Gordon G

2010-09-15

The purpose of this work was to investigate the potential biomedical application of novel aligned electrospun polypyrrole (PPy)/poly(styrene-beta-isobutylene-beta-styrene) (SIBS) fibers. After successfully aligning the electroactive PPy/SIBS fibers based on our modified electrospinning method, we demonstrated that neurite outgrowth from PC12 cells could be highly orientated parallel to the aligned PPy/SIBS fibers. Physical interactions between the nerve cells and PPy/SIBS fibers through filopodia "sensing" were observed using atomic force microscopy. These observations indicate a role of contact guidance as a mechanism for the observed alignment. This work highlights the capacity for electroactive PPy/SIBS fibers to support and guide nerve cell differentiation through topographic cues, which is a highly desirable characteristic in medical implants for neurological applications. (c) 2010 Wiley Periodicals, Inc.

Clustering PPI data by combining FA and SHC method.

PubMed

Lei, Xiujuan; Ying, Chao; Wu, Fang-Xiang; Xu, Jin

2015-01-01

Clustering is one of main methods to identify functional modules from protein-protein interaction (PPI) data. Nevertheless traditional clustering methods may not be effective for clustering PPI data. In this paper, we proposed a novel method for clustering PPI data by combining firefly algorithm (FA) and synchronization-based hierarchical clustering (SHC) algorithm. Firstly, the PPI data are preprocessed via spectral clustering (SC) which transforms the high-dimensional similarity matrix into a low dimension matrix. Then the SHC algorithm is used to perform clustering. In SHC algorithm, hierarchical clustering is achieved by enlarging the neighborhood radius of synchronized objects continuously, while the hierarchical search is very difficult to find the optimal neighborhood radius of synchronization and the efficiency is not high. So we adopt the firefly algorithm to determine the optimal threshold of the neighborhood radius of synchronization automatically. The proposed algorithm is tested on the MIPS PPI dataset. The results show that our proposed algorithm is better than the traditional algorithms in precision, recall and f-measure value.

Clustering PPI data by combining FA and SHC method

PubMed Central

2015-01-01

Clustering is one of main methods to identify functional modules from protein-protein interaction (PPI) data. Nevertheless traditional clustering methods may not be effective for clustering PPI data. In this paper, we proposed a novel method for clustering PPI data by combining firefly algorithm (FA) and synchronization-based hierarchical clustering (SHC) algorithm. Firstly, the PPI data are preprocessed via spectral clustering (SC) which transforms the high-dimensional similarity matrix into a low dimension matrix. Then the SHC algorithm is used to perform clustering. In SHC algorithm, hierarchical clustering is achieved by enlarging the neighborhood radius of synchronized objects continuously, while the hierarchical search is very difficult to find the optimal neighborhood radius of synchronization and the efficiency is not high. So we adopt the firefly algorithm to determine the optimal threshold of the neighborhood radius of synchronization automatically. The proposed algorithm is tested on the MIPS PPI dataset. The results show that our proposed algorithm is better than the traditional algorithms in precision, recall and f-measure value. PMID:25707632

Synthesis, characterization and antimicrobial activity of biodegradable conducting polypyrrole-graft-chitosan copolymer

NASA Astrophysics Data System (ADS)

Cabuk, Mehmet; Alan, Yusuf; Yavuz, Mustafa; Unal, Halil Ibrahim

2014-11-01

In this study, polypyrrole-graft-chitosan (PPy-g-CS) copolymer was chemically synthesized and its structural and morphological properties characterized by FTIR, UV-vis, SEM, XRD, TGA and zeta-potential techniques. The results revealed that there were strong interactions between PPy and CS chains. The electrical conductivity of CS increased to semiconducting range by grafting. The crystallinity and thermal stability of PPy-g-CS copolymer improved when compared to CS. The copolymer was tested against various bacterial and fungal strains at various concentrations and results obtained were compared with the reference antibiotics. The results indicated that the antibacterial activity of PPy-g-CS copolymer was stronger than CS and PPy alone. The antibacterial activity of the PPy-g-CS copolymer observed to increase with rising concentration, and showed stronger activity against bacteria than Penicillin (10 mg), Rifampicin (5 mg) and Trimethoprim (25 mg), whereas showed equipotent activity with Amikacin (30 mg) and Erythromycin (15 mg) antibiotics.

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.

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.

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.

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.

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.

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.

In vitro and in vivo evaluation of drug-drug interaction between dabigatran and proton pump inhibitors.

PubMed

Ollier, Edouard; Hodin, Sophie; Basset, Thierry; Accassat, Sandrine; Bertoletti, Laurent; Mismetti, Patrick; Delavenne, Xavier

2015-12-01

To quantify the drug-drug interactions between dabigatran etexilate (DE) and proton pump inhibitors (PPI) and in particular the role of P-gp activity modulation. In the first part of the study, efflux ratios of DE were evaluated using the caco-2 cell line in the presence of pantoprazole, omeprazole, rabeprazole, lansoprazole and ciclosporin A (positive control). The two PPI that reduced the efflux ratio of dabigatran to the greatest and least extent, respectively, were used during the second part of the study, comprising a single-centre, randomised, open-label study with an incomplete Latin square design. Nine healthy volunteers received DE (150 mg) alone, DE (150 mg) with the first PPI and DE (150 mg) with the second PPI in randomised sequence. Dabigatran plasma concentration and thrombin time were measured in blood samples withdrawn at 11 time points after each treatment. Models were built using a nonlinear mixed-effect modelling approach. Omeprazole and rabeprazole were the two PPI that reduced the efflux ratio of DE least and most, respectively. The PK model was based on an inverse Gaussian absorption process with one compartment. The relationship between dabigatran concentration and thrombin time was considered linear. Some PK profiles had dramatically low concentration values due to poor absorption. These profiles were clustered using a between subject model mixture with interoccasion variability. The concomitant administration of PPI did not significantly change dabigatran pharmacokinetics. DE is subject to high absorption variability, precluding evaluation of the effect of PPI on its pharmacokinetics. © 2015 Société Française de Pharmacologie et de Thérapeutique.

Natural products used as a chemical library for protein-protein interaction targeted drug discovery.

PubMed

Jin, Xuemei; Lee, Kyungro; Kim, Nam Hee; Kim, Hyun Sil; Yook, Jong In; Choi, Jiwon; No, Kyoung Tai

2018-01-01

Protein-protein interactions (PPIs), which are essential for cellular processes, have been recognized as attractive therapeutic targets. Therefore, the construction of a PPI-focused chemical library is an inevitable necessity for future drug discovery. Natural products have been used as traditional medicines to treat human diseases for millennia; in addition, their molecular scaffolds have been used in diverse approved drugs and drug candidates. The recent discovery of the ability of natural products to inhibit PPIs led us to use natural products as a chemical library for PPI-targeted drug discovery. In this study, we collected natural products (NPDB) from non-commercial and in-house databases to analyze their similarities to small-molecule PPI inhibitors (iPPIs) and FDA-approved drugs by using eight molecular descriptors. Then, we evaluated the distribution of NPDB and iPPIs in the chemical space, represented by the molecular fingerprint and molecular scaffolds, to identify the promising scaffolds, which could interfere with PPIs. To investigate the ability of natural products to inhibit PPI targets, molecular docking was used. Then, we predicted a set of high-potency natural products by using the iPPI-likeness score based on a docking score-weighted model. These selected natural products showed high binding affinities to the PPI target, namely XIAP, which were validated in an in vitro experiment. In addition, the natural products with novel scaffolds might provide a promising starting point for further medicinal chemistry developments. Overall, our study shows the potency of natural products in targeting PPIs, which might help in the design of a PPI-focused chemical library for future drug discovery. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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.

Behavioral and Pharmacokinetic Interactions Between Monoamine Oxidase Inhibitors and the Hallucinogen 5-Methoxy-N,N-dimethyltryptamine

PubMed Central

Halberstadt, Adam L.

2016-01-01

Monoamine oxidase inhibitors (MAOIs) are often ingested together with tryptamine hallucinogens, but relatively little is known about the consequences of their combined use. We have shown previously that monoamine oxidase-A (MAO-A) inhibitors alter the locomotor profile of the hallucinogen 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) in rats, and enhance its interaction with 5-HT2A receptors. The goal of the present studies was to investigate the mechanism for the interaction between 5-MeO-DMT and MAOIs, and to determine whether other behavioral responses to 5-MeO-DMT are similarly affected. Hallucinogens disrupt prepulse inhibition (PPI) in rats, an effect typically mediated by 5-HT2A activation. 5-MeO-DMT also disrupts PPI but the effect is primarily attributable to 5-HT1A activation. The present studies examined whether an MAOI can alter the respective contributions of 5-HT1A and 5-HT2A receptors to the effects of 5-MeO-DMT on PPI. A series of interaction studies using the 5-HT1A antagonist WAY-100635 and the 5-HT2A antagonist MDL 11,939 were performed to assess the respective contributions of these receptors to the behavioral effects of 5-MeO-DMT in rats pretreated with an MAOI. The effects of MAO-A inhibition on the pharmacokinetics of 5-MeO-DMT and its metabolism to bufotenine were assessed using liquid chromatography–electrospray ionization–selective reaction monitoring–tandem mass spectrometry (LC-ESI-SRM-MS/MS). 5-MeO-DMT (1 mg/kg) had no effect on PPI when tested 45-min post-injection but disrupted PPI in animals pretreated with the MAO-A inhibitor clorgyline or the MAO-A/B inhibitor pargyline. The combined effect of 5-MeO-DMT and pargyline on PPI was antagonized by pretreatment with either WAY-100635 or MDL 11,939. Inhibition of MAO-A increased the level of 5-MeO-DMT in plasma and whole brain, but had no effect on the conversion of 5-MeO-DMT to bufotenine, which was found to be negligible. The present results confirm that 5-MeO-DMT can disrupt PPI by activating 5-HT2A, and indicate that MAOIs alter 5-MeO-DMT pharmacodynamics by increasing its accumulation in the central nervous system. PMID:26780349

Pantoprazole-Induced Delirium: Review of a Case and Associated Literature.

PubMed

Razdan, Anupriya; Viswanathan, Ramaswamy; Tusher, Alan

2018-01-01

Proton pump inhibitors (PPIs) are frequently prescribed antiulcer agents in hospitals and are shown to be safer than H-2 blockers. We present a case report of PPI-induced delirium, regarding which not much has been written in the literature. We present a case of a 93-year-old woman with no known past psychiatric history, who was hospitalized for syncope workup and who developed delirium after a double dose of pantoprazole. Very few reports of PPI-induced delirium exist in the literature. In this case report, we attempt to highlight the mechanism of PPI induced delirium which in our case was most likely due to the primary effects of PPI and drug-drug interactions. Given the paucity of literature on this topic, we encourage further research into relationship between PPI and delirium and urge caution while using PPIs in geriatric population.

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.

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/ .

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).

Discovery and Development of Kelch-like ECH-Associated Protein 1. Nuclear Factor Erythroid 2-Related Factor 2 (KEAP1:NRF2) Protein-Protein Interaction Inhibitors: Achievements, Challenges, and Future Directions.

PubMed

Jiang, Zheng-Yu; Lu, Meng-Chen; You, Qi-Dong

2016-12-22

The transcription factor Nrf2 is the primary regulator of the cellular defense system, and enhancing Nrf2 activity has potential usages in various diseases, especially chronic age-related and inflammatory diseases. Recently, directly targeting Keap1-Nrf2 protein-protein interaction (PPI) has been an emerging strategy to selectively and effectively activate Nrf2. This Perspective summarizes the progress in the discovery and development of Keap1-Nrf2 PPI inhibitors, including the Keap1-Nrf2 regulatory mechanisms, biochemical techniques for inhibitor identification, and approaches for identifying peptide and small-molecule inhibitors, as well as discusses privileged structures and future directions for further development of Keap1-Nrf2 PPI inhibitors.

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.

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

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

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.

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.

A Two-State Model for the Dynamics of the Pyrophosphate Ion Release in Bacterial RNA Polymerase

PubMed Central

Da, Lin-Tai; Pardo Avila, Fátima; Wang, Dong; Huang, Xuhui

2013-01-01

The dynamics of the PPi release during the transcription elongation of bacterial RNA polymerase and its effects on the Trigger Loop (TL) opening motion are still elusive. Here, we built a Markov State Model (MSM) from extensive all-atom molecular dynamics (MD) simulations to investigate the mechanism of the PPi release. Our MSM has identified a simple two-state mechanism for the PPi release instead of a more complex four-state mechanism observed in RNA polymerase II (Pol II). We observed that the PPi release in bacterial RNA polymerase occurs at sub-microsecond timescale, which is ∼3-fold faster than that in Pol II. After escaping from the active site, the (Mg-PPi)2− group passes through a single elongated metastable region where several positively charged residues on the secondary channel provide favorable interactions. Surprisingly, we found that the PPi release is not coupled with the TL unfolding but correlates tightly with the side-chain rotation of the TL residue R1239. Our work sheds light on the dynamics underlying the transcription elongation of the bacterial RNA polymerase. PMID:23592966

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.

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.

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.

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.

Clopidogrel-Proton Pump Inhibitor Drug-Drug Interaction and Risk of Adverse Clinical Outcomes Among PCI-Treated ACS Patients: A Meta-analysis.

PubMed

Serbin, Michael A; Guzauskas, Gregory F; Veenstra, David L

2016-08-01

Uncertainty regarding clopidogrel effectiveness attenuation because of a drug-drug interaction with proton pump inhibitors (PPI) has led to conflicting guidelines on concomitant therapy. In particular, the effect of this interaction in patients who undergo a percutaneous coronary intervention (PCI), a population known to have increased risk of adverse cardiovascular events, has not been systematically evaluated. To synthesize the evidence of the effect of clopidogrel-PPI drug interaction on adverse cardiovascular outcomes in a PCI patient population. We conducted a systematic literature review for studies reporting clinical outcomes in patients who underwent a PCI and were initiated on clopidogrel with or without a PPI. Studies were included in the analysis if they reported at least 1 of the clinical outcomes of interest (major adverse cardiovascular event [MACE], cardiovascular death, all-cause death, myocardial infarction, stroke, stent thrombosis, and bleed events). We excluded studies that were not exclusive to PCI patients or had no PCI subgroup analysis and/or did not report at least a 6-month follow-up. Statistical and clinical heterogeneity were evaluated and HRs and 95% CIs for adverse clinical events were pooled using the DerSimonian and Laird random-effects meta-analysis method. We identified 12 studies comprising 50,277 PCI patients that met our inclusion and exclusion criteria. Our analysis included retrospective analyses of randomized controlled trials (2), health registries (3), claims databases (2), and institutional records (5); no prospective studies of PCI patients were identified. On average, patients were in their mid-60s, male, and had an array of comorbidities, including hyperlipidemia, diabetes, hypertension, and smoking history. Concomitant therapy following PCI resulted in statistically significant increases in composite MACE (HR = 1.28; 95% CI = 1.24-1.32), myocardial infarction (HR = 1.51; 95% CI = 1.40-1.62), and stroke (HR = 1.46; 95% CI = 1.15-1.86). However, concomitant therapy had no statistically significant effect on stent thrombosis, mortality measured by all-cause or cardiovascular death, or major bleeding before or after the grouping of studies that reported a major or minor bleed outcome. Only 1 study reported on gastrointestinal bleed, and pooled analysis could not be conducted. Statistical testing suggested heterogeneity among studies, but subgroup analysis did not reveal a clear source. Based on the results from this meta-analysis of retrospective analyses of randomized controlled trials and observational studies, concomitant clopidogrel-PPI therapy following PCI appears to be significantly associated with adverse cardiovascular events. Further research on the effect of individual PPIs is needed. Serbin, Guzauskas, and Veenstra were supported by the NIH Common Fund and NIA (1U01AG047109-01, Veenstra, PI) via the Personalized Medicine Economics Research (PriMER) project. The authors do not report any conflicting interests. All authors contributed to the study concept and design. Serbin took the lead in data collection; data interpretation was performed primarily by Serbin, with assistance from the other authors. The manuscript was written primarily by Serbin, along with Guzauskas, and revised by Guzauskas and Veenstra, with assistance from Serbin.

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.

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.

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.

The two-factor model of psychopathic personality: evidence from the psychopathic personality inventory.

PubMed

Marcus, David K; Fulton, Jessica J; Edens, John F

2013-01-01

Psychopathy or psychopathic personality disorder represents a constellation of traits characterized by superficial charm, egocentricity, irresponsibility, fearlessness, persistent violation of social norms, and a lack of empathy, guilt, and remorse. Factor analyses of the Psychopathic Personality Inventory (PPI)typically yield two factors: Fearless Dominance (FD) and Self-Centered Impulsivity (SCI). Additionally, the Coldheartedness (CH) subscale typically does not load on either factor. The current paper includes a meta-analysis of studies that have examined theoretically important correlates of the two PPI factors and CH. Results suggest that (a) FD and SCI are orthogonal or weakly correlated, (b) each factor predicts distinct (and sometimes opposite) correlates, and (c) the FD factor is not highly correlated with most other measures of psychopathy. This pattern of results raises important questions about the relation between FD and SCI and the role of FD in conceptualizations of psychopathy. Our findings also indicate the need for future studies using the two-factor model of the PPI to conduct moderational analyses to examine potential interactions between FD and SCI in the prediction of important criterion measures.

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?

Decreased cerebellar-cerebral connectivity contributes to complex task performance

PubMed Central

Knops, André

2016-01-01

The cerebellum's role in nonmotor processes is now well accepted, but cerebellar interaction with cerebral targets is not well understood. Complex cognitive tasks activate cerebellar, parietal, and frontal regions, but the effective connectivity between these regions has never been tested. To this end, we used psycho-physiological interactions (PPI) analysis to test connectivity changes of cerebellar and parietal seed regions in complex (2-digit by 1-digit multiplication, e.g., 12 × 3) vs. simple (1-digit by 1-digit multiplication, e.g., 4 × 3) task conditions (“complex − simple”). For cerebellar seed regions (lobule VI, hemisphere and vermis), we found significantly decreased cerebellar-parietal, cerebellar-cingulate, and cerebellar-frontal connectivity in complex multiplication. For parietal seed regions (PFcm, PFop, PFm) we found significantly increased parietal-parietal and parietal-frontal connectivity in complex multiplication. These results suggest that decreased cerebellar-cerebral connectivity contributes to complex task performance. Interestingly, BOLD activity contrasts revealed partially overlapping parietal areas of increased BOLD activity but decreased cerebellar-parietal PPI connectivity. PMID:27334957

Features of Protein-Protein Interactions that Translate into Potent Inhibitors: Topology, Surface Area and Affinity

PubMed Central

Smith, Matthew C.; Gestwicki, Jason E.

2013-01-01

Protein-protein interactions (PPIs) control the assembly of multi-protein complexes and, thus, these contacts have enormous potential as drug targets. However, the field has produced a mix of both exciting success stories and frustrating challenges. Here, we review known examples and explore how the physical features of a PPI, such as its affinity, hotspots, off-rates, buried surface area and topology, may influence the chances of success in finding inhibitors. This analysis suggests that concise, tight binding PPIs are most amenable to inhibition. However, it is also clear that emerging technical methods are expanding the repertoire of “druggable” protein contacts and increasing the odds against difficult targets. In particular, natural product-like compound libraries, high throughput screens specifically designed for PPIs and approaches that favor discovery of allosteric inhibitors appear to be attractive routes. The first group of PPI inhibitors has entered clinical trials, further motivating the need to understand the challenges and opportunities in pursuing these types of targets. PMID:22831787

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.

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.

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

Structure-Based Design of Inhibitors of Protein–Protein Interactions: Mimicking Peptide Binding Epitopes

PubMed Central

Pelay-Gimeno, Marta; Glas, Adrian; Koch, Oliver; Grossmann, Tom N

2015-01-01

Protein–protein interactions (PPIs) are involved at all levels of cellular organization, thus making the development of PPI inhibitors extremely valuable. The identification of selective inhibitors is challenging because of the shallow and extended nature of PPI interfaces. Inhibitors can be obtained by mimicking peptide binding epitopes in their bioactive conformation. For this purpose, several strategies have been evolved to enable a projection of side chain functionalities in analogy to peptide secondary structures, thereby yielding molecules that are generally referred to as peptidomimetics. Herein, we introduce a new classification of peptidomimetics (classes A–D) that enables a clear assignment of available approaches. Based on this classification, the Review summarizes strategies that have been applied for the structure-based design of PPI inhibitors through stabilizing or mimicking turns, β-sheets, and helices. PMID:26119925

Processable dodecylbenzene sulfonic acid (DBSA) doped poly(N-vinyl carbazole)-poly(pyrrole) for optoelectronic applications

PubMed Central

Hammed, W. A.; Rahman, M. S.; Mahmud, H. N. M. E.; Yahya, R.; Sulaiman, K.

2017-01-01

Abstract A soluble poly (n-vinyl carbazole)–polypyrrole (PNVC–Ppy) copolymer was prepared through oxidative chemical polymerization wherein dodecyl benzene sulfonic acid (DBSA) was used as a dopant to facilitate polymer-organic solvent interaction and ammonium persulfate (APS) was used as an oxidant. Compared with undoped PNVC–Ppy, the DBSA-doped PNVC–Ppy copolymer showed higher solubility in some selected organic solvents. The composition and structural characteristics of the DBSA-doped PNVC–Ppy were determined by Fourier transform infrared, ultraviolet–visible, and X-ray diffraction spectroscopic methods. Field emission scanning electron microscopic method was employed to observe the morphology of the DBSA-doped PNVC–Ppy copolymer. The electrical conductivity of the DBSA-doped PNVC–Ppy copolymer was measured at room temperature. The conductivity increased with increasing concentration of APS oxidant, and the highest conductivity was recorded at 0.004 mol/dm3 APS at a polymerization temperature of −5 °C. The increased conductivity can be explained by the extended half-life of pyrrole free radical at a lower temperature and a gradual increase in chain length over a prolonged time due to the slow addition of APS. Furthermore, the obtained soluble copolymer exhibits unique optical and thermal properties different from those of PNVC and Ppy. PMID:29491808

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.

