A Practical Method for Identifying Significant Change Scores

ERIC Educational Resources Information Center

Cascio, Wayne F.; Kurtines, William M.

1977-01-01

A test of significance for identifying individuals who are most influenced by an experimental treatment as measured by pre-post test change score is presented. The technique requires true difference scores, the reliability of obtained differences, and their standard error of measurement. (Author/JKS)

A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure.

PubMed

Sung, Yun J; Winkler, Thomas W; de Las Fuentes, Lisa; Bentley, Amy R; Brown, Michael R; Kraja, Aldi T; Schwander, Karen; Ntalla, Ioanna; Guo, Xiuqing; Franceschini, Nora; Lu, Yingchang; Cheng, Ching-Yu; Sim, Xueling; Vojinovic, Dina; Marten, Jonathan; Musani, Solomon K; Li, Changwei; Feitosa, Mary F; Kilpeläinen, Tuomas O; Richard, Melissa A; Noordam, Raymond; Aslibekyan, Stella; Aschard, Hugues; Bartz, Traci M; Dorajoo, Rajkumar; Liu, Yongmei; Manning, Alisa K; Rankinen, Tuomo; Smith, Albert Vernon; Tajuddin, Salman M; Tayo, Bamidele O; Warren, Helen R; Zhao, Wei; Zhou, Yanhua; Matoba, Nana; Sofer, Tamar; Alver, Maris; Amini, Marzyeh; Boissel, Mathilde; Chai, Jin Fang; Chen, Xu; Divers, Jasmin; Gandin, Ilaria; Gao, Chuan; Giulianini, Franco; Goel, Anuj; Harris, Sarah E; Hartwig, Fernando Pires; Horimoto, Andrea R V R; Hsu, Fang-Chi; Jackson, Anne U; Kähönen, Mika; Kasturiratne, Anuradhani; Kühnel, Brigitte; Leander, Karin; Lee, Wen-Jane; Lin, Keng-Hung; 'an Luan, Jian; McKenzie, Colin A; Meian, He; Nelson, Christopher P; Rauramaa, Rainer; Schupf, Nicole; Scott, Robert A; Sheu, Wayne H H; Stančáková, Alena; Takeuchi, Fumihiko; van der Most, Peter J; Varga, Tibor V; Wang, Heming; Wang, Yajuan; Ware, Erin B; Weiss, Stefan; Wen, Wanqing; Yanek, Lisa R; Zhang, Weihua; Zhao, Jing Hua; Afaq, Saima; Alfred, Tamuno; Amin, Najaf; Arking, Dan; Aung, Tin; Barr, R Graham; Bielak, Lawrence F; Boerwinkle, Eric; Bottinger, Erwin P; Braund, Peter S; Brody, Jennifer A; Broeckel, Ulrich; Cabrera, Claudia P; Cade, Brian; Caizheng, Yu; Campbell, Archie; Canouil, Mickaël; Chakravarti, Aravinda; Chauhan, Ganesh; Christensen, Kaare; Cocca, Massimiliano; Collins, Francis S; Connell, John M; de Mutsert, Renée; de Silva, H Janaka; Debette, Stephanie; Dörr, Marcus; Duan, Qing; Eaton, Charles B; Ehret, Georg; Evangelou, Evangelos; Faul, Jessica D; Fisher, Virginia A; Forouhi, Nita G; Franco, Oscar H; Friedlander, Yechiel; Gao, He; Gigante, Bruna; Graff, Misa; Gu, C Charles; Gu, Dongfeng; Gupta, Preeti; Hagenaars, Saskia P; Harris, Tamara B; He, Jiang; Heikkinen, Sami; Heng, Chew-Kiat; Hirata, Makoto; Hofman, Albert; Howard, Barbara V; Hunt, Steven; Irvin, Marguerite R; Jia, Yucheng; Joehanes, Roby; Justice, Anne E; Katsuya, Tomohiro; Kaufman, Joel; Kerrison, Nicola D; Khor, Chiea Chuen; Koh, Woon-Puay; Koistinen, Heikki A; Komulainen, Pirjo; Kooperberg, Charles; Krieger, Jose E; Kubo, Michiaki; Kuusisto, Johanna; Langefeld, Carl D; Langenberg, Claudia; Launer, Lenore J; Lehne, Benjamin; Lewis, Cora E; Li, Yize; Lim, Sing Hui; Lin, Shiow; Liu, Ching-Ti; Liu, Jianjun; Liu, Jingmin; Liu, Kiang; Liu, Yeheng; Loh, Marie; Lohman, Kurt K; Long, Jirong; Louie, Tin; Mägi, Reedik; Mahajan, Anubha; Meitinger, Thomas; Metspalu, Andres; Milani, Lili; Momozawa, Yukihide; Morris, Andrew P; Mosley, Thomas H; Munson, Peter; Murray, Alison D; Nalls, Mike A; Nasri, Ubaydah; Norris, Jill M; North, Kari; Ogunniyi, Adesola; Padmanabhan, Sandosh; Palmas, Walter R; Palmer, Nicholette D; Pankow, James S; Pedersen, Nancy L; Peters, Annette; Peyser, Patricia A; Polasek, Ozren; Raitakari, Olli T; Renström, Frida; Rice, Treva K; Ridker, Paul M; Robino, Antonietta; Robinson, Jennifer G; Rose, Lynda M; Rudan, Igor; Sabanayagam, Charumathi; Salako, Babatunde L; Sandow, Kevin; Schmidt, Carsten O; Schreiner, Pamela J; Scott, William R; Seshadri, Sudha; Sever, Peter; Sitlani, Colleen M; Smith, Jennifer A; Snieder, Harold; Starr, John M; Strauch, Konstantin; Tang, Hua; Taylor, Kent D; Teo, Yik Ying; Tham, Yih Chung; Uitterlinden, André G; Waldenberger, Melanie; Wang, Lihua; Wang, Ya X; Wei, Wen Bin; Williams, Christine; Wilson, Gregory; Wojczynski, Mary K; Yao, Jie; Yuan, Jian-Min; Zonderman, Alan B; Becker, Diane M; Boehnke, Michael; Bowden, Donald W; Chambers, John C; Chen, Yii-Der Ida; de Faire, Ulf; Deary, Ian J; Esko, Tõnu; Farrall, Martin; Forrester, Terrence; Franks, Paul W; Freedman, Barry I; Froguel, Philippe; Gasparini, Paolo; Gieger, Christian; Horta, Bernardo Lessa; Hung, Yi-Jen; Jonas, Jost B; Kato, Norihiro; Kooner, Jaspal S; Laakso, Markku; Lehtimäki, Terho; Liang, Kae-Woei; Magnusson, Patrik K E; Newman, Anne B; Oldehinkel, Albertine J; Pereira, Alexandre C; Redline, Susan; Rettig, Rainer; Samani, Nilesh J; Scott, James; Shu, Xiao-Ou; van der Harst, Pim; Wagenknecht, Lynne E; Wareham, Nicholas J; Watkins, Hugh; Weir, David R; Wickremasinghe, Ananda R; Wu, Tangchun; Zheng, Wei; Kamatani, Yoichiro; Laurie, Cathy C; Bouchard, Claude; Cooper, Richard S; Evans, Michele K; Gudnason, Vilmundur; Kardia, Sharon L R; Kritchevsky, Stephen B; Levy, Daniel; O'Connell, Jeff R; Psaty, Bruce M; van Dam, Rob M; Sims, Mario; Arnett, Donna K; Mook-Kanamori, Dennis O; Kelly, Tanika N; Fox, Ervin R; Hayward, Caroline; Fornage, Myriam; Rotimi, Charles N; Province, Michael A; van Duijn, Cornelia M; Tai, E Shyong; Wong, Tien Yin; Loos, Ruth J F; Reiner, Alex P; Rotter, Jerome I; Zhu, Xiaofeng; Bierut, Laura J; Gauderman, W James; Caulfield, Mark J; Elliott, Paul; Rice, Kenneth; Munroe, Patricia B; Morrison, Alanna C; Cupples, L Adrienne; Rao, Dabeeru C; Chasman, Daniel I

2018-03-01

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined ∼18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p < 5 × 10 -8 ) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p < 5 × 10 -8 ). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling (MSRA, EBF2). Copyright © 2018 American Society of Human Genetics. All rights reserved.

Semantic integration to identify overlapping functional modules in protein interaction networks

PubMed Central

Cho, Young-Rae; Hwang, Woochang; Ramanathan, Murali; Zhang, Aidong

2007-01-01

Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO) annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification. PMID:17650343

Identifying and quantifying interactions in a laboratory swarm

NASA Astrophysics Data System (ADS)

Puckett, James; Kelley, Douglas; Ouellette, Nicholas

2013-03-01

Emergent collective behavior, such as in flocks of birds or swarms of bees, is exhibited throughout the animal kingdom. Many models have been developed to describe swarming and flocking behavior using systems of self-propelled particles obeying simple rules or interacting via various potentials. However, due to experimental difficulties and constraints, little empirical data exists for characterizing the exact form of the biological interactions. We study laboratory swarms of flying Chironomus riparius midges, using stereoimaging and particle tracking techniques to record three-dimensional trajectories for all the individuals in the swarm. We describe methods to identify and quantify interactions by examining these trajectories, and report results on interaction magnitude, frequency, and mutuality.

Identifying Mother-Child Interaction Styles Using a Person-Centered Approach.

PubMed

Nelson, Jackie A; O'Brien, Marion; Grimm, Kevin J; Leerkes, Esther M

2014-05-01

Parent-child conflict in the context of a supportive relationship has been discussed as a potentially constructive interaction pattern; the current study is the first to test this using a holistic analytic approach. Interaction styles, defined as mother-child conflict in the context of maternal sensitivity, were identified and described with demographic and stress-related characteristics of families. Longitudinal associations were tested between interaction styles and children's later social competence. Participants included 814 partnered mothers with a first-grade child. Latent profile analysis identified agreeable , dynamic , and disconnected interaction styles. Mothers' intimacy with a partner, depressive symptoms, and authoritarian childrearing beliefs, along with children's later conflict with a best friend and externalizing problems, were associated with group membership. Notably, the dynamic style, characterized by high sensitivity and high conflict, included families who experienced psychological and relational stressors. Findings are discussed with regard to how family stressors shape parent-child interaction patterns.

Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges

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

Fan, Jiwen; Wang, Yuan; Rosenfeld, Daniel

2016-11-01

Over the past decade, the number of studies that investigate aerosol-cloud interactions has increased considerably. Although tremendous progress has been made to improve our understanding of basic physical mechanisms of aerosol-cloud interactions and reduce their uncertainties in climate forcing, we are still in poor understanding of (1) some of the mechanisms that interact with each other over multiple spatial and temporal scales, (2) the feedback between microphysical and dynamical processes and between local-scale processes and large-scale circulations, and (3) the significance of cloud-aerosol interactions on weather systems as well as regional and global climate. This review focuses on recent theoreticalmore » studies and important mechanisms on aerosol-cloud interactions, and discusses the significances of aerosol impacts on raditative forcing and precipitation extremes associated with different cloud systems. Despite significant understanding has been gained about aerosol impacts on the main cloud types, there are still many unknowns especially associated with various deep convective systems. Therefore, large efforts are needed to escalate our understanding. Future directions should focus on obtaining concurrent measurements of aerosol properties, cloud microphysical and dynamic properties over a range of temporal and spatial scales collected over typical climate regimes and closure studies, as well as improving understanding and parameterizations of cloud microphysics such as ice nucleation, mixed-phase properties, and hydrometeor size and fall speed« less

Identifying Mother-Child Interaction Styles Using a Person-Centered Approach

PubMed Central

Nelson, Jackie A.; O’Brien, Marion; Grimm, Kevin J.; Leerkes, Esther M.

2016-01-01

Parent-child conflict in the context of a supportive relationship has been discussed as a potentially constructive interaction pattern; the current study is the first to test this using a holistic analytic approach. Interaction styles, defined as mother-child conflict in the context of maternal sensitivity, were identified and described with demographic and stress-related characteristics of families. Longitudinal associations were tested between interaction styles and children’s later social competence. Participants included 814 partnered mothers with a first-grade child. Latent profile analysis identified agreeable, dynamic, and disconnected interaction styles. Mothers’ intimacy with a partner, depressive symptoms, and authoritarian childrearing beliefs, along with children’s later conflict with a best friend and externalizing problems, were associated with group membership. Notably, the dynamic style, characterized by high sensitivity and high conflict, included families who experienced psychological and relational stressors. Findings are discussed with regard to how family stressors shape parent-child interaction patterns. PMID:28751818

Physical and genetic-interaction density reveals functional organization and informs significance cutoffs in genome-wide screens

PubMed Central

Dittmar, John C.; Pierce, Steven; Rothstein, Rodney; Reid, Robert J. D.

2013-01-01

Genome-wide experiments often measure quantitative differences between treated and untreated cells to identify affected strains. For these studies, statistical models are typically used to determine significance cutoffs. We developed a method termed “CLIK” (Cutoff Linked to Interaction Knowledge) that overlays biological knowledge from the interactome on screen results to derive a cutoff. The method takes advantage of the fact that groups of functionally related interacting genes often respond similarly to experimental conditions and, thus, cluster in a ranked list of screen results. We applied CLIK analysis to five screens of the yeast gene disruption library and found that it defined a significance cutoff that differed from traditional statistics. Importantly, verification experiments revealed that the CLIK cutoff correlated with the position in the rank order where the rate of true positives drops off significantly. In addition, the gene sets defined by CLIK analysis often provide further biological perspectives. For example, applying CLIK analysis retrospectively to a screen for cisplatin sensitivity allowed us to identify the importance of the Hrq1 helicase in DNA crosslink repair. Furthermore, we demonstrate the utility of CLIK to determine optimal treatment conditions by analyzing genome-wide screens at multiple rapamycin concentrations. We show that CLIK is an extremely useful tool for evaluating screen quality, determining screen cutoffs, and comparing results between screens. Furthermore, because CLIK uses previously annotated interaction data to determine biologically informed cutoffs, it provides additional insights into screen results, which supplement traditional statistical approaches. PMID:23589890

Significance of Cuscutain, a cysteine protease from Cuscuta reflexa, in host-parasite interactions.

PubMed

Bleischwitz, Marc; Albert, Markus; Fuchsbauer, Hans-Lothar; Kaldenhoff, Ralf

2010-10-22

Plant infestation with parasitic weeds like Cuscuta reflexa induces morphological as well as biochemical changes in the host and the parasite. These modifications could be caused by a change in protein or gene activity. Using a comparative macroarray approach Cuscuta genes specifically upregulated at the host attachment site were identified. One of the infestation specific Cuscuta genes encodes a cysteine protease. The protein and its intrinsic inhibitory peptide were heterologously expressed, purified and biochemically characterized. The haustoria specific enzyme was named cuscutain in accordance with similar proteins from other plants, e.g. papaya. The role of cuscutain and its inhibitor during the host parasite interaction was studied by external application of an inhibitor suspension, which induced a significant reduction of successful infection events. The study provides new information about molecular events during the parasitic plant--host interaction. Inhibition of cuscutain cysteine proteinase could provide means for antagonizing parasitic plants.

Robust and Comprehensive Analysis of 20 Osteoporosis Candidate Genes by Very High-Density Single-Nucleotide Polymorphism Screen Among 405 White Nuclear Families Identified Significant Association and Gene–Gene Interaction

PubMed Central

Xiong, Dong-Hai; Shen, Hui; Zhao, Lan-Juan; Xiao, Peng; Yang, Tie-Lin; Guo, Yan; Wang, Wei; Guo, Yan-Fang; Liu, Yong-Jun; Recker, Robert R; Deng, Hong-Wen

2007-01-01

Many “novel” osteoporosis candidate genes have been proposed in recent years. To advance our knowledge of their roles in osteoporosis, we screened 20 such genes using a set of high-density SNPs in a large family-based study. Our efforts led to the prioritization of those osteoporosis genes and the detection of gene–gene interactions. Introduction We performed large-scale family-based association analyses of 20 novel osteoporosis candidate genes using 277 single nucleotide polymorphisms (SNPs) for the quantitative trait BMD variation and the qualitative trait osteoporosis (OP) at three clinically important skeletal sites: spine, hip, and ultradistal radius (UD). Materials and Methods One thousand eight hundred seventy-three subjects from 405 white nuclear families were genotyped and analyzed with an average density of one SNP per 4 kb across the 20 genes. We conducted association analyses by SNP- and haplotype-based family-based association test (FBAT) and performed gene–gene interaction analyses using multianalytic approaches such as multifactor-dimensionality reduction (MDR) and conditional logistic regression. Results and Conclusions We detected four genes (DBP, LRP5, CYP17, and RANK) that showed highly suggestive associations (10,000-permutation derived empirical global p ≤ 0.01) with spine BMD/OP; four genes (CYP19, RANK, RANKL, and CYP17) highly suggestive for hip BMD/OP; and four genes (CYP19, BMP2, RANK, and TNFR2) highly suggestive for UD BMD/OP. The associations between BMP2 with UD BMD and those between RANK with OP at the spine, hip, and UD also met the experiment-wide stringent criterion (empirical global p ≤ 0.0007). Sex-stratified analyses further showed that some of the significant associations in the total sample were driven by either male or female subjects. In addition, we identified and validated a two-locus gene–gene interaction model involving GCR and ESR2, for which prior biological evidence exists. Our results suggested the

Genome-wide approach identifies a novel gene-maternal pre-pregnancy BMI interaction on preterm birth

PubMed Central

Hong, Xiumei; Hao, Ke; Ji, Hongkai; Peng, Shouneng; Sherwood, Ben; Di Narzo, Antonio; Tsai, Hui-Ju; Liu, Xin; Burd, Irina; Wang, Guoying; Ji, Yuelong; Caruso, Deanna; Mao, Guangyun; Bartell, Tami R.; Zhang, Zhongyang; Pearson, Colleen; Heffner, Linda; Cerda, Sandra; Beaty, Terri H.; Fallin, M. Daniele; Lee-Parritz, Aviva; Zuckerman, Barry; Weeks, Daniel E.; Wang, Xiaobin

2017-01-01

Preterm birth (PTB) contributes significantly to infant mortality and morbidity with lifelong impact. Few robust genetic factors of PTB have been identified. Such ‘missing heritability' may be partly due to gene × environment interactions (G × E), which is largely unexplored. Here we conduct genome-wide G × E analyses of PTB in 1,733 African-American women (698 mothers of PTB; 1,035 of term birth) from the Boston Birth Cohort. We show that maternal COL24A1 variants have a significant genome-wide interaction with maternal pre-pregnancy overweight/obesity on PTB risk, with rs11161721 (PG × E=1.8 × 10−8; empirical PG × E=1.2 × 10−8) as the top hit. This interaction is replicated in African-American mothers (PG × E=0.01) from an independent cohort and in meta-analysis (PG × E=3.6 × 10−9), but is not replicated in Caucasians. In adipose tissue, rs11161721 is significantly associated with altered COL24A1 expression. Our findings may provide new insight into the aetiology of PTB and improve our ability to predict and prevent PTB. PMID:28598419

Significance of Cuscutain, a cysteine protease from Cuscuta reflexa, in host-parasite interactions

PubMed Central

2010-01-01

Background Plant infestation with parasitic weeds like Cuscuta reflexa induces morphological as well as biochemical changes in the host and the parasite. These modifications could be caused by a change in protein or gene activity. Using a comparative macroarray approach Cuscuta genes specifically upregulated at the host attachment site were identified. Results One of the infestation specific Cuscuta genes encodes a cysteine protease. The protein and its intrinsic inhibitory peptide were heterologously expressed, purified and biochemically characterized. The haustoria specific enzyme was named cuscutain in accordance with similar proteins from other plants, e.g. papaya. The role of cuscutain and its inhibitor during the host parasite interaction was studied by external application of an inhibitor suspension, which induced a significant reduction of successful infection events. Conclusions The study provides new information about molecular events during the parasitic plant - host interaction. Inhibition of cuscutain cysteine proteinase could provide means for antagonizing parasitic plants. PMID:20964874

Identifying Measures of Student Behavior from Interaction with a Course Management System

ERIC Educational Resources Information Center

Nickles, George M., III

2006-01-01

The purpose of this work is to identify process measures of student interaction with a course management system (CMS). Logs maintained by Web servers capture aggregate user interactions with a Website. When combined with a login system and context from the course recorded in the CMS, more detailed measures of individual student interaction can be…

GOTHiC, a probabilistic model to resolve complex biases and to identify real interactions in Hi-C data.