Novel in vitro protein fragment complementation assay applicable to high-throughput screening in a 1536-well format.

PubMed

Hashimoto, Junko; Watanabe, Taku; Seki, Tatsuya; Karasawa, Satoshi; Izumikawa, Miho; Seki, Tomoe; Iemura, Shun-Ichiro; Natsume, Tohru; Nomura, Nobuo; Goshima, Naoki; Miyawaki, Atsushi; Takagi, Motoki; Shin-Ya, Kazuo

2009-09-01

Protein-protein interactions (PPIs) play key roles in all cellular processes and hence are useful as potential targets for new drug development. To facilitate the screening of PPI inhibitors as anticancer drugs, the authors have developed a high-throughput screening (HTS) system using an in vitro protein fragment complementation assay (PCA) with monomeric Kusabira-Green fluorescent protein (mKG). The in vitro PCA system was established by the topological formation of a functional complex between 2 split inactive mKG fragments fused to target proteins, which fluoresces when 2 target proteins interact to allow complementation of the mKG fragments. Using this assay system, the authors screened inhibitors for TCF7/beta-catenin, PAC1/PAC2, and PAC3 homodimer PPIs from 123,599 samples in their natural product library. Compound TB1 was identified as a specific inhibitor for PPI of PAC3 homodimer. TB1 strongly inhibited the PPI of PAC3 homodimer with an IC(50) value of 0.020 microM and did not inhibit PPI between TCF7/beta-catenin and PAC1/PAC2 even at a concentration of 250 microM. The authors thus demonstrated that this in vitro PCA system applicable to HTS in a 1536-well format is capable of screening for PPI inhibitors from a huge natural product library.

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.

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).

Behavioral and pharmacokinetic interactions between monoamine oxidase inhibitors and the hallucinogen 5-methoxy-N,N-dimethyltryptamine.

PubMed

Halberstadt, Adam L

2016-04-01

Monoamine oxidase inhibitors (MAOIs) are often ingested together with tryptamine hallucinogens, but relatively little is known about the consequences of their combined use. We have shown previously that monoamine oxidase-A (MAO-A) inhibitors alter the locomotor profile of the hallucinogen 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) in rats, and enhance its interaction with 5-HT2A receptors. The goal of the present studies was to investigate the mechanism for the interaction between 5-MeO-DMT and MAOIs, and to determine whether other behavioral responses to 5-MeO-DMT are similarly affected. Hallucinogens disrupt prepulse inhibition (PPI) in rats, an effect typically mediated by 5-HT2A activation. 5-MeO-DMT also disrupts PPI but the effect is primarily attributable to 5-HT1A activation. The present studies examined whether an MAOI can alter the respective contributions of 5-HT1A and 5-HT2A receptors to the effects of 5-MeO-DMT on PPI. A series of interaction studies using the 5-HT1A antagonist WAY-100,635 and the 5-HT2A antagonist MDL 11,939 were performed to assess the respective contributions of these receptors to the behavioral effects of 5-MeO-DMT in rats pretreated with an MAOI. The effects of MAO-A inhibition on the pharmacokinetics of 5-MeO-DMT and its metabolism to bufotenine were assessed using liquid chromatography-electrospray ionization-selective reaction monitoring-tandem mass spectrometry (LC-ESI-SRM-MS/MS). 5-MeO-DMT (1mg/kg) had no effect on PPI when tested 45-min post-injection but disrupted PPI in animals pretreated with the MAO-A inhibitor clorgyline or the MAO-A/B inhibitor pargyline. The combined effect of 5-MeO-DMT and pargyline on PPI was antagonized by pretreatment with either WAY-100,635 or MDL 11,939. Inhibition of MAO-A increased the level of 5-MeO-DMT in plasma and whole brain, but had no effect on the conversion of 5-MeO-DMT to bufotenine, which was found to be negligible. The present results confirm that 5-MeO-DMT can disrupt PPI by activating 5-HT2A, and indicate that MAOIs alter 5-MeO-DMT pharmacodynamics by increasing its accumulation in the central nervous system. Copyright © 2016 Elsevier Inc. 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.

Demonstration of protein-fragment complementation assay using purified firefly luciferase fragments

PubMed Central

2013-01-01

Background Human interactome is predicted to contain 150,000 to 300,000 protein-protein interactions, (PPIs). Protein-fragment complementation assay (PCA) is one of the most widely used methods to detect PPI, as well as Förster resonance energy transfer (FRET). To date, successful applications of firefly luciferase (Fluc)-based PCA have been reported in vivo, in cultured cells and in cell-free lysate, owing to its high sensitivity, high signal-to-background (S/B) ratio, and reversible response. Here we show the assay also works with purified proteins with unexpectedly rapid kinetics. Results Split Fluc fragments both fused with a rapamycin-dependently interacting protein pair were made and expressed in E. coli system, and purified to homogeneity. When the proteins were used for PCA to detect rapamycin-dependent PPI, they enabled a rapid detection (~1 s) of PPI with high S/B ratio. When Fn7-8 domains (7 nm in length) that was shown to abrogate GFP mutant-based FRET was inserted between split Fluc and FKBP12 as a rigid linker, it still showed some response, suggesting less limitation in interacting partner’s size. Finally, the stability of the probe was investigated. Preincubation of the probes at 37 degreeC up to 1 h showed marked decrease of the luminescent signal to 1.5%, showing the limited stability of this system. Conclusion Fluc PCA using purified components will enable a rapid and handy detection of PPIs with high S/B ratio, avoiding the effects of concomitant components. Although the system might not be suitable for large-scale screening due to its limited stability, it can detect an interaction over larger distance than by FRET. This would be the first demonstration of Fluc PCA in vitro, which has a distinct advantage over other PPI assays. Our system enables detection of direct PPIs without risk of perturbation by PPI mediators in the complex cellular milieu. PMID:23536995

Increased proximal reflux in a hypersensitive esophagus might explain symptoms resistant to proton pump inhibitors in patients with gastroesophageal reflux disease.

PubMed

Rohof, Wout O; Bennink, Roelof J; de Jonge, Hugo; Boeckxstaens, Guy E

2014-10-01

Approximately 30% of patients with gastroesophageal reflux disease have symptoms resistant to treatment with proton pump inhibitors (PPIs). Several mechanisms such as esophageal hypersensitivity, increased mucosal permeability, and possibly the position of the gastric acid pocket might underlie a partial response to PPIs. To what extent these mechanisms interact and contribute to PPI-resistant symptoms, however, has not been investigated previously. In 18 gastroesophageal reflux disease patients (9 PPI responders and 9 PPI partial responders), esophageal sensitivity, mucosal permeability, and postprandial reflux parameters were determined during PPI use. Esophageal sensitivity for distension was measured by gradual balloon inflation at 5 and 15 cm above the lower esophageal sphincter. The mucosal permeability of 4 esophageal biopsy specimens per patient was determined in Ussing chambers by measuring the transepithelial electrical resistance and transmucosal flux of fluorescein. Postprandial reflux parameters were determined using concurrent high-resolution manometry/pH impedance after a standardized meal. In addition, the acid pocket was visualized using scintigraphy. No difference in the rate of postprandial acid reflux, in the pH of the acid pocket (PPI responders 3.7 ± 0.7 vs PPI partial responders 4.2 ± 0.4; P = .54), or in the position of the acid pocket was observed in PPI partial responders compared with PPI responders. In addition, the permeability of the esophageal mucosa was similar in both groups, as shown by a similar transepithelial electrical resistance and flux of fluorescein. PPI partial responders had more reflux episodes with a higher mean proximal extent, compared with PPI responders, and were more sensitive to balloon distension, both in the upper and lower esophagus. PPI-resistant symptoms most likely are explained by increased proximal reflux in a hypersensitive esophagus and less likely by increased mucosal permeability or the position of the acid pocket. Copyright © 2014 AGA Institute. Published by Elsevier Inc. All rights reserved.

A coproduced patient and public event: An approach to developing and prioritizing ambulance performance measures.

PubMed

Irving, Andy; Turner, Janette; Marsh, Maggie; Broadway-Parkinson, Andrea; Fall, Dan; Coster, Joanne; Siriwardena, A Niroshan

2018-02-01

Patient and public involvement (PPI) is recognized as an important component of high-quality health services research. PPI is integral to the Pre-hospital Outcomes for Evidence Based Evaluation (PhOEBE) programme. The PPI event described in detail in this article focusses on the process of involving patients and public representatives in identifying, prioritizing and refining a set of outcome measures that can be used to support ambulance service performance measurement. To obtain public feedback on little known, complex aspects of ambulance service performance measurement. The event was codesigned and coproduced with the PhOEBE PPI reference group and PhOEBE research team. The event consisted of brief researcher-led presentations, group discussions facilitated by the PPI reference group members and electronic voting. Data were collected from eighteen patient and public representatives who attended an event venue in Yorkshire. The results of the PPI event showed that this interactive format and mode of delivery was an effective method to obtain public feedback and produced a clear indication of which ambulance performance measures were most highly favoured by event participants. The event highlighted valuable contributions the PPI reference group made to the design process, supporting participant recruitment and facilitation of group discussions. In addition, the positive team working experience of the event proved a catalyst for further improvements in PPI within the PhOEBE project. © 2017 The Authors Health Expectations Published by John Wiley & Sons Ltd.

Clopidogrel and proton pump inhibitors - where do we stand in 2012?

PubMed Central

Drepper, Michael D; Spahr, Laurent; Frossard, Jean Louis

2012-01-01

Clopidogrel in association with aspirine is considered state of the art of medical treatment for acute coronary syndrome by reducing the risk of new ischemic events. Concomitant treatment with proton pump inhibitors in order to prevent gastrointestinal side effects is recommended by clinical guidelines. Clopidogrel needs metabolic activation predominantly by the hepatic cytochrome P450 isoenzyme Cytochrome 2C19 (CYP2C19) and proton pump inhibitors (PPIs) are extensively metabolized by the CYP2C19 isoenzyme as well. Several pharmacodynamic studies investigating a potential clopidogrel-PPI interaction found a significant decrease of the clopidogrel platelet antiaggregation effect for omeprazole, but not for pantoprazole. Initial clinical cohort studies in 2009 reported an increased risk for adverse cardiovascular events, when under clopidogrel and PPI treatment at the same time. These observations led the United States Food and Drug Administration and the European Medecines Agency to discourage the combination of clopidogrel and PPI (especially omeprazole) in the same year. In contrast, more recent retrospective cohort studies including propensity score matching and the only existing randomized trial have not shown any difference concerning adverse cardiovascular events when concomitantly on clopidogrel and PPI or only on clopidogrel. Three meta-analyses report an inverse correlation between clopidogrel-PPI interaction and study quality, with high and moderate quality studies not reporting any association, rising concern about unmeasured confounders biasing the low quality studies. Thus, no definite evidence exists for an effect on mortality. Because PPI induced risk reduction clearly overweighs the possible adverse cardiovascular risk in patients with high risk of gastrointestinal bleeding, combination of clopidogrel with the less CYP2C19 inhibiting pantoprazole should be recommended. PMID:22611308

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.

Control of intramolecular π-π stacking interaction in cationic iridium complexes via fluorination of pendant phenyl rings.

PubMed

He, Lei; Ma, Dongxin; Duan, Lian; Wei, Yongge; Qiao, Juan; Zhang, Deqiang; Dong, Guifang; Wang, Liduo; Qiu, Yong

2012-04-16

Intramolecular π-π stacking interaction in one kind of phosphorescent cationic iridium complexes has been controlled through fluorination of the pendant phenyl rings on the ancillary ligands. Two blue-green-emitting cationic iridium complexes, [Ir(ppy)(2)(F2phpzpy)]PF(6) (2) and [Ir(ppy)(2)(F5phpzpy)]PF(6) (3), with the pendant phenyl rings on the ancillary ligands substituted with two and five fluorine atoms, respectively, have been synthesized and compared to the parent complex, [Ir(ppy)(2)(phpzpy)]PF(6) (1). Here Hppy is 2-phenylpyridine, F2phpzpy is 2-(1-(3,5-difluorophenyl)-1H-pyrazol-3-yl)pyridine, F5phpzpy is 2-(1-pentafluorophenyl-1H-pyrazol-3-yl)-pyridine, and phpzpy is 2-(1-phenyl-1H-pyrazol-3-yl)pyridine. Single crystal structures reveal that the pendant phenyl rings on the ancillary ligands stack to the phenyl rings of the ppy ligands, with dihedral angles of 21°, 18°, and 5.0° between least-squares planes for complexes 1, 2, and 3, respectively, and centroid-centroid distances of 3.75, 3.65, and 3.52 Å for complexes 1, 2, and 3, respectively, indicating progressively reinforced intramolecular π-π stacking interactions from complexes 1 to 2 and 3. Compared to complex 1, complex 3 with a significantly reinforced intramolecular face-to-face π-π stacking interaction exhibits a significantly enhanced (by 1 order of magnitude) photoluminescent efficiency in solution. Theoretical calculations reveal that in complex 3 it is unfavorable in energy for the pentafluorophenyl ring to swing by a large degree and the intramolecular π-π stacking interaction remains on the lowest triplet state. © 2012 American Chemical Society

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

Electrochemical direct immobilization of DNA sequences for label-free herpes virus detection

NASA Astrophysics Data System (ADS)

Tam, Phuong Dinh; Trung, Tran; Tuan, Mai Anh; Chien, Nguyen Duc

2009-09-01

DNA sequences/bio-macromolecules of herpes virus (5'-AT CAC CGA CCC GGA GAG GGA C-3') were directly immobilized into polypyrrole matrix by using the cyclic voltammetry method, and grafted onto arrays of interdigitated platinum microelectrodes. The morphology surface of the obtained PPy/DNA of herpes virus composite films was investigated by a FESEM Hitachi-S 4800. Fourier transform infrared spectroscopy (FTIR) was used to characterize the PPy/DNA film and to study the specific interactions that may exist between DNA biomacromolecules and PPy chains. Attempts are made to use these PPy/DNA composite films for label-free herpes virus detection revealed a response time of 60 s in solutions containing as low as 2 nM DNA concentration, and self life of six months when immerged in double distilled water and kept refrigerated.

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.

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.

Detecting complexes from edge-weighted PPI networks via genes expression analysis.

PubMed

Zhang, Zehua; Song, Jian; Tang, Jijun; Xu, Xinying; Guo, Fei

2018-04-24

Identifying complexes from PPI networks has become a key problem to elucidate protein functions and identify signal and biological processes in a cell. Proteins binding as complexes are important roles of life activity. Accurate determination of complexes in PPI networks is crucial for understanding principles of cellular organization. We propose a novel method to identify complexes on PPI networks, based on different co-expression information. First, we use Markov Cluster Algorithm with an edge-weighting scheme to calculate complexes on PPI networks. Then, we propose some significant features, such as graph information and gene expression analysis, to filter and modify complexes predicted by Markov Cluster Algorithm. To evaluate our method, we test on two experimental yeast PPI networks. On DIP network, our method has Precision and F-Measure values of 0.6004 and 0.5528. On MIPS network, our method has F-Measure and S n values of 0.3774 and 0.3453. Comparing to existing methods, our method improves Precision value by at least 0.1752, F-Measure value by at least 0.0448, S n value by at least 0.0771. Experiments show that our method achieves better results than some state-of-the-art methods for identifying complexes on PPI networks, with the prediction quality improved in terms of evaluation criteria.

Poly(4-vinylphenylboronic acid) functionalized polypyrrole/graphene oxide nanosheets for simultaneous electrochemical determination of catechol and hydroquinone

NASA Astrophysics Data System (ADS)

Mao, Hui; Liu, Meihong; Cao, Zhenqian; Ji, Chunguang; Sun, Ying; Liu, Daliang; Wu, Shuyao; Zhang, Yu; Song, Xi-Ming

2017-10-01

Novel poly(4-vinylphenylboronic acid) (P4VPBA) functionalized polypyrrole/graphene oxide (PPy/GO) nanosheets, which combined the advantages of GO, PPy and PBA groups, were successfully prepared by a simple polymerization of 4-vinylphenylboronic acid (4VPBA) on the surface of pre-treated PPy/GO containing vinyl groups. Because of the synergistic effects of GO with excellent 2D structures and large surface area, PPy with good electronic conductivity and PBA with high recognition capability, P4VPBA/PPy/GO modified glassy carbon electrode presented excellent electrochemical sensing capabilities toward catechol (CC) and hydroquinone (HQ) with good stability, high sensitivity and selectivity, especially giving a large anodic peak potential difference between CC and HQ enough to well distinguish and simultaneously determine the two dihydroxybenzene isomers in their mixture. It is found that PBA groups on the surface of P4VPBA/PPy/GO nanosheets played an essential role for the discrimination and simultaneous electrochemical determination of CC and HQ, which may be due to the selective formation of stable cyclic esters by the covalent interaction between PBA groups and related molecules with a cis-diol in an alkaline aqueous solution. Therefore, P4VPBA/PPy/GO nanosheets can act as a good electrode material for building a steady electrochemical sensor for detecting the two dihydroxybenzene isomers with high sensitivity and selectivity.

Towards a pedagogy for patient and public involvement in medical education.

PubMed

Regan de Bere, Sam; Nunn, Suzanne

2016-01-01

This paper presents a critique of current knowledge on the engagement of patients and the public, referred to here as patient and public involvement (PPI), and calls for the development of robust and theoretically informed strategies across the continuum of medical education. The study draws on a range of relevant literatures and presents PPI as a response process in relation to patient-centred learning agendas. Through reference to original research it discusses three key priorities for medical educators developing early PPI pedagogies, including: (i) the integration of evidence on PPI relevant to medical education, via a unifying corpus of literature; (ii) conceptual clarity through shared definitions of PPI in medical education, and (iii) an academically rigorous approach to managing complexity in the evaluation of PPI initiatives. As a response to these challenges, the authors demonstrate how activity modelling may be used as an analytical heuristic to provide an understanding of a number of PPI systems that may interact within complex and dynamic educational contexts. The authors highlight the need for a range of patient voices to be evident within such work, from its generation through to dissemination, in order that patients and the public are partners and not merely objects of this endeavour. To this end, this paper has been discussed with and reviewed by our own patient and public research partners throughout the writing process. © 2015 John Wiley & Sons Ltd.

Utilizing knowledge base of amino acids structural neighborhoods to predict protein-protein interaction sites.

PubMed

Jelínek, Jan; Škoda, Petr; Hoksza, David

2017-12-06

Protein-protein interactions (PPI) play a key role in an investigation of various biochemical processes, and their identification is thus of great importance. Although computational prediction of which amino acids take part in a PPI has been an active field of research for some time, the quality of in-silico methods is still far from perfect. We have developed a novel prediction method called INSPiRE which benefits from a knowledge base built from data available in Protein Data Bank. All proteins involved in PPIs were converted into labeled graphs with nodes corresponding to amino acids and edges to pairs of neighboring amino acids. A structural neighborhood of each node was then encoded into a bit string and stored in the knowledge base. When predicting PPIs, INSPiRE labels amino acids of unknown proteins as interface or non-interface based on how often their structural neighborhood appears as interface or non-interface in the knowledge base. We evaluated INSPiRE's behavior with respect to different types and sizes of the structural neighborhood. Furthermore, we examined the suitability of several different features for labeling the nodes. Our evaluations showed that INSPiRE clearly outperforms existing methods with respect to Matthews correlation coefficient. In this paper we introduce a new knowledge-based method for identification of protein-protein interaction sites called INSPiRE. Its knowledge base utilizes structural patterns of known interaction sites in the Protein Data Bank which are then used for PPI prediction. Extensive experiments on several well-established datasets show that INSPiRE significantly surpasses existing PPI approaches.

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

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

Content Analysis of Standardized-Patients' Descriptive Feedback on Student Performance on the CPX.

PubMed

Lee, Young Hee; Lee, Young-Mee; Kim, Byung Soo

2010-12-01

The goal of this study was to explore what kind of additional information is provided by the descriptive comments other than the rating scales, on the physician-patient interaction (PPI) in the clinical performance examination (CPX) and its feedback role in identifying students' strengths and weaknesses in communication skills. The data were collected from 18 medical schools in Seoul and Gyeonggi region, which participated in the CPX for fourth-year medical students in 2006 and 2007. In total 12,650 examination cases in 2006 and 12,814 cases in 2007 were analyzed. Descriptive comments from the standardized patients (SPs) were analyzed by content analysis, which includes a 4-step process: coding, conceptualizing, categorizing and explanation. Ten categories (41 concepts) for 'strength' and 11 for 'weakness' (40 concepts) in the PPI were extracted. Among them, 10 categories were the same in both strength and weakness: providing adequate interview atmosphere, attentive listening, providing emotional support, non-verbal behaviors, professional attitude, questioning, explanation, reaching agreement, counseling & education and conducting adequate physical examination. For the 'structured and organized interview', only weakness was described. In 'providing emotional support' and 'adequate interview atmosphere', comments on strengths were more frequently mentioned than weaknesses. However, communication skills that were related to non-verbal behaviors were more frequently considered weaknesses rather than strengths. The numbers and content of the SP's comments on students' strengths and weaknesses in the PPI varied depending on the case specificities. The results suggest that the SPs' descriptive comments on student' performance on the CPX can provide additional information versus structured quantitative assessment tools such as performance checklists and rating scales. In particular, this information can be used as valuable feedback to identify the advantages and dicadvantages of the PPI and to enhance students' communication skills.

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.

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.

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.

Insight into the fundamental interactions between LEDGF binding site inhibitors and integrase combining docking and molecular dynamics simulations.

PubMed

De Luca, Laura; Morreale, Francesca; Chimirri, Alba

2012-12-21

In recent years, HIV-1 integrase (IN) has emerged as an attractive target for novel anti-AIDS agents. In particular, nonactive-site-binding IN inhibitors would display synergy with current strand-transfer-specific IN inhibitors and other antiretroviral drugs in clinical use. An effective allosteric inhibitory approach would be the disruption of protein-protein interaction (PPI) between IN and cellular cofactors, such as LEDGF/p75. To date, several small molecules have been reported to be inhibitors of the PPI between IN and LEDGF/p75. In this study, we investigated the most relevant interactions between five selected PPI inhibitors and IN comparing them to the naturally occurring IN-LEDGF/p75 complex. We calculated the binding free energies by using the method of molecular mechanics-generalized Born surface area (MM-GBSA). Total energy was decomposed on per residue contribution, and hydrogen bond occupancies were monitored throughout the simulations. Considering all these results we obtained a good correlation with experimental activity and useful insights for the development of new inhibitors.

T36. THE ANTIPSYCHOTIC-LIKE PROPERTIES OF EVENAMIDE (NW-3509) REFLECT THE MODULATION OF GLUTAMATERGIC DYSREGULATION

PubMed Central

Bortolato, Marco; Faravelli, Laura; Anand, Ravi

2018-01-01

Abstract Background The lack of adequate benefit with current 5HT2 / D2 antipsychotics in large proportions of schizophrenic patients suggests it is essential to modulate other mechanisms for improving symptoms of schizophrenia (SCZ). Increasing evidence implicates NMDAr hypofunction, and hippocampal hyperactivity, in the dysregulation not only of mesolimbic DA neurons but also of Glu neurons, leading to increasing synaptic activity of Glu in the PFC. Injection of NMDAr antagonists (PCP, ketamine) at doses that produce psychotomimetic effects lead to a downstream increase of Glu neurotransmission at non-NMDAr. The excessive firing and the hyper-glutamatergic tone represent alternative targets of treatment for SCZ ultimately affecting positive, negative, cognitive symptoms. The addition of Glu release inhibitors may augment the benefits of the antipsychotics in patients showing inadequate response. Evenamide uniquely does not interact with monoaminergic (DA, 5-HT, NA, H) pathways affected by current antipsychotics, or with more than 130 different targets that are involved in CNS activity, except sodium channels. Preclinical data suggests that by the modulation of the firing abnormalities, evenamide normalizes the aberrant spread of Glu excitatory transmission that occurs in the brains of patients with SCZ. Evenamide showed efficacy in animal models relevant to SCZ (sensory motor gating, mania, psychosis, depression, impulse control, cognition, social interaction), in monotherapy and as an add on to first or second generation antipsychotics irrespective of whether impairment was either spontaneous, induced by amphetamine or NMDAr antagonists or stress. Evenamide, has also shown significant benefit in a p.c phase 2 trial as an add-on to risperidone and aripiprazole in patients worsening on dopaminergic/serotoninergic antagonist medication, suggesting it acts through other mechanisms. New animal data further confirm evenamide’s activity in reducing SCZ symptoms provoked by Glu alteration. Methods Effects of evenamide (EVE 1.25, 5, 15 mg/kg PO) to restore the impaired information processing (a deficit observed in SCZ), were evaluated in the rat model of the Pre-Pulse Inhibition (PPI) deficit induced by injection of the NMDAr antagonist ketamine (KET 6 mg/kg, SC). Clozapine (CLO 7.5 mg/kg, IP) was used as a positive control. Results PPI analysis showed significant main effects for KET to lower PPI levels [F(1,264)=139.67, P<0.0001], for EVE [F(3,264)=3.14, P<0.05] and CLO to enhance PPI levels [F(1,98)=30.89, P<0.001]. Notably, significant EVE x KET [F(3,264)=2.79, P<0.05] and CLO x KET interactions [F(1,98)=5.45, P<0.05] were found. Post-hoc analyses (Tukey’s) revealed that KET significantly lowered PPI (P<0.0001) for each group; both EVE (5 mg/kg) and CLO significantly increased PPI in KET-treated rats (P=0.02; p<0.001). Discussion Evenamide as monotherapy has similar effect to clozapine in reversing ketamine- induced worsening of PPI. Together with previously demonstrated effects to reverse PCP-induced PPI and social interaction deficits, this further supports its potential to affect both positive and negative symptoms of SCZ by targeting altered Glu transmission. Efficacy of evenamide as an add-on to antipsychotics would revolutionize development of novel antipsychotics that would target aberrant firing and Glu transmission in SCZ. Two clinical trials have been planned to support the hypothesis that the addition of evenamide should add a non-dopaminergic mechanism for augmenting antipsychotic efficacy in patients who are not responding adequately to current antipsychotic, and in patients with treatment resistant SCZ who are not responding/worsening on clozapine.

Enhanced magnetic performance of metal-organic nanowire arrays by FeCo/polypyrrole co-electrodeposition

NASA Astrophysics Data System (ADS)

Luo, X. J.; Xia, W. B.; Gao, J. L.; Zhang, S. Y.; Li, Y. L.; Tang, S. L.; Du, Y. W.

2013-05-01

FeCo/polypyrrole (PPy) composite nanowire array, which shows enhanced magnetic remanence and coercivity along the nanowires, was fabricated by AC electrodeposition using anodic aluminum oxide templates. High resolution transmission electron microscopy shows that PPy grows on the surface of FeCo nanowires forming a coaxial nanowire structure, with a coating layer of about 4 nm. It suggests that the decreased dipolar interaction due to the reduced nanowire diameters is responsible for the enhancement of magnetic performance. The possible mechanism of this coating may be that PPy is inclined to nucleate along the pore wall of the templates.

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.

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

Phosphorescence quenching of fac-tris(2-phenylpyridyl)iridium(iii) complexes in thin films on dielectric surfaces.

PubMed

Ribierre, J C; Ruseckas, A; Staton, S V; Knights, K; Cumpstey, N; Burn, P L; Samuel, I D W

2016-02-07

We study the influence of the film thickness on the time-resolved phosphorescence and the luminescence quantum yield of fac-tris(2-phenylpyridyl)iridium(iii) [Ir(ppy)3]-cored dendrimers deposited on dielectric substrates. A correlation is observed between the surface quenching velocity and the quenching rate by intermolecular interactions in the bulk film, which suggests that both processes are controlled by dipole-dipole interactions between Ir(ppy)3 complexes at the core of the dendrimers. It is also found that the surface quenching velocity decreases as the refractive index of the substrate is increased. This can be explained by partial screening of dipole-dipole interactions by the dielectric environment.

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

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

Redox-induced surface stress of polypyrrole-based actuators.

PubMed

Tabard-Cossa, Vincent; Godin, Michel; Grütter, Peter; Burgess, Ian; Lennox, R B

2005-09-22

We measure the surface stress induced by electrochemical transformations of a thin conducting polymer film. One side of a micromechanical cantilever-based sensor is covered with an electropolymerized dodecyl benzenesulfonate-doped polypyrrole (PPyDBS) film. The microcantilever serves as both the working electrode (in a conventional three-electrode cell configuration) and as the mechanical transducer for simultaneous, in situ, and real-time measurements of the current and interfacial stress changes. A compressive change in surface stress of about -2 N/m is observed when the conducting polymer is electrochemically switched between its oxidized (PPy+) and neutral (PPy0) state by cyclic voltammetry. The surface stress sensor's response during the anomalous first reductive scan is examined. The effect of long-term cycling on the mechanical transformation ability of PPy(DBS) films in both surfactant and halide-based electrolytes is also discussed. We have identified two main competing origins of surface stress acting on the PPy(DBS)/ gold-coated microcantilever: one purely mechanical due to the volume change of the conducting polymer, and a second charge-induced, owing to the interaction of anions of the supporting electrolyte with the gold surface.

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.

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.

Core-Shell Composite Fibers for High-Performance Flexible Supercapacitor Electrodes.

PubMed

Lu, Xiaoyan; Shen, Chen; Zhang, Zeyang; Barrios, Elizabeth; Zhai, Lei

2018-01-31

Core-shell nanofibers containing poly(acrylic acid) (PAA) and manganese oxide nanoparticles as the core and polypyrrole (PPy) as the shell were fabricated through electrospinning the solution of PAA and manganese ions (PAA/Mn 2+ ). The obtained nanofibers were stabilized by Fe 3+ through the interaction between Fe 3+ ions and carboxylate groups. Subsequent oxidation of Mn 2+ by KMnO 4 produced uniform manganese dioxide (MnO 2 ) nanoparticles in the fibers. A PPy shell was created on the fibers by immersing the fibers in a pyrrole solution where the Fe 3+ ions in the fiber polymerized the pyrrole on the fiber surfaces. In the MnO 2 @PAA/PPy core-shell composite fibers, MnO 2 nanoparticles function as high-capacity materials, while the PPy shell prevents the loss of MnO 2 during the charge/discharge process. Such a unique structure makes the composite fibers efficient electrode materials for supercapacitors. The gravimetric specific capacity of the MnO 2 @PAA/PPy core-shell composite fibers was 564 F/g based on cyclic voltammetry curves at 10 mV/s and 580 F/g based on galvanostatic charge/discharge studies at 5 A/g. The MnO 2 @PAA/PPy core-shell composite fibers also present stable cycling performance with 100% capacitance retention after 5000 cycles.

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,…

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.

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.

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

Discovery of direct inhibitors of Keap1-Nrf2 protein-protein interaction as potential therapeutic and preventive agents.

PubMed

Abed, Dhulfiqar Ali; Goldstein, Melanie; Albanyan, Haifa; Jin, Huijuan; Hu, Longqin

2015-07-01

The Keap1-Nrf2-ARE pathway is an important antioxidant defense mechanism that protects cells from oxidative stress and the Keap1-Nrf2 protein-protein interaction (PPI) has become an important drug target to upregulate the expression of ARE-controlled cytoprotective oxidative stress response enzymes in the development of therapeutic and preventive agents for a number of diseases and conditions. However, most known Nrf2 activators/ARE inducers are indirect inhibitors of Keap1-Nrf2 PPI and they are electrophilic species that act by modifying the sulfhydryl groups of Keap1׳s cysteine residues. The electrophilicity of these indirect inhibitors may cause "off-target" side effects by reacting with cysteine residues of other important cellular proteins. Efforts have recently been focused on the development of direct inhibitors of Keap1-Nrf2 PPI. This article reviews these recent research efforts including the development of high throughput screening assays, the discovery of peptide and small molecule direct inhibitors, and the biophysical characterization of the binding of these inhibitors to the target Keap1 Kelch domain protein. These non-covalent direct inhibitors of Keap1-Nrf2 PPI could potentially be developed into effective therapeutic or preventive agents for a variety of diseases and conditions.

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.

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.

High-Content Positional Biosensor Screening Assay for Compounds to Prevent or Disrupt Androgen Receptor and Transcriptional Intermediary Factor 2 Protein–Protein Interactions

PubMed Central

Hua, Yun; Shun, Tong Ying; Strock, Christopher J.

2014-01-01

Abstract The androgen receptor–transcriptional intermediary factor 2 (AR-TIF2) positional protein–protein interaction (PPI) biosensor assay described herein combines physiologically relevant cell-based assays with the specificity of binding assays by incorporating structural information of AR and TIF2 functional domains along with intracellular targeting sequences and fluorescent reporters. Expression of the AR-red fluorescent protein (RFP) “prey” and TIF2-green fluorescent protein (GFP) “bait” components of the biosensor was directed by recombinant adenovirus constructs that expressed the ligand binding and activation function 2 surface domains of AR fused to RFP with nuclear localization and nuclear export sequences, and three α-helical LXXLL motifs from TIF2 fused to GFP and an HIV Rev nucleolar targeting sequence. In unstimulated cells, AR-RFP was localized predominantly to the cytoplasm and TIF2-GFP was localized to nucleoli. Dihydrotestosterone (DHT) treatment induced AR-RFP translocation into the nucleus where the PPIs between AR and TIF2 resulted in the colocalization of both biosensors within the nucleolus. We adapted the translocation enhanced image analysis module to quantify the colocalization of the AR-RFP and TIF2-GFP biosensors in images acquired on the ImageXpress platform. DHT induced a concentration-dependent AR-TIF2 colocalization and produced a characteristic condensed punctate AR-RFP PPI nucleolar distribution pattern. The heat-shock protein 90 inhibitor 17-N-allylamino-17-demethoxygeldanamycin (17-AAG) and antiandrogens flutamide and bicalutamide inhibited DHT-induced AR-TIF2 PPI formation with 50% inhibition concentrations (IC50s) of 88.5±12.5 nM, 7.6±2.4 μM, and 1.6±0.4 μM, respectively. Images of the AR-RFP distribution phenotype allowed us to distinguish between 17-AAG and flutamide, which prevented AR translocation, and bicalutamide, which blocked AR-TIF2 PPIs. We screened the Library of Pharmacologically Active Compounds (LOPAC) set for compounds that inhibited AR-TIF2 PPI formation or disrupted preexisting complexes. Eleven modulators of steroid family nuclear receptors (NRs) and 6 non-NR ligands inhibited AR-TIF2 PPI formation, and 10 disrupted preexisting complexes. The hits appear to be either AR antagonists or nonspecific inhibitors of NR activation and trafficking. Given that the LOPAC set represents such a small and restricted biological and chemical diversity, it is anticipated that screening a much larger and more diverse compound library will be required to find AR-TIF2 PPI inhibitors/disruptors. The AR-TIF2 protein–protein interaction biosensor (PPIB) approach offers significant promise for identifying molecules with potential to modulate AR transcriptional activity in a cell-specific manner that is distinct from the existing antiandrogen drugs that target AR binding or production. Small molecules that disrupt AR signaling at the level of AR-TIF2 PPIs may also overcome the development of resistance and progression to castration-resistant prostate cancer. PMID:25181412

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.

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.

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.

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.

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

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.

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.

Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitors

NASA Astrophysics Data System (ADS)

Lagorce, David; Douguet, Dominique; Miteva, Maria A.; Villoutreix, Bruno O.

2017-04-01

The modulation of PPIs by low molecular weight chemical compounds, particularly by orally bioavailable molecules, would be very valuable in numerous disease indications. However, it is known that PPI inhibitors (iPPIs) tend to have properties that are linked to poor Absorption, Distribution, Metabolism, Excretion and Toxicity (ADMET) and in some cases to poor clinical outcomes. Previously reported in silico analyses of iPPIs have essentially focused on physicochemical properties but several other ADMET parameters would be important to assess. In order to gain new insights into the ADMET properties of iPPIs, computations were carried out on eight datasets collected from several databases. These datasets involve compounds targeting enzymes, GPCRs, ion channels, nuclear receptors, allosteric modulators, oral marketed drugs, oral natural product-derived marketed drugs and iPPIs. Several trends are reported that should assist the design and optimization of future PPI inhibitors, either for drug discovery endeavors or for chemical biology projects.

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.

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.

Disbalance of calcium regulation-related genes in broiler hearts induced by selenium deficiency.

PubMed

Zhang, Ziwei; Liu, Man; Guan, Zhenqiong; Yang, Jie; Liu, Zhonghua; Xu, Shiwen

2017-06-01

Dietary selenium (Se) deficiency may influence the calcium (Ca) homeostasis in broilers. Our objective was to investigate the effects of Se deficiency on Ca regulation-related genes in broiler hearts. In the present study, 1-day-old broilers were fed either a commercial diet (as control group) with 0.15 mg/kg Se or a Se-deficient diet (as L group) with 0.033 mg/kg Se for 35 days. We examined the mRNA expression levels of 15 Ca regulation-related genes (ITPR 1, ITPR 2, ITPR3, RyR2, RyR3, SERCA1s, SLC8A1, PMCA1, CACNA1S, TRPC1, TRPC3, stromal interacting molecule 1, ORAI1, calmodulin (CaLM) and calreticulin (CRT) in broiler hearts. Then, Kyoto Encyclopedia of Genes and Genomes analysis, protein-protein interactions (PPI) analysis and correlation analysis were performed to analyse the relationships between these genes. The results showed that the mRNA expression levels of ITPR 1, ITPR 2, RyR2, RyR3, SERCA1s, SLC8A1, PMCA1, CACNA1S, CaLM and CRT were generally decreased by Se deficiency, while mRNA expression levels of TRPC1, TRPC3, stromal interacting molecule 1, ORAI1 and ITPR3 were increased by Se deficiency. Kyoto Encyclopedia of Genes and Genomes and PPI analysis showed that these Ca regulation-related genes are involved in the Ca signalling pathway and a total of 15 PPIs with a combined score of >0.4 were obtained. In conclusion, the results demonstrated that Se deficiency might cause heart injury via modulating the Ca-related pathway genes, and then induce Ca 2+ overload in the heart of broilers.

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

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.

Studies on gallium nitride doped ferrite-polypyrrole nanocomposites

NASA Astrophysics Data System (ADS)

Indrakanti, Rajani; Brahmaji Rao, V.; Udaya Kiran, C.

2018-06-01

This communication reports the synthesis and characterisation of two novel Intrinsic conducting polymer nano composites (ICPN s) with the formulae Ga (2x+2) N Fe 2(49-x) O3—PPY synthesized using Impregnation technique. The Gallium nitride ferrite nano particles were synthesized for x = 1 and x = 5 using the above stichiometric equation earlier by Sol—Gel route. The chemical composition in the assembly of the ICPNs were Ga4NFe96O3-3%,10%,30% Polypyrrole, Ga12NFe88O3-3%,10%,30% Polypyrrole by weight. The Sci-Finder software failed to trace any earlier articles or reviews related to these ICNPs synthesised by us in the literature. X-ray Diffractometric (Structural), Morphological, EDAX SAED, IR spectroscopic characterizations were done on the synthesized nanocomposites. Structural studies reveal the semi-crystalline nature of composites. The average crystallite size of nano composites is decreased when compared with nano ferrites. SEM findings reveal that the shape for higher percentage of PPY is nano rods; for lower percentage it is globular. TEM reveals good dispersion and average particle size from histograms are calculated. The FT- IR bands of PPY and GaNFe2O3 are observed which show strong interaction between PPY- GaNFe2O3. Also there is a shift of bands in GaNFe2O3-PPY nano composites when compared to the bands of PPY.

Delocalization of π electrons and trapping action of ZnO nanoparticles in PPY matrix for hybrid solar cell application

NASA Astrophysics Data System (ADS)

Singh, Rajinder; Choudhary, Ram Bilash; Kandulna, Rohit

2018-03-01

Polypyrrole (PPY)-Zinc Oxide (ZnO) nanocomposites with varying concentration of ZnO (1:1-1:4) were prepared via in-situ polymerization technique by using pyrrole monomer in the presence of ammonium persulphate (APS) as oxidant. Globular morphology of PPY and sheet like structure of ZnO was examined using FESEM and EDAX. FTIR showed the presence of vibration modes in fingerprint region (1500 cm-1-500 cm-1) for metal oxides confirming the presence and interaction of ZnO with the polymer matrix in nanocomposites. Amorphous nature of PPY and hexagonal wurtzite structure of ZnO was confirmed using XRD with average crystallite size within 20 nm-30 nm. PANI-ZnO (1:1) exhibited blue shift in comparison to PPY (neat) and optimized optical band gap ∼ 1.81 eV. The effect of carrier concentration was investigated using electrochemical analyzer and maximum current was recorded for PANI-ZnO (1:1). The highest conductance was calculated for PANI-ZnO (1:1) ∼ 7.3242 × 10-3 S using current -voltage characteristics. Thermal stability was found to be increasing with the increase in ZnO concentration PANI-ZnO nanocomposite.

Stabilization of protein-protein interactions in drug discovery.

PubMed

Andrei, Sebastian A; Sijbesma, Eline; Hann, Michael; Davis, Jeremy; O'Mahony, Gavin; Perry, Matthew W D; Karawajczyk, Anna; Eickhoff, Jan; Brunsveld, Luc; Doveston, Richard G; Milroy, Lech-Gustav; Ottmann, Christian

2017-09-01

PPIs are involved in every disease and specific modulation of these PPIs with small molecules would significantly improve our prospects of developing therapeutic agents. Both industry and academia have engaged in the identification and use of PPI inhibitors. However in comparison, the opposite strategy of employing small-molecule stabilizers of PPIs is underrepresented in drug discovery. Areas covered: PPI stabilization has not been exploited in a systematic manner. Rather, this concept validated by a number of therapeutically used natural products like rapamycin and paclitaxel has been shown retrospectively to be the basis of the activity of synthetic molecules originating from drug discovery projects among them lenalidomide and tafamidis. Here, the authors cover the growing number of synthetic small-molecule PPI stabilizers to advocate for a stronger consideration of this as a drug discovery approach. Expert opinion: Both the natural products and the growing number of synthetic molecules show that PPI stabilization is a viable strategy for drug discovery. There is certainly a significant challenge to adapt compound libraries, screening techniques and downstream methodologies to identify, characterize and optimize PPI stabilizers, but the examples of molecules reviewed here in our opinion justify these efforts.

Titanium carbide nanocube core induced interfacial growth of crystalline polypyrrole/polyvinyl alcohol lamellar shell for wide-temperature range supercapacitors

NASA Astrophysics Data System (ADS)

Weng, Yu-Ting; Pan, Hsiao-An; Wu, Nae-Lih; Chen, Geroge Zheng

2015-01-01

This is the first investigation on electrically conducting polymers-based supercapacitor electrodes over a wide temperature range, from -18 °C to 60 °C. A high-performance supercapacitor electrode material consisting of TiC nanocube core and conformal crystalline polypyrrole (PPy)/poly-vinyl-alcohol (PVA) lamellar shell has been synthesized by heterogeneous nucleation-induced interfacial crystallization. PPy is induced to crystallize on the negatively charged TiC nanocube surfaces via strong interfacial interactions. In this organic-inorganic hybrid nanocomposite, the long chain PVA enables enhanced cycle life due to improved mechanical properties, and the TiC nanocube not only contributes to electron conduction, but also dictates the PPy morphology/crystallinity for maximizing the charging-discharging performance. The crystalline PPy/PAV layer on the TiC nanocube offers unprecedented high capacity (>350 F g-1-PPy at 300 mV s-1 with ΔV = 1.6 V) and cycling stability in a temperature range from -18 °C to 60 °C. The presented hybrid-filler and interfacial crystallization strategies can be applied to the exploration of new-generation high-power conducting polymer-based supercapacitor materials.

Mechanism of reactant and product dissociation from the anthrax edema factor: a locally enhanced sampling and steered molecular dynamics study.