PubMed

Mifsud, Borbala; Martincorena, Inigo; Darbo, Elodie; Sugar, Robert; Schoenfelder, Stefan; Fraser, Peter; Luscombe, Nicholas M

2017-01-01

Hi-C is one of the main methods for investigating spatial co-localisation of DNA in the nucleus. However, the raw sequencing data obtained from Hi-C experiments suffer from large biases and spurious contacts, making it difficult to identify true interactions. Existing methods use complex models to account for biases and do not provide a significance threshold for detecting interactions. Here we introduce a simple binomial probabilistic model that resolves complex biases and distinguishes between true and false interactions. The model corrects biases of known and unknown origin and yields a p-value for each interaction, providing a reliable threshold based on significance. We demonstrate this experimentally by testing the method against a random ligation dataset. Our method outperforms previous methods and provides a statistical framework for further data analysis, such as comparisons of Hi-C interactions between different conditions. GOTHiC is available as a BioConductor package (http://www.bioconductor.org/packages/release/bioc/html/GOTHiC.html).

Efficiently Identifying Significant Associations in Genome-wide Association Studies

PubMed Central

Eskin, Eleazar

2013-01-01

Abstract Over the past several years, genome-wide association studies (GWAS) have implicated hundreds of genes in common disease. More recently, the GWAS approach has been utilized to identify regions of the genome that harbor variation affecting gene expression or expression quantitative trait loci (eQTLs). Unlike GWAS applied to clinical traits, where only a handful of phenotypes are analyzed per study, in eQTL studies, tens of thousands of gene expression levels are measured, and the GWAS approach is applied to each gene expression level. This leads to computing billions of statistical tests and requires substantial computational resources, particularly when applying novel statistical methods such as mixed models. We introduce a novel two-stage testing procedure that identifies all of the significant associations more efficiently than testing all the single nucleotide polymorphisms (SNPs). In the first stage, a small number of informative SNPs, or proxies, across the genome are tested. Based on their observed associations, our approach locates the regions that may contain significant SNPs and only tests additional SNPs from those regions. We show through simulations and analysis of real GWAS datasets that the proposed two-stage procedure increases the computational speed by a factor of 10. Additionally, efficient implementation of our software increases the computational speed relative to the state-of-the-art testing approaches by a factor of 75. PMID:24033261

Automated Analysis of Fluorescence Microscopy Images to Identify Protein-Protein Interactions

DOE PAGES

Venkatraman, S.; Doktycz, M. J.; Qi, H.; ...

2006-01-01

The identification of protein interactions is important for elucidating biological networks. One obstacle in comprehensive interaction studies is the analyses of large datasets, particularly those containing images. Development of an automated system to analyze an image-based protein interaction dataset is needed. Such an analysis system is described here, to automatically extract features from fluorescence microscopy images obtained from a bacterial protein interaction assay. These features are used to relay quantitative values that aid in the automated scoring of positive interactions. Experimental observations indicate that identifying at least 50% positive cells in an image is sufficient to detect a protein interaction.more » Based on this criterion, the automated system presents 100% accuracy in detecting positive interactions for a dataset of 16 images. Algorithms were implemented using MATLAB and the software developed is available on request from the authors.« less

Interactions between the Nse3 and Nse4 Components of the SMC5-6 Complex Identify Evolutionarily Conserved Interactions between MAGE and EID Families

PubMed Central

Kozakova, Lucie; Liao, Chunyan; Guerineau, Marc; Colnaghi, Rita; Vidot, Susanne; Marek, Jaromir; Bathula, Sreenivas R.; Lehmann, Alan R.; Palecek, Jan

2011-01-01

Background The SMC5-6 protein complex is involved in the cellular response to DNA damage. It is composed of 6–8 polypeptides, of which Nse1, Nse3 and Nse4 form a tight sub-complex. MAGEG1, the mammalian ortholog of Nse3, is the founding member of the MAGE (melanoma-associated antigen) protein family and Nse4 is related to the EID (E1A-like inhibitor of differentiation) family of transcriptional repressors. Methodology/Principal Findings Using site-directed mutagenesis, protein-protein interaction analyses and molecular modelling, we have identified a conserved hydrophobic surface on the C-terminal domain of Nse3 that interacts with Nse4 and identified residues in its N-terminal domain that are essential for interaction with Nse1. We show that these interactions are conserved in the human orthologs. Furthermore, interaction of MAGEG1, the mammalian ortholog of Nse3, with NSE4b, one of the mammalian orthologs of Nse4, results in transcriptional co-activation of the nuclear receptor, steroidogenic factor 1 (SF1). In an examination of the evolutionary conservation of the Nse3-Nse4 interactions, we find that several MAGE proteins can interact with at least one of the NSE4/EID proteins. Conclusions/Significance We have found that, despite the evolutionary diversification of the MAGE family, the characteristic hydrophobic surface shared by all MAGE proteins from yeast to humans mediates its binding to NSE4/EID proteins. Our work provides new insights into the interactions, evolution and functions of the enigmatic MAGE proteins. PMID:21364888

CLINICALLY SIGNIFICANT PSYCHOTROPIC DRUG-DRUG INTERACTIONS IN THE PRIMARY CARE SETTING

PubMed Central

English, Brett A.; Dortch, Marcus; Ereshefsky, Larry; Jhee, Stanford

2014-01-01

In recent years, the growing numbers of patients seeking care for a wide range of psychiatric illnesses in the primary care setting has resulted in an increase in the number of psychotropic medications prescribed. Along with the increased utilization of psychotropic medications, considerable variability is noted in the prescribing patterns of primary care providers and psychiatrists. Because psychiatric patients also suffer from a number of additional medical comorbidities, the increased utilization of psychotropic medications presents an elevated risk of clinically significant drug interactions in these patients. While life-threatening drug interactions are rare, clinically significant drug interactions impacting drug response or appearance of serious adverse drug reactions have been documented and can impact long-term outcomes. Additionally, the impact of genetic variability on the psychotropic drug’s pharmacodynamics and/or pharmacokinetics may further complicate drug therapy. Increased awareness of clinically relevant psychotropic drug interactions can aid clinicians to achieve optimal therapeutic outcomes in patients in the primary care setting. PMID:22707017

Mapping of Chikungunya Virus Interactions with Host Proteins Identified nsP2 as a Highly Connected Viral Component

PubMed Central

Bouraï, Mehdi; Lucas-Hourani, Marianne; Gad, Hans Henrik; Drosten, Christian; Jacob, Yves; Tafforeau, Lionel; Cassonnet, Patricia; Jones, Louis M.; Judith, Delphine; Couderc, Thérèse; Lecuit, Marc; André, Patrice; Kümmerer, Beate Mareike; Lotteau, Vincent; Desprès, Philippe; Vidalain, Pierre-Olivier

2012-01-01

Chikungunya virus (CHIKV) is a mosquito-transmitted alphavirus that has been responsible for an epidemic outbreak of unprecedented magnitude in recent years. Since then, significant efforts have been made to better understand the biology of this virus, but we still have poor knowledge of CHIKV interactions with host cell components at the molecular level. Here we describe the extensive use of high-throughput yeast two-hybrid (HT-Y2H) assays to characterize interactions between CHIKV and human proteins. A total of 22 high-confidence interactions, which essentially involved the viral nonstructural protein nsP2, were identified and further validated in protein complementation assay (PCA). These results were integrated to a larger network obtained by extensive mining of the literature for reports on alphavirus-host interactions. To investigate the role of cellular proteins interacting with nsP2, gene silencing experiments were performed in cells infected by a recombinant CHIKV expressing Renilla luciferase as a reporter. Collected data showed that heterogeneous nuclear ribonucleoprotein K (hnRNP-K) and ubiquilin 4 (UBQLN4) participate in CHIKV replication in vitro. In addition, we showed that CHIKV nsP2 induces a cellular shutoff, as previously reported for other Old World alphaviruses, and determined that among binding partners identified by yeast two-hybrid methods, the tetratricopeptide repeat protein 7B (TTC7B) plays a significant role in this activity. Altogether, this report provides the first interaction map between CHIKV and human proteins and describes new host cell proteins involved in the replication cycle of this virus. PMID:22258240

Clinically significant drug-drug interactions involving opioid analgesics used for pain treatment in patients with cancer: a systematic review.

PubMed

Kotlinska-Lemieszek, Aleksandra; Klepstad, Pål; Haugen, Dagny Faksvåg

2015-01-01

Opioids are the most frequently used drugs to treat pain in cancer patients. In some patients, however, opioids can cause adverse effects and drug-drug interactions. No advice concerning the combination of opioids and other drugs is given in the current European guidelines. To identify studies that report clinically significant drug-drug interactions involving opioids used for pain treatment in adult cancer patients. Systematic review with searches in Embase, MEDLINE, and Cochrane Central Register of Controlled Trials from the start of the databases (Embase from 1980) through January 2014. In addition, reference lists of relevant full-text papers were hand-searched. Of 901 retrieved papers, 112 were considered as potentially eligible. After full-text reading, 17 were included in the final analysis, together with 15 papers identified through hand-searching of reference lists. All of the 32 included publications were case reports or case series. Clinical manifestations of drug-drug interactions involving opioids were grouped as follows: 1) sedation and respiratory depression, 2) other central nervous system symptoms, 3) impairment of pain control and/or opioid withdrawal, and 4) other symptoms. The most common mechanisms eliciting drug-drug interactions were alteration of opioid metabolism by inhibiting the activity of cytochrome P450 3A4 and pharmacodynamic interactions due to the combined effect on opioid, dopaminergic, cholinergic, and serotonergic activity in the central nervous system. Evidence for drug-drug interactions associated with opioids used for pain treatment in cancer patients is very limited. Still, the cases identified in this systematic review give some important suggestions for clinical practice. Physicians prescribing opioids should recognize the risk of drug-drug interactions and if possible avoid polypharmacy.

Identifying high risk medications causing potential drug-drug interactions in outpatients: A prescription database study based on an online surveillance system.

PubMed

Toivo, T M; Mikkola, J A V; Laine, K; Airaksinen, M

2016-01-01

Drug-drug interactions (DDIs) are a significant cause for adverse drug events (ADEs). DDIs are often predictable and preventable, but their prevention and management require systematic service development. Most DDI studies focus on interaction rates in hospitalized patients. Less is known of DDIs in outpatients, particularly how community pharmacists could contribute to DDI management by applying their surveillance systems for identifying high-risk medications. The study was related to the implementation of the first online DDI surveillance system in Finnish community pharmacies. The goal was to demonstrate how community pharmacies can utilize their prospective surveillance system 1) for identifying high risk medications causing potential DDIs in outpatients, 2) for collaborative service development with local physicians, and 3) for academic risk management research purposes. All DDI alerts given by the online surveillance system were collected during a one-month period in 16 out of 17 University Pharmacy outlets in Finland, covering approximately 10% of the national outpatient prescription volume. The surveillance system was based on the FASS database, which categorizes DDIs into four classes (A-D) according to their clinical significance. Potential drug-drug DDIs were analyzed for 276,891 dispensed community pharmacy prescriptions. Potential DDIs were associated with 10.8%, or 31,110 of these prescriptions. Clinically significant interaction alerts categorized as FASS classes D (most severe, should be avoided) and C (clinically significant but controllable) were associated with 0.5% and 7.0% of the prescriptions, respectively. Methotrexate and warfarin had the highest risk of causing potentially serious (class D) interactions. These interaction alerts were most frequently between methotrexate and NSAIDs and warfarin and NSAIDs. In general, NSAIDs were the most commonly interacting drugs in this study. This study demonstrates that community pharmacies can actively

A lanthipeptide library used to identify a protein-protein interaction inhibitor.

PubMed

Yang, Xiao; Lennard, Katherine R; He, Chang; Walker, Mark C; Ball, Andrew T; Doigneaux, Cyrielle; Tavassoli, Ali; van der Donk, Wilfred A

2018-04-01

In this article we describe the production and screening of a genetically encoded library of 10 6 lanthipeptides in Escherichia coli using the substrate-tolerant lanthipeptide synthetase ProcM. This plasmid-encoded library was combined with a bacterial reverse two-hybrid system for the interaction of the HIV p6 protein with the UEV domain of the human TSG101 protein, which is a critical protein-protein interaction for HIV budding from infected cells. Using this approach, we identified an inhibitor of this interaction from the lanthipeptide library, whose activity was verified in vitro and in cell-based virus-like particle-budding assays. Given the variety of lanthipeptide backbone scaffolds that may be produced with ProcM, this method may be used for the generation of genetically encoded libraries of natural product-like lanthipeptides containing substantial structural diversity. Such libraries may be combined with any cell-based assay to identify lanthipeptides with new biological activities.

Significance of Interactions of Low Molecular Weight Crystallin Fragments in Lens Aging and Cataract Formation*

PubMed Central

Santhoshkumar, Puttur; Udupa, Padmanabha; Murugesan, Raju; Sharma, K. Krishna

2008-01-01

Analysis of aged and cataract lenses shows the presence of increased amounts of crystallin fragments in the high molecular weight aggregates of water-soluble and water-insoluble fractions. However, the significance of accumulation and interaction of low molecular weight crystallin fragments in aging and cataract development is not clearly understood. In this study, 23 low molecular mass (<3.5-kDa) peptides in the urea-soluble fractions of young, aged, and aged cataract human lenses were identified by mass spectroscopy. Two peptides, αB-(1–18) (MDIAIHHPWIRRPFFPFH) and βA3/A1-(59–74) (SD(N)AYHIERLMSFRPIC), present in aged and cataract lens but not young lens, and a third peptide, γS-(167–178) (SPAVQSFRRIVE) present in all three lens groups were synthesized to study the effects of interaction of these peptides with intact α-, β-, and γ-crystallins and alcohol dehydrogenase, a protein used in aggregation studies. Interaction of αB-(1–18) and βA3/A1-(59–74) peptides increased the scattering of light by β- and γ-crystallin and alcohol dehydrogenase. The ability of α-crystallin subunits to function as molecular chaperones was significantly reduced by interaction with αB-(1–18) and βA3/A1-(59–74) peptides, whereas γS peptide had no effect on chaperone-like activity of α-crystallin. The βA3/A1-(59–74 peptide caused a 5.64-fold increase in αB-crystallin oligomeric mass and partial precipitation. Replacing hydrophobic residues in αB-(1–18) and βA3/A1-(59–74) peptides abolished their ability to induce crystallin aggregation and light scattering. Our study suggests that interaction of crystallin-derived peptides with intact crystallins could be a key event in age-related protein aggregation in lens and cataractogenesis. PMID:18227073

Knowledge-Driven Analysis Identifies a Gene–Gene Interaction Affecting High-Density Lipoprotein Cholesterol Levels in Multi-Ethnic Populations

PubMed Central

Ma, Li; Brautbar, Ariel; Boerwinkle, Eric; Sing, Charles F.