PubMed

Martínez, Leandro; Malliavin, Thérèse E; Blondel, Arnaud

2011-05-01

The anthrax edema factor is a toxin overproducing damaging levels of cyclic adenosine monophosphate (cAMP) and pyrophosphate (PPi) from ATP. Here, mechanisms of dissociation of ATP and products (cAMP, PPi) from the active site are studied using locally enhanced sampling (LES) and steered molecular dynamics simulations. Various substrate conformations and ionic binding modes found in crystallographic structures are considered. LES simulations show that PPi and cAMP dissociate through different solvent accessible channels, while ATP dissociation requires significant active site exposure to solvent. The ionic content of the active site directly affects the dissociation of ATP and products. Only one ion dissociates along with ATP in the two-Mg(2+) binding site, suggesting that the other ion binds EF prior to ATP association. Dissociation of reaction products cAMP and PPi is impaired by direct electrostatic interactions between products and Mg(2+) ions. This provides an explanation for the inhibitory effect of high Mg(2+) concentrations on EF enzymatic activity. Breaking of electrostatic interactions is dependent on a competitive binding of water molecules to the ions, and thus on the solvent accessibility of the active site. Consequently, product dissociation seems to be a two-step process. First, ligands are progressively solvated while preserving the most important electrostatic interactions, in a process that is dependent on the flexibility of the active site. Second, breakage of the electrostatic bonds follows, and ligands diffuse into solvent. In agreement with this mechanism, product protonation facilitates dissociation.

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.

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.

Relevance of protein-protein interactions on the biological identity of nanoparticles.

PubMed

Vasti, Cecilia; Bonnet, Laura V; Galiano, Mauricio R; Rojas, Ricardo; Giacomelli, Carla E

2018-06-01

Considering that the use of nanoparticles (NPs) as carriers of therapeutic or theranostic agents has increased in the last years, it is mandatory to understand the interaction between NPs and living systems. In contact with biological fluids, the NPs (synthetic identity) are covered with biomolecules that form a protein corona, which defines the biological identity. It is well known that the protein corona formation is mediated by non-specific physical interactions, but protein-protein interactions (PPI), involving specific recognition sites of the polypeptides, are also involved. This work explores the relationship between the synthetic and biological identities of layered double hydroxides nanoparticles (LDH-NPs) and the effect of the protein corona on the cellular response. With such a purpose, the synthetic identity was modified by coating LDH-NPs with either a single protein or a complex mixture of them, followed by the characterization of the protein corona formed in a commonly used cell culture medium. A proteomic approach was used to identify the protein corona molecules and the PPI network was constructed with a novel bioinformatic tool. The coating on LDH-NPs defines the biological identity in such a way that the composition of the protein corona as well as PPI are changed. Electrostatic interactions appear not to be the only driving force regulating the interactions between NPs, proteins and cells since the specific recognition also play a fundamental role. However, the biological identity of LDH-NPs does not affect the interactions with cells that shows negligible cytotoxicity and high internalization levels. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

An unexpected way forward: towards a more accurate and rigorous protein-protein binding affinity scoring function by eliminating terms from an already simple scoring function.

PubMed

Swanson, Jon; Audie, Joseph

2018-01-01

A fundamental and unsolved problem in biophysical chemistry is the development of a computationally simple, physically intuitive, and generally applicable method for accurately predicting and physically explaining protein-protein binding affinities from protein-protein interaction (PPI) complex coordinates. Here, we propose that the simplification of a previously described six-term PPI scoring function to a four term function results in a simple expression of all physically and statistically meaningful terms that can be used to accurately predict and explain binding affinities for a well-defined subset of PPIs that are characterized by (1) crystallographic coordinates, (2) rigid-body association, (3) normal interface size, and hydrophobicity and hydrophilicity, and (4) high quality experimental binding affinity measurements. We further propose that the four-term scoring function could be regarded as a core expression for future development into a more general PPI scoring function. Our work has clear implications for PPI modeling and structure-based drug design.

Incorporation of hydrogel as a sensing medium for recycle of sensing material in chemical sensors

NASA Astrophysics Data System (ADS)

Hwang, Yunjung; Park, Jeong Yong; Kwon, Oh Seok; Joo, Seokwon; Lee, Chang-Soo; Bae, Joonwon

2018-01-01

A hydrogel, produced with agarose extracted from seaweed, was introduced as a reusable medium in ultrasensitive sensors employing conducting polymer nanomaterials and aptamers. A basic dopamine (DA) sensor was constructed by placing a hydrogel, containing a sensing material composed of aptamer-linked carboxylated polypyrrole nanotubes (PPy-COOH NTs), onto a micropatterned gold electrode. The hydrogel provided a benign electrochemical environment, facilitated specific interactions between DA and the PPy-COOH NT sensing material, and simplified the retrieval of PPy-COOH NTs after detection. It was demonstrated that the agarose hydrogel was successfully employed as a sensing medium for detection of DA, providing a benign environment for the electrode type sensor. PPy-COOH NTs were recovered by simply heating the hydrogel in water. The hydrogel also afforded stable signal intensity after repeated use with a limit of detection of 1 nmol and a clear, stable signal up to 100 nmol DA. This work provides relevant information for future research on reusable or recyclable sensors.

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.

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.

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.

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.

Multi-indication Pharmacotherapeutic Multicriteria Decision Analytic Model for the Comparative Formulary Inclusion of Proton Pump Inhibitors in Qatar.

PubMed

Al-Badriyeh, Daoud; Alabbadi, Ibrahim; Fahey, Michael; Al-Khal, Abdullatif; Zaidan, Manal

2016-05-01

The formulary inclusion of proton pump inhibitors (PPIs) in the government hospital health services in Qatar is not comparative or restricted. Requests to include a PPI in the formulary are typically accepted if evidence of efficacy and tolerability is presented. There are no literature reports of a PPI scoring model that is based on comparatively weighted multiple indications and no reports of PPI selection in Qatar or the Middle East. This study aims to compare first-line use of the PPIs that exist in Qatar. The economic effect of the study recommendations was also quantified. A comparative, evidence-based multicriteria decision analysis (MCDA) model was constructed to follow the multiple indications and pharmacotherapeutic criteria of PPIs. Literature and an expert panel informed the selection criteria of PPIs. Input from the relevant local clinician population steered the relative weighting of selection criteria. Comparatively scored PPIs, exceeding a defined score threshold, were recommended for selection. Weighted model scores were successfully developed, with 95% CI and 5% margin of error. The model comprised 7 main criteria and 38 subcriteria. Main criteria are indication, dosage frequency, treatment duration, best published evidence, available formulations, drug interactions, and pharmacokinetic and pharmacodynamic properties. Most weight was achieved for the indications selection criteria. Esomeprazole and rabeprazole were suggested as formulary options, followed by lansoprazole for nonformulary use. The estimated effect of the study recommendations was up to a 15.3% reduction in the annual PPI expenditure. Robustness of study conclusions against variabilities in study inputs was confirmed via sensitivity analyses. The implementation of a locally developed PPI-specific comparative MCDA scoring model, which is multiweighted indication and criteria based, into the Qatari formulary selection practices is a successful evidence-based cost-cutting exercise. Esomeprazole and rabeprazole should be the first-line choice from among the PPIs available at the Qatari government hospital health services. Copyright © 2016 Elsevier HS Journals, Inc. 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.

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.

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/.

Prediction of Protein-Protein Interaction Sites with Machine-Learning-Based Data-Cleaning and Post-Filtering Procedures.

PubMed

Liu, Guang-Hui; Shen, Hong-Bin; Yu, Dong-Jun

2016-04-01

Accurately predicting protein-protein interaction sites (PPIs) is currently a hot topic because it has been demonstrated to be very useful for understanding disease mechanisms and designing drugs. Machine-learning-based computational approaches have been broadly utilized and demonstrated to be useful for PPI prediction. However, directly applying traditional machine learning algorithms, which often assume that samples in different classes are balanced, often leads to poor performance because of the severe class imbalance that exists in the PPI prediction problem. In this study, we propose a novel method for improving PPI prediction performance by relieving the severity of class imbalance using a data-cleaning procedure and reducing predicted false positives with a post-filtering procedure: First, a machine-learning-based data-cleaning procedure is applied to remove those marginal targets, which may potentially have a negative effect on training a model with a clear classification boundary, from the majority samples to relieve the severity of class imbalance in the original training dataset; then, a prediction model is trained on the cleaned dataset; finally, an effective post-filtering procedure is further used to reduce potential false positive predictions. Stringent cross-validation and independent validation tests on benchmark datasets demonstrated the efficacy of the proposed method, which exhibits highly competitive performance compared with existing state-of-the-art sequence-based PPIs predictors and should supplement existing PPI prediction methods.

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.

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.

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.

MEGADOCK: An All-to-All Protein-Protein Interaction Prediction System Using Tertiary Structure Data

PubMed Central

Ohue, Masahito; Matsuzaki, Yuri; Uchikoga, Nobuyuki; Ishida, Takashi; Akiyama, Yutaka

2014-01-01

The elucidation of protein-protein interaction (PPI) networks is important for understanding cellular structure and function and structure-based drug design. However, the development of an effective method to conduct exhaustive PPI screening represents a computational challenge. We have been investigating a protein docking approach based on shape complementarity and physicochemical properties. We describe here the development of the protein-protein docking software package “MEGADOCK” that samples an extremely large number of protein dockings at high speed. MEGADOCK reduces the calculation time required for docking by using several techniques such as a novel scoring function called the real Pairwise Shape Complementarity (rPSC) score. We showed that MEGADOCK is capable of exhaustive PPI screening by completing docking calculations 7.5 times faster than the conventional docking software, ZDOCK, while maintaining an acceptable level of accuracy. When MEGADOCK was applied to a subset of a general benchmark dataset to predict 120 relevant interacting pairs from 120 x 120 = 14,400 combinations of proteins, an F-measure value of 0.231 was obtained. Further, we showed that MEGADOCK can be applied to a large-scale protein-protein interaction-screening problem with accuracy better than random. When our approach is combined with parallel high-performance computing systems, it is now feasible to search and analyze protein-protein interactions while taking into account three-dimensional structures at the interactome scale. MEGADOCK is freely available at http://www.bi.cs.titech.ac.jp/megadock. PMID:23855673

Rice cyclophilin OsCYP18-2 is translocated to the nucleus by an interaction with SKIP and enhances drought tolerance in rice and Arabidopsis.

PubMed

Lee, Sang Sook; Park, Hyun Ji; Yoon, Dae Hwa; Kim, Beom-Gi; Ahn, Jun Cheul; Luan, Sheng; Cho, Hye Sun

2015-10-01

Cyclophilin 18-2 (CYP18-2) genes, homologues of human peptidyl-prolyl isomerase-like 1 (PPiL1), are conserved across multicellular organisms and Schizosaccharomyces pombe. Although PPiL1 is known to interact with ski-interacting protein (SKIP), a transcriptional co-regulator and spliceosomal component, there have been no functional analyses of PPiL1 homologues in plants. Rice cyclophilin 18-2 (OsCYP18-2) bound directly to amino acids 56-95 of OsSKIP and its binding was independent of cyclosporin A, a cyclophilin-binding drug. Moreover, OsCYP18-2 exhibited PPIase activity regardless of its interaction with OsSKIP. Therefore, the binding site for OsCYP18-2's interaction with SKIP was distinct from the PPIase active site. OsCYP18-2's interaction with SKIP full-length protein enabled OsCYP18-2's translocation from the cytoplasm into the nucleus and AtSKIP interacted in planta with both AtCYP18-2 and OsCYP18-2. Drought and salt stress induced similar expression of OsCYP18-2 and OsSKIP. Overexpression of OsCYP18-2 in transgenic rice and Arabidopsis thaliana plants enhanced drought tolerance and altered expression and pre-mRNA splicing patterns of stress-related genes in Arabidopsis under drought conditions. Furthermore, OsCYP18-2 caused transcriptional activation with/without OsSKIP in the GAL4 system of yeast; thus the OsSKIP-OsCYP18-2 interaction has an important role in the transcriptional and post-transcriptional regulation of stress-related genes and increases tolerance to drought stress. © 2015 John Wiley & Sons Ltd.

Prediction and redesign of protein–protein interactions

PubMed Central

Lua, Rhonald C.; Marciano, David C.; Katsonis, Panagiotis; Adikesavan, Anbu K.; Wilkins, Angela D.; Lichtarge, Olivier

2014-01-01

Understanding the molecular basis of protein function remains a central goal of biology, with the hope to elucidate the role of human genes in health and in disease, and to rationally design therapies through targeted molecular perturbations. We review here some of the computational techniques and resources available for characterizing a critical aspect of protein function – those mediated by protein–protein interactions (PPI). We describe several applications and recent successes of the Evolutionary Trace (ET) in identifying molecular events and shapes that underlie protein function and specificity in both eukaryotes and prokaryotes. ET is a part of analytical approaches based on the successes and failures of evolution that enable the rational control of PPI. PMID:24878423

Polymerase Acidic Protein-Basic Protein 1 (PA-PB1) Protein-Protein Interaction as a Target for Next-Generation Anti-influenza Therapeutics.

PubMed

Massari, Serena; Goracci, Laura; Desantis, Jenny; Tabarrini, Oriana

2016-09-08

The limited therapeutic options against the influenza virus (flu) and increasing challenges in drug resistance make the search for next-generation agents imperative. In this context, heterotrimeric viral PA/PB1/PB2 RNA-dependent RNA polymerase is an attractive target for a challenging but strategic protein-protein interaction (PPI) inhibition approach. Since 2012, the inhibition of the polymerase PA-PB1 subunit interface has become an active field of research following the publication of PA-PB1 crystal structures. In this Perspective, we briefly discuss the validity of flu polymerase as a drug target and its inhibition through a PPI inhibition strategy, including a comprehensive analysis of available PA-PB1 structures. An overview of all of the reported PA-PB1 complex formation inhibitors is provided, and approaches used for identification of the inhibitors, the hit-to-lead studies, and the emerged structure-activity relationship are described. In addition to highlighting the strengths and weaknesses of all of the PA-PB1 heterodimerization inhibitors, we analyze their hypothesized binding modes and alignment with a pharmacophore model that we have developed.

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.

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.

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.

Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature

PubMed Central

Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

2017-01-01

Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems. PMID:29099838

Distributed smoothed tree kernel for protein-protein interaction extraction from the biomedical literature.

PubMed

Murugesan, Gurusamy; Abdulkadhar, Sabenabanu; Natarajan, Jeyakumar

2017-01-01

Automatic extraction of protein-protein interaction (PPI) pairs from biomedical literature is a widely examined task in biological information extraction. Currently, many kernel based approaches such as linear kernel, tree kernel, graph kernel and combination of multiple kernels has achieved promising results in PPI task. However, most of these kernel methods fail to capture the semantic relation information between two entities. In this paper, we present a special type of tree kernel for PPI extraction which exploits both syntactic (structural) and semantic vectors information known as Distributed Smoothed Tree kernel (DSTK). DSTK comprises of distributed trees with syntactic information along with distributional semantic vectors representing semantic information of the sentences or phrases. To generate robust machine learning model composition of feature based kernel and DSTK were combined using ensemble support vector machine (SVM). Five different corpora (AIMed, BioInfer, HPRD50, IEPA, and LLL) were used for evaluating the performance of our system. Experimental results show that our system achieves better f-score with five different corpora compared to other state-of-the-art systems.

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

An enhanced functional interrogation/manipulation of intracellular signaling pathways with the peptide 'stapling' technology.

PubMed

He, Y; Chen, D; Zheng, W

2015-11-12

Specific protein-protein interactions (PPIs) constitute a key underlying mechanism for the presence of a multitude of intracellular signaling pathways, which are essential for the survival of normal and cancer cells. Specific molecular blockers for a crucial PPI would therefore be invaluable tools for an enhanced functional interrogation of the signaling pathway harboring this particular PPI. On the other hand, if a particular PPI is essential for the survival of cancer cells but is absent in or dispensable for the survival of normal cells, its specific molecular blockers could potentially be developed into effective anticancer therapeutics. Due to the flat and extended PPI interface, it would be conceivably difficult for small molecules to achieve an effective blockade, a problem which could be potentially circumvented with peptides or proteins. However, the well-documented proteolytic instability and cellular impermeability of peptides and proteins in general would make their developing into effective intracellular PPI blockers quite a challenge. With the advent of the peptide 'stapling' technology which was demonstrated to be able to stabilize the α-helical conformation of a peptide via bridging two neighboring amino-acid side chains with a 'molecular staple', a linear parent peptide could be transformed into a stronger PPI blocker with enhanced proteolytic stability and cellular permeability. This review will furnish an account on the peptide 'stapling' technology and its exploitation in efforts to achieve an enhanced functional interrogation or manipulation of intracellular signaling pathways especially those that are cancer relevant.

Association between arginine vasopressin 1a receptor (AVPR1a) promoter region polymorphisms and prepulse inhibition.

PubMed

Levin, Raz; Heresco-Levy, Uriel; Bachner-Melman, Rachel; Israel, Salomon; Shalev, Idan; Ebstein, Richard P

2009-07-01

Arginine vasopressin and the arginine vasopressin 1a (AVPR1a) gene contribute to a range of social behaviors both in lower vertebrates and in humans. Human promoter-region microsatellite repeat regions (RS1 and RS3) in the AVPR1a gene region have been associated with autism spectrum disorders, prosocial behavior and social cognition. Prepulse inhibition (PPI) of the startle response to auditory stimuli is a largely autonomic response that resonates with social cognition in both animal models and humans. Reduced PPI has been observed in disorders including schizophrenia that are distinguished by deficits in social skills. In the current investigation association was examined between PPI and the AVPR1a RS1 and RS repeat regions and PPI in a group of 113 nonclinical subjects. Using a robust family-based strategy, association was observed between AVPR1a promoter-region repeat length, especially RS3) and PPI (30 ms: global p=0.04; 60 ms p=0.006; 120 ms p=0.008). Notably, longer RS3 alleles were associated with greater levels of prepulse inhibition. Using a short/long classification scheme for the repeat regions, significant association was also observed between all three PPI intervals (30, 60 and 120 ms) and both RS1 and RS3 polymorphisms (PBAT: FBAT-PC(2) statistic p=0.047). Tests of within-subject effects (SPSS GLM) showed significant sexxRS3 interactions at 30 ms (p=0.045) and 60 ms (p=0.01). Longer alleles, especially in male subjects, are associated with significantly higher PPI response, consistent with a role for the promoter repeat region in partially molding social behavior in both animals and humans. This is the first report in humans demonstrating a role of the AVPR1a gene in contributing to the PPI response to auditory stimuli.

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.

Selective enhancement of NMDA receptor-mediated locomotor hyperactivity by male sex hormones in mice.

PubMed

van den Buuse, Maarten; Low, Jac Kee; Kwek, Perrin; Martin, Sally; Gogos, Andrea

2017-09-01

Altered glutamate NMDA receptor function is implicated in schizophrenia, and gender differences have been demonstrated in this illness. This study aimed to investigate the interaction of gonadal hormones with NMDA receptor-mediated locomotor hyperactivity and PPI disruption in mice. The effect of 0.25 mg/kg of MK-801 on locomotor activity was greater in male mice than in female mice. Gonadectomy (by surgical castration) significantly reduced MK-801-induced hyperlocomotion in male mice, but no effect of gonadectomy was seen in female mice or on amphetamine-induced locomotor hyperactivity. The effect of MK-801 on prepulse inhibition of startle (PPI) was similar in intact and castrated male mice and in ovariectomized (OVX) female mice. In contrast, there was no effect of MK-801 on PPI in intact female mice. Forebrain NMDA receptor density, as measured with [ 3 H]MK-801 autoradiography, was significantly higher in male than in female mice but was not significantly altered by either castration or OVX. These results suggest that male sex hormones enhance the effect of NMDA receptor blockade on psychosis-like behaviour. This interaction was not seen in female mice and was independent of NMDA receptor density in the forebrain. Male sex hormones may be involved in psychosis by an interaction with NMDA receptor hypofunction.

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.

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

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.

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.

Facile preparation of polypyrrole/graphene oxide nanocomposites with large areal capacitance using electrochemical codeposition for supercapacitors

NASA Astrophysics Data System (ADS)

Zhou, Haihan; Han, Gaoyi; Xiao, Yaoming; Chang, Yunzhen; Zhai, Hua-Jin

2014-10-01

A simple and low-cost electrochemical codeposition method has been introduced to fabricate polypyrrole/graphene oxide (PPy/GO) nanocomposites and the areal capacitance of conducting polymer/GO composites is reported for the first time. Fourier transform infrared spectroscopy (FTIR), Transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD) are implemented to determine the PPy/GO nanocomposites are successfully prepared and the interaction between PPy and GO. The as-prepared PPy/GO nanocomposites show the curly sheet-like morphology, superior capacitive behaviors and cyclic stability. Furthermore, the varying deposition time is implemented to investigate the impact of the loading amount on electrochemical behavior of the composites, and a high areal capacitance of 152 mF cm-2 is achieved at 10 mV s-1 CV scan. However, the thicker films caused by the long deposition time would result in larger diffusion resistance of electrolyte ions, consequently exhibit the relatively lower capacitance value at the high current density. The GCD tests indicate moderate deposition time is more suitable for the fast charge/discharge. Considering the very simple and effective synthetic process, the PPy/GO nanocomposites with relatively high areal capacitance are competitive candidate for supercapacitor application, and its capacitive performances can be easily tuned by varying the deposition time.

Assembling of stimuli-responsive tumor targeting polypyrrole nanotubes drug carrier system for controlled release.

PubMed

Chen, Jian; Li, Xiufang; Li, Jiawen; Li, Jianbing; Huang, Ling; Ren, Tao; Yang, Xiao; Zhong, Shian

2018-08-01

A stimuli-responsive polypyrrole (PPy) nanotubes drug carrier system has been designed to deliver anticancer drugs to tumor cells in a targeted and controlled manner. The PPy nanotubes drug carrier was fabricated by a template method. The nanotubes surface was functionalized with cleavable acylhydrazone and disulfide bonds by attaching thiolated β-cyclodextrin (β-CD). The solubilizing poly(ethylene glycol) polymer (PEG), attached with an adamantane (Ad) entity at one end and a folate (FA) entity at the other end, was introduced onto the nanotubes surface via β-cyclodextrin-adamantane interaction. The synthesized FA-PEG-Ad-β-CD-PPy showed excellent biocompatibility and low cytotoxicity for two cell lines. Doxorubicin (Dox) loaded FA-PEG-Ad-β-CD-PPy nanotubes showed a triggered in vitro drug release behavior in the presence of acidic media and reducing agents. The folate-mediated endocytosis and intracellular release of Dox-loaded nanoparticles were confirmed by fluorescence microscopy and cell viability evaluations. In the in vitro study, Dox loaded within the nanoparticles showed enhanced selectivity for cancerous cells and reduced cytotoxicity for normal cells compared to free Dox. The PPy based targeted drug vehicle shows excellent promise for drug delivery. Copyright © 2018 Elsevier B.V. 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.

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.

Quantitative genetic-interaction mapping in mammalian cells

PubMed Central

Roguev, Assen; Talbot, Dale; Negri, Gian Luca; Shales, Michael; Cagney, Gerard; Bandyopadhyay, Sourav; Panning, Barbara; Krogan, Nevan J

2013-01-01

Mapping genetic interactions (GIs) by simultaneously perturbing pairs of genes is a powerful tool for understanding complex biological phenomena. Here we describe an experimental platform for generating quantitative GI maps in mammalian cells using a combinatorial RNA interference strategy. We performed ~11,000 pairwise knockdowns in mouse fibroblasts, focusing on 130 factors involved in chromatin regulation to create a GI map. Comparison of the GI and protein-protein interaction (PPI) data revealed that pairs of genes exhibiting positive GIs and/or similar genetic profiles were predictive of the corresponding proteins being physically associated. The mammalian GI map identified pathways and complexes but also resolved functionally distinct submodules within larger protein complexes. By integrating GI and PPI data, we created a functional map of chromatin complexes in mouse fibroblasts, revealing that the PAF complex is a central player in the mammalian chromatin landscape. PMID:23407553

Insight into the Intermolecular Recognition Mechanism between Keap1 and IKKβ Combining Homology Modelling, Protein-Protein Docking, Molecular Dynamics Simulations and Virtual Alanine Mutation

PubMed Central

Jiang, Zheng-Yu; Chu, Hong-Xi; Xi, Mei-Yang; Yang, Ting-Ting; Jia, Jian-Min; Huang, Jing-Jie; Guo, Xiao-Ke; Zhang, Xiao-Jin; You, Qi-Dong; Sun, Hao-Peng

2013-01-01

Degradation of certain proteins through the ubiquitin-proteasome pathway is a common strategy taken by the key modulators responsible for stress responses. Kelch-like ECH-associated protein-1(Keap1), a substrate adaptor component of the Cullin3 (Cul3)-based ubiquitin E3 ligase complex, mediates the ubiquitination of two key modulators, NF-E2-related factor 2 (Nrf2) and IκB kinase β (IKKβ), which are involved in the redox control of gene transcription. However, compared to the Keap1-Nrf2 protein-protein interaction (PPI), the intermolecular recognition mechanism of Keap1 and IKKβ has been poorly investigated. In order to explore the binding pattern between Keap1 and IKKβ, the PPI model of Keap1 and IKKβ was investigated. The structure of human IKKβ was constructed by means of the homology modeling method and using reported crystal structure of Xenopus laevis IKKβ as the template. A protein-protein docking method was applied to develop the Keap1-IKKβ complex model. After the refinement and visual analysis of docked proteins, the chosen pose was further optimized through molecular dynamics simulations. The resulting structure was utilized to conduct the virtual alanine mutation for the exploration of hot-spots significant for the intermolecular interaction. Overall, our results provided structural insights into the PPI model of Keap1-IKKβ and suggest that the substrate specificity of Keap1 depend on the interaction with the key tyrosines, namely Tyr525, Tyr574 and Tyr334. The study presented in the current project may be useful to design molecules that selectively modulate Keap1. The selective recognition mechanism of Keap1 with IKKβ or Nrf2 will be helpful to further know the crosstalk between NF-κB and Nrf2 signaling. PMID:24066166

Insight into the intermolecular recognition mechanism between Keap1 and IKKβ combining homology modelling, protein-protein docking, molecular dynamics simulations and virtual alanine mutation.

PubMed

Jiang, Zheng-Yu; Chu, Hong-Xi; Xi, Mei-Yang; Yang, Ting-Ting; Jia, Jian-Min; Huang, Jing-Jie; Guo, Xiao-Ke; Zhang, Xiao-Jin; You, Qi-Dong; Sun, Hao-Peng

2013-01-01

Degradation of certain proteins through the ubiquitin-proteasome pathway is a common strategy taken by the key modulators responsible for stress responses. Kelch-like ECH-associated protein-1(Keap1), a substrate adaptor component of the Cullin3 (Cul3)-based ubiquitin E3 ligase complex, mediates the ubiquitination of two key modulators, NF-E2-related factor 2 (Nrf2) and IκB kinase β (IKKβ), which are involved in the redox control of gene transcription. However, compared to the Keap1-Nrf2 protein-protein interaction (PPI), the intermolecular recognition mechanism of Keap1 and IKKβ has been poorly investigated. In order to explore the binding pattern between Keap1 and IKKβ, the PPI model of Keap1 and IKKβ was investigated. The structure of human IKKβ was constructed by means of the homology modeling method and using reported crystal structure of Xenopus laevis IKKβ as the template. A protein-protein docking method was applied to develop the Keap1-IKKβ complex model. After the refinement and visual analysis of docked proteins, the chosen pose was further optimized through molecular dynamics simulations. The resulting structure was utilized to conduct the virtual alanine mutation for the exploration of hot-spots significant for the intermolecular interaction. Overall, our results provided structural insights into the PPI model of Keap1-IKKβ and suggest that the substrate specificity of Keap1 depend on the interaction with the key tyrosines, namely Tyr525, Tyr574 and Tyr334. The study presented in the current project may be useful to design molecules that selectively modulate Keap1. The selective recognition mechanism of Keap1 with IKKβ or Nrf2 will be helpful to further know the crosstalk between NF-κB and Nrf2 signaling.

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.

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.

The impact of newly produced protein and dietary fiber rich fractions of yellow pea (Pisum sativum L.) on the structure and mechanical properties of pasta-like sheets.

PubMed

Muneer, Faraz; Johansson, Eva; Hedenqvist, Mikael S; Plivelic, Tomás S; Markedal, Keld Ejdrup; Petersen, Iben Lykke; Sørensen, Jens Christian; Kuktaite, Ramune

2018-04-01

Two fractions from pea (Pisum sativum L.), protein isolate (PPI) and dietary fiber (PF), were newly produced by extraction-fractionation method and characterized in terms of particle size distribution and structural morphology using SEM. The newly produced PPI and PF fractions were processed into pasta-like sheets with varying protein to fiber ratios (100/0, 90/10, 80/20, 70/30 and 50/50, respectively) using high temperature compression molding. We studied protein polymerization, molecular structure and protein-fiber interactions, as well as mechanical performance and cooking characteristics of processed PPI-PF blends. Bi-modal particle size distribution and chemical composition of the PPI and PF fractions influenced significantly the physicochemical properties of the pasta-like sheets. Polymerization was most pronounced for the 100 PPI, 90/10 and 80/20 PPI-PF samples as studied by SE-HPLC, and polymerization decreased with addition of the PF fraction. The mechanical properties, as strength and extensibility, were likewise the highest for the 100 PPI and 90/10 PPI-PF blends, while the E-modulus was similar for all the studied blends (around 38 MPa). The extensibility decreased with the increasing amount of PF in the blend. The highest amounts of β-sheets were found in the pasta-like sheets with high amounts of PPI (100, 90 and 80%), by FT-IR. An increase in PF fraction in the blend, resulted into the high amounts of unordered structures as observed by FT-IR, as well as in an increase in the molecular scattering distances observed by SAXS. The water uptake increased and cooking loss decreased with increased proportions of the PF fraction, and the consistency of 10 min cooked pasta-like sheets were alike al dente texture. The new knowledge obtained in this study on the use of extraction-fractionation method to produce novel PPI and PF fractions for developing innovative high nutritious food can be of a great importance. The obtained knowledge on the pea protein and fiber processing behaviour could greatly contribute to a better control of functional properties of various temperature-processed products from yellow pea. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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.

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.

A coarse grained molecular dynamics simulation study on the structural properties of carbon nanotube-dendrimer composites.

PubMed

Kavyani, Sajjad; Dadvar, Mitra; Modarress, Hamid; Amjad-Iranagh, Sepideh

2018-04-25

By employing coarse grained (CG) molecular dynamics (MD) simulation, the effect of the size and hydrophilic/hydrophobic properties of the interior/exterior structures of the dendrimers in carbon nanotube (CNT)-dendrimer composites has been studied, to find a stable composite with high solubility in water and the capability to be used in drug delivery applications. For this purpose, composites consisting of core-shell dendrimer complexes including: [PPI{core}-PAMAM{shell}], [PAMAM{core}-polyethyleneglycol (PEG){shell}] and [PAMAM{core}-fattyacid (FTA){shell}] were constructed. A new CG model for the fatty acid (FTA) molecules as functionalized to the dendrimer was developed, which, unlike the previous models, could generate the structural conformations of the FTA properly. The obtained results indicated that the dendrimer complexes with short FTA chains can form stable composites with the CNT. Also, it was found that the pristine PAMAM and PPI-PAMAM with small PPI, and PAMAM-PEG dendrimers with short PEG chains, can distribute their chains into the water medium and interact with the CNT efficiently, to form a stable water-soluble CNT-dendrimer composite. The results demonstrated that the structural difference between the interior and exterior of a core-shell dendrimer complex can prevent the core and the interior layers of the dendrimer complex from interacting with the CNT. An overall analysis of the results manifested that the CNT-PAMAM:4-PEG:4 is the most stable composite, due to strong binding of the dendrimer with the CNT while also having high solubility in water, and its core retains its structure properly and unchanged, suitable for encapsulating drugs in the targeted delivery applications.

Design, fabrication, and characterization of polymeric bioMEMS for the detection of feline immunodeficiency virus (FIV)

NASA Astrophysics Data System (ADS)

Cohen, Brian; Gadre, Anand; Kaloyeros, Alain E.

2007-02-01

This project comprises the development of a novel polymeric BioMEMS device capable of rapidly detecting FIV in a minimally invasive manner. FIV severely inhibits the infected feline from mounting an immune response, and causes susceptibility to other types of diseases. Vaccines against FIV do exist, but have some strong limitations to their effectiveness; so early detection is the best method to combat the spread of the disease. Current testing methods look for antibodies to the FIV protein p24 in feline blood using established Enzyme Linked ImmunoSorbent Assay (ELISA) protocols. The focus of this research is to design and construct a device that can detect antibodies to p24 in a salivary sample by non-intrusive electrochemical means. The device is constructed upon a silicon substrate with gold microelectrodes coated with polypyrrole (PPy), an electrically conducting and biocompatible polymer. In the current phase of the research, the PPy deposition process has been optimized with regards to film thickness, uniformity and conductivity. Microfluidic channels have been fabricated using SU-8, an epoxy based polymer that enables the test sample and other solutions to pass freely through the device. The PPy will be coated with anti-FIV p24 antibodies that can capture FIV p24 antigens present in a salivary sample. Future research will involve the analysis of PPy/antibody interaction and its effect on functionality. The capture of such antigens will interfere with a reduction-oxidation (redox) reaction in a subsequently added ionic solution. This interference will change the characteristic resistance of the solution yielding a qualitative test for the presence of the viral antigens in the sample and hence determining the occurrence of infection.

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.

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.

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.

Changes in cerebro-cerebellar interaction during response inhibition after performance improvement.

PubMed

Hirose, Satoshi; Jimura, Koji; Kunimatsu, Akira; Abe, Osamu; Ohtomo, Kuni; Miyashita, Yasushi; Konishi, Seiki

2014-10-01

It has been demonstrated that motor learning is supported by the cerebellum and the cerebro-cerebellar interaction. Response inhibition involves motor responses and the higher-order inhibition that controls the motor responses. In this functional MRI study, we measured the cerebro-cerebellar interaction during response inhibition in two separate days of task performance, and detected the changes in the interaction following performance improvement. Behaviorally, performance improved in the second day, compared to the first day. The psycho-physiological interaction (PPI) analysis revealed the interaction decrease from the right inferior frontal cortex (rIFC) to the cerebellum (lobule VII or VI). It was also revealed that the interaction increased from the same cerebellar region to the primary motor area. These results suggest the involvement of the cerebellum in response inhibition, and raise the possibility that the performance improvement was supported by the changes in the cerebro-cerebellar interaction. Copyright © 2014 Elsevier Inc. All rights reserved.

Synergistic Effect of Polypyrrole-Intercalated Graphene for Enhanced Corrosion Protection of Aqueous Coating in 3.5% NaCl Solution.

PubMed

Qiu, Shihui; Li, Wei; Zheng, Wenru; Zhao, Haichao; Wang, Liping

2017-10-04

Dispersion of graphene in water and its incorporation into waterborne resin have been rarely researched and hardly achieved owing to its hydrophobicity. Furthermore, it has largely been reported that graphene with impermeability contributed to the improved anticorrosion property. Here, we show that highly concentrated graphene aqueous solution up to 5 mg/mL can be obtained by synthesizing hydrophilic polypyrrole (PPy) nanocolloids as intercalators and ultrasonic vibration. On the basis of π-π interaction between PPy and graphene, stacked graphene sheets are exfoliated to the thickness of three to five layers without increasing defects. The corrosion performance of coatings without and with PPy and graphene is obtained by potential and impedance measurements, Tafel curves, and fitted pore resistance by immersing in a 3.5 wt % NaCl solution. It turns out that composite coating with 0.5 wt % graphene additive exhibits superior anticorrosive ability. The mechanism of intercalated graphene-based coating is interpreted as the synergistic protection of impermeable graphene sheets and self-healing PPy and proved by the identification of corrosion products and the scanning vibrating electrode technique.

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.

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.

SPR Biosensors in Direct Molecular Fishing: Implications for Protein Interactomics.

PubMed

Florinskaya, Anna; Ershov, Pavel; Mezentsev, Yuri; Kaluzhskiy, Leonid; Yablokov, Evgeniy; Medvedev, Alexei; Ivanov, Alexis

2018-05-18

We have developed an original experimental approach based on the use of surface plasmon resonance (SPR) biosensors, applicable for investigation of potential partners involved in protein⁻protein interactions (PPI) as well as protein⁻peptide or protein⁻small molecule interactions. It is based on combining a SPR biosensor, size exclusion chromatography (SEC), mass spectrometric identification of proteins (LC-MS/MS) and direct molecular fishing employing principles of affinity chromatography for isolation of potential partner proteins from the total lysate of biological samples using immobilized target proteins (or small non-peptide compounds) as ligands. Applicability of this approach has been demonstrated within the frame of the Human Proteome Project (HPP) and PPI regulation by a small non-peptide biologically active compound, isatin.

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

Atomic analysis of protein-protein interfaces with known inhibitors: the 2P2I database.

PubMed

Bourgeas, Raphaël; Basse, Marie-Jeanne; Morelli, Xavier; Roche, Philippe

2010-03-09

In the last decade, the inhibition of protein-protein interactions (PPIs) has emerged from both academic and private research as a new way to modulate the activity of proteins. Inhibitors of these original interactions are certainly the next generation of highly innovative drugs that will reach the market in the next decade. However, in silico design of such compounds still remains challenging. Here we describe this particular PPI chemical space through the presentation of 2P2I(DB), a hand-curated database dedicated to the structure of PPIs with known inhibitors. We have analyzed protein/protein and protein/inhibitor interfaces in terms of geometrical parameters, atom and residue properties, buried accessible surface area and other biophysical parameters. The interfaces found in 2P2I(DB) were then compared to those of representative datasets of heterodimeric complexes. We propose a new classification of PPIs with known inhibitors into two classes depending on the number of segments present at the interface and corresponding to either a single secondary structure element or to a more globular interacting domain. 2P2I(DB) complexes share global shape properties with standard transient heterodimer complexes, but their accessible surface areas are significantly smaller. No major conformational changes are seen between the different states of the proteins. The interfaces are more hydrophobic than general PPI's interfaces, with less charged residues and more non-polar atoms. Finally, fifty percent of the complexes in the 2P2I(DB) dataset possess more hydrogen bonds than typical protein-protein complexes. Potential areas of study for the future are proposed, which include a new classification system consisting of specific families and the identification of PPI targets with high druggability potential based on key descriptors of the interaction. 2P2I database stores structural information about PPIs with known inhibitors and provides a useful tool for biologists to assess the potential druggability of their interfaces. The database can be accessed at http://2p2idb.cnrs-mrs.fr.

High-Affinity Small-Molecule Inhibitors of the Menin-Mixed Lineage Leukemia (MLL) Interaction Closely Mimic a Natural Protein-Protein Interaction

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Shihan; Senter, Timothy J.; Pollock, Jonathan

2014-10-02

The protein–protein interaction (PPI) between menin and mixed lineage leukemia (MLL) plays a critical role in acute leukemias, and inhibition of this interaction represents a new potential therapeutic strategy for MLL leukemias. We report development of a novel class of small-molecule inhibitors of the menin–MLL interaction, the hydroxy- and aminomethylpiperidine compounds, which originated from HTS of ~288000 small molecules. We determined menin–inhibitor co-crystal structures and found that these compounds closely mimic all key interactions of MLL with menin. Extensive crystallography studies combined with structure-based design were applied for optimization of these compounds, resulting in MIV-6R, which inhibits the menin–MLL interactionmore » with IC 50 = 56 nM. Treatment with MIV-6 demonstrated strong and selective effects in MLL leukemia cells, validating specific mechanism of action. Our studies provide novel and attractive scaffold as a new potential therapeutic approach for MLL leukemias and demonstrate an example of PPI amenable to inhibition by small molecules.« less

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

Predicting domain-domain interaction based on domain profiles with feature selection and support vector machines

PubMed Central

2010-01-01

Background Protein-protein interaction (PPI) plays essential roles in cellular functions. The cost, time and other limitations associated with the current experimental methods have motivated the development of computational methods for predicting PPIs. As protein interactions generally occur via domains instead of the whole molecules, predicting domain-domain interaction (DDI) is an important step toward PPI prediction. Computational methods developed so far have utilized information from various sources at different levels, from primary sequences, to molecular structures, to evolutionary profiles. Results In this paper, we propose a computational method to predict DDI using support vector machines (SVMs), based on domains represented as interaction profile hidden Markov models (ipHMM) where interacting residues in domains are explicitly modeled according to the three dimensional structural information available at the Protein Data Bank (PDB). Features about the domains are extracted first as the Fisher scores derived from the ipHMM and then selected using singular value decomposition (SVD). Domain pairs are represented by concatenating their selected feature vectors, and classified by a support vector machine trained on these feature vectors. The method is tested by leave-one-out cross validation experiments with a set of interacting protein pairs adopted from the 3DID database. The prediction accuracy has shown significant improvement as compared to InterPreTS (Interaction Prediction through Tertiary Structure), an existing method for PPI prediction that also uses the sequences and complexes of known 3D structure. Conclusions We show that domain-domain interaction prediction can be significantly enhanced by exploiting information inherent in the domain profiles via feature selection based on Fisher scores, singular value decomposition and supervised learning based on support vector machines. Datasets and source code are freely available on the web at http://liao.cis.udel.edu/pub/svdsvm. Implemented in Matlab and supported on Linux and MS Windows. PMID:21034480

Protein-Protein Interactions (PPI) reagents: | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below.

Modulators of 14-3-3 Protein–Protein Interactions

PubMed Central

2017-01-01

Direct interactions between proteins are essential for the regulation of their functions in biological pathways. Targeting the complex network of protein–protein interactions (PPIs) has now been widely recognized as an attractive means to therapeutically intervene in disease states. Even though this is a challenging endeavor and PPIs have long been regarded as “undruggable” targets, the last two decades have seen an increasing number of successful examples of PPI modulators, resulting in growing interest in this field. PPI modulation requires novel approaches and the integrated efforts of multiple disciplines to be a fruitful strategy. This perspective focuses on the hub-protein 14-3-3, which has several hundred identified protein interaction partners, and is therefore involved in a wide range of cellular processes and diseases. Here, we aim to provide an integrated overview of the approaches explored for the modulation of 14-3-3 PPIs and review the examples resulting from these efforts in both inhibiting and stabilizing specific 14-3-3 protein complexes by small molecules, peptide mimetics, and natural products. PMID:28968506

Transient protein-protein interactions perturb E. coli metabolome and cause gene dosage toxicity

PubMed Central

Bhattacharyya, Sanchari; Bershtein, Shimon; Yan, Jin; Argun, Tijda; Gilson, Amy I; Trauger, Sunia A; Shakhnovich, Eugene I

2016-01-01

Gene dosage toxicity (GDT) is an important factor that determines optimal levels of protein abundances, yet its molecular underpinnings remain unknown. Here, we demonstrate that overexpression of DHFR in E. coli causes a toxic metabolic imbalance triggered by interactions with several functionally related enzymes. Though deleterious in the overexpression regime, surprisingly, these interactions are beneficial at physiological concentrations, implying their functional significance in vivo. Moreover, we found that overexpression of orthologous DHFR proteins had minimal effect on all levels of cellular organization – molecular, systems, and phenotypic, in sharp contrast to E. coli DHFR. Dramatic difference of GDT between ‘E. coli’s self’ and ‘foreign’ proteins suggests the crucial role of evolutionary selection in shaping protein-protein interaction (PPI) networks at the whole proteome level. This study shows how protein overexpression perturbs a dynamic metabolon of weak yet potentially functional PPI, with consequences for the metabolic state of cells and their fitness. DOI: http://dx.doi.org/10.7554/eLife.20309.001 PMID:27938662

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

Predicting Protein-Protein Interaction Sites with a Novel Membership Based Fuzzy SVM Classifier.