2012-01-01

Total cholesterol, low-density lipoprotein cholesterol, triglyceride, and high-density lipoprotein cholesterol (HDL-C) levels are among the most important risk factors for coronary artery disease. We tested for gene–gene interactions affecting the level of these four lipids based on prior knowledge of established genome-wide association study (GWAS) hits, protein–protein interactions, and pathway information. Using genotype data from 9,713 European Americans from the Atherosclerosis Risk in Communities (ARIC) study, we identified an interaction between HMGCR and a locus near LIPC in their effect on HDL-C levels (Bonferroni corrected P c = 0.002). Using an adaptive locus-based validation procedure, we successfully validated this gene–gene interaction in the European American cohorts from the Framingham Heart Study (P c = 0.002) and the Multi-Ethnic Study of Atherosclerosis (MESA; P c = 0.006). The interaction between these two loci is also significant in the African American sample from ARIC (P c = 0.004) and in the Hispanic American sample from MESA (P c = 0.04). Both HMGCR and LIPC are involved in the metabolism of lipids, and genome-wide association studies have previously identified LIPC as associated with levels of HDL-C. However, the effect on HDL-C of the novel gene–gene interaction reported here is twice as pronounced as that predicted by the sum of the marginal effects of the two loci. In conclusion, based on a knowledge-driven analysis of epistasis, together with a new locus-based validation method, we successfully identified and validated an interaction affecting a complex trait in multi-ethnic populations. PMID:22654671

Busulfan and metronidazole: an often forgotten but significant drug interaction.

PubMed

Gulbis, Alison M; Culotta, Kirk S; Jones, Roy B; Andersson, Borje S

2011-07-01

To report the case of a clinically significant drug interaction between intravenous busulfan and oral metronidazole observed through busulfan therapeutic drug monitoring (TDM). A 7-year-old boy with a history of myelodysplasia that progressed to acute myeloid leukemia received busulfan with therapeutic drug monitoring (TDM), clofarabine, and thiotepa as a pretransplant conditioning regimen for a cord blood transplant. The patient received metronidazole the day after a busulfan test dose of 0.5 mg/kg was administered. On the day of the first busulfan therapeutic dose, TDM was performed and the clearance of busulfan was significantly decreased by 46%. After 2 doses of busulfan therapy, the course area under the curve was exceeded, requiring discontinuation of busulfan. Metronidazole is not known to affect glutathione or the glutathione S-transferase A1 (GSTA1) enzyme system or cytochrome P450 (CYP) 3A4. Busulfan is a bifunctional alkylating agent widely used in pretransplant conditioning regimens in patients undergoing stem cell transplantation for hematologic malignancies. Busulfan metabolism is best described by hepatic conjugation to glutathione by GSTA1, although some CYP-dependent pathways have been described. Currently there is 1 publication describing the drug interaction between oral busulfan and oral metronidazole, in which concomitant use of metronidazole resulted in higher busulfan trough concentrations and higher risk of veno-occlusive disease. Our case represents a possible drug interaction based on the Horn Drug Interaction Probability Scale. Though the mechanistic basis for this interaction is unknown, the risks and benefits of using metronidazole during and in close proximity to busulfan should be carefully considered and therapeutic alternatives to metronidazole should be used when appropriate.

Significant Deregulated Pathways in Diabetes Type II Complications Identified through Expression Based Network Biology

NASA Astrophysics Data System (ADS)

Ukil, Sanchaita; Sinha, Meenakshee; Varshney, Lavneesh; Agrawal, Shipra

Type 2 Diabetes is a complex multifactorial disease, which alters several signaling cascades giving rise to serious complications. It is one of the major risk factors for cardiovascular diseases. The present research work describes an integrated functional network biology approach to identify pathways that get transcriptionally altered and lead to complex complications thereby amplifying the phenotypic effect of the impaired disease state. We have identified two sub-network modules, which could be activated under abnormal circumstances in diabetes. Present work describes key proteins such as P85A and SRC serving as important nodes to mediate alternate signaling routes during diseased condition. P85A has been shown to be an important link between stress responsive MAPK and CVD markers involved in fibrosis. MAPK8 has been shown to interact with P85A and further activate CTGF through VEGF signaling. We have traced a novel and unique route correlating inflammation and fibrosis by considering P85A as a key mediator of signals. The next sub-network module shows SRC as a junction for various signaling processes, which results in interaction between NF-kB and beta catenin to cause cell death. The powerful interaction between these important genes in response to transcriptionally altered lipid metabolism and impaired inflammatory response via SRC causes apoptosis of cells. The crosstalk between inflammation, lipid homeostasis and stress, and their serious effects downstream have been explained in the present analyses.

Interactive cervical motion kinematics: sensitivity, specificity and clinically significant values for identifying kinematic impairments in patients with chronic neck pain.

PubMed

Sarig Bahat, Hilla; Chen, Xiaoqi; Reznik, David; Kodesh, Einat; Treleaven, Julia

2015-04-01

Chronic neck pain has been consistently shown to be associated with impaired kinematic control including reduced range, velocity and smoothness of cervical motion, that seem relevant to daily function as in quick neck motion in response to surrounding stimuli. The objectives of this study were: to compare interactive cervical kinematics in patients with neck pain and controls; to explore the new measures of cervical motion accuracy; and to find the sensitivity, specificity, and optimal cutoff values for defining impaired kinematics in those with neck pain. In this cross-section study, 33 patients with chronic neck pain and 22 asymptomatic controls were assessed for their cervical kinematic control using interactive virtual reality hardware and customized software utilizing a head mounted display with built-in head tracking. Outcome measures included peak and mean velocity, smoothness (represented by number of velocity peaks (NVP)), symmetry (represented by time to peak velocity percentage (TTPP)), and accuracy of cervical motion. Results demonstrated significant and strong effect-size differences in peak and mean velocities, NVP and TTPP in all directions excluding TTPP in left rotation, and good effect-size group differences in 5/8 accuracy measures. Regression results emphasized the high clinical value of neck motion velocity, with very high sensitivity and specificity (85%-100%), followed by motion smoothness, symmetry and accuracy. These finding suggest cervical kinematics should be evaluated clinically, and screened by the provided cut off values for identification of relevant impairments in those with neck pain. Such identification of presence or absence of kinematic impairments may direct treatment strategies and additional evaluation when needed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Biomedical Informatics Approaches to Identifying Drug-Drug Interactions: Application to Insulin Secretagogues

PubMed Central

Han, Xu; Chiang, ChienWei; Leonard, Charles E.; Bilker, Warren B.; Brensinger, Colleen M.; Li, Lang; Hennessy, Sean

2017-01-01

Background Drug-drug interactions with insulin secretagogues are associated with increased risk of serious hypoglycemia in patients with type 2 diabetes. We aimed to systematically screen for drugs that interact with the five most commonly used secretagogues―glipizide, glyburide, glimepiride, repaglinide, and nateglinide―to cause serious hypoglycemia. Methods We screened 400 drugs frequently co-prescribed with the secretagogues as candidate interacting precipitants. We first predicted the drug–drug interaction potential based on the pharmacokinetics of each secretagogue–precipitant pair. We then performed pharmacoepidemiologic screening for each secretagogue of interest, and for metformin as a negative control, using an administrative claims database and the self-controlled case series design. The overall rate ratios (RRs) and those for four predefined risk periods were estimated using Poisson regression. The RRs were adjusted for multiple estimation using semi-Bayes method, and then adjusted for metformin results to distinguish native effects of the precipitant from a drug–drug interaction. Results We predicted 34 pharmacokinetic drug–drug interactions with the secretagogues, nine moderate and 25 weak. There were 140 and 61 secretagogue–precipitant pairs associated with increased rates of serious hypoglycemia before and after the metformin adjustment, respectively. The results from pharmacokinetic prediction correlated poorly with those from pharmacoepidemiologic screening. Conclusions The self-controlled case series design has the potential to be widely applicable to screening for drug–drug interactions that lead to adverse outcomes identifiable in healthcare databases. Coupling pharmacokinetic prediction with pharmacoepidemiologic screening did not notably improve the ability to identify drug–drug interactions in this case. PMID:28169935

Promoter-enhancer interactions identified from Hi-C data using probabilistic models and hierarchical topological domains.

PubMed

Ron, Gil; Globerson, Yuval; Moran, Dror; Kaplan, Tommy

2017-12-21

Proximity-ligation methods such as Hi-C allow us to map physical DNA-DNA interactions along the genome, and reveal its organization into topologically associating domains (TADs). As the Hi-C data accumulate, computational methods were developed for identifying domain borders in multiple cell types and organisms. Here, we present PSYCHIC, a computational approach for analyzing Hi-C data and identifying promoter-enhancer interactions. We use a unified probabilistic model to segment the genome into domains, which we then merge hierarchically and fit using a local background model, allowing us to identify over-represented DNA-DNA interactions across the genome. By analyzing the published Hi-C data sets in human and mouse, we identify hundreds of thousands of putative enhancers and their target genes, and compile an extensive genome-wide catalog of gene regulation in human and mouse. As we show, our predictions are highly enriched for ChIP-seq and DNA accessibility data, evolutionary conservation, eQTLs and other DNA-DNA interaction data.

Identifying Drug-Drug Interactions by Data Mining: A Pilot Study of Warfarin-Associated Drug Interactions.

PubMed

Hansen, Peter Wæde; Clemmensen, Line; Sehested, Thomas S G; Fosbøl, Emil Loldrup; Torp-Pedersen, Christian; Køber, Lars; Gislason, Gunnar H; Andersson, Charlotte

2016-11-01

Knowledge about drug-drug interactions commonly arises from preclinical trials, from adverse drug reports, or based on knowledge of mechanisms of action. Our aim was to investigate whether drug-drug interactions were discoverable without prior hypotheses using data mining. We focused on warfarin-drug interactions as the prototype. We analyzed altered prothrombin time (measured as international normalized ratio [INR]) after initiation of a novel prescription in previously INR-stable warfarin-treated patients with nonvalvular atrial fibrillation. Data sets were retrieved from clinical work. Random forest (a machine-learning method) was set up to predict altered INR levels after novel prescriptions. The most important drug groups from the analysis were further investigated using logistic regression in a new data set. Two hundred and twenty drug groups were analyzed in 61 190 novel prescriptions. We rediscovered 2 drug groups having known interactions (β-lactamase-resistant penicillins [dicloxacillin] and carboxamide derivatives) and 3 antithrombotic/anticoagulant agents (platelet aggregation inhibitors excluding heparin, direct thrombin inhibitors [dabigatran etexilate], and heparins) causing decreasing INR. Six drug groups with known interactions were rediscovered causing increasing INR (antiarrhythmics class III [amiodarone], other opioids [tramadol], glucocorticoids, triazole derivatives, and combinations of penicillins, including β-lactamase inhibitors) and two had a known interaction in a closely related drug group (oripavine derivatives [buprenorphine] and natural opium alkaloids). Antipropulsives had an unknown signal of increasing INR. We were able to identify known warfarin-drug interactions without a prior hypothesis using clinical registries. Additionally, we discovered a few potentially novel interactions. This opens up for the use of data mining to discover unknown drug-drug interactions in cardiovascular medicine. © 2016 American Heart Association

A Modified Delphi to Identify the Significant Works Pertaining to the Understanding of Reading Comprehension and Content Analysis of the Identified Works

ERIC Educational Resources Information Center

Zunker, Norma D.; Pearce, Daniel L.

2012-01-01

The first part of this study explored the significant works pertaining to the understanding of reading comprehension using a Modified Delphi Method. A panel of reading comprehension experts identified 19 works they considered to be significant to the understanding of reading comprehension. The panel of experts identified the reasons they…

Identifying and modeling the structural discontinuities of human interactions

NASA Astrophysics Data System (ADS)

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-04-01

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales.

Identifying and modeling the structural discontinuities of human interactions

PubMed Central

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-01-01

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales. PMID:28443647

Identifying and modeling the structural discontinuities of human interactions.

PubMed

Grauwin, Sebastian; Szell, Michael; Sobolevsky, Stanislav; Hövel, Philipp; Simini, Filippo; Vanhoof, Maarten; Smoreda, Zbigniew; Barabási, Albert-László; Ratti, Carlo

2017-04-26

The idea of a hierarchical spatial organization of society lies at the core of seminal theories in human geography that have strongly influenced our understanding of social organization. Along the same line, the recent availability of large-scale human mobility and communication data has offered novel quantitative insights hinting at a strong geographical confinement of human interactions within neighboring regions, extending to local levels within countries. However, models of human interaction largely ignore this effect. Here, we analyze several country-wide networks of telephone calls - both, mobile and landline - and in either case uncover a systematic decrease of communication induced by borders which we identify as the missing variable in state-of-the-art models. Using this empirical evidence, we propose an alternative modeling framework that naturally stylizes the damping effect of borders. We show that this new notion substantially improves the predictive power of widely used interaction models. This increases our ability to understand, model and predict social activities and to plan the development of infrastructures across multiple scales.

Empirical Methods for Identifying Specific Peptide-protein Interactions for Smart Reagent Development

DTIC Science & Technology

2012-09-01

orientated immobilization of proteins,” Biotechnology Progress, 22(2), 401-405 ( 2006 ). [26] J. M. Kogot, D. A. Sarkes , I. Val-Addo et al...Empirical Methods for Identifying Specific Peptide-protein Interactions for Smart Reagent Development by Joshua M. Kogot, Deborah A. Sarkes ...Peptide-protein Interactions for Smart Reagent Development Joshua M. Kogot, Deborah A. Sarkes , Dimitra N. Stratis-Cullum, and Paul M

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/.

Genome wide approaches to identify protein-DNA interactions.

PubMed

Ma, Tao; Ye, Zhenqing; Wang, Liguo

2018-05-29

Transcription factors are DNA-binding proteins that play key roles in many fundamental biological processes. Unraveling their interactions with DNA is essential to identify their target genes and understand the regulatory network. Genome-wide identification of their binding sites became feasible thanks to recent progress in experimental and computational approaches. ChIP-chip, ChIP-seq, and ChIP-exo are three widely used techniques to demarcate genome-wide transcription factor binding sites. This review aims to provide an overview of these three techniques including their experiment procedures, computational approaches, and popular analytic tools. ChIP-chip, ChIP-seq, and ChIP-exo have been the major techniques to study genome-wide in vivo protein-DNA interaction. Due to the rapid development of next-generation sequencing technology, array-based ChIP-chip is deprecated and ChIP-seq has become the most widely used technique to identify transcription factor binding sites in genome-wide. The newly developed ChIP-exo further improves the spatial resolution to single nucleotide. Numerous tools have been developed to analyze ChIP-chip, ChIP-seq and ChIP-exo data. However, different programs may employ different mechanisms or underlying algorithms thus each will inherently include its own set of statistical assumption and bias. So choosing the most appropriate analytic program for a given experiment needs careful considerations. Moreover, most programs only have command line interface so their installation and usage will require basic computation expertise in Unix/Linux. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Active Learning with Rationales for Identifying Operationally Significant Anomalies in Aviation

NASA Technical Reports Server (NTRS)

Sharma, Manali; Das, Kamalika; Bilgic, Mustafa; Matthews, Bryan; Nielsen, David Lynn; Oza, Nikunj C.

2016-01-01

A major focus of the commercial aviation community is discovery of unknown safety events in flight operations data. Data-driven unsupervised anomaly detection methods are better at capturing unknown safety events compared to rule-based methods which only look for known violations. However, not all statistical anomalies that are discovered by these unsupervised anomaly detection methods are operationally significant (e.g., represent a safety concern). Subject Matter Experts (SMEs) have to spend significant time reviewing these statistical anomalies individually to identify a few operationally significant ones. In this paper we propose an active learning algorithm that incorporates SME feedback in the form of rationales to build a classifier that can distinguish between uninteresting and operationally significant anomalies. Experimental evaluation on real aviation data shows that our approach improves detection of operationally significant events by as much as 75% compared to the state-of-the-art. The learnt classifier also generalizes well to additional validation data sets.

A Statistical Method of Identifying Interactions in Neuron–Glia Systems Based on Functional Multicell Ca2+ Imaging

PubMed Central

Nakae, Ken; Ikegaya, Yuji; Ishikawa, Tomoe; Oba, Shigeyuki; Urakubo, Hidetoshi; Koyama, Masanori; Ishii, Shin

2014-01-01

Crosstalk between neurons and glia may constitute a significant part of information processing in the brain. We present a novel method of statistically identifying interactions in a neuron–glia network. We attempted to identify neuron–glia interactions from neuronal and glial activities via maximum-a-posteriori (MAP)-based parameter estimation by developing a generalized linear model (GLM) of a neuron–glia network. The interactions in our interest included functional connectivity and response functions. We evaluated the cross-validated likelihood of GLMs that resulted from the addition or removal of connections to confirm the existence of specific neuron-to-glia or glia-to-neuron connections. We only accepted addition or removal when the modification improved the cross-validated likelihood. We applied the method to a high-throughput, multicellular in vitro Ca2+ imaging dataset obtained from the CA3 region of a rat hippocampus, and then evaluated the reliability of connectivity estimates using a statistical test based on a surrogate method. Our findings based on the estimated connectivity were in good agreement with currently available physiological knowledge, suggesting our method can elucidate undiscovered functions of neuron–glia systems. PMID:25393874

Use of electronic data and existing screening tools to identify clinically significant obstructive sleep apnea.

PubMed

Severson, Carl A; Pendharkar, Sachin R; Ronksley, Paul E; Tsai, Willis H

2015-01-01

To assess the ability of electronic health data and existing screening tools to identify clinically significant obstructive sleep apnea (OSA), as defined by symptomatic or severe OSA. The present retrospective cohort study of 1041 patients referred for sleep diagnostic testing was undertaken at a tertiary sleep centre in Calgary, Alberta. A diagnosis of clinically significant OSA or an alternative sleep diagnosis was assigned to each patient through blinded independent chart review by two sleep physicians. Predictive variables were identified from online questionnaire data, and diagnostic algorithms were developed. The performance of electronically derived algorithms for identifying patients with clinically significant OSA was determined. Diagnostic performance of these algorithms was compared with versions of the STOP-Bang questionnaire and adjusted neck circumference score (ANC) derived from electronic data. Electronic questionnaire data were highly sensitive (>95%) at identifying clinically significant OSA, but not specific. Sleep diagnostic testing-determined respiratory disturbance index was very specific (specificity ≥95%) for clinically relevant disease, but not sensitive (<35%). Derived algorithms had similar accuracy to the STOP-Bang or ANC, but required fewer questions and calculations. These data suggest that a two-step process using a small number of clinical variables (maximizing sensitivity) and objective diagnostic testing (maximizing specificity) is required to identify clinically significant OSA. When used in an online setting, simple algorithms can identify clinically relevant OSA with similar performance to existing decision rules such as the STOP-Bang or ANC.