PubMed

Sriwastava, Brijesh K; Basu, Subhadip; Maulik, Ujjwal

2015-01-01

Predicting residues that participate in protein-protein interactions (PPI) helps to identify, which amino acids are located at the interface. In this paper, we show that the performance of the classical support vector machine (SVM) algorithm can further be improved with the use of a custom-designed fuzzy membership function, for the partner-specific PPI interface prediction problem. We evaluated the performances of both classical SVM and fuzzy SVM (F-SVM) on the PPI databases of three different model proteomes of Homo sapiens, Escherichia coli and Saccharomyces Cerevisiae and calculated the statistical significance of the developed F-SVM over classical SVM algorithm. We also compared our performance with the available state-of-the-art fuzzy methods in this domain and observed significant performance improvements. To predict interaction sites in protein complexes, local composition of amino acids together with their physico-chemical characteristics are used, where the F-SVM based prediction method exploits the membership function for each pair of sequence fragments. The average F-SVM performance (area under ROC curve) on the test samples in 10-fold cross validation experiment are measured as 77.07, 78.39, and 74.91 percent for the aforementioned organisms respectively. Performances on independent test sets are obtained as 72.09, 73.24 and 82.74 percent respectively. The software is available for free download from http://code.google.com/p/cmater-bioinfo.

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.

Proton-pump inhibitors adverse effects: a review of the evidence and position statement by the Sociedad Española de Patología Digestiva.

PubMed

de la Coba Ortiz, Cristóbal; Argüelles Arias, Federico; Martín de Argila de Prados, Carlos; Júdez Gutiérrez, Javier; Linares Rodríguez, Antonio; Ortega Alonso, Aida; Rodríguez de Santiago, Enrique; Rodríguez-Téllez, Manuel; Vera Mendoza, María Isabel; Aguilera Castro, Lara; Álvarez Sánchez, Ángel; Andrade Bellido, Raúl Jesús; Bao Pérez, Fidencio; Castro Fernández, Manuel; Giganto Tomé, Froilán

2016-04-01

In the last few years a significant number of papers have related the use of proton-pump inhibitors (PPIs) to potential serious adverse effects that have resulted in social unrest. The goal of this paper was to provide a literature review for the development of an institutional position statement by Sociedad Española de Patología Digestiva (SEPD) regarding the safety of long-term PPI use. A comprehensive review of the literature was performed to draw conclusions based on a critical assessment of the following: a) current PPI indications; b) vitamin B12 deficiency and neurological disorders; c) magnesium deficiency; d) bone fractures; e) enteric infection and pneumonia; f) interactions with thienopyridine derivatives; e) complications in cirrhotic patients. Current PPI indications have remained unchanged for years now, and are well established. A general screening of vitamin B12 levels is not recommended for all patients on a PPI; however, it does seem necessary that magnesium levels be measured at therapy onset, and then monitored in subjects on other drugs that may induce hypomagnesemia. A higher risk for bone fractures is present, even though causality cannot be concluded for this association. The association between PPIs and infection with Clostridium difficile is mild to moderate, and the risk for pneumonia is low. In patients with cardiovascular risk receiving thienopyridines derivatives it is prudent to adequately consider gastrointestinal and cardiovascular risks, given the absence of definitive evidence regardin potential drug-drug interactions; if gastrointestinal risk is found to be moderate or high, effective prevention should be in place with a PPI. PPIs should be cautiously indicated in patients with decompensated cirrhosis. PPIs are safe drugs whose benefits outweigh their potential side effects both short-term and long-term, provided their indication, dosage, and duration are appropriate.

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.

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.

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

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

Macrocyclic peptide inhibitors for the protein-protein interaction of Zaire Ebola virus protein 24 and karyopherin alpha 5.

PubMed

Song, Xiao; Lu, Lu-Yi; Passioura, Toby; Suga, Hiroaki

2017-06-21

Ebola virus infection leads to severe hemorrhagic fever in human and non-human primates with an average case fatality rate of 50%. To date, numerous potential therapies are in development, but FDA-approved drugs or vaccines are yet unavailable. Ebola viral protein 24 (VP24) is a multifunctional protein that plays critical roles in the pathogenesis of Ebola virus infection, e.g. innate immune suppression by blocking the interaction between KPNA and PY-STAT1. Here we report macrocyclic peptide inhibitors of the VP24-KPNA5 protein-protein interaction (PPI) by means of the RaPID (Random non-standard Peptides Integrated Discovery) system. These macrocyclic peptides showed remarkably high affinity to recombinant Zaire Ebola virus VP24 (eVP24), with a dissociation constant in the single digit nanomolar range, and could also successfully disrupt the eVP24-KPNA interaction. This work provides for the first time a chemical probe capable of modulating this PPI interaction and is the starting point for the development of unique anti-viral drugs against the Ebola virus.

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.

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.

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

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.

[Impact of an evaluation of the professional practices on the relevance of proton pump inhibitors prescriptions pertinence at the hospital].

PubMed

Daumas, A; Garros, E; Mendizabal, H; Gayet, S; Bernard, F; Bagnères, D; Demoux, A-L; Rossi, P; Villani, P; Granel, B

2018-04-05

Proton pump inhibitors (PPI) are widely prescribed for unrecognized indications, at high a dose and for a long duration, in spite of side effects and numerous drug interactions. In 2009, the HAS (French Health Authority) published recommendations of good prescription but the latter are poorly respected. In this context of over prescription and additional cost for the society, we performed a professional practice evaluation of on the model of the Deming wheel. The objective of this work was to optimize the relevance of the prescriptions of the IPP in two services of internal medicine and geriatrics through an evaluation of the professional practices. All PPI prescriptions introduced in outpatient visits or during hospitalization were analyzed. Data collection was prospective, over two periods of 2 months and included 163 (first phase), then 139 patients (second phase). An assessment grid of PPI prescriptions was completed by physicians regarding the active substance, the dose, the duration and the indication of the prescription. The relevance of the prescription corresponded to PPI with a conformed indication and duration and to the prescriptions no recommended stopped. Following the first period of data collection, information was given to medical students and physicians on the relevance of their prescriptions with regard to the current recommendations and informative flyers were offered with the aim of improving the practices before the second period of evaluation (second phase). During the first phase, only 25% of the pre-hospital prescriptions and 33% of the hospital prescriptions respected the HAS recommendations. The main indication of the PPI was the prevention of peptic ulcers in a context of associated drug estimated at risk. An improvement of the global relevance of prescription was observed after awareness of the physicians: 26% relevance during the first phase and 60% in the second one (P<0.012). During the second phase, the part of PPI prescriptions introduced at hospital decreased from 33 to 17% and the discontinuation of the not corresponding prescriptions increased from 6 to 33%, with an additional information given to the general practitioner (P<0.001). However, during the second phase, 33% of the prescriptions introduced in hospitalization were always not corresponding and 61% of the not corresponding prescriptions begun in outpatient visits were always pursued on discharge, probably due to the lack of sufficient information to stop the prescription. Our study underlines the frequent disrespect of the indications in the prescription of PPI. Interestingly, a professional practices evaluation improved the relevance of the prescriptions with a more frequent withdrawal of the not corresponding exposure and a decrease in global not corresponding prescriptions. Our study suggests that it is crucial to regularly inform physicians on the good prescription of PPI. Patient information focused on the indications and the limited duration of PPI prescription, potentially severe side effects of chronic exposure and on the risk of drug interactions also remains necessary in order to facilitate the stop of the exposure and restrict self-medication. Copyright © 2018 Société Nationale Française de Médecine Interne (SNFMI). Published by Elsevier SAS. All rights reserved.

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.

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.

Comprehensive Experimental and Computational Analysis of Binding Energy Hot Spots at the NF-κB Essential Modulator (NEMO)/IKKβ Protein-Protein Interface

PubMed Central

Golden, Mary S.; Cote, Shaun M.; Sayeg, Marianna; Zerbe, Brandon S.; Villar, Elizabeth A.; Beglov, Dmitri; Sazinsky, Stephen L.; Georgiadis, Rosina M.; Vajda, Sandor; Kozakov, Dima; Whitty, Adrian

2013-01-01

We report a comprehensive analysis of binding energy hot spots at the protein-protein interaction (PPI) interface between NF-κB Essential Modulator (NEMO) and IκB kinase subunit β (IKKβ), an interaction that is critical for NF-κB pathway signaling, using experimental alanine scanning mutagenesis and also the FTMap method for computational fragment screening. The experimental results confirm that the previously identified NBD region of IKKβ contains the highest concentration of hot spot residues, the strongest of which are W739, W741 and L742 (ΔΔG = 4.3, 3.5 and 3.2 kcal/mol, respectively). The region occupied by these residues defines a potentially druggable binding site on NEMO that extends for ~16 Å to additionally include the regions that bind IKKβ L737 and F734. NBD residues D738 and S740 are also important for binding but do not make direct contact with NEMO, instead likely acting to stabilize the active conformation of surrounding residues. We additionally found two previously unknown hot spot regions centered on IKKβ residues L708/V709 and L719/I723. The computational approach successfully identified all three hot spot regions on IKKβ. Moreover, the method was able to accurately quantify the energetic importance of all hot spots residues involving direct contact with NEMO. Our results provide new information to guide the discovery of small molecule inhibitors that target the NEMO/IKKβ interaction. They additionally clarify the structural and energetic complementarity between “pocket-forming” and “pocket occupying” hot spot residues, and further validate computational fragment mapping as a method for identifying hot spots at PPI interfaces. PMID:23506214

Protein-Protein Interaction Reagents | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below. Emory_CTD^2_PPI_Reagents.xlsx Contact: Haian Fu

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.

Recycling nicotinamide. The transition-state structure of human nicotinamide phosphoribosyltransferase

PubMed Central

Burgos, Emmanuel S.; Vetticatt, Mathew J.; Schramm, Vern L.

2013-01-01

Human nicotinamide phosphoribosyltransferase (NAMPT) replenishes the NAD pool and controls the activities of sirtuins (SIRT), mono- and poly-(ADP-ribose) polymerases (PARP) and NAD nucleosidase (CD38). The nature of the enzymatic transition-state (TS) is central to understanding the function of NAMPT. We determined the TS structure for pyrophosphorolysis of nicotinamide mononucleotide (NMN) by kinetic isotope effects (KIEs). With the natural substrates, NMN and pyrophosphate (PPi), the intrinsic KIEs of [1′-14C], [1-15N], [1′-3H] and [2′-3H] are 1.047, 1.029, 1.154 and 1.093, respectively. A unique quantum computational approach was used for TS analysis that included structural elements of the catalytic site. Without constraints (e.g. imposed torsion angles), the theoretical and experimental data are in good agreement. The quantum-mechanical calculations incorporated a crucial catalytic site residue (D313), two magnesium atoms and coordinated water molecules. The transition state model predicts primary 14C, α-secondary 3H, β-secondary 3H and primary 15N KIE close to the experimental values. The analysis reveals significant ribocation character at the TS. The attacking PPi nucleophile is weakly interacting (rC-O = 2.60 Å) and the N-ribosidic C1′-N bond is highly elongated at the TS (rC-N = 2.35 Å), consistent with an ANDN mechanism. Together with the crystal structure of the NMN•PPi•Mg2•enzyme complex, the reaction coordinate is defined. The enzyme holds the nucleophile and leaving group in relatively fixed positions to create a reaction coordinate with C1′-anomeric migration from nicotinamide to the PPi. The transition state is reached by a 0.85 Å migration of C1′. PMID:23373462

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

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.

Discrete structural features among interface residue-level classes.

PubMed

Sowmya, Gopichandran; Ranganathan, Shoba

2015-01-01

Protein-protein interaction (PPI) is essential for molecular functions in biological cells. Investigation on protein interfaces of known complexes is an important step towards deciphering the driving forces of PPIs. Each PPI complex is specific, sensitive and selective to binding. Therefore, we have estimated the relative difference in percentage of polar residues between surface and the interface for each complex in a non-redundant heterodimer dataset of 278 complexes to understand the predominant forces driving binding. Our analysis showed ~60% of protein complexes with surface polarity greater than interface polarity (designated as class A). However, a considerable number of complexes (~40%) have interface polarity greater than surface polarity, (designated as class B), with a significantly different p-value of 1.66E-45 from class A. Comprehensive analyses of protein complexes show that interface features such as interface area, interface polarity abundance, solvation free energy gain upon interface formation, binding energy and the percentage of interface charged residue abundance distinguish among class A and class B complexes, while electrostatic visualization maps also help differentiate interface classes among complexes. Class A complexes are classical with abundant non-polar interactions at the interface; however class B complexes have abundant polar interactions at the interface, similar to protein surface characteristics. Five physicochemical interface features analyzed from the protein heterodimer dataset are discriminatory among the interface residue-level classes. These novel observations find application in developing residue-level models for protein-protein binding prediction, protein-protein docking studies and interface inhibitor design as drugs.

Discrete structural features among interface residue-level classes

PubMed Central

2015-01-01

Background Protein-protein interaction (PPI) is essential for molecular functions in biological cells. Investigation on protein interfaces of known complexes is an important step towards deciphering the driving forces of PPIs. Each PPI complex is specific, sensitive and selective to binding. Therefore, we have estimated the relative difference in percentage of polar residues between surface and the interface for each complex in a non-redundant heterodimer dataset of 278 complexes to understand the predominant forces driving binding. Results Our analysis showed ~60% of protein complexes with surface polarity greater than interface polarity (designated as class A). However, a considerable number of complexes (~40%) have interface polarity greater than surface polarity, (designated as class B), with a significantly different p-value of 1.66E-45 from class A. Comprehensive analyses of protein complexes show that interface features such as interface area, interface polarity abundance, solvation free energy gain upon interface formation, binding energy and the percentage of interface charged residue abundance distinguish among class A and class B complexes, while electrostatic visualization maps also help differentiate interface classes among complexes. Conclusions Class A complexes are classical with abundant non-polar interactions at the interface; however class B complexes have abundant polar interactions at the interface, similar to protein surface characteristics. Five physicochemical interface features analyzed from the protein heterodimer dataset are discriminatory among the interface residue-level classes. These novel observations find application in developing residue-level models for protein-protein binding prediction, protein-protein docking studies and interface inhibitor design as drugs. PMID:26679043

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®

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.

Psychophysiological interaction between superior temporal gyrus (STG) and cerebellum: An fMRI study

NASA Astrophysics Data System (ADS)

Yusoff, A. N.; Teng, X. L.; Ng, S. B.; Hamid, A. I. A.; Mukari, S. Z. M.

2016-03-01

This study aimed to model the psychophysiological interaction (PPI) between the bilateral STG and cerebellum (lobule VI and lobule VII) during an arithmetic addition task. Eighteen young adults participated in this study. They were instructed to solve single-digit addition tasks in quiet and noisy backgrounds during an fMRI scan. Results showed that in both hemispheres, the response in the cerebellum was found to be linearly influenced by the activity in STG (vice-versa) for both in-quiet and in-noise conditions. However, the influence of the cerebellum on STG seemed to be modulated by noise. A two-way PPI model between STG and cerebellum is suggested. The connectivity between the two regions during a simple addition task in a noisy condition is modulated by the participants’ higher attention to perceive.

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.

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.

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.

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

Adverse drug reactions due to drug-drug interactions with proton pump inhibitors: assessment of systematic reviews with AMSTAR method.

PubMed

Yucel, Emre; Sancar, Mesut; Yucel, Aylin; Okuyan, Betul

2016-01-01

Many systematic reviews resulted in claims on drug-drug interactions (DDIs) with proton pump inhibitors (PPIs). Such a large number begs for consensus on the clinical significance of findings. We critically evaluated the safety of PPI use with respect to DDIs with a meta-review of systematic reviews published between 1978 and 2015. We assessed the evidence by their reliability, repeatability, transparency, and objectivity according to the Assessment of Multiple Systematic Reviews (AMSTAR) criteria. Clinicians must assess risks for each PPI for certain comorbid conditions. DDIs don't substantiate class effect for PPIs; each PPI could induce unique DDIs. Concomitant use of PPIs with thienopyridines (e.g. clopidogrel) could be justified in patients without strong affinity to cytochrome CYP2C19 and with high risk of bleeding (e.g. patients with prior upper gastrointestinal bleeding, Helicobacter pylori infection, advanced age, steroid treatment, and nonsteroidal anti-inflammatory drug use). DDIs could occur in an AIDS subpopulation treated with highly active antiretroviral therapy (HAART). DDIs exist for cancer patients undergoing targeted therapy. Hypomagnesemia could increase in the setting of advanced age and polypharmacy. Omeprazole poses high risks owing to its pharmacokinetic DDI profile. Future systematic reviews should incorporate these additional risks for better clinical guidance.

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.

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.

Discovery of high-affinity BCL6-binding peptide and its structure-activity relationship

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sakamoto, Kotaro; Sogabe, Satoshi; Kamada, Yusuke

B cell lymphoma 6 (BCL6) is a transcriptional repressor that interacts with its corepressors BcoR and SMRT. Since this protein-protein interaction (PPI) induces activation and differentiation of B lymphocytes, BCL6 has been an attractive drug target for potential autoimmune disease treatments. Here we report a novel BCL6 inhibitory peptide, F1324 (Ac-LWYTDIRMSWRVP-OH), which we discovered using phage display technology; we also discuss this peptide's structure-activity relationship (SAR). For BCL6(5-129) binding, K{sub D} and IC{sub 50} values of F1324 were 0.57 nM and 1 nM according to the results of an SPR analysis and cell-free ELISA assay, respectively. In contrast, BcoR(Arg498-514Pro) and SMRT(Leu1422-Arg1438) exhibitedmore » relatively weak micromole-order binding to BCL6. Furthermore, Fusion protein AcGFP-F1324 transiently expressed in HEK293T cells inhibited intracellular PPI in cell-based M2H assay. By examination of the truncation and fragmentation of F1324, the C-terminal sequence WRVP, which is similar to the BcoR(509-512) sequence WVVP, was identified as being critical for BCL6 binding. In addition, subsequent single-crystal X-ray diffraction analysis of F1324/BCL6(5-129) complex revealed that the high affinity of F1324 was caused by effective interaction of its side chains while its main chain structure was similar to that of BcoR(Arg498-514Pro). To our knowledge, F1324 is the strongest BCL6-binding peptide yet reported. - Highlights: • F1324 was discovered as 5000-times higher affinity peptide to BCL6 than that of BcoR(R498-P514). • X-ray crystal structure analysis revealed the binding mode. • To our knowledge, F1324 is the strongest BCL6-binding and -inhibition peptide so far.« less

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.

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.

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.

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.

Ligand-bridged dinuclear cyclometalated Ir(III) complexes: from metallamacrocycles to discrete dimers.

PubMed

Chandrasekhar, Vadapalli; Hajra, Tanima; Bera, Jitendra K; Rahaman, S M Wahidur; Satumtira, Nisa; Elbjeirami, Oussama; Omary, Mohammad A

2012-02-06

Metallamacrocycles 1, 2, and 3 of the general formula [{Ir(ppy)(2)}(2)(μ-BL)(2)](OTf)(2) (ppyH = 2-phenyl pyridine; BL = 1,2-bis(4-pyridyl)ethane (bpa) (1), 1,3-bis(4-pyridyl)propane (bpp) (2), and trans-1,2-bis(4-pyridyl)ethylene (bpe) (3)) have been synthesized by the reaction of [{(ppy)(2)Ir}(2)(μ-Cl)(2)], first with AgOTf to effect dechlorination and later with various bridging ligands. Open-frame dimers [{Ir(ppy)(2)}(2)(μ-BL)](OTf)(2) were obtained in a similar manner by utilizing N,N'-bis(2-pyridyl)methylene-hydrazine (abp) and N,N'-(bis(2-pyridyl)formylidene)ethane-1,2-diamine (bpfd) (for compounds 4 and 5, respectively) as bridging ligands. Molecular structures of 1, 3, 4, and 5 were established by X-ray crystallography. Cyclic voltammetry experiments reveal weakly interacting "Ir(ppy)(2)" units bridged by ethylene-linked bpe ligand in 3; on the contrary the metal centers are electronically isolated in 1 and 2 where the bridging ligands are based on ethane and propane linkers. The dimer 4 exhibits two accessible reversible reduction couples separated by 570 mV indicating the stability of the one-electron reduced species located on the diimine-based bridge abp. The "Ir(ppy)(2)" units in compound 5 are noninteracting as the electronic conduit is truncated by the ethane spacer in the bpfd bridge. The dinuclear compounds 1-5 show ligand centered (LC) transitions involving ppy ligands and mixed metal to ligand/ligand to ligand charge transfer (MLCT/LLCT) transitions involving both the cyclometalating ppy and bridging ligands (BL) in the UV-vis spectra. For the conjugated bridge bpe in compound 3 and abp in compound 4, the lowest-energy charge-transfer absorptions are red-shifted with enhanced intensity. In accordance with their similar electronic structures, compounds 1 and 2 exhibit identical emissions. The presence of vibronic structures in these compounds indicates a predominantly (3)LC excited states. On the contrary, broad and unstructured phosphorescence bands in compounds 3-5 strongly suggest emissive states of mixed (3)MLCT/(3)LLCT character. Density functional theory (DFT) calculations have been carried out to gain insight on the frontier orbitals, and to rationalize the electrochemical and photophysical properties of the compounds based on their electronic structures.

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.

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

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.

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

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.

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.

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.

Improving prediction of heterodimeric protein complexes using combination with pairwise kernel.