A combinatorial extracellular matrix platform identifies cell-extracellular matrix interactions that correlate with metastasis

PubMed Central

Reticker-Flynn, Nathan E.; Braga Malta, David F.; Winslow, Monte M.; Lamar, John M.; Xu, Mary J.; Underhill, Gregory H.; Hynes, Richard O.; Jacks, Tyler E.; Bhatia, Sangeeta N.

2013-01-01

Extracellular matrix interactions play essential roles in normal physiology and many pathological processes. While the importance of ECM interactions in metastasis is well documented, systematic approaches to identify their roles in distinct stages of tumorigenesis have not been described. Here we report a novel screening platform capable of measuring phenotypic responses to combinations of ECM molecules. Using a genetic mouse model of lung adenocarcinoma, we measure the ECM-dependent adhesion of tumor-derived cells. Hierarchical clustering of the adhesion profiles differentiates metastatic cell lines from primary tumor lines. Furthermore, we uncovered that metastatic cells selectively associate with fibronectin when in combination with galectin-3, galectin-8, or laminin. We show that these molecules correlate with human disease and that their interactions are mediated in part by α3β1 integrin. Thus, our platform allowed us to interrogate interactions between metastatic cells and their microenvironments, and identified ECM and integrin interactions that could serve as therapeutic targets. PMID:23047680

A new strategy to identify hepatitis B virus entry inhibitors by AlphaScreen technology targeting the envelope-receptor interaction.

PubMed

Saso, Wakana; Tsukuda, Senko; Ohashi, Hirofumi; Fukano, Kento; Morishita, Ryo; Matsunaga, Satoko; Ohki, Mio; Ryo, Akihide; Park, Sam-Yong; Suzuki, Ryosuke; Aizaki, Hideki; Muramatsu, Masamichi; Sureau, Camille; Wakita, Takaji; Matano, Tetsuro; Watashi, Koichi

2018-06-22

Current anti-hepatitis B virus (HBV) agents have limited effect in curing HBV infection, and thus novel anti-HBV agents with different modes of action are in demand. In this study, we applied AlphaScreen assay to high-throughput screening of small molecules inhibiting the interaction between HBV large surface antigen (LHBs) and the HBV entry receptor, sodium taurocholate cotransporting polypeptide (NTCP). From the chemical screening, we identified that rapamycin, an immunosuppressant, strongly inhibited the LHBs-NTCP interaction. Rapamycin inhibited hepatocyte infection with HBV without significant cytotoxicity. This activity was due to impaired attachment of the LHBs preS1 domain to cell surface. Pretreatment of target cells with rapamycin remarkably reduced their susceptibility to preS1 attachment, while rapamycin pretreatment to preS1 did not affect its attachment activity, suggesting that rapamycin targets the host side. In support of this, a surface plasmon resonance analysis showed a direct interaction of rapamycin with NTCP. Consistently, rapamycin also prevented hepatitis D virus infection, whose entry into cells is also mediated by NTCP. We also identified two rapamycin derivatives, everolimus and temsirolimus, which possessed higher anti-HBV potencies than rapamycin. Thus, this is the first report for application of AlphaScreen technology that monitors a viral envelope-receptor interaction to identify viral entry inhibitors. Copyright © 2018 Elsevier Inc. All rights reserved.

Using peptide array to identify binding motifs and interaction networks for modular domains.

PubMed

Li, Shawn S-C; Wu, Chenggang

2009-01-01

Specific protein-protein interactions underlie all essential biological processes and form the basis of cellular signal transduction. The recognition of a short, linear peptide sequence in one protein by a modular domain in another represents a common theme of macromolecular recognition in cells, and the importance of this mode of protein-protein interaction is highlighted by the large number of peptide-binding domains encoded by the human genome. This phenomenon also provides a unique opportunity to identify protein-protein binding events using peptide arrays and complementary biochemical assays. Accordingly, high-density peptide array has emerged as a useful tool by which to map domain-mediated protein-protein interaction networks at the proteome level. Using the Src-homology 2 (SH2) and 3 (SH3) domains as examples, we describe the application of oriented peptide array libraries in uncovering specific motifs recognized by an SH2 domain and the use of high-density peptide arrays in identifying interaction networks mediated by the SH3 domain. Methods reviewed here could also be applied to other modular domains, including catalytic domains, that recognize linear peptide sequences.

A protein isolated from human oviductal tissue in vitro secretion, identified as human lactoferrin, interacts with spermatozoa and oocytes and modulates gamete interaction.

PubMed

Zumoffen, C M; Gil, R; Caille, A M; Morente, C; Munuce, M J; Ghersevich, S A

2013-05-01

reaction was assessed with Pisum sativum agglutinin conjugated with rhodamine. The effect of increasing concentrations of LF (0.1-100 µg/ml) on gamete interaction was evaluated by a sperm-ZP binding assay, using human oocytes donated by women undergoing IVF procedures. A protein isolated by the affinity column was identified as human LF. LF was immunolocalized in human oviductal tissue and detected in oviductal fluid and oviduct epithelial cell homogenates. In the latter case, LF expression was highest at the periovulatory phase of the menstrual cycle (P < 0.01). Different LF binding patterns were observed on spermatozoa depending upon capacitation stage and if the acrosome reaction had occurred. Unstained sperm were most prevalent before capacitation, but after incubation for 6 h under capacitating conditions and in acrosome-reacted sperm LF binding was observed, mainly localized in the equatorial segment and post-acrosomal region of the sperm head. LF binding studies on ZP showed homogenous staining. LF caused a dose-dependent significant inhibition of sperm-ZP interaction, and the effect was already significant (P < 0.01) with the lowest LF concentration used. This study has investigated the effect of LF only on human gamete interaction in vitro and thus has some limitations. Further investigations of the potential mechanisms involved in LF action both on gamete function in vitro and in vivo in animal models are needed to confirm the role of this protein in the reproductive process. The present data indicate that human oviductal LF expression is cycle dependent and inhibited gamete interaction in vitro. No previous data were available about potential direct effects of LF on gamete interaction. It could be thought that the protein is involved in the regulation of the reproductive process, perhaps contributing to prevent polyspermy. Thus, further research is needed to clarify the potential role of LF in the regulation of the fertilization process. This study was

Identifying environmental variables explaining genotype-by-environment interaction for body weight of rainbow trout (Onchorynchus mykiss): reaction norm and factor analytic models.

PubMed

Sae-Lim, Panya; Komen, Hans; Kause, Antti; Mulder, Han A

2014-02-26

Identifying the relevant environmental variables that cause GxE interaction is often difficult when they cannot be experimentally manipulated. Two statistical approaches can be applied to address this question. When data on candidate environmental variables are available, GxE interaction can be quantified as a function of specific environmental variables using a reaction norm model. Alternatively, a factor analytic model can be used to identify the latent common factor that explains GxE interaction. This factor can be correlated with known environmental variables to identify those that are relevant. Previously, we reported a significant GxE interaction for body weight at harvest in rainbow trout reared on three continents. Here we explore their possible causes. Reaction norm and factor analytic models were used to identify which environmental variables (age at harvest, water temperature, oxygen, and photoperiod) may have caused the observed GxE interaction. Data on body weight at harvest was recorded on 8976 offspring reared in various locations: (1) a breeding environment in the USA (nucleus), (2) a recirculating aquaculture system in the Freshwater Institute in West Virginia, USA, (3) a high-altitude farm in Peru, and (4) a low-water temperature farm in Germany. Akaike and Bayesian information criteria were used to compare models. The combination of days to harvest multiplied with daily temperature (Day*Degree) and photoperiod were identified by the reaction norm model as the environmental variables responsible for the GxE interaction. The latent common factor that was identified by the factor analytic model showed the highest correlation with Day*Degree. Day*Degree and photoperiod were the environmental variables that differed most between Peru and other environments. Akaike and Bayesian information criteria indicated that the factor analytical model was more parsimonious than the reaction norm model. Day*Degree and photoperiod were identified as environmental

Identifying environmental variables explaining genotype-by-environment interaction for body weight of rainbow trout (Onchorynchus mykiss): reaction norm and factor analytic models

PubMed Central

2014-01-01

Background Identifying the relevant environmental variables that cause GxE interaction is often difficult when they cannot be experimentally manipulated. Two statistical approaches can be applied to address this question. When data on candidate environmental variables are available, GxE interaction can be quantified as a function of specific environmental variables using a reaction norm model. Alternatively, a factor analytic model can be used to identify the latent common factor that explains GxE interaction. This factor can be correlated with known environmental variables to identify those that are relevant. Previously, we reported a significant GxE interaction for body weight at harvest in rainbow trout reared on three continents. Here we explore their possible causes. Methods Reaction norm and factor analytic models were used to identify which environmental variables (age at harvest, water temperature, oxygen, and photoperiod) may have caused the observed GxE interaction. Data on body weight at harvest was recorded on 8976 offspring reared in various locations: (1) a breeding environment in the USA (nucleus), (2) a recirculating aquaculture system in the Freshwater Institute in West Virginia, USA, (3) a high-altitude farm in Peru, and (4) a low-water temperature farm in Germany. Akaike and Bayesian information criteria were used to compare models. Results The combination of days to harvest multiplied with daily temperature (Day*Degree) and photoperiod were identified by the reaction norm model as the environmental variables responsible for the GxE interaction. The latent common factor that was identified by the factor analytic model showed the highest correlation with Day*Degree. Day*Degree and photoperiod were the environmental variables that differed most between Peru and other environments. Akaike and Bayesian information criteria indicated that the factor analytical model was more parsimonious than the reaction norm model. Conclusions Day*Degree and

Structural mode significance using INCA. [Interactive Controls Analysis computer program

NASA Technical Reports Server (NTRS)

Bauer, Frank H.; Downing, John P.; Thorpe, Christopher J.

1990-01-01

Structural finite element models are often too large to be used in the design and analysis of control systems. Model reduction techniques must be applied to reduce the structural model to manageable size. In the past, engineers either performed the model order reduction by hand or used distinct computer programs to retrieve the data, to perform the significance analysis and to reduce the order of the model. To expedite this process, the latest version of INCA has been expanded to include an interactive graphical structural mode significance and model order reduction capability.

Using host-pathogen protein interactions to identify and characterize Francisella tularensis virulence factors.

PubMed

Wallqvist, Anders; Memišević, Vesna; Zavaljevski, Nela; Pieper, Rembert; Rajagopala, Seesandra V; Kwon, Keehwan; Yu, Chenggang; Hoover, Timothy A; Reifman, Jaques

2015-12-29

Francisella tularensis is a select bio-threat agent and one of the most virulent intracellular pathogens known, requiring just a few organisms to establish an infection. Although several virulence factors are known, we lack an understanding of virulence factors that act through host-pathogen protein interactions to promote infection. To address these issues in the highly infectious F. tularensis subsp. tularensis Schu S4 strain, we deployed a combined in silico, in vitro, and in vivo analysis to identify virulence factors and their interactions with host proteins to characterize bacterial infection mechanisms. We initially used comparative genomics and literature to identify and select a set of 49 putative and known virulence factors for analysis. Each protein was then subjected to proteome-scale yeast two-hybrid (Y2H) screens with human and murine cDNA libraries to identify potential host-pathogen protein-protein interactions. Based on the bacterial protein interaction profile with both hosts, we selected seven novel putative virulence factors for mutant construction and animal validation experiments. We were able to create five transposon insertion mutants and used them in an intranasal BALB/c mouse challenge model to establish 50 % lethal dose estimates. Three of these, ΔFTT0482c, ΔFTT1538c, and ΔFTT1597, showed attenuation in lethality and can thus be considered novel F. tularensis virulence factors. The analysis of the accompanying Y2H data identified intracellular protein trafficking between the early endosome to the late endosome as an important component in virulence attenuation for these virulence factors. Furthermore, we also used the Y2H data to investigate host protein binding of two known virulence factors, showing that direct protein binding was a component in the modulation of the inflammatory response via activation of mitogen-activated protein kinases and in the oxidative stress response. Direct interactions with specific host proteins and the

Identifying Ant-Mirid Spatial Interactions to Improve Biological Control in Cacao-Based Agroforestry System.

PubMed

Bagny Beilhe, Leïla; Piou, Cyril; Tadu, Zéphirin; Babin, Régis

2018-06-06

The use of ants for biological control of insect pests was the first reported case of conservation biological control. Direct and indirect community interactions between ants and pests lead to differential spatial pattern. We investigated spatial interactions between mirids, the major cocoa pest in West Africa and numerically dominant ant species, using bivariate point pattern analysis to identify potential biological control agents. We assume that potential biological control agents should display negative spatial interactions with mirids considering their niche overlap. The mirid/ant data were collected in complex cacao-based agroforestry systems sampled in three agroecological areas over a forest-savannah gradient in Cameroon. Three species, Crematogaster striatula Emery (Hymenoptera: Formicidae), Crematogaster clariventris Mayr (Hymenoptera: Formicidae), and Oecophylla longinoda Latreille (Hymenoptera: Formicidae) with high predator and aggressive behaviors were identified as dominant and showed negative spatial relationships with mirids. The weaver ant, O. longinoda was identified as the only potential biological control agent, considering its ubiquity in the plots, the similarity in niche requirements, and the spatial segregation with mirids resulting probably from exclusion mechanisms. Combining bivariate point pattern analysis to good knowledge of insect ecology was an effective method to identify a potentially good biological control agent.

Noise in NC-AFM measurements with significant tip–sample interaction

PubMed Central

Lübbe, Jannis; Temmen, Matthias

2016-01-01

The frequency shift noise in non-contact atomic force microscopy (NC-AFM) imaging and spectroscopy consists of thermal noise and detection system noise with an additional contribution from amplitude noise if there are significant tip–sample interactions. The total noise power spectral density D Δ f(f m) is, however, not just the sum of these noise contributions. Instead its magnitude and spectral characteristics are determined by the strongly non-linear tip–sample interaction, by the coupling between the amplitude and tip–sample distance control loops of the NC-AFM system as well as by the characteristics of the phase locked loop (PLL) detector used for frequency demodulation. Here, we measure D Δ f(f m) for various NC-AFM parameter settings representing realistic measurement conditions and compare experimental data to simulations based on a model of the NC-AFM system that includes the tip–sample interaction. The good agreement between predicted and measured noise spectra confirms that the model covers the relevant noise contributions and interactions. Results yield a general understanding of noise generation and propagation in the NC-AFM and provide a quantitative prediction of noise for given experimental parameters. We derive strategies for noise-optimised imaging and spectroscopy and outline a full optimisation procedure for the instrumentation and control loops. PMID:28144538

Noise in NC-AFM measurements with significant tip-sample interaction.

PubMed

Lübbe, Jannis; Temmen, Matthias; Rahe, Philipp; Reichling, Michael

2016-01-01

The frequency shift noise in non-contact atomic force microscopy (NC-AFM) imaging and spectroscopy consists of thermal noise and detection system noise with an additional contribution from amplitude noise if there are significant tip-sample interactions. The total noise power spectral density D Δ f ( f m ) is, however, not just the sum of these noise contributions. Instead its magnitude and spectral characteristics are determined by the strongly non-linear tip-sample interaction, by the coupling between the amplitude and tip-sample distance control loops of the NC-AFM system as well as by the characteristics of the phase locked loop (PLL) detector used for frequency demodulation. Here, we measure D Δ f ( f m ) for various NC-AFM parameter settings representing realistic measurement conditions and compare experimental data to simulations based on a model of the NC-AFM system that includes the tip-sample interaction. The good agreement between predicted and measured noise spectra confirms that the model covers the relevant noise contributions and interactions. Results yield a general understanding of noise generation and propagation in the NC-AFM and provide a quantitative prediction of noise for given experimental parameters. We derive strategies for noise-optimised imaging and spectroscopy and outline a full optimisation procedure for the instrumentation and control loops.

Mitochondrial Protein Interaction Mapping Identifies Regulators of Respiratory Chain Function.

PubMed

Floyd, Brendan J; Wilkerson, Emily M; Veling, Mike T; Minogue, Catie E; Xia, Chuanwu; Beebe, Emily T; Wrobel, Russell L; Cho, Holly; Kremer, Laura S; Alston, Charlotte L; Gromek, Katarzyna A; Dolan, Brendan K; Ulbrich, Arne; Stefely, Jonathan A; Bohl, Sarah L; Werner, Kelly M; Jochem, Adam; Westphall, Michael S; Rensvold, Jarred W; Taylor, Robert W; Prokisch, Holger; Kim, Jung-Ja P; Coon, Joshua J; Pagliarini, David J

2016-08-18

Mitochondria are essential for numerous cellular processes, yet hundreds of their proteins lack robust functional annotation. To reveal functions for these proteins (termed MXPs), we assessed condition-specific protein-protein interactions for 50 select MXPs using affinity enrichment mass spectrometry. Our data connect MXPs to diverse mitochondrial processes, including multiple aspects of respiratory chain function. Building upon these observations, we validated C17orf89 as a complex I (CI) assembly factor. Disruption of C17orf89 markedly reduced CI activity, and its depletion is found in an unresolved case of CI deficiency. We likewise discovered that LYRM5 interacts with and deflavinates the electron-transferring flavoprotein that shuttles electrons to coenzyme Q (CoQ). Finally, we identified a dynamic human CoQ biosynthetic complex involving multiple MXPs whose topology we map using purified components. Collectively, our data lend mechanistic insight into respiratory chain-related activities and prioritize hundreds of additional interactions for further exploration of mitochondrial protein function. Copyright © 2016 Elsevier Inc. All rights reserved.