PubMed

Ruan, Peiying; Hayashida, Morihiro; Akutsu, Tatsuya; Vert, Jean-Philippe

2018-02-19

Since many proteins become functional only after they interact with their partner proteins and form protein complexes, it is essential to identify the sets of proteins that form complexes. Therefore, several computational methods have been proposed to predict complexes from the topology and structure of experimental protein-protein interaction (PPI) network. These methods work well to predict complexes involving at least three proteins, but generally fail at identifying complexes involving only two different proteins, called heterodimeric complexes or heterodimers. There is however an urgent need for efficient methods to predict heterodimers, since the majority of known protein complexes are precisely heterodimers. In this paper, we use three promising kernel functions, Min kernel and two pairwise kernels, which are Metric Learning Pairwise Kernel (MLPK) and Tensor Product Pairwise Kernel (TPPK). We also consider the normalization forms of Min kernel. Then, we combine Min kernel or its normalization form and one of the pairwise kernels by plugging. We applied kernels based on PPI, domain, phylogenetic profile, and subcellular localization properties to predicting heterodimers. Then, we evaluate our method by employing C-Support Vector Classification (C-SVC), carrying out 10-fold cross-validation, and calculating the average F-measures. The results suggest that the combination of normalized-Min-kernel and MLPK leads to the best F-measure and improved the performance of our previous work, which had been the best existing method so far. We propose new methods to predict heterodimers, using a machine learning-based approach. We train a support vector machine (SVM) to discriminate interacting vs non-interacting protein pairs, based on informations extracted from PPI, domain, phylogenetic profiles and subcellular localization. We evaluate in detail new kernel functions to encode these data, and report prediction performance that outperforms the state-of-the-art.

Identification of Small Molecule Translesion Synthesis Inhibitors That Target the Rev1-CT/RIR Protein-Protein Interaction.

PubMed

Sail, Vibhavari; Rizzo, Alessandro A; Chatterjee, Nimrat; Dash, Radha C; Ozen, Zuleyha; Walker, Graham C; Korzhnev, Dmitry M; Hadden, M Kyle

2017-07-21

Translesion synthesis (TLS) is an important mechanism through which proliferating cells tolerate DNA damage during replication. The mutagenic Rev1/Polζ-dependent branch of TLS helps cancer cells survive first-line genotoxic chemotherapy and introduces mutations that can contribute to the acquired resistance so often observed with standard anticancer regimens. As such, inhibition of Rev1/Polζ-dependent TLS has recently emerged as a strategy to enhance the efficacy of first-line chemotherapy and reduce the acquisition of chemoresistance by decreasing tumor mutation rate. The TLS DNA polymerase Rev1 serves as an integral scaffolding protein that mediates the assembly of the active multiprotein TLS complexes. Protein-protein interactions (PPIs) between the C-terminal domain of Rev1 (Rev1-CT) and the Rev1-interacting region (RIR) of other TLS DNA polymerases play an essential role in regulating TLS activity. To probe whether disrupting the Rev1-CT/RIR PPI is a valid approach for developing a new class of targeted anticancer agents, we designed a fluorescence polarization-based assay that was utilized in a pilot screen for small molecule inhibitors of this PPI. Two small molecule scaffolds that disrupt this interaction were identified, and secondary validation assays confirmed that compound 5 binds to Rev1-CT at the RIR interface. Finally, survival and mutagenesis assays in mouse embryonic fibroblasts and human fibrosarcoma HT1080 cells treated with cisplatin and ultraviolet light indicate that these compounds inhibit mutagenic Rev1/Polζ-dependent TLS in cells, validating the Rev1-CT/RIR PPI for future anticancer drug discovery and identifying the first small molecule inhibitors of TLS that target Rev1-CT.

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.

Sky-blue emitting bridged diiridium complexes: beneficial effects of intramolecular π-π stacking.

PubMed

Congrave, Daniel G; Hsu, Yu-Ting; Batsanov, Andrei S; Beeby, Andrew; Bryce, Martin R

2018-02-06

The potential of intramolecular π-π interactions to influence the photophysical properties of diiridium complexes is an unexplored topic, and provides the motivation for the present study. A series of diarylhydrazide-bridged diiridium complexes functionalised with phenylpyridine (ppy)-based cyclometalating ligands is reported. It is shown by NMR studies in solution and single crystal X-ray analysis that intramolecular π-π interactions between the bridging and cyclometalating ligands rigidify the complexes leading to high luminescence quantum efficiencies in solution and in doped films. Fluorine substituents on the phenyl rings of the bridge promote the intramolecular π-π interactions. Notably, these non-covalent interactions are harnessed in the rational design and synthesis of the first examples of highly emissive sky-blue diiridium complexes featuring conjugated bridging ligands, for which they play a vital role in the structural and photophysical properties. Experimental results are supported by computational studies.

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

Poly(zwitterionic liquids) functionalized polypyrrole/graphene oxide nanosheets for electrochemically detecting dopamine at low concentration.

PubMed

Mao, Hui; Liang, Jiachen; Ji, Chunguang; Zhang, Haifeng; Pei, Qi; Zhang, Yuyang; Zhang, Yu; Hisaeda, Yoshio; Song, Xi-Ming

2016-08-01

Poly(3-(1-vinylimidazolium-3-yl)propane-1-sulfonate) (PVIPS), a novel kind of poly(zwitterionic liquids) (PZILs) containing both imidazolium cation and sulfonate anion, was successfully modified on the surface of polypyrrole/graphene oxide nanosheets (PPy/GO) by covalent bonding. The obtained novel PZILs functionalized PPy/GO nanosheets (PVIPS/PPy/GO) modified glassy carbon electrode (GCE) presented the excellent electrochemical catalytic activity towards dopamine (DA) with high stability, sensitivity, selectivity and wide linear range (40-1220nM), especially having a lower detection limit (17.3nM). The excellent analytical performance is attributed to the strongly negative charges on the surface of modified GCE in aqueous solution, which is different from conventional poly(ionic liquids) modified GCE. DA cations could be quickly enriched on the electrode surface by electrostatic interaction in solution due to the existence of SO3(-) groups with negative charge at the end of pendant groups in zwitterionic PVIPS, resulting in a change of the electrons transmission mode in the oxidation of DA, that is, from a typical diffusion-controlled process at conventional poly(1-vinyl-3-ethylimidazole bromide) (PVEIB)/PPy/GO modified GCE to a typical surface-controlled process. Copyright © 2016 Elsevier B.V. All rights reserved.

Medial prefrontal cortex lesions in the female rat affect sexual and maternal behavior and their sequential organization.

PubMed

Afonso, Veronica M; Sison, Margarette; Lovic, Vedran; Fleming, Alison S

2007-06-01

Temporal sequences of sexual and maternal behaviors in female rats and their correlation with each other and with performance on a sensory-motor gating response inhibition task assessed by prepulse inhibition (PPI) were investigated following medial prefrontal cortex (mPFC) lesions. Following excitotoxic mPFC (n = 10) or sham (n = 9) lesions, sexual behaviors across the ovarian cycle were scored. After mating and parturition, maternal interactions were scored until pups reached postnatal Day 10. After resumption of the ovarian cycle, the female rats were tested for PPI. Compared with sham lesions, mPFC lesions impaired proceptive behaviors and some maternal behaviors (e.g., pup retrieval, pup licking) but did not affect others (e.g., nest building, pup mouthing). Lesions disrupted temporal sequences of solicitations (number of male orientations followed, within 4 s, by a level change) and pup retrievals (number of pup retrievals followed, within 5 s, by another retrieval). These sequential behavior patterns were significantly correlated with each other and with PPI. However, when PPI effects were partialled out, group differences were less strong, but persisted. This study demonstrated that mPFC manipulations affect actions rich in sequential structure in response to biologically relevant stimuli. Copyright (c) 2007 APA, all rights reserved.

The effects of Eph-ephrin mutations on pre-pulse inhibition in mice.

PubMed

Liuzzo, Andrea; Gray, Lincoln; Wallace, Matthew; Gabriele, Mark

2014-08-01

Eph-ephrin signaling is known to be important in directing topographic projections in the afferent auditory pathway, including connections to various subdivisions of the inferior colliculus (IC). The acoustic startle-response (ASR) is a reliable reflexive behavioral response in mammals elicited by an unexpected intense acoustic startle-eliciting stimulus (ES). It is mediated by a sub-cortical pathway that includes the IC. The ASR amplitude can be measured with an accelerometer under the subject and can be decreased in amplitude by presenting a less intense, non-startling stimulus 5-300ms before the ES. This reflexive decrement in ASR is called pre-pulse inhibition (PPI) and indicates that the relatively soft pre-pulse was heard. PPI is a general trait among mammals. Mice have been used recently to study this response and to reveal how genetic mutations affect neural circuits and hence the ASR and PPI. In this experiment, we measured the effect of Eph-ephrin mutations using control mice (C57BL/6J), mice with compromised EphA4 signaling (EphA4(lacZ/+), EphA4(lacZ/lacZ)), and knockout ephrin-B3 mice (ephrin-B3 (+/-, -/-)). Control and EphA4(lacZ/+s)trains showed robust PPI (up to 75% decrement in ASR) to an offset of a 70dB SPL background noise at 50ms before the ES. Ephrin-B3 knockout mice and EphA4 homozygous mutants were only marginally significant in PPI (<25% decrement and <33% decrement, respectively) to the same conditions. This decrement in PPI highlights the importance of ephrin-B3 and EphA4 interactions in ordering auditory behavioral circuits. Thus, different mutations in certain members of the signaling family produce a full range of changes in PPI, from minimal to nearly maximal. This technique can be easily adapted to study other aspects of hearing in a wider range of mutations. Along with ongoing neuroanatomical studies, this allows careful quantification of how the auditory anatomical, physiological and now behavioral phenotype is affected by changes in Eph-ephrin expression and functionality. Copyright © 2014 Elsevier Inc. All rights reserved.

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.

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.

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.

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.

A coevolution analysis for identifying protein-protein interactions by Fourier transform.

PubMed

Yin, Changchuan; Yau, Stephen S-T

2017-01-01

Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI).

A coevolution analysis for identifying protein-protein interactions by Fourier transform

PubMed Central

Yin, Changchuan; Yau, Stephen S. -T.

2017-01-01

Protein-protein interactions (PPIs) play key roles in life processes, such as signal transduction, transcription regulations, and immune response, etc. Identification of PPIs enables better understanding of the functional networks within a cell. Common experimental methods for identifying PPIs are time consuming and expensive. However, recent developments in computational approaches for inferring PPIs from protein sequences based on coevolution theory avoid these problems. In the coevolution theory model, interacted proteins may show coevolutionary mutations and have similar phylogenetic trees. The existing coevolution methods depend on multiple sequence alignments (MSA); however, the MSA-based coevolution methods often produce high false positive interactions. In this paper, we present a computational method using an alignment-free approach to accurately detect PPIs and reduce false positives. In the method, protein sequences are numerically represented by biochemical properties of amino acids, which reflect the structural and functional differences of proteins. Fourier transform is applied to the numerical representation of protein sequences to capture the dissimilarities of protein sequences in biophysical context. The method is assessed for predicting PPIs in Ebola virus. The results indicate strong coevolution between the protein pairs (NP-VP24, NP-VP30, NP-VP40, VP24-VP30, VP24-VP40, and VP30-VP40). The method is also validated for PPIs in influenza and E.coli genomes. Since our method can reduce false positive and increase the specificity of PPI prediction, it offers an effective tool to understand mechanisms of disease pathogens and find potential targets for drug design. The Python programs in this study are available to public at URL (https://github.com/cyinbox/PPI). PMID:28430779

The roles of 5-HT1A and 5-HT2 receptors in the effects of 5-MeO-DMT on locomotor activity and prepulse inhibition in rats.

PubMed

Krebs-Thomson, Kirsten; Ruiz, Erbert M; Masten, Virginia; Buell, Mahalah; Geyer, Mark A

2006-12-01

The hallucinogen 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) is structurally similar to other indoleamine hallucinogens such as LSD. The present study examined the effects of 5-MeO-DMT in rats using the Behavioral Pattern Monitor (BPM), which enables analyses of patterns of locomotor activity and exploration, and the prepulse inhibition of startle (PPI) paradigm. A series of interaction studies using the serotonin (5-HT)(1A) antagonist WAY-100635 (1.0 mg/kg), the 5-HT(2A) antagonist M100907 (1.0 mg/kg), and the 5-HT(2C) antagonist SER-082 (0.5 mg/kg) were performed to assess the respective contributions of these receptors to the behavioral effects of 5-MeO-DMT (0.01, 0.1, and 1.0 mg/kg) in the BPM and PPI paradigms. 5-MeO-DMT decreased locomotor activity, investigatory behavior, the time spent in the center of the BPM chamber, and disrupted PPI. All of these effects were antagonized by WAY-100635 pretreatment. M100907 pretreatment failed to attenuate any of these effects, while SER-082 pretreatment only antagonized the PPI disruption produced by 5-MeO-DMT. While the prevailing view was that the activation of 5-HT(2) receptors is solely responsible for hallucinogenic drug effects, these results support a role for 5-HT(1A) receptors in the effects of the indoleamine hallucinogen 5-MeO-DMT on locomotor activity and PPI in rats.

Nonsteroid anti-inflammatory drug-induced gastroduodenal injury.

PubMed

Lai, Larry H; Chan, Francis K L

2009-11-01

This article reviews selected publications related to nonsteroid anti-inflammatory drug (NSAID)-induced gastroduodenal toxicity in recent years. This article provides a comprehensive review of the latest evidence on the epidemiology of NSAID-induced gastroduodenal injury, recommendations on optimal gastroprotective regimens among patients in need of NSAID, risk stratification approach by considering gastrointestinal and cardiovascular risks, and negative interaction between proton pump inhibitors (PPIs) and clopidogrel. Current evidence indicates that a PPI and a cyclooxygenase (COX)-2-selective NSAID provides the best gastric protection. In light of potential cardiovascular hazard of NSAIDs, physicians should select an NSAID according to individual patients' cardiovascular risk (i.e., naproxen vs. a nonnaproxen NSAID). The choice of gastroprotective therapy depends on the number and nature of gastrointestinal risk factors. PPI co-therapy is recommended in patients with high gastrointestinal risk on aspirin. Whether there is any clinically important interaction between PPIs and clopidogrel remains uncertain.

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.

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

Protein-protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM.

PubMed

Sriwastava, Brijesh Kumar; Basu, Subhadip; Maulik, Ujjwal

2015-10-01

Protein-protein interaction (PPI) site prediction aids to ascertain the interface residues that participate in interaction processes. Fuzzy support vector machine (F-SVM) is proposed as an effective method to solve this problem, and we have shown that the performance of the classical SVM can be enhanced with the help of an interaction-affinity based fuzzy membership function. The performances of both SVM and F-SVM on the PPI databases of the Homo sapiens and E. coli organisms are evaluated and estimated the statistical significance of the developed method over classical SVM and other fuzzy membership-based SVM methods available in the literature. Our membership function uses the residue-level interaction affinity scores for each pair of positive and negative sequence fragments. The average AUC scores in the 10-fold cross-validation experiments are measured as 79.94% and 80.48% for the Homo sapiens and E. coli organisms respectively. On the independent test datasets, AUC scores are obtained as 76.59% and 80.17% respectively for the two organisms. In almost all cases, the developed F-SVM method improves the performances obtained by the corresponding classical SVM and the other classifiers, available in the literature.

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.

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.

Detection of membrane protein-protein interaction in planta based on dual-intein-coupled tripartite split-GFP association.

PubMed

Liu, Tzu-Yin; Chou, Wen-Chun; Chen, Wei-Yuan; Chu, Ching-Yi; Dai, Chen-Yi; Wu, Pei-Yu

2018-05-01

Despite the great interest in identifying protein-protein interactions (PPIs) in biological systems, only a few attempts have been made at large-scale PPI screening in planta. Unlike biochemical assays, bimolecular fluorescence complementation allows visualization of transient and weak PPIs in vivo at subcellular resolution. However, when the non-fluorescent fragments are highly expressed, spontaneous and irreversible self-assembly of the split halves can easily generate false positives. The recently developed tripartite split-GFP system was shown to be a reliable PPI reporter in mammalian and yeast cells. In this study, we adapted this methodology, in combination with the β-estradiol-inducible expression cassette, for the detection of membrane PPIs in planta. Using a transient expression assay by agroinfiltration of Nicotiana benthamiana leaves, we demonstrate the utility of the tripartite split-GFP association in plant cells and affirm that the tripartite split-GFP system yields no spurious background signal even with abundant fusion proteins readily accessible to the compartments of interaction. By validating a few of the Arabidopsis PPIs, including the membrane PPIs implicated in phosphate homeostasis, we proved the fidelity of this assay for detection of PPIs in various cellular compartments in planta. Moreover, the technique combining the tripartite split-GFP association and dual-intein-mediated cleavage of polyprotein precursor is feasible in stably transformed Arabidopsis plants. Our results provide a proof-of-concept implementation of the tripartite split-GFP system as a potential tool for membrane PPI screens in planta. © 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.

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.

Computational Framework for Prediction of Peptide Sequences That May Mediate Multiple Protein Interactions in Cancer-Associated Hub Proteins.

PubMed

Sarkar, Debasree; Patra, Piya; Ghosh, Abhirupa; Saha, Sudipto

2016-01-01

A considerable proportion of protein-protein interactions (PPIs) in the cell are estimated to be mediated by very short peptide segments that approximately conform to specific sequence patterns known as linear motifs (LMs), often present in the disordered regions in the eukaryotic proteins. These peptides have been found to interact with low affinity and are able bind to multiple interactors, thus playing an important role in the PPI networks involving date hubs. In this work, PPI data and de novo motif identification based method (MEME) were used to identify such peptides in three cancer-associated hub proteins-MYC, APC and MDM2. The peptides corresponding to the significant LMs identified for each hub protein were aligned, the overlapping regions across these peptides being termed as overlapping linear peptides (OLPs). These OLPs were thus predicted to be responsible for multiple PPIs of the corresponding hub proteins and a scoring system was developed to rank them. We predicted six OLPs in MYC and five OLPs in MDM2 that scored higher than OLP predictions from randomly generated protein sets. Two OLP sequences from the C-terminal of MYC were predicted to bind with FBXW7, component of an E3 ubiquitin-protein ligase complex involved in proteasomal degradation of MYC. Similarly, we identified peptides in the C-terminal of MDM2 interacting with FKBP3, which has a specific role in auto-ubiquitinylation of MDM2. The peptide sequences predicted in MYC and MDM2 look promising for designing orthosteric inhibitors against possible disease-associated PPIs. Since these OLPs can interact with other proteins as well, these inhibitors should be specific to the targeted interactor to prevent undesired side-effects. This computational framework has been designed to predict and rank the peptide regions that may mediate multiple PPIs and can be applied to other disease-associated date hub proteins for prediction of novel therapeutic targets of small molecule PPI modulators.

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®

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.

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.

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

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.

A novel feature extraction scheme with ensemble coding for protein-protein interaction prediction.

PubMed

Du, Xiuquan; Cheng, Jiaxing; Zheng, Tingting; Duan, Zheng; Qian, Fulan

2014-07-18

Protein-protein interactions (PPIs) play key roles in most cellular processes, such as cell metabolism, immune response, endocrine function, DNA replication, and transcription regulation. PPI prediction is one of the most challenging problems in functional genomics. Although PPI data have been increasing because of the development of high-throughput technologies and computational methods, many problems are still far from being solved. In this study, a novel predictor was designed by using the Random Forest (RF) algorithm with the ensemble coding (EC) method. To reduce computational time, a feature selection method (DX) was adopted to rank the features and search the optimal feature combination. The DXEC method integrates many features and physicochemical/biochemical properties to predict PPIs. On the Gold Yeast dataset, the DXEC method achieves 67.2% overall precision, 80.74% recall, and 70.67% accuracy. On the Silver Yeast dataset, the DXEC method achieves 76.93% precision, 77.98% recall, and 77.27% accuracy. On the human dataset, the prediction accuracy reaches 80% for the DXEC-RF method. We extended the experiment to a bigger and more realistic dataset that maintains 50% recall on the Yeast All dataset and 80% recall on the Human All dataset. These results show that the DXEC method is suitable for performing PPI prediction. The prediction service of the DXEC-RF classifier is available at http://ailab.ahu.edu.cn:8087/ DXECPPI/index.jsp.

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

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.

Design of Microstructured Conducting Polymer Films for Enhanced Trace Explosives Detection

NASA Astrophysics Data System (ADS)

Laster, Jennifer S.

The detection of trace amounts of explosive material is critical to national security. Ion mobility spectrometer (IMS)-based contact sampling continues to be a common method employed for the detection of explosives in high security checkpoint applications, such as airport security. In this process a surface of interest, such as a passenger's hands or luggage, is probed by a swab or particle trap to collect and transfer residue to an IMS for analysis. The collection of residue on a sampling swab has been shown to be a limiting step in this detection process. As such, there is significant need to develop new materials with increased adhesion to explosive analytes and with superior particle removal abilities. Here, the design of novel sampling swabs is presented for the enhanced collection of trace explosive residue from surfaces. First, the influence of the swab microstructure on the ability to remove particles from representative substrates is demonstrated. Free-standing microstructured polypyrrole (PPy) films of a variety of dimensions and form factors are fabricated using a templated electropolymerization process. The removal of polystyrene fluorescent particles from an aluminum substrate of varying surface roughness is examined as a function of the polymer microstructure. PPy microstructured films display enhanced particle removal abilities compared to PPy non-structured and current commercial films. This increase in particle removal is attributed to the increased particle-swab contact from the microstructured films. Next, the influence of the surface chemistry of sampling swabs on the collection of a representative explosive analyte, trinitrotoluene (TNT) is explored. The surface chemistry of PPy films is modified by electropolymerizaton of an N-substituted pyrrole monomer. The surface chemistries examined include a methyl, carboxylic acid, and amino-phenyl functionality. The vapor deposition of TNT on the surface of the functionalized PPy films is quantified through ultraviolet-visible (UV-vis) absorption and compared to commercial swabbing materials of varying chemistry and surface roughness. The PPy modified films with potential sites for hydrogen bonding display the highest deposition of TNT, while the Teflon coated commercial films display the lowest interaction with TNT. Finally, the desorption and release of TNT from sampling swabs is studied as an effect of temperature and of applied bias. For successful analyte detection within an IMS, the residue collected on a sampling swab must be released from the swab, typically through a thermal desorption process. In this work the release of TNT from sampling swabs is determined through solid-phase microextraction-gas chromatography mass spectrometry (SPME-GCMS). The results of this thesis provide important information on the design considerations for the development of novel particle sampling swabs with increased performance.