Identifying the preferred RNA motifs and chemotypes that interact by probing millions of combinations.

PubMed

Tran, Tuan; Disney, Matthew D

2012-01-01

RNA is an important therapeutic target but information about RNA-ligand interactions is limited. Here, we report a screening method that probes over 3,000,000 combinations of RNA motif-small molecule interactions to identify the privileged RNA structures and chemical spaces that interact. Specifically, a small molecule library biased for binding RNA was probed for binding to over 70,000 unique RNA motifs in a high throughput solution-based screen. The RNA motifs that specifically bind each small molecule were identified by microarray-based selection. In this library-versus-library or multidimensional combinatorial screening approach, hairpin loops (among a variety of RNA motifs) were the preferred RNA motif space that binds small molecules. Furthermore, it was shown that indole, 2-phenyl indole, 2-phenyl benzimidazole and pyridinium chemotypes allow for specific recognition of RNA motifs. As targeting RNA with small molecules is an extremely challenging area, these studies provide new information on RNA-ligand interactions that has many potential uses.

Identifying the Preferred RNA Motifs and Chemotypes that Interact by Probing Millions of Combinations

PubMed Central

Tran, Tuan; Disney, Matthew D.

2012-01-01

RNA is an important therapeutic target but information about RNA-ligand interactions is limited. Here we report a screening method that probes over 3,000,000 combinations of RNA motif-small molecule interactions to identify the privileged RNA structures and chemical spaces that interact. Specifically, a small molecule library biased for binding RNA was probed for binding to over 70,000 unique RNA motifs in a high throughput solution-based screen. The RNA motifs that specifically bind each small molecule were identified by microarray-based selection. In this library-versus-library or multidimensional combinatorial screening approach, hairpin loops (amongst a variety of RNA motifs) were the preferred RNA motif space that binds small molecules. Furthermore, it was shown that indole, 2-phenyl indole, 2-phenyl benzimidazole, and pyridinium chemotypes allow for specific recognition of RNA motifs. Since targeting RNA with small molecules is an extremely challenging area, these studies provide new information on RNA-ligand interactions that has many potential uses. PMID:23047683

Imaging host-Leishmania interactions: significance in visceral leishmaniasis.

PubMed

Forestier, C-L

2013-01-01

Leishmaniasis is a neglected disease that is associated with a spectrum of clinical manifestations ranging from self-healing cutaneous lesions to fatal visceral infections, which primarily depends on the parasite species. In visceral leishmaniasis (VL), as opposed to cutaneous leishmaniasis (CL), parasites that infect host cells at the sand fly bite site have the striking ability to disseminate to visceral organs where they proliferate and persist for long periods of time. Imaging the dynamics of the host-Leishmania interaction in VL provides a powerful approach to understanding the mechanisms underlying host cell invasion, Leishmania dissemination and persistence within visceral organs and, to dissecting the immune responses to infection. Therefore, by allowing the visualization of the critical steps involved in the pathogenesis of VL, state-of-the-art microscopy technologies have the great potential to aid in the identification of better intervention strategies for this devastating disease. In this review, we emphasize the current knowledge and the potential significance of imaging technologies in understanding the infection process of visceralizing Leishmania species. Then, we discuss how application of innovative microscopy technologies to the study of VL will provide rich opportunities for investigating host-parasite interactions at a previously unexplored level and elucidating visceral disease-promoting mechanisms. © 2013 John Wiley & Sons Ltd.

The accuracy of physical examination in identifying significant pathologies in penetrating thoracic trauma.

PubMed

Kong, V Y; Sartorius, B; Clarke, D L

2015-12-01

Accurate physical examination (PE) remains a key component in the assessment of penetrating thoracic trauma (PTT), despite the increasing availability of advanced radiological imaging. Evidence regarding the accuracy of PE in identifying significant pathology following PTT is limited. A retrospective review of 405 patients was undertaken over a twelve-month period to determine the accuracy of PE in identifying significant pathology (SP) subsequently confirmed on chest radiographs (CXRs) in patients who sustained stab injuries to the thorax. Ninety-seven per cent (372/405) of patients were males, and the mean age was 24 years. The weapons involved were knives in 98 % (398/405), screwdrivers in 1 % (3/405) and unknown in the remaining 1 %. Fifty-nine per cent (238/405) of all injuries were on the left side. There were 306 (76 %) SPs identified on CXR. Ninety-nine (24 %) CXRs were entirely normal. Based on PE alone, 223 (55 %) patients were thought to have SPs present, 182 (45 %) patients were thought to have no SPs. The overall sensitivity of PE in identifying SPs was 68 % (63-73, 95 % CI), with a specificity of 86 % (77-92, 95 % CI). The PPV of PE was 94 % (90-97, 95 % CI) and the NPV was 47 % (39-54, 95 % CI). The sensitivity of PE for identifying a pneumothorax was 59 % (51-66, 95 % CI), with a specificity of 96 % (89-99, 95 % CI) and the sensitivity of PE for identifying a haemothorax was 79 % (72-86, 95 % CI), with a specificity of 96 % (89-99, 95 % CI). PE is inaccurate in identifying SPs in PTT. The increased reliance on advanced radiological imaging and the subsequent reduced emphasis on PE may have contributed to rapid deskilling amongst surgical residents. The importance of PE must be repeatedly re-emphasised.

In vivo significance of ITK-SLP-76 interaction in cytokine production.

PubMed

Grasis, Juris A; Guimond, David M; Cam, Nicholas R; Herman, Krystal; Magotti, Paola; Lambris, John D; Tsoukas, Constantine D

2010-07-01

In vitro data have suggested that activation of the inducible T-cell kinase (ITK) requires an interaction with the adaptor protein SLP-76. One means for this interaction involves binding of the ITK SH3 domain to the polyproline-rich (PR) region of SLP-76. However, the biological significance of this association in live cells and the consequences of its disruption have not been demonstrated. Here, we utilized a polyarginine-rich, cell-permeable peptide that represents the portion of the SLP-76 PR region that interacts with the ITK SH3 domain as a competitive inhibitor to disrupt the association between ITK and SLP-76 in live cells. We demonstrate that treatment of cells with this peptide, by either in vitro incubation or intraperitoneal injection of the peptide in mice, inhibits the T-cell receptor (TCR)-induced association between ITK and SLP-76, recruitment and transphosphorylation of ITK, actin polarization at the T-cell contact site, and expression of Th2 cytokines. The inhibition is specific, as indicated by lack of effects by the polyarginine vehicle alone or a scrambled sequence of the cargo peptide. In view of the role of ITK as a regulator of Th2 cytokine expression, the data underscore the significance of ITK as a target for pharmacological intervention.

Use of Phage Display to Identify Novel Mineralocorticoid Receptor-Interacting Proteins

PubMed Central

Yang, Jun; Fuller, Peter J.; Morgan, James; Shibata, Hirotaka; McDonnell, Donald P.; Clyne, Colin D.

2014-01-01

The mineralocorticoid receptor (MR) plays a central role in salt and water homeostasis via the kidney; however, inappropriate activation of the MR in the heart can lead to heart failure. A selective MR modulator that antagonizes MR signaling in the heart but not the kidney would provide the cardiovascular protection of current MR antagonists but allow for normal electrolyte balance. The development of such a pharmaceutical requires an understanding of coregulators and their tissue-selective interactions with the MR, which is currently limited by the small repertoire of MR coregulators described in the literature. To identify potential novel MR coregulators, we used T7 phage display to screen tissue-selective cDNA libraries for MR-interacting proteins. Thirty MR binding peptides were identified, from which three were chosen for further characterization based on their nuclear localization and their interaction with other MR-interacting proteins or, in the case of x-ray repair cross-complementing protein 6, its known status as an androgen receptor coregulator. Eukaryotic elongation factor 1A1, structure-specific recognition protein 1, and x-ray repair cross-complementing protein 6 modulated MR-mediated transcription in a ligand-, cell- and/or promoter-specific manner and colocalized with the MR upon agonist treatment when imaged using immunofluorescence microscopy. These results highlight the utility of phage display for rapid and sensitive screening of MR binding proteins and suggest that eukaryotic elongation factor 1A1, structure-specific recognition protein 1, and x-ray repair cross-complementing protein 6 may be potential MR coactivators whose activity is dependent on the ligand, cellular context, and target gene promoter. PMID:25000480

Investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors.

PubMed

Rudolph, Anja; Milne, Roger L; Truong, Thérèse; Knight, Julia A; Seibold, Petra; Flesch-Janys, Dieter; Behrens, Sabine; Eilber, Ursula; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Dunning, Alison M; Shah, Mitul; Munday, Hannah R; Darabi, Hatef; Eriksson, Mikael; Brand, Judith S; Olson, Janet; Vachon, Celine M; Hallberg, Emily; Castelao, J Esteban; Carracedo, Angel; Torres, Maria; Li, Jingmei; Humphreys, Keith; Cordina-Duverger, Emilie; Menegaux, Florence; Flyger, Henrik; Nordestgaard, Børge G; Nielsen, Sune F; Yesilyurt, Betul T; Floris, Giuseppe; Leunen, Karin; Engelhardt, Ellen G; Broeks, Annegien; Rutgers, Emiel J; Glendon, Gord; Mulligan, Anna Marie; Cross, Simon; Reed, Malcolm; Gonzalez-Neira, Anna; Arias Perez, José Ignacio; Provenzano, Elena; Apicella, Carmel; Southey, Melissa C; Spurdle, Amanda; Häberle, Lothar; Beckmann, Matthias W; Ekici, Arif B; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; McLean, Catriona; Baglietto, Laura; Chanock, Stephen J; Lissowska, Jolanta; Sherman, Mark E; Brüning, Thomas; Hamann, Ute; Ko, Yon-Dschun; Orr, Nick; Schoemaker, Minouk; Ashworth, Alan; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M; Mannermaa, Arto; Swerdlow, Anthony; Giles, Graham G; Brenner, Hermann; Fasching, Peter A; Chenevix-Trench, Georgia; Hopper, John; Benítez, Javier; Cox, Angela; Andrulis, Irene L; Lambrechts, Diether; Gago-Dominguez, Manuela; Couch, Fergus; Czene, Kamila; Bojesen, Stig E; Easton, Doug F; Schmidt, Marjanka K; Guénel, Pascal; Hall, Per; Pharoah, Paul D P; Garcia-Closas, Montserrat; Chang-Claude, Jenny

2015-03-15

A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes-type shrinkage estimator. Six SNPs showed interactions with associated p-values (pint ) <1.1 × 10(-3) . None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER-negative BC risk in women ≥170 cm (OR = 1.22, p = 0.017), but inversely associated with ER-negative BC risk in women <160 cm (OR = 0.83, p = 0.039, pint = 1.9 × 10(-4) ). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR = 0.85, p = 2.0 × 10(-4) ), and absent in women who had had just one (OR = 0.96, p = 0.19, pint = 6.1 × 10(-4) ). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR = 0.93, p = 2.8 × 10(-5) ), but no association was observed in current smokers (OR = 1.07, p = 0.14, pint = 3.4 × 10(-4) ). In conclusion, recently identified BC susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies. © 2014 UICC.

Significance of likes: Analysing passive interactions on Facebook during campaigning

PubMed Central

2017-01-01

With more and more political candidates using social media for campaigning, researchers are looking at measuring the effectiveness of this medium. Most research, however, concentrates on the bare count of likes (or twitter mentions) in an attempt to correlate social media presence and winning. In this paper, we propose a novel method, Interaction Strength Plot (IntS) to measure the passive interactions between a candidate’s posts on Facebook and the users (liking the posts). Using this method on original Malaysian General Election (MGE13) and Australian Federal Elections (AFE13) Facebook Pages (FP) campaign data, we label an FP as performing well if both the posting frequency and the likes gathered are above average. Our method shows that over 60% of the MGE13 candidates and 85% of the AFE13 candidates studied in this paper had under-performing FP. Some of these FP owners would have been identified as popular based on bare count. Thus our performance chart is a vital step forward in measuring the effectiveness of online campaigning. PMID:28622350

Significance of likes: Analysing passive interactions on Facebook during campaigning.

PubMed

Khairuddin, Mohammad Adib; Rao, Asha

2017-01-01

With more and more political candidates using social media for campaigning, researchers are looking at measuring the effectiveness of this medium. Most research, however, concentrates on the bare count of likes (or twitter mentions) in an attempt to correlate social media presence and winning. In this paper, we propose a novel method, Interaction Strength Plot (IntS) to measure the passive interactions between a candidate's posts on Facebook and the users (liking the posts). Using this method on original Malaysian General Election (MGE13) and Australian Federal Elections (AFE13) Facebook Pages (FP) campaign data, we label an FP as performing well if both the posting frequency and the likes gathered are above average. Our method shows that over 60% of the MGE13 candidates and 85% of the AFE13 candidates studied in this paper had under-performing FP. Some of these FP owners would have been identified as popular based on bare count. Thus our performance chart is a vital step forward in measuring the effectiveness of online campaigning.

Students' Understanding on Newton's Third Law in Identifying the Reaction Force in Gravity Interactions

ERIC Educational Resources Information Center

Zhou, Shaona; Zhang, Chunbin; Xiao, Hua

2015-01-01

In the past three decades, previous researches showed that students had various misconceptions of Newton's Third Law. The present study focused on students' difficulties in identifying the third-law force pair in gravity interaction situations. An instrument involving contexts with gravity and non-gravity associated interactions was designed and…

Identifying significant environmental features using feature recognition.

DOT National Transportation Integrated Search

2015-10-01

The Department of Environmental Analysis at the Kentucky Transportation Cabinet has expressed an interest in feature-recognition capability because it may help analysts identify environmentally sensitive features in the landscape, : including those r...

InterPred: A pipeline to identify and model protein-protein interactions.

PubMed

Mirabello, Claudio; Wallner, Björn

2017-06-01

Protein-protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time-consuming. The fact that the number of PPIs is vastly larger than the number of individual proteins makes it practically impossible to characterize all interactions experimentally. Computational approaches that can bridge this gap and predict PPIs and model the interactions in molecular detail are greatly needed. Here we present InterPred, a fully automated pipeline that predicts and model PPIs from sequence using structural modeling combined with massive structural comparisons and molecular docking. A key component of the method is the use of a novel random forest classifier that integrate several structural features to distinguish correct from incorrect protein-protein interaction models. We show that InterPred represents a major improvement in protein-protein interaction detection with a performance comparable or better than experimental high-throughput techniques. We also show that our full-atom protein-protein complex modeling pipeline performs better than state of the art protein docking methods on a standard benchmark set. In addition, InterPred was also one of the top predictors in the latest CAPRI37 experiment. InterPred source code can be downloaded from http://wallnerlab.org/InterPred Proteins 2017; 85:1159-1170. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

A splicing variant of TERT identified by GWAS interacts with menopausal estrogen therapy in risk of ovarian cancer.

PubMed

Lee, Alice W; Bomkamp, Ashley; Bandera, Elisa V; Jensen, Allan; Ramus, Susan J; Goodman, Marc T; Rossing, Mary Anne; Modugno, Francesmary; Moysich, Kirsten B; Chang-Claude, Jenny; Rudolph, Anja; Gentry-Maharaj, Aleksandra; Terry, Kathryn L; Gayther, Simon A; Cramer, Daniel W; Doherty, Jennifer A; Schildkraut, Joellen M; Kjaer, Susanne K; Ness, Roberta B; Menon, Usha; Berchuck, Andrew; Mukherjee, Bhramar; Roman, Lynda; Pharoah, Paul D; Chenevix-Trench, Georgia; Olson, Sara; Hogdall, Estrid; Wu, Anna H; Pike, Malcolm C; Stram, Daniel O; Pearce, Celeste Leigh

2016-12-15

Menopausal estrogen-alone therapy (ET) is a well-established risk factor for serous and endometrioid ovarian cancer. Genetics also plays a role in ovarian cancer, which is partly attributable to 18 confirmed ovarian cancer susceptibility loci identified by genome-wide association studies. The interplay among these loci, ET use and ovarian cancer risk has yet to be evaluated. We analyzed data from 1,414 serous cases, 337 endometrioid cases and 4,051 controls across 10 case-control studies participating in the Ovarian Cancer Association Consortium (OCAC). Conditional logistic regression was used to determine the association between the confirmed susceptibility variants and risk of serous and endometrioid ovarian cancer among ET users and non-users separately and to test for statistical interaction. A splicing variant in TERT, rs10069690, showed a statistically significant interaction with ET use for risk of serous ovarian cancer (p int  = 0.013). ET users carrying the T allele had a 51% increased risk of disease (OR = 1.51, 95% CI 1.19-1.91), which was stronger for long-term ET users of 10+ years (OR = 1.85, 95% CI 1.28-2.66, p int  = 0.034). Non-users showed essentially no association (OR = 1.08, 95% CI 0.96-1.21). Two additional genomic regions harboring rs7207826 (C allele) and rs56318008 (T allele) also had significant interactions with ET use for the endometrioid histotype (p int  = 0.021 and p int  = 0.037, respectively). Hence, three confirmed susceptibility variants were identified whose associations with ovarian cancer risk are modified by ET exposure; follow-up is warranted given that these interactions are not adjusted for multiple comparisons. These findings, if validated, may elucidate the mechanism of action of these loci. © 2016 UICC.

Identifying functional cancer-specific miRNA-mRNA interactions in testicular germ cell tumor.