An integrative system biology approach to unravel potential drug candidates for multiple age related disorders.

PubMed

Srivastava, Isha; Khurana, Pooja; Yadav, Mohini; Hasija, Yasha

2017-12-01

Aging, though an inevitable part of life, is becoming a worldwide social and economic problem. Healthy aging is usually marked by low probability of age related disorders. Good therapeutic approaches are still in need to cure age related disorders. Occurrence of more than one ARD in an individual, expresses the need of discovery of such target proteins, which can affect multiple ARDs. Advanced scientific and medical research technologies throughout last three decades have arrived to the point where lots of key molecular determinants affect human disorders can be examined thoroughly. In this study, we designed and executed an approach to prioritize drugs that may target multiple age related disorders. Our methodology, focused on the analysis of biological pathways and protein protein interaction networks that may contribute to the pharmacology of age related disorders, included various steps such as retrieval and analysis of data, protein-protein interaction network analysis, and statistical and comparative analysis of topological coefficients, pathway, and functional enrichment analysis, and identification of drug-target proteins. We assume that the identified molecular determinants may be prioritized for further screening as novel drug targets to cure multiple ARDs. Based on the analysis, an online tool named as 'ARDnet' has been developed to construct and demonstrate ARD interactions at the level of PPI, ARDs and ARDs protein interaction, ARDs pathway interaction and drug-target interaction. The tool is freely made available at http://genomeinformatics.dtu.ac.in/ARDNet/Index.html. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

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.

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.

Development of automated high throughput single molecular microfluidic detection platform for signal transduction analysis

NASA Astrophysics Data System (ADS)

Huang, Po-Jung; Baghbani Kordmahale, Sina; Chou, Chao-Kai; Yamaguchi, Hirohito; Hung, Mien-Chie; Kameoka, Jun

2016-03-01

Signal transductions including multiple protein post-translational modifications (PTM), protein-protein interactions (PPI), and protein-nucleic acid interaction (PNI) play critical roles for cell proliferation and differentiation that are directly related to the cancer biology. Traditional methods, like mass spectrometry, immunoprecipitation, fluorescence resonance energy transfer, and fluorescence correlation spectroscopy require a large amount of sample and long processing time. "microchannel for multiple-parameter analysis of proteins in single-complex (mMAPS)"we proposed can reduce the process time and sample volume because this system is composed by microfluidic channels, fluorescence microscopy, and computerized data analysis. In this paper, we will present an automated mMAPS including integrated microfluidic device, automated stage and electrical relay for high-throughput clinical screening. Based on this result, we estimated that this automated detection system will be able to screen approximately 150 patient samples in a 24-hour period, providing a practical application to analyze tissue samples in a clinical setting.

Polypropyleneimine and polyamidoamine dendrimer mediated enhanced solubilization of bortezomib: Comparison and evaluation of mechanistic aspects by thermodynamics and molecular simulations.

PubMed

Chaudhary, Sonam; Gothwal, Avinash; Khan, Iliyas; Srivastava, Shubham; Malik, Ruchi; Gupta, Umesh

2017-03-01

Bortezomib (BTZ) is the first proteasome inhibitor approved by the US-FDA is majorly used for the treatment of newly diagnosed and relapsed multiple myeloma including mantle cell lymphoma. BTZ is hydrophobic in nature and is a major cause for its minimal presence as marketed formulations. The present study reports the design, development and characterization of dendrimer based formulation for the improved solubility and effectivity of bortezomib. The study also equally focuses on the mechanistic elucidation of solubilization by two types of dendrimers i.e. fourth generation of poly (amidoamine) dendrimers (G4-PAMAM-NH 2 ) and fifth generation of poly (propylene) imine dendrimers (G5-PPI-NH 2 ). It was observed that aqueous solubility of BTZ was concentration and pH dependent. At 2mM G5-PPI-NH 2 concentration, the fold increase in bortezomib solubility was 1152.63 times in water, while approximately 3426.69 folds increase in solubility was observed at pH10.0, respectively (p<0.05). The solubility of the drug was increased to a greater extent with G5-PPI-NH 2 dendrimers because it has more hydrophobic interior than G4-PAMAM-NH 2 dendrimers. The release of BTZ from G5-PPI-NH 2 complex was comparatively slower than G4-PAMAM-NH 2 . The thermodynamic treatment of data proved that dendrimer drug complexes were stable at all pH with values of ΔG always negative. The experimental findings were also proven by molecular simulation studies and by calculating RMSD and intermolecular hydrogen bonding through Schrodinger software. It was concluded that PPI dendrimers were able to solubilize the drug more effectively than PAMAM dendrimers through electrostatic interactions. Copyright © 2016 Elsevier B.V. All rights reserved.

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

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.

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

INTERSPIA: a web application for exploring the dynamics of protein-protein interactions among multiple species.

PubMed

Kwon, Daehong; Lee, Daehwan; Kim, Juyeon; Lee, Jongin; Sim, Mikang; Kim, Jaebum

2018-05-09

Proteins perform biological functions through cascading interactions with each other by forming protein complexes. As a result, interactions among proteins, called protein-protein interactions (PPIs) are not completely free from selection constraint during evolution. Therefore, the identification and analysis of PPI changes during evolution can give us new insight into the evolution of functions. Although many algorithms, databases and websites have been developed to help the study of PPIs, most of them are limited to visualize the structure and features of PPIs in a chosen single species with limited functions in the visualization perspective. This leads to difficulties in the identification of different patterns of PPIs in different species and their functional consequences. To resolve these issues, we developed a web application, called INTER-Species Protein Interaction Analysis (INTERSPIA). Given a set of proteins of user's interest, INTERSPIA first discovers additional proteins that are functionally associated with the input proteins and searches for different patterns of PPIs in multiple species through a server-side pipeline, and second visualizes the dynamics of PPIs in multiple species using an easy-to-use web interface. INTERSPIA is freely available at http://bioinfo.konkuk.ac.kr/INTERSPIA/.

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.

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.

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

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

Systematic Prioritization and Integrative Analysis of Copy Number Variations in Schizophrenia Reveal Key Schizophrenia Susceptibility Genes

PubMed Central

Luo, Xiongjian; Huang, Liang; Han, Leng; Luo, Zhenwu; Hu, Fang; Tieu, Roger; Gan, Lin

2014-01-01

Schizophrenia is a common mental disorder with high heritability and strong genetic heterogeneity. Common disease-common variants hypothesis predicts that schizophrenia is attributable in part to common genetic variants. However, recent studies have clearly demonstrated that copy number variations (CNVs) also play pivotal roles in schizophrenia susceptibility and explain a proportion of missing heritability. Though numerous CNVs have been identified, many of the regions affected by CNVs show poor overlapping among different studies, and it is not known whether the genes disrupted by CNVs contribute to the risk of schizophrenia. By using cumulative scoring, we systematically prioritized the genes affected by CNVs in schizophrenia. We identified 8 top genes that are frequently disrupted by CNVs, including NRXN1, CHRNA7, BCL9, CYFIP1, GJA8, NDE1, SNAP29, and GJA5. Integration of genes affected by CNVs with known schizophrenia susceptibility genes (from previous genetic linkage and association studies) reveals that many genes disrupted by CNVs are also associated with schizophrenia. Further protein-protein interaction (PPI) analysis indicates that protein products of genes affected by CNVs frequently interact with known schizophrenia-associated proteins. Finally, systematic integration of CNVs prioritization data with genetic association and PPI data identifies key schizophrenia candidate genes. Our results provide a global overview of genes impacted by CNVs in schizophrenia and reveal a densely interconnected molecular network of de novo CNVs in schizophrenia. Though the prioritized top genes represent promising schizophrenia risk genes, further work with different prioritization methods and independent samples is needed to confirm these findings. Nevertheless, the identified key candidate genes may have important roles in the pathogenesis of schizophrenia, and further functional characterization of these genes may provide pivotal targets for future therapeutics and diagnostics. PMID:24664977

The left dorsolateral prefrontal cortex and caudate pathway: New evidence for cue-induced craving of smokers.

PubMed

Yuan, Kai; Yu, Dahua; Bi, Yanzhi; Wang, Ruonan; Li, Min; Zhang, Yajuan; Dong, Minghao; Zhai, Jinquan; Li, Yangding; Lu, Xiaoqi; Tian, Jie

2017-09-01

Although the activation of the prefrontal cortex (PFC) and the striatum had been found in smoking cue induced craving task, whether and how the functional interactions and white matter integrity between these brain regions contribute to craving processing during smoking cue exposure remains unknown. Twenty-five young male smokers and 26 age- and gender-matched nonsmokers participated in the smoking cue-reactivity task. Craving related brain activation was extracted and psychophysiological interactions (PPI) analysis was used to specify the PFC-efferent pathways contributed to smoking cue-induced craving. Diffusion tensor imaging (DTI) and probabilistic tractography was used to explore whether the fiber connectivity strength facilitated functional coupling of the circuit with the smoking cue-induced craving. The PPI analysis revealed the negative functional coupling of the left dorsolateral prefrontal cortex (DLPFC) and the caudate during smoking cue induced craving task, which positively correlated with the craving score. Neither significant activation nor functional connectivity in smoking cue exposure task was detected in nonsmokers. DTI analyses revealed that fiber tract integrity negatively correlated with functional coupling in the DLPFC-caudate pathway and activation of the caudate induced by smoking cue in smokers. Moreover, the relationship between the fiber connectivity integrity of the left DLPFC-caudate and smoking cue induced caudate activation can be fully mediated by functional coupling strength of this circuit in smokers. The present study highlighted the left DLPFC-caudate pathway in smoking cue-induced craving in smokers, which may reflect top-down prefrontal modulation of striatal reward processing in smoking cue induced craving processing. Hum Brain Mapp 38:4644-4656, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A Genomic and Protein-Protein Interaction Analyses of Nonsyndromic Hearing Impairment in Cameroon Using Targeted Genomic Enrichment and Massively Parallel Sequencing.

PubMed

Lebeko, Kamogelo; Manyisa, Noluthando; Chimusa, Emile R; Mulder, Nicola; Dandara, Collet; Wonkam, Ambroise

2017-02-01

Hearing impairment (HI) is one of the leading causes of disability in the world, impacting the social, economic, and psychological well-being of the affected individual. This is particularly true in sub-Saharan Africa, which carries one of the highest burdens of this condition. Despite this, there are limited data on the most prevalent genes or mutations that cause HI among sub-Saharan Africans. Next-generation technologies, such as targeted genomic enrichment and massively parallel sequencing, offer new promise in this context. This study reports, for the first time to the best of our knowledge, on the prevalence of novel mutations identified through a platform of 116 HI genes (OtoSCOPE ® ), among 82 African probands with HI. Only variants OTOF NM_194248.2:c.766-2A>G and MYO7A NM_000260.3:c.1996C>T, p.Arg666Stop were found in 3 (3.7%) and 5 (6.1%) patients, respectively. In addition and uniquely, the analysis of protein-protein interactions (PPI), through interrogation of gene subnetworks, using a custom script and two databases (Enrichr and PANTHER), and an algorithm in the igraph package of R, identified the enrichment of sensory perception and mechanical stimulus biological processes, and the most significant molecular functions of these variants pertained to binding or structural activity. Furthermore, 10 genes (MYO7A, MYO6, KCTD3, NUMA1, MYH9, KCNQ1, UBC, DIAPH1, PSMC2, and RDX) were identified as significant hubs within the subnetworks. Results reveal that the novel variants identified among familial cases of HI in Cameroon are not common, and PPI analysis has highlighted the role of 10 genes, potentially important in understanding HI genomics among Africans.

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®

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.

Preparation and application of conducting polymer/Ag/clay composite nanoparticles formed by in situ UV-induced dispersion polymerization

PubMed Central

Zang, Limin; Qiu, Jianhui; Yang, Chao; Sakai, Eiichi

2016-01-01

In this work, composite nanoparticles containing polypyrrole, silver and attapulgite (PPy/Ag/ATP) were prepared via UV-induced dispersion polymerization of pyrrole using ATP clay as a templet and silver nitrate as photoinitiator. The effects of ATP concentration on morphology, structure and electrical conductivity were studied. The obtained composite nanoparticles with an interesting beads-on-a-string morphology can be obtained in a short time (10 min), which indicates the preparation method is facile and feasible. To explore the potential applications of the prepared PPy/Ag/ATP composite nanoparticles, they were served as multifunctional filler and blended with poly(butylene succinate) (PBS) matrix to prepare biodegradable composite material. The distribution of fillers in polymer matrix and the interfacial interaction between fillers and PBS were confirmed by scanning electron microscope, elemental mapping and dynamic mechanical analysis. The well dispersed fillers in PBS matrix impart outstanding antibacterial property to the biodegradable composite material as well as enhanced storage modulus due to Ag nanoparticles and ATP clay. The biodegradable composite material also possesses modest surface resistivity (106 ~ 109 Ω/◻). PMID:26839126

Preparation and application of conducting polymer/Ag/clay composite nanoparticles formed by in situ UV-induced dispersion polymerization.

PubMed

Zang, Limin; Qiu, Jianhui; Yang, Chao; Sakai, Eiichi

2016-02-03

In this work, composite nanoparticles containing polypyrrole, silver and attapulgite (PPy/Ag/ATP) were prepared via UV-induced dispersion polymerization of pyrrole using ATP clay as a templet and silver nitrate as photoinitiator. The effects of ATP concentration on morphology, structure and electrical conductivity were studied. The obtained composite nanoparticles with an interesting beads-on-a-string morphology can be obtained in a short time (10 min), which indicates the preparation method is facile and feasible. To explore the potential applications of the prepared PPy/Ag/ATP composite nanoparticles, they were served as multifunctional filler and blended with poly(butylene succinate) (PBS) matrix to prepare biodegradable composite material. The distribution of fillers in polymer matrix and the interfacial interaction between fillers and PBS were confirmed by scanning electron microscope, elemental mapping and dynamic mechanical analysis. The well dispersed fillers in PBS matrix impart outstanding antibacterial property to the biodegradable composite material as well as enhanced storage modulus due to Ag nanoparticles and ATP clay. The biodegradable composite material also possesses modest surface resistivity (10(6)~ 10(9) Ω/◻).

Directing Stem Cell Differentiation via Electrochemical Reversible Switching between Nanotubes and Nanotips of Polypyrrole Array.

PubMed

Wei, Yan; Mo, Xiaoju; Zhang, Pengchao; Li, Yingying; Liao, Jingwen; Li, Yongjun; Zhang, Jinxing; Ning, Chengyun; Wang, Shutao; Deng, Xuliang; Jiang, Lei

2017-06-27

Control of stem cell behaviors at solid biointerfaces is critical for stem-cell-based regeneration and generally achieved by engineering chemical composition, topography, and stiffness. However, the influence of dynamic stimuli at the nanoscale from solid biointerfaces on stem cell fate remains unclear. Herein, we show that electrochemical switching of a polypyrrole (Ppy) array between nanotubes and nanotips can alter surface adhesion, which can strongly influence mechanotransduction activation and guide differentiation of mesenchymal stem cells (MSCs). The Ppy array, prepared via template-free electrochemical polymerization, can be reversibly switched between highly adhesive hydrophobic nanotubes and poorly adhesive hydrophilic nanotips through an electrochemical oxidation/reduction process, resulting in dynamic attachment and detachment to MSCs at the nanoscale. Multicyclic attachment/detachment of the Ppy array to MSCs can activate intracellular mechanotransduction and osteogenic differentiation independent of surface stiffness and chemical induction. This smart surface, permitting transduction of nanoscaled dynamic physical inputs into biological outputs, provides an alternative to classical cell culture substrates for regulating stem cell fate commitment. This study represents a general strategy to explore nanoscaled interactions between stem cells and stimuli-responsive surfaces.

PPInterFinder--a mining tool for extracting causal relations on human proteins from literature.

PubMed

Raja, Kalpana; Subramani, Suresh; Natarajan, Jeyakumar

2013-01-01

One of the most common and challenging problem in biomedical text mining is to mine protein-protein interactions (PPIs) from MEDLINE abstracts and full-text research articles because PPIs play a major role in understanding the various biological processes and the impact of proteins in diseases. We implemented, PPInterFinder--a web-based text mining tool to extract human PPIs from biomedical literature. PPInterFinder uses relation keyword co-occurrences with protein names to extract information on PPIs from MEDLINE abstracts and consists of three phases. First, it identifies the relation keyword using a parser with Tregex and a relation keyword dictionary. Next, it automatically identifies the candidate PPI pairs with a set of rules related to PPI recognition. Finally, it extracts the relations by matching the sentence with a set of 11 specific patterns based on the syntactic nature of PPI pair. We find that PPInterFinder is capable of predicting PPIs with the accuracy of 66.05% on AIMED corpus and outperforms most of the existing systems. DATABASE URL: http://www.biomining-bu.in/ppinterfinder/

PPInterFinder—a mining tool for extracting causal relations on human proteins from literature

PubMed Central

Raja, Kalpana; Subramani, Suresh; Natarajan, Jeyakumar

2013-01-01

One of the most common and challenging problem in biomedical text mining is to mine protein–protein interactions (PPIs) from MEDLINE abstracts and full-text research articles because PPIs play a major role in understanding the various biological processes and the impact of proteins in diseases. We implemented, PPInterFinder—a web-based text mining tool to extract human PPIs from biomedical literature. PPInterFinder uses relation keyword co-occurrences with protein names to extract information on PPIs from MEDLINE abstracts and consists of three phases. First, it identifies the relation keyword using a parser with Tregex and a relation keyword dictionary. Next, it automatically identifies the candidate PPI pairs with a set of rules related to PPI recognition. Finally, it extracts the relations by matching the sentence with a set of 11 specific patterns based on the syntactic nature of PPI pair. We find that PPInterFinder is capable of predicting PPIs with the accuracy of 66.05% on AIMED corpus and outperforms most of the existing systems. Database URL: http://www.biomining-bu.in/ppinterfinder/ PMID:23325628

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.

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.

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.

Predicting protein complexes from weighted protein-protein interaction graphs with a novel unsupervised methodology: Evolutionary enhanced Markov clustering.

PubMed

Theofilatos, Konstantinos; Pavlopoulou, Niki; Papasavvas, Christoforos; Likothanassis, Spiros; Dimitrakopoulos, Christos; Georgopoulos, Efstratios; Moschopoulos, Charalampos; Mavroudi, Seferina

2015-03-01

Proteins are considered to be the most important individual components of biological systems and they combine to form physical protein complexes which are responsible for certain molecular functions. Despite the large availability of protein-protein interaction (PPI) information, not much information is available about protein complexes. Experimental methods are limited in terms of time, efficiency, cost and performance constraints. Existing computational methods have provided encouraging preliminary results, but they phase certain disadvantages as they require parameter tuning, some of them cannot handle weighted PPI data and others do not allow a protein to participate in more than one protein complex. In the present paper, we propose a new fully unsupervised methodology for predicting protein complexes from weighted PPI graphs. The proposed methodology is called evolutionary enhanced Markov clustering (EE-MC) and it is a hybrid combination of an adaptive evolutionary algorithm and a state-of-the-art clustering algorithm named enhanced Markov clustering. EE-MC was compared with state-of-the-art methodologies when applied to datasets from the human and the yeast Saccharomyces cerevisiae organisms. Using public available datasets, EE-MC outperformed existing methodologies (in some datasets the separation metric was increased by 10-20%). Moreover, when applied to new human datasets its performance was encouraging in the prediction of protein complexes which consist of proteins with high functional similarity. In specific, 5737 protein complexes were predicted and 72.58% of them are enriched for at least one gene ontology (GO) function term. EE-MC is by design able to overcome intrinsic limitations of existing methodologies such as their inability to handle weighted PPI networks, their constraint to assign every protein in exactly one cluster and the difficulties they face concerning the parameter tuning. This fact was experimentally validated and moreover, new potentially true human protein complexes were suggested as candidates for further validation using experimental techniques. Copyright © 2015 Elsevier B.V. All rights reserved.

Reconfiguring the AR-TIF2 Protein–Protein Interaction HCS Assay in Prostate Cancer Cells and Characterizing the Hits from a LOPAC Screen

PubMed Central

Fancher, Ashley T.; Hua, Yun; Camarco, Daniel P.; Close, David A.; Strock, Christopher J.

2016-01-01

Abstract The continued activation of androgen receptor (AR) transcription and elevated expression of AR and transcriptional intermediary factor 2 (TIF2) coactivator observed in prostate cancer (CaP) recurrence and the development of castration-resistant CaP (CRPC) support a screening strategy for small-molecule inhibitors of AR-TIF2 protein–protein interactions (PPIs) to find new drug candidates. Small molecules can elicit tissue selective effects, because the cells of distinct tissues express different levels and cohorts of coregulatory proteins. We reconfigured the AR-TIF2 PPI biosensor (PPIB) assay in the PC-3 CaP cell line to determine whether AR modulators and hits from an AR-TIF2 PPIB screen conducted in U-2 OS cells would behave differently in the CaP cell background. Although we did not observe any significant differences in the compound responses between the assay performed in osteosarcoma and CaP cells, the U-2 OS AR-TIF2 PPIB assay would be more amenable to screening, because both the virus and cell culture demands are lower. We implemented a testing paradigm of counter-screens and secondary hit characterization assays that allowed us to identify and deprioritize hits that inhibited/disrupted AR-TIF2 PPIs and AR transcriptional activation (AR-TA) through antagonism of AR ligand binding or by non-specifically blocking nuclear receptor trafficking. Since AR-TIF2 PPI inhibitor/disruptor molecules act distally to AR ligand binding, they have the potential to modulate AR-TA in a cell-specific manner that is distinct from existing anti-androgen drugs, and to overcome the development of resistance to AR antagonism. We anticipate that the application of this testing paradigm to characterize the hits from an AR-TIF2 PPI high-content screening campaign will enable us to prioritize the AR-TIF2 PPI inhibitor/disruptor leads that have potential to be developed into novel therapeutics for CaP and CRPC. PMID:27606620

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

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.

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