PubMed

Sedaghat, Nafiseh; Fathy, Mahmood; Modarressi, Mohammad Hossein; Shojaie, Ali

2016-09-07

Testicular cancer is the most common cancer in men aged between 15 and 35 and more than 90% of testicular neoplasms are originated at germ cells. Recent research has shown the impact of microRNAs (miRNAs) in different types of cancer, including testicular germ cell tumor (TGCT). MicroRNAs are small non-coding RNAs which affect the development and progression of cancer cells by binding to mRNAs and regulating their expressions. The identification of functional miRNA-mRNA interactions in cancers, i.e. those that alter the expression of genes in cancer cells, can help delineate post-regulatory mechanisms and may lead to new treatments to control the progression of cancer. A number of sequence-based methods have been developed to predict miRNA-mRNA interactions based on the complementarity of sequences. While necessary, sequence complementarity is, however, not sufficient for presence of functional interactions. Alternative methods have thus been developed to refine the sequence-based interactions using concurrent expression profiles of miRNAs and mRNAs. This study aims to find functional cancer-specific miRNA-mRNA interactions in TGCT. To this end, the sequence-based predicted interactions are first refined using an ensemble learning method, based on two well-known methods of learning miRNA-mRNA interactions, namely, TaLasso and GenMiR++. Additional functional analyses were then used to identify a subset of interactions to be most likely functional and specific to TGCT. The final list of 13 miRNA-mRNA interactions can be potential targets for identifying TGCT-specific interactions and future laboratory experiments to develop new therapies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computational Framework for Analysis of Prey–Prey Associations in Interaction Proteomics Identifies Novel Human Protein–Protein Interactions and Networks

PubMed Central

Saha, Sudipto; Dazard, Jean-Eudes; Xu, Hua; Ewing, Rob M.

2013-01-01

Large-scale protein–protein interaction data sets have been generated for several species including yeast and human and have enabled the identification, quantification, and prediction of cellular molecular networks. Affinity purification-mass spectrometry (AP-MS) is the preeminent methodology for large-scale analysis of protein complexes, performed by immunopurifying a specific “bait” protein and its associated “prey” proteins. The analysis and interpretation of AP-MS data sets is, however, not straightforward. In addition, although yeast AP-MS data sets are relatively comprehensive, current human AP-MS data sets only sparsely cover the human interactome. Here we develop a framework for analysis of AP-MS data sets that addresses the issues of noise, missing data, and sparsity of coverage in the context of a current, real world human AP-MS data set. Our goal is to extend and increase the density of the known human interactome by integrating bait–prey and cocomplexed preys (prey–prey associations) into networks. Our framework incorporates a score for each identified protein, as well as elements of signal processing to improve the confidence of identified protein–protein interactions. We identify many protein networks enriched in known biological processes and functions. In addition, we show that integrated bait–prey and prey–prey interactions can be used to refine network topology and extend known protein networks. PMID:22845868

ChIP-PaM: an algorithm to identify protein-DNA interaction using ChIP-Seq data.

PubMed

Wu, Song; Wang, Jianmin; Zhao, Wei; Pounds, Stanley; Cheng, Cheng

2010-06-03

ChIP-Seq is a powerful tool for identifying the interaction between genomic regulators and their bound DNAs, especially for locating transcription factor binding sites. However, high cost and high rate of false discovery of transcription factor binding sites identified from ChIP-Seq data significantly limit its application. Here we report a new algorithm, ChIP-PaM, for identifying transcription factor target regions in ChIP-Seq datasets. This algorithm makes full use of a protein-DNA binding pattern by capitalizing on three lines of evidence: 1) the tag count modelling at the peak position, 2) pattern matching of a specific tag count distribution, and 3) motif searching along the genome. A novel data-based two-step eFDR procedure is proposed to integrate the three lines of evidence to determine significantly enriched regions. Our algorithm requires no technical controls and efficiently discriminates falsely enriched regions from regions enriched by true transcription factor (TF) binding on the basis of ChIP-Seq data only. An analysis of real genomic data is presented to demonstrate our method. In a comparison with other existing methods, we found that our algorithm provides more accurate binding site discovery while maintaining comparable statistical power.

42 CFR 137.22 - May the Secretary consider uncorrected significant and material audit exceptions identified...

Code of Federal Regulations, 2010 CFR

2010-10-01

... and material audit exceptions identified regarding centralized financial and administrative functions... Tribes for Participation in Self-Governance Planning Phase § 137.22 May the Secretary consider uncorrected significant and material audit exceptions identified regarding centralized financial and...

Nanoparticle-Protein Interaction: The Significance and Role of Protein Corona.

PubMed

Ahsan, Saad Mohammad; Rao, Chintalagiri Mohan; Ahmad, Md Faiz

2018-01-01

The physico-chemical properties of nanoparticles, as characterized under idealized laboratory conditions, have been suggested to differ significantly when studied under complex physiological environments. A major reason for this variation has been the adsorption of biomolecules (mainly proteins) on the nanoparticle surface, constituting the so-called "biomolecular corona". The formation of biomolecular corona on the nanoparticle surface has been reported to influence various nanoparticle properties viz. cellular targeting, cellular interaction, in vivo clearance, toxicity, etc. Understanding the interaction of nanoparticles with proteins upon administration in vivo thus becomes important for the development of effective nanotechnology-based platforms for biomedical applications. In this chapter, we describe the formation of protein corona on nanoparticles and the differences arising in its composition due to variations in nanoparticle properties. Also discussed is the influence of protein corona on various nanoparticle activities.

Technology and Interactive Multimedia. Identifying Emerging Issues and Trends in Technology for Special Education.

ERIC Educational Resources Information Center

Ashton, Ray

As part of a 3-year study to identify emerging issues and trends in technology for special education, this paper addresses the role of interactive multimedia, especially the digital, optical compact disc technologies, in providing instructional services to special education students. An overview identifies technological and economic trends,…

Network Modeling of microRNA-mRNA Interactions in Neuroblastoma Tumorigenesis Identifies miR-204 as a Direct Inhibitor of MYCN.

PubMed

Ooi, Chi Yan; Carter, Daniel R; Liu, Bing; Mayoh, Chelsea; Beckers, Anneleen; Lalwani, Amit; Nagy, Zsuzsanna; De Brouwer, Sara; Decaesteker, Bieke; Hung, Tzong-Tyng; Norris, Murray D; Haber, Michelle; Liu, Tao; De Preter, Katleen; Speleman, Frank; Cheung, Belamy B; Marshall, Glenn M

2018-06-15

Neuroblastoma is a pediatric cancer of the sympathetic nervous system where MYCN amplification is a key indicator of poor prognosis. However, mechanisms by which MYCN promotes neuroblastoma tumorigenesis are not fully understood. In this study, we analyzed global miRNA and mRNA expression profiles of tissues at different stages of tumorigenesis from TH-MYCN transgenic mice, a model of MYCN-driven neuroblastoma. On the basis of a Bayesian learning network model in which we compared pretumor ganglia from TH-MYCN +/+ mice to age-matched wild-type controls, we devised a predicted miRNA-mRNA interaction network. Among the miRNA-mRNA interactions operating during human neuroblastoma tumorigenesis, we identified miR-204 as a tumor suppressor miRNA that inhibited a subnetwork of oncogenes strongly associated with MYCN -amplified neuroblastoma and poor patient outcome. MYCN bound to the miR-204 promoter and repressed miR-204 transcription. Conversely, miR-204 directly bound MYCN mRNA and repressed MYCN expression. miR-204 overexpression significantly inhibited neuroblastoma cell proliferation in vitro and tumorigenesis in vivo Together, these findings identify novel tumorigenic miRNA gene networks and miR-204 as a tumor suppressor that regulates MYCN expression in neuroblastoma tumorigenesis. Significance: Network modeling of miRNA-mRNA regulatory interactions in a mouse model of neuroblastoma identifies miR-204 as a tumor suppressor and negative regulator of MYCN. Cancer Res; 78(12); 3122-34. ©2018 AACR . ©2018 American Association for Cancer Research.

Bispectral pairwise interacting source analysis for identifying systems of cross-frequency interacting brain sources from electroencephalographic or magnetoencephalographic signals

NASA Astrophysics Data System (ADS)

Chella, Federico; Pizzella, Vittorio; Zappasodi, Filippo; Nolte, Guido; Marzetti, Laura

2016-05-01

Brain cognitive functions arise through the coordinated activity of several brain regions, which actually form complex dynamical systems operating at multiple frequencies. These systems often consist of interacting subsystems, whose characterization is of importance for a complete understanding of the brain interaction processes. To address this issue, we present a technique, namely the bispectral pairwise interacting source analysis (biPISA), for analyzing systems of cross-frequency interacting brain sources when multichannel electroencephalographic (EEG) or magnetoencephalographic (MEG) data are available. Specifically, the biPISA makes it possible to identify one or many subsystems of cross-frequency interacting sources by decomposing the antisymmetric components of the cross-bispectra between EEG or MEG signals, based on the assumption that interactions are pairwise. Thanks to the properties of the antisymmetric components of the cross-bispectra, biPISA is also robust to spurious interactions arising from mixing artifacts, i.e., volume conduction or field spread, which always affect EEG or MEG functional connectivity estimates. This method is an extension of the pairwise interacting source analysis (PISA), which was originally introduced for investigating interactions at the same frequency, to the study of cross-frequency interactions. The effectiveness of this approach is demonstrated in simulations for up to three interacting source pairs and for real MEG recordings of spontaneous brain activity. Simulations show that the performances of biPISA in estimating the phase difference between the interacting sources are affected by the increasing level of noise rather than by the number of the interacting subsystems. The analysis of real MEG data reveals an interaction between two pairs of sources of central mu and beta rhythms, localizing in the proximity of the left and right central sulci.

Activated fluid transport regulates bacterial-epithelial interactions and significantly shifts the murine colonic microbiome

PubMed Central

Keely, Simon; Kelly, Caleb J.; Weissmueller, Thomas; Burgess, Adrianne; Wagner, Brandie D.; Robertson, Charles E.; Harris, J. Kirk; Colgan, Sean P.

2012-01-01

Within the intestinal mucosa, epithelial cells serve multiple functions to partition the lumen from the lamina propria. As part of their natural function, intestinal epithelial cells actively transport electrolytes with passive water movement as a mechanism for mucosal hydration. Here, we hypothesized that electrogenic Cl- secretion, and associated mucosal hydration, influences bacterial-epithelial interactions and significantly influences the composition of the intestinal microbiota. An initial screen of different epithelial secretagogues identified lubiprostone as the most potent agonist for which to define these principles. In in vitro studies using cultured T84 cells, lubiprostone decreased E. coli translocation in a concentration-dependent manner (p < 0.001) and decreased S. typhimurium internalization and translocation by as much as 71 ± 6% (p < 0.01). Such decreases in bacterial translocation were abolished by inhibition of electrogenic Cl- secretion and water transport using the Na-K-Cl- antagonist bumetanide (p < 0.01). Extensions of these findings to microbiome analysis in vivo revealed that lubiprostone delivered orally to mice fundamentally shifted the intestinal microbiota, with notable changes within the Firmicutes and Bacteroidetes phyla of resident colonic bacteria. Such findings document a previously unappreciated role for epithelial Cl- secretion and water transport in influencing bacterial-epithelial interactions and suggest that active mucosal hydration functions as a primitive innate epithelial defense mechanism. PMID:22614705

A functional cancer genomics screen identifies a druggable synthetic lethal interaction between MSH3 and PRKDC.

PubMed

Dietlein, Felix; Thelen, Lisa; Jokic, Mladen; Jachimowicz, Ron D; Ivan, Laura; Knittel, Gero; Leeser, Uschi; van Oers, Johanna; Edelmann, Winfried; Heukamp, Lukas C; Reinhardt, H Christian

2014-05-01

Here, we use a large-scale cell line-based approach to identify cancer cell-specific mutations that are associated with DNA-dependent protein kinase catalytic subunit (DNA-PKcs) dependence. For this purpose, we profiled the mutational landscape across 1,319 cancer-associated genes of 67 distinct cell lines and identified numerous genes involved in homologous recombination-mediated DNA repair, including BRCA1, BRCA2, ATM, PAXIP, and RAD50, as being associated with non-oncogene addiction to DNA-PKcs. Mutations in the mismatch repair gene MSH3, which have been reported to occur recurrently in numerous human cancer entities, emerged as the most significant predictors of DNA-PKcs addiction. Concordantly, DNA-PKcs inhibition robustly induced apoptosis in MSH3-mutant cell lines in vitro and displayed remarkable single-agent efficacy against MSH3-mutant tumors in vivo. Thus, we here identify a therapeutically actionable synthetic lethal interaction between MSH3 and the non-homologous end joining kinase DNA-PKcs. Our observations recommend DNA-PKcs inhibition as a therapeutic concept for the treatment of human cancers displaying homologous recombination defects.

Identifying interacting proteins of a Caenorhabditis elegans voltage-gated chloride channel CLH-1 using GFP-Trap and mass spectrometry.

PubMed

Zhou, Zi-Liang; Jiang, Jing; Yin, Jiang-An; Cai, Shi-Qing

2014-06-25

Chloride channels belong to a superfamily of ion channels that permit passive passage of anions, mainly chloride, across cell membrane. They play a variety of important physiological roles in regulation of cytosolic pH, cell volume homeostasis, organic solute transport, cell migration, cell proliferation, and differentiation. However, little is known about the functional regulation of these channels. In this study, we generated an integrated transgenic worm strain expressing green fluorescence protein (GFP) fused CLC-type chloride channel 1 (CLH-1::GFP), a voltage-gated chloride channel in Caenorhabditis elegans (C. elegans). CLH-1::GFP was expressed in some unidentified head neurons and posterior intestinal cells of C. elegans. Interacting proteins of CLH-1::GFP were purified by GFP-Trap, a novel system for efficient isolation of GFP fusion proteins and their interacting factors. Mass spectrometry (MS) analysis revealed that a total of 27 high probability interacting proteins were co-trapped with CLHp-1::GFP. Biochemical evidence showed that eukaryotic translation elongation factor 1 (EEF-1), one of these co-trapped proteins identified by MS, physically interacted with CLH-1, in consistent with GFP-Trap experiments. Further immunostaining data revealed that the protein level of CLH-1 was significantly increased upon co-expression with EEF-1. These results suggest that the combination of GFP-Trap purification with MS is an excellent tool to identify novel interacting proteins of voltage-gated chloride channels in C. elegans. Our data also show that EEF-1 is a regulator of voltage-gated chloride channel CLH-1.

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

Solubility of methane in water: the significance of the methane-water interaction potential.

PubMed

Konrad, Oliver; Lankau, Timm

2005-12-15

The influence of the methane-water interaction potential on the value of the Henry constant obtained from molecular dynamics simulations was investigated. The SPC, SPC/E, MSPC/E, and TIP3P potentials were used to describe water and the OPLS-UA and TraPPE potentials for methane. Nonbonding interactions between unlike atoms were calculated both with one of four mixing rules and with our new methane-water interaction potential. The Henry constants obtained from simulations using any of the mixing rules differed significantly from the experimental ones. Good agreement between simulation and experiment was achieved with the new potential over the whole temperature range.

Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining.

PubMed

Reps, Jenna M; Aickelin, Uwe; Hubbard, Richard B

2016-02-01

To develop a framework for identifying and incorporating candidate confounding interaction terms into a regularised cox regression analysis to refine adverse drug reaction signals obtained via longitudinal observational data. We considered six drug families that are commonly associated with myocardial infarction in observational healthcare data, but where the causal relationship ground truth is known (adverse drug reaction or not). We applied emergent pattern mining to find itemsets of drugs and medical events that are associated with the development of myocardial infarction. These are the candidate confounding interaction terms. We then implemented a cohort study design using regularised cox regression that incorporated and accounted for the candidate confounding interaction terms. The methodology was able to account for signals generated due to confounding and a cox regression with elastic net regularisation correctly ranking the drug families known to be true adverse drug reactions above those that are not. This was not the case without the inclusion of the candidate confounding interaction terms, where confounding leads to a non-adverse drug reaction being ranked highest. The methodology is efficient, can identify high-order confounding interactions and does not require expert input to specify outcome specific confounders, so it can be applied for any outcome of interest to quickly refine its signals. The proposed method shows excellent potential to overcome some forms of confounding and therefore reduce the false positive rate for signal analysis using longitudinal data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identifying Interacting Genetic Variations by Fish-Swarm Logic Regression

PubMed Central

Yang, Aiyuan; Yan, Chunxia; Zhu, Feng; Zhao, Zhongmeng; Cao, Zhi

2013-01-01

Understanding associations between genotypes and complex traits is a fundamental problem in human genetics. A major open problem in mapping phenotypes is that of identifying a set of interacting genetic variants, which might contribute to complex traits. Logic regression (LR) is a powerful multivariant association tool. Several LR-based approaches have been successfully applied to different datasets. However, these approaches are not adequate with regard to accuracy and efficiency. In this paper, we propose a new LR-based approach, called fish-swarm logic regression (FSLR), which improves the logic regression process by incorporating swarm optimization. In our approach, a school of fish agents are conducted in parallel. Each fish agent holds a regression model, while the school searches for better models through various preset behaviors. A swarm algorithm improves the accuracy and the efficiency by speeding up the convergence and preventing it from dropping into local optimums. We apply our approach on a real screening dataset and a series of simulation scenarios. Compared to three existing LR-based approaches, our approach outperforms them by having lower type I and type II error rates, being able to identify more preset causal sites, and performing at faster speeds. PMID:23984382

GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature.

PubMed

Ye, Ning; Yin, Hengfu; Liu, Jingjing; Dai, Xiaogang; Yin, Tongming

2015-01-01

The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI) toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

An investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors

PubMed Central

Rudolph, Anja; Milne, Roger L.; Truong, Thérèse; Knight, Julia A.; Seibold, Petra; Flesch-Janys, Dieter; Behrens, Sabine; Eilber, Ursula; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Dunning, Alison M.; Shah, Mitul; Munday, Hannah R.; Darabi, Hatef; Eriksson, Mikael; Brand, Judith S.; Olson, Janet; Vachon, Celine M.; Hallberg, Emily; Castelao, J. Esteban; Carracedo, Angel; Torres, Maria; Li, Jingmei; Humphreys, Keith; Cordina-Duverger, Emilie; Menegaux, Florence; Flyger, Henrik; Nordestgaard, Børge G.; Nielsen, Sune F.; Yesilyurt, Betul T.; Floris, Giuseppe; Leunen, Karin; Engelhardt, Ellen G.; Broeks, Annegien; Rutgers, Emiel J.; Glendon, Gord; Mulligan, Anna Marie; Cross, Simon; Reed, Malcolm; Gonzalez-Neira, Anna; Perez, José Ignacio Arias; Provenzano, Elena; Apicella, Carmel; Southey, Melissa C.; Spurdle, Amanda; Investigators, kConFab; Group, AOCS; Häberle, Lothar; Beckmann, Matthias W.; Ekici, Arif B.; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; McLean, Catriona; Baglietto, Laura; Chanock, Stephen J.; Lissowska, Jolanta; Sherman, Mark E.; Brüning, Thomas; Hamann, Ute; Ko, Yon-Dschun; Orr, Nick; Schoemaker, Minouk; Ashworth, Alan; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M.; Mannermaa, Arto; Swerdlow, Anthony; Giles, Graham G.; Brenner, Hermann; Fasching, Peter A.; Chenevix-Trench, Georgia; Hopper, John; Benítez, Javier; Cox, Angela; Andrulis, Irene L.; Lambrechts, Diether; Gago-Dominguez, Manuela; Couch, Fergus; Czene, Kamila; Bojesen, Stig E.; Easton, Doug F.; Schmidt, Marjanka K.; Guénel, Pascal; Hall, Per; Pharoah, Paul D. P.; Garcia-Closas, Montserrat; Chang-Claude, Jenny

2014-01-01

A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen receptor (ER) negative BC risk are modified by 13 environmental risk factors for BC. Data from 22 studies participating in BCAC were pooled, comprising up to 26,633 cases and 30,119 controls. Interactions between SNPs and environmental factors were evaluated using an empirical Bayes-type shrinkage estimator. Six SNPs showed interactions with associated p-values (pint) <1.1×10−3. None of the observed interactions was significant after accounting for multiple testing. The Bayesian False Discovery Probability was used to rank the findings, which indicated three interactions as being noteworthy at 1% prior probability of interaction. SNP rs6828523 was associated with increased ER-negative BC risk in women ≥170cm (OR=1.22, p=0.017), but inversely associated with ER-negative BC risk in women <160cm (OR=0.83, p=0.039, pint=1.9×10−4). The inverse association between rs4808801 and overall BC risk was stronger for women who had had four or more pregnancies (OR=0.85, p=2.0×10−4), and absent in women who had had just one (OR=0.96, p=0.19, pint = 6.1×10−4). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR=0.93, p=2.8×10−5), but no association was observed in current smokers (OR=1.07, p=0.14, pint = 3.4×10−4). In conclusion, recently identified breast cancer susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies. PMID:25227710

Significant wilderness qualities: can they be identified and monitored?

Treesearch

David N. Cole; Robert C. Lucas

1989-01-01

The third Research Colloquium, sponsored by the National Outdoor Leadership School (NOLS), convened the week of August 10-15 in the Popo Agie Wilderness, Shoshone National Forest, Wyoming. The purpose of these colloquia is to facilitate interaction and discussion between wilderness managers, researchers, and NOLS personnel in a wilderness setting. At each colloquium,...

Genome-wide gene by lead exposure interaction analysis identifies UNC5D as a candidate gene for neurodevelopment.

PubMed

Wang, Zhaoxi; Claus Henn, Birgit; Wang, Chaolong; Wei, Yongyue; Su, Li; Sun, Ryan; Chen, Han; Wagner, Peter J; Lu, Quan; Lin, Xihong; Wright, Robert; Bellinger, David; Kile, Molly; Mazumdar, Maitreyi; Tellez-Rojo, Martha Maria; Schnaas, Lourdes; Christiani, David C

2017-07-28

Neurodevelopment is a complex process involving both genetic and environmental factors. Prenatal exposure to lead (Pb) has been associated with lower performance on neurodevelopmental tests. Adverse neurodevelopmental outcomes are more frequent and/or more severe when toxic exposures interact with genetic susceptibility. To explore possible loci associated with increased susceptibility to prenatal Pb exposure, we performed a genome-wide gene-environment interaction study (GWIS) in young children from Mexico (n = 390) and Bangladesh (n = 497). Prenatal Pb exposure was estimated by cord blood Pb concentration. Neurodevelopment was assessed using the Bayley Scales of Infant Development. We identified a locus on chromosome 8, containing UNC5D, and demonstrated evidence of its genome-wide significance with mental composite scores (rs9642758, p meta  = 4.35 × 10 -6 ). Within this locus, the joint effects of two independent single nucleotide polymorphisms (SNPs, rs9642758 and rs10503970) had a p-value of 4.38 × 10 -9 for mental composite scores. Correlating GWIS results with in vitro transcriptomic profiles identified one common gene, SLC1A5, which is involved in synaptic function, neuronal development, and excitotoxicity. Further analysis revealed interconnected interactions that formed a large network of 52 genes enriched with oxidative stress genes and neurodevelopmental genes. Our findings suggest that certain genetic polymorphisms within/near genes relevant to neurodevelopment might modify the toxic effects of Pb exposure via oxidative stress.

4C-ker: A Method to Reproducibly Identify Genome-Wide Interactions Captured by 4C-Seq Experiments.

PubMed

Raviram, Ramya; Rocha, Pedro P; Müller, Christian L; Miraldi, Emily R; Badri, Sana; Fu, Yi; Swanzey, Emily; Proudhon, Charlotte; Snetkova, Valentina; Bonneau, Richard; Skok, Jane A

2016-03-01

4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or "bait") that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes.

4C-ker: A Method to Reproducibly Identify Genome-Wide Interactions Captured by 4C-Seq Experiments

PubMed Central

Raviram, Ramya; Rocha, Pedro P.; Müller, Christian L.; Miraldi, Emily R.; Badri, Sana; Fu, Yi; Swanzey, Emily; Proudhon, Charlotte; Snetkova, Valentina

2016-01-01

4C-Seq has proven to be a powerful technique to identify genome-wide interactions with a single locus of interest (or “bait”) that can be important for gene regulation. However, analysis of 4C-Seq data is complicated by the many biases inherent to the technique. An important consideration when dealing with 4C-Seq data is the differences in resolution of signal across the genome that result from differences in 3D distance separation from the bait. This leads to the highest signal in the region immediately surrounding the bait and increasingly lower signals in far-cis and trans. Another important aspect of 4C-Seq experiments is the resolution, which is greatly influenced by the choice of restriction enzyme and the frequency at which it can cut the genome. Thus, it is important that a 4C-Seq analysis method is flexible enough to analyze data generated using different enzymes and to identify interactions across the entire genome. Current methods for 4C-Seq analysis only identify interactions in regions near the bait or in regions located in far-cis and trans, but no method comprehensively analyzes 4C signals of different length scales. In addition, some methods also fail in experiments where chromatin fragments are generated using frequent cutter restriction enzymes. Here, we describe 4C-ker, a Hidden-Markov Model based pipeline that identifies regions throughout the genome that interact with the 4C bait locus. In addition, we incorporate methods for the identification of differential interactions in multiple 4C-seq datasets collected from different genotypes or experimental conditions. Adaptive window sizes are used to correct for differences in signal coverage in near-bait regions, far-cis and trans chromosomes. Using several datasets, we demonstrate that 4C-ker outperforms all existing 4C-Seq pipelines in its ability to reproducibly identify interaction domains at all genomic ranges with different resolution enzymes. PMID:26938081

Dogs Identify Agents in Third-Party Interactions on the Basis of the Observed Degree of Contingency.

PubMed

Tauzin, Tibor; Kovács, Krisztina; Topál, József

2016-08-01

To investigate whether dogs could recognize contingent reactivity as a marker of agents' interaction, we performed an experiment in which dogs were presented with third-party contingent events. In the perfect-contingency condition, dogs were shown an unfamiliar self-propelled agent (SPA) that performed actions corresponding to audio clips of verbal commands played by a computer. In the high-but-imperfect-contingency condition, the SPA responded to the verbal commands on only two thirds of the trials; in the low-contingency condition, the SPA responded to the commands on only one third of the trials. In the test phase, the SPA approached one of two tennis balls, and then the dog was allowed to choose one of the balls. The proportion of trials on which a dog chose the object indicated by the SPA increased with the degree of contingency: Dogs chose the target object significantly above chance level only in the perfect-contingency condition. This finding suggests that dogs may use the degree of temporal contingency observed in third-party interactions as a cue to identify agents. © The Author(s) 2016.

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.

Detection of Significant Pneumococcal Meningitis Biomarkers by Ego Network.

PubMed

Wang, Qian; Lou, Zhifeng; Zhai, Liansuo; Zhao, Haibin

2017-06-01

To identify significant biomarkers for detection of pneumococcal meningitis based on ego network. Based on the gene expression data of pneumococcal meningitis and global protein-protein interactions (PPIs) data recruited from open access databases, the authors constructed a differential co-expression network (DCN) to identify pneumococcal meningitis biomarkers in a network view. Here EgoNet algorithm was employed to screen the significant ego networks that could accurately distinguish pneumococcal meningitis from healthy controls, by sequentially seeking ego genes, searching candidate ego networks, refinement of candidate ego networks and significance analysis to identify ego networks. Finally, the functional inference of the ego networks was performed to identify significant pathways for pneumococcal meningitis. By differential co-expression analysis, the authors constructed the DCN that covered 1809 genes and 3689 interactions. From the DCN, a total of 90 ego genes were identified. Starting from these ego genes, three significant ego networks (Module 19, Module 70 and Module 71) that could predict clinical outcomes for pneumococcal meningitis were identified by EgoNet algorithm, and the corresponding ego genes were GMNN, MAD2L1 and TPX2, respectively. Pathway analysis showed that these three ego networks were related to CDT1 association with the CDC6:ORC:origin complex, inactivation of APC/C via direct inhibition of the APC/C complex pathway, and DNA strand elongation, respectively. The authors successfully screened three significant ego modules which could accurately predict the clinical outcomes for pneumococcal meningitis and might play important roles in host response to pathogen infection in pneumococcal meningitis.

TAGCNA: A Method to Identify Significant Consensus Events of Copy Number Alterations in Cancer

PubMed Central

Yuan, Xiguo; Zhang, Junying; Yang, Liying; Zhang, Shengli; Chen, Baodi; Geng, Yaojun; Wang, Yue

2012-01-01

Somatic copy number alteration (CNA) is a common phenomenon in cancer genome. Distinguishing significant consensus events (SCEs) from random background CNAs in a set of subjects has been proven to be a valuable tool to study cancer. In order to identify SCEs with an acceptable type I error rate, better computational approaches should be developed based on reasonable statistics and null distributions. In this article, we propose a new approach named TAGCNA for identifying SCEs in somatic CNAs that may encompass cancer driver genes. TAGCNA employs a peel-off permutation scheme to generate a reasonable null distribution based on a prior step of selecting tag CNA markers from the genome being considered. We demonstrate the statistical power of TAGCNA on simulated ground truth data, and validate its applicability using two publicly available cancer datasets: lung and prostate adenocarcinoma. TAGCNA identifies SCEs that are known to be involved with proto-oncogenes (e.g. EGFR, CDK4) and tumor suppressor genes (e.g. CDKN2A, CDKN2B), and provides many additional SCEs with potential biological relevance in these data. TAGCNA can be used to analyze the significance of CNAs in various cancers. It is implemented in R and is freely available at http://tagcna.sourceforge.net/. PMID:22815924

Identifying Systems of Interaction in Mathematical Engagement

ERIC Educational Resources Information Center

Brown, Bruce J. L.

2014-01-01

Mathematical engagement is a complex process of interaction between the person and the world. This interaction is strongly influenced by the concepts and structure of the mathematical field, by the practical and symbolic tools of mathematics and by the focus of investigation in the world. This paper reports on research that involves a detailed…

[Predictive factors of clinically significant drug-drug interactions among regimens based on protease inhibitors, non-nucleoside reverse transcriptase inhibitors and raltegravir].

PubMed

Cervero, Miguel; Torres, Rafael; Jusdado, Juan José; Pastor, Susana; Agud, Jose Luis

2016-04-15

To determine the prevalence and types of clinically significant drug-drug interactions (CSDI) in the drug regimens of HIV-infected patients receiving antiretroviral treatment. retrospective review of database. Centre: Hospital Universitario Severo Ochoa, Infectious Unit. one hundred and forty-two participants followed by one of the authors were selected from January 1985 to December 2014. from their outpatient medical records we reviewed information from the last available visit of the participants, in relation to HIV infection, comorbidities, demographics and the drugs that they were receiving; both antiretroviral drugs and drugs not related to HIV infection. We defined CSDI from the information sheet and/or database on antiretroviral drug interactions of the University of Liverpool (http://www.hiv-druginteractions.org) and we developed a diagnostic tool to predict the possibility of CSDI. By multivariate logistic regression analysis and by estimating the diagnostic performance curve obtained, we identified a quick tool to predict the existence of drug interactions. Of 142 patients, 39 (29.11%) had some type of CSDI and in 11.2% 2 or more interactions were detected. In only one patient the combination of drugs was contraindicated (this patient was receiving darunavir/r and quetiapine). In multivariate analyses, predictors of CSDI were regimen type (PI or NNRTI) and the use of 3 or more non-antiretroviral drugs (AUC 0.886, 95% CI 0.828 to 0.944; P=.0001). The risk was 18.55 times in those receiving NNRTI and 27,95 times in those receiving IP compared to those taking raltegravir. Drug interactions, including those defined as clinically significant, are common in HIV-infected patients treated with antiretroviral drugs, and the risk is greater in IP-based regimens. Raltegravir-based prescribing, especially in patients who receive at least 3 non-HIV drugs could avoid interactions. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

Novel Interactions Identified between μ-Conotoxin and the Na+ Channel Domain I P-loop: Implications for Toxin-Pore Binding Geometry

PubMed Central

Xue, Tian; Ennis, Irene L.; Sato, Kazuki; French, Robert J.; Li, Ronald A.

2003-01-01

μ-Conotoxins (μ-CTX) are peptides that inhibit Na+ flux by blocking the Na+ channel pore. Toxin residue arginine 13 is critical for both high affinity binding and for complete block of the single channel current, prompting the simple conventional view that residue 13 (R13) leads toxin docking by entering the channel along the pore axis. To date, the strongest interactions identified are between μ-CTX and domain II (DII) or DIII pore residues of the rat skeletal muscle (Nav1.4) Na+ channels, but little data is available for the role of the DI P-loop in μ-CTX binding due to the lack of critical determinants identified in this domain. Despite being an essential determinant of isoform-specific tetrodotoxin sensitivity, the DI-Y401C variant had little effect on μ-CTX block. Here we report that the charge-changing substitution Y401K dramatically reduced the μ-CTX affinity (∼300-fold). Using mutant cycle analysis, we demonstrate that K401 couples strongly to R13 (ΔΔG > 3.0 kcal/mol) but not R1, K11, or R14 (≪1 kcal/mol). Unlike K401, however, a significant coupling was detected between toxin residue 14 and DI-E403K (ΔΔG = 1.4 kcal/mol for the E403K-Q14D pair). This appears to underlie the ability of DI-E403K channels to discriminate between the GIIIA and GIIIB isoforms of μ-CTX (p < 0.05), whereas Y401K, DII-E758Q, and DIII-D1241K do not. We also identify five additional, novel toxin-channel interactions (>0.75 kcal/mol) in DII (E758-K16, D762-R13, D762-K16, E765-R13, E765-K16). Considered together, these new interactions suggest that the R13 side chain and the bulk of the bound toxin μ-CTX molecule may be significantly tilted with respect to pore axis. PMID:14507694

Identifying Drug-Target Interactions with Decision Templates.

PubMed

Yan, Xiao-Ying; Zhang, Shao-Wu

2018-01-01

During the development process of new drugs, identification of the drug-target interactions wins primary concerns. However, the chemical or biological experiments bear the limitation in coverage as well as the huge cost of both time and money. Based on drug similarity and target similarity, chemogenomic methods can be able to predict potential drug-target interactions (DTIs) on a large scale and have no luxurious need about target structures or ligand entries. In order to reflect the cases that the drugs having variant structures interact with common targets and the targets having dissimilar sequences interact with same drugs. In addition, though several other similarity metrics have been developed to predict DTIs, the combination of multiple similarity metrics (especially heterogeneous similarities) is too naïve to sufficiently explore the multiple similarities. In this paper, based on Gene Ontology and pathway annotation, we introduce two novel target similarity metrics to address above issues. More importantly, we propose a more effective strategy via decision template to integrate multiple classifiers designed with multiple similarity metrics. In the scenarios that predict existing targets for new drugs and predict approved drugs for new protein targets, the results on the DTI benchmark datasets show that our target similarity metrics are able to enhance the predictive accuracies in two scenarios. And the elaborate fusion strategy of multiple classifiers has better predictive power than the naïve combination of multiple similarity metrics. Compared with other two state-of-the-art approaches on the four popular benchmark datasets of binary drug-target interactions, our method achieves the best results in terms of AUC and AUPR for predicting available targets for new drugs (S2), and predicting approved drugs for new protein targets (S3).These results demonstrate that our method can effectively predict the drug-target interactions. The software package can

Genome-wide association study for rotator cuff tears identifies two significant single-nucleotide polymorphisms.

PubMed

Tashjian, Robert Z; Granger, Erin K; Farnham, James M; Cannon-Albright, Lisa A; Teerlink, Craig C

2016-02-01

The precise etiology of rotator cuff disease is unknown, but prior evidence suggests a role for genetic factors. Limited data exist identifying specific genes associated with rotator cuff tearing. The purpose of this study was to identify specific genes or genetic variants associated with rotator cuff tearing by a genome-wide association study with an independent set of rotator cuff tear cases. A set of 311 full-thickness rotator cuff tear cases genotyped on the Illumina 5M single-nucleotide polymorphism (SNP) platform were used in a genome-wide association study with 2641 genetically matched white population controls available from the Illumina iControls database. Tests of association were performed with GEMMA software at 257,558 SNPs that compose the intersection of Illumina SNP platforms and that passed general quality control metrics. SNPs were considered significant if P < 1.94 × 10(-7) (Bonferroni correction: 0.05/257,558). Tests of association revealed 2 significantly associated SNPs, one occurring in SAP30BP (rs820218; P = 3.8E-9) on chromosome 17q25 and another occurring in SASH1 (rs12527089; P = 1.9E-7) on chromosome 6q24. This study represents the first attempt to identify genetic factors influencing rotator cuff tearing by a genome-wide association study using a dense/complete set of SNPs. Two SNPs were significantly associated with rotator cuff tearing, residing in SAP30BP on chromosome 17 and SASH1 on chromosome 6. Both genes are associated with the cellular process of apoptosis. Identification of potential genes or genetic variants associated with rotator cuff tearing may help in identifying individuals at risk for the development of rotator cuff tearing. Copyright © 2016 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

40 CFR 141.723 - Requirements to respond to significant deficiencies identified in sanitary surveys performed by EPA.

Code of Federal Regulations, 2011 CFR

2011-07-01

... deficiencies identified in sanitary surveys performed by EPA. 141.723 Section 141.723 Protection of Environment... REGULATIONS Enhanced Treatment for Cryptosporidium Requirements for Sanitary Surveys Performed by Epa § 141.723 Requirements to respond to significant deficiencies identified in sanitary surveys performed by...

40 CFR 141.723 - Requirements to respond to significant deficiencies identified in sanitary surveys performed by EPA.

Code of Federal Regulations, 2014 CFR

2014-07-01

... deficiencies identified in sanitary surveys performed by EPA. 141.723 Section 141.723 Protection of Environment... REGULATIONS Enhanced Treatment for Cryptosporidium Requirements for Sanitary Surveys Performed by Epa § 141.723 Requirements to respond to significant deficiencies identified in sanitary surveys performed by...

40 CFR 141.723 - Requirements to respond to significant deficiencies identified in sanitary surveys performed by EPA.

Code of Federal Regulations, 2013 CFR

2013-07-01

... deficiencies identified in sanitary surveys performed by EPA. 141.723 Section 141.723 Protection of Environment... REGULATIONS Enhanced Treatment for Cryptosporidium Requirements for Sanitary Surveys Performed by Epa § 141.723 Requirements to respond to significant deficiencies identified in sanitary surveys performed by...

40 CFR 141.723 - Requirements to respond to significant deficiencies identified in sanitary surveys performed by EPA.

Code of Federal Regulations, 2012 CFR

2012-07-01

... deficiencies identified in sanitary surveys performed by EPA. 141.723 Section 141.723 Protection of Environment... REGULATIONS Enhanced Treatment for Cryptosporidium Requirements for Sanitary Surveys Performed by Epa § 141.723 Requirements to respond to significant deficiencies identified in sanitary surveys performed by...

40 CFR 141.723 - Requirements to respond to significant deficiencies identified in sanitary surveys performed by EPA.

Code of Federal Regulations, 2010 CFR

2010-07-01

... deficiencies identified in sanitary surveys performed by EPA. 141.723 Section 141.723 Protection of Environment... REGULATIONS Enhanced Treatment for Cryptosporidium Requirements for Sanitary Surveys Performed by Epa § 141.723 Requirements to respond to significant deficiencies identified in sanitary surveys performed by...

Using video-annotation software to identify interactions in group therapies for schizophrenia: assessing reliability and associations with outcomes.

PubMed

Orfanos, Stavros; Akther, Syeda Ferhana; Abdul-Basit, Muhammad; McCabe, Rosemarie; Priebe, Stefan

2017-02-10

Research has shown that interactions in group therapies for people with schizophrenia are associated with a reduction in negative symptoms. However, it is unclear which specific interactions in groups are linked with these improvements. The aims of this exploratory study were to i) develop and test the reliability of using video-annotation software to measure interactions in group therapies in schizophrenia and ii) explore the relationship between interactions in group therapies for schizophrenia with clinically relevant changes in negative symptoms. Video-annotation software was used to annotate interactions from participants selected across nine video-recorded out-patient therapy groups (N = 81). Using the Individual Group Member Interpersonal Process Scale, interactions were coded from participants who demonstrated either a clinically significant improvement (N = 9) or no change (N = 8) in negative symptoms at the end of therapy. Interactions were measured from the first and last sessions of attendance (>25 h of therapy). Inter-rater reliability between two independent raters was measured. Binary logistic regression analysis was used to explore the association between the frequency of interactive behaviors and changes in negative symptoms, assessed using the Positive and Negative Syndrome Scale. Of the 1275 statements that were annotated using ELAN, 1191 (93%) had sufficient audio and visual quality to be coded using the Individual Group Member Interpersonal Process Scale. Rater-agreement was high across all interaction categories (>95% average agreement). A higher frequency of self-initiated statements measured in the first session was associated with improvements in negative symptoms. The frequency of questions and giving advice measured in the first session of attendance was associated with improvements in negative symptoms; although this was only a trend. Video-annotation software can be used to reliably identify interactive behaviors in groups

Identifying genetic loci affecting antidepressant drug response in depression using drug–gene interaction models

PubMed Central

Noordam, Raymond; Avery, Christy L; Visser, Loes E; Stricker, Bruno H

2016-01-01

Antidepressants are often only moderately successful in decreasing the severity of depressive symptoms. In part, antidepressant treatment response in patients with depression is genetically determined. However, although a large number of studies have been conducted aiming to identify genetic variants associated with antidepressant drug response in depression, only a few variants have been repeatedly identified. Within the present review, we will discuss the methodological challenges and limitations of the studies that have been conducted on this topic to date (e.g., ‘treated-only design’, statistical power) and we will discuss how specifically drug–gene interaction models can be used to be better able to identify genetic variants associated with antidepressant drug response in depression. PMID:27248517

Genomic Characterization of Vulvar (Pre)cancers Identifies Distinct Molecular Subtypes with Prognostic Significance.

PubMed

Nooij, Linda S; Ter Haar, Natalja T; Ruano, Dina; Rakislova, Natalia; van Wezel, Tom; Smit, Vincent T H B M; Trimbos, Baptist J B M Z; Ordi, Jaume; van Poelgeest, Mariette I E; Bosse, Tjalling

2017-11-15

Purpose: Vulvar cancer (VC) can be subclassified by human papillomavirus (HPV) status. HPV-negative VCs frequently harbor TP53 mutations; however, in-depth analysis of other potential molecular genetic alterations is lacking. We comprehensively assessed somatic mutations in a large series of vulvar (pre)cancers. Experimental Design: We performed targeted next-generation sequencing (17 genes), p53 immunohistochemistry and HPV testing on 36 VC and 82 precursors (sequencing cohort). Subsequently, the prognostic significance of the three subtypes identified in the sequencing cohort was assessed in a series of 236 VC patients (follow-up cohort). Results: Frequent recurrent mutations were identified in HPV-negative vulvar (pre)cancers in TP53 (42% and 68%), NOTCH1 (28% and 41%), and HRAS (20% and 31%). Mutation frequency in HPV-positive vulvar (pre)cancers was significantly lower ( P = 0.001). Furthermore, a substantial subset of the HPV-negative precursors (35/60, 58.3%) and VC (10/29, 34.5%) were TP53 wild-type (wt), suggesting a third, not-previously described, molecular subtype. Clinical outcomes in the three different subtypes (HPV + , HPV - /p53wt, HPV - /p53abn) were evaluated in a follow-up cohort consisting of 236 VC patients. Local recurrence rate was 5.3% for HPV + , 16.3% for HPV - /p53wt and 22.6% for HPV - /p53abn tumors ( P = 0.044). HPV positivity remained an independent prognostic factor for favorable outcome in the multivariable analysis ( P = 0.020). Conclusions: HPV - and HPV + vulvar (pre)cancers display striking differences in somatic mutation patterns. HPV - /p53wt VC appear to be a distinct clinicopathologic subgroup with frequent NOTCH1 mutations. HPV + VC have a significantly lower local recurrence rate, independent of clinicopathological variables, opening opportunities for reducing overtreatment in VC. Clin Cancer Res; 23(22); 6781-9. ©2017 AACR . ©2017 American Association for Cancer Research.

Identifying Successful Learners from Interaction Behaviour

ERIC Educational Resources Information Center

McCuaig, Judi; Baldwin, Julia

2012-01-01

The interaction behaviours of successful, high-achieving learners when using a Learning Management System (LMS) are different than the behaviours of learners who are having more difficulty mastering the course material. This paper explores the idea that conventional Learning Management Systems can exploit data mining techniques to predict the…

Determining coding CpG islands by identifying regions significant for pattern statistics on Markov chains.

PubMed

Singer, Meromit; Engström, Alexander; Schönhuth, Alexander; Pachter, Lior

2011-09-23

Recent experimental and computational work confirms that CpGs can be unmethylated inside coding exons, thereby showing that codons may be subjected to both genomic and epigenomic constraint. It is therefore of interest to identify coding CpG islands (CCGIs) that are regions inside exons enriched for CpGs. The difficulty in identifying such islands is that coding exons exhibit sequence biases determined by codon usage and constraints that must be taken into account. We present a method for finding CCGIs that showcases a novel approach we have developed for identifying regions of interest that are significant (with respect to a Markov chain) for the counts of any pattern. Our method begins with the exact computation of tail probabilities for the number of CpGs in all regions contained in coding exons, and then applies a greedy algorithm for selecting islands from among the regions. We show that the greedy algorithm provably optimizes a biologically motivated criterion for selecting islands while controlling the false discovery rate. We applied this approach to the human genome (hg18) and annotated CpG islands in coding exons. The statistical criterion we apply to evaluating islands reduces the number of false positives in existing annotations, while our approach to defining islands reveals significant numbers of undiscovered CCGIs in coding exons. Many of these appear to be examples of functional epigenetic specialization in coding exons.

Interactions between household air pollution and GWAS-identified lung cancer susceptibility markers in the Female Lung Cancer Consortium in Asia (FLCCA).

PubMed

Hosgood, H Dean; Song, Minsun; Hsiung, Chao Agnes; Yin, Zhihua; Shu, Xiao-Ou; Wang, Zhaoming; Chatterjee, Nilanjan; Zheng, Wei; Caporaso, Neil; Burdette, Laurie; Yeager, Meredith; Berndt, Sonja I; Landi, Maria Teresa; Chen, Chien-Jen; Chang, Gee-Chen; Hsiao, Chin-Fu; Tsai, Ying-Huang; Chien, Li-Hsin; Chen, Kuan-Yu; Huang, Ming-Shyan; Su, Wu-Chou; Chen, Yuh-Min; Chen, Chung-Hsing; Yang, Tsung-Ying; Wang, Chih-Liang; Hung, Jen-Yu; Lin, Chien-Chung; Perng, Reury-Perng; Chen, Chih-Yi; Chen, Kun-Chieh; Li, Yao-Jen; Yu, Chong-Jen; Chen, Yi-Song; Chen, Ying-Hsiang; Tsai, Fang-Yu; Kim, Christopher; Seow, Wei Jie; Bassig, Bryan A; Wu, Wei; Guan, Peng; He, Qincheng; Gao, Yu-Tang; Cai, Qiuyin; Chow, Wong-Ho; Xiang, Yong-Bing; Lin, Dongxin; Wu, Chen; Wu, Yi-Long; Shin, Min-Ho; Hong, Yun-Chul; Matsuo, Keitaro; Chen, Kexin; Wong, Maria Pik; Lu, Dara; Jin, Li; Wang, Jiu-Cun; Seow, Adeline; Wu, Tangchun; Shen, Hongbing; Fraumeni, Joseph F; Yang, Pan-Chyr; Chang, I-Shou; Zhou, Baosen; Chanock, Stephen J; Rothman, Nathaniel; Lan, Qing

2015-03-01

We previously carried out a multi-stage genome-wide association study (GWAS) on lung cancer among never smokers in the Female Lung Cancer Consortium in Asia (FLCCA) (6,609 cases, 7,457 controls) that identified novel susceptibility loci at 10q25.2, 6q22.2, and 6p21.32, and confirmed two previously identified loci at 5p15.33 and 3q28. Household air pollution (HAP) attributed to solid fuel burning for heating and cooking, is the leading cause of the overall disease burden in Southeast Asia, and is known to contain lung carcinogens. To evaluate the gene-HAP interactions associated with lung cancer in loci independent of smoking, we analyzed data from studies participating in FLCCA with fuel use information available (n = 3; 1,731 cases; 1,349 controls). Coal use was associated with a 30% increased risk of lung cancer (OR 1.3, 95% CI 1.0-1.6). Among the five a priori SNPs identified by our GWAS, two showed a significant interaction with coal use (HLA Class II rs2395185, p = 0.02; TP63 rs4488809 (rs4600802), p = 0.04). The risk of lung cancer associated with coal exposure varied with the respective alleles for these two SNPs. Our observations provide evidence that genetic variation in HLA Class II and TP63 may modify the association between HAP and lung cancer risk. The roles played in the cell cycle and inflammation pathways by the proteins encoded by these two genes provide biological plausibility for these interactions; however, additional replication studies are needed in other non-smoking populations.

Adding biological meaning to human protein-protein interactions identified by yeast two-hybrid screenings: A guide through bioinformatics tools.

PubMed

Felgueiras, Juliana; Silva, Joana Vieira; Fardilha, Margarida

2018-01-16

"A man is known by the company he keeps" is a popular expression that perfectly fits proteins. A common approach to characterize the function of a target protein is to identify its interacting partners and thus infer its roles based on the known functions of the interactors. Protein-protein interaction networks (PPINs) have been created for several organisms, including humans, primarily as results of high-throughput screenings, such as yeast two-hybrid (Y2H). Their unequivocal use to understand events underlying human pathophysiology is promising in identifying genes and proteins associated with diseases. Therefore, numerous opportunities have emerged for PPINs as tools for clinical management of diseases: network-based disease classification systems, discovery of biomarkers and identification of therapeutic targets. Despite the great advantages of PPINs, their use is still unrecognised by several researchers who generate high-throughput data to generally characterize interactions in a certain model or to select an interaction to study in detail. We strongly believe that both approaches are not exclusive and that we can use PPINs as a complementary methodology and rich-source of information to the initial study proposal. Here, we suggest a pipeline to deal with Y2H results using bioinformatics tools freely available for academics. Yeast two-hybrid is widely-used to identify protein-protein interactions. Conventionally, the positive clones that result from a yeast two-hybrid screening are sequenced to identify the interactors of the protein of interest (also known as bait protein), and few interactions, thought as potentially relevant for the model in study, are selected for further validation using biochemical methods (e.g. co-immunoprecipitation and co-localization). The huge amount of data that is potentially lost during this conservative approach motivated us to write this tutorial-like review, so that researchers feel encouraged to take advantage of

Chemical ecology of insect-plant interactions: ecological significance of plant secondary metabolites.

PubMed

Nishida, Ritsuo

2014-01-01

Plants produce a diverse array of secondary metabolites as chemical barriers against herbivores. Many phytophagous insects are highly adapted to these allelochemicals and use such unique substances as the specific host-finding cues, defensive substances of their own, and even as sex pheromones or their precursors by selectively sensing, incorporating, and/or processing these phytochemicals. Insects also serve as pollinators often effectively guided by specific floral fragrances. This review demonstrates the ecological significance of such plant secondary metabolites in the highly diverse interactions between insects and plants.

Loss of Cbl-PI3K interaction in mice prevents significant bone loss following ovariectomy

PubMed Central

Adapala, Naga Suresh; Holland, Danielle; Piccuillo, Vanessa; Barbe, Mary F.; Langdon, Wallace Y.; Tsygankov, Alexander Y.; Lorenzo, Joseph A.; Sanjay, Archana

2014-01-01

Cbl and Cbl-b are E3 ubiquitin ligases and adaptor proteins, which perform regulatory roles in bone remodeling. Cbl−/− mice have delayed bone development due to decreased osteoclast migration. Cbl-b−/− mice are osteopenic due to increased bone resorbing activity of osteoclasts. Unique to Cbl, but not present in Cbl-b, is tyrosine 737 in the YEAM motif, which upon phosphorylation provides a binding site for the regulatory p85 subunit of PI3K. Substitution of tyrosine 737 with phenylalanine (Y737F, CblYF/YF mice) prevents Y737 phosphorylation and abrogates the Cbl-PI3K interaction. We have previously reported that CblYF/YF mice had increased bone volume due to defective bone resorption and increased bone formation. Here we show that the lumbar vertebra from CblYF/YF mice did not have significant bone loss following ovariectomy. Our data also suggests that abrogation of Cbl-PI3K interaction in mice results in the loss of coupling between bone resorption and formation, since ovariectomized CblYF/YF mice did not show significant changes in serum levels of c-terminal telopeptide (CTX), whereas the serum levels of pro-collagen type-1 amino-terminal pro-peptide (P1NP) were decreased. In contrast, following ovariectomy, Cbl−/− and Cbl-b−/− mice showed significant bone loss in tibiae and L2 vertebrae, concomitant with increased serum CTX and P1NP levels. These data indicate that while lack of Cbl or Cbl-b distinctly affects bone remodeling, only the loss of Cbl-PI3K interaction protects mice from significant bone loss following ovariectomy. PMID:24994594

Loss of Cbl-PI3K interaction in mice prevents significant bone loss following ovariectomy.

PubMed

Adapala, Naga Suresh; Holland, Danielle; Scanlon, Vanessa; Barbe, Mary F; Langdon, Wallace Y; Tsygankov, Alexander Y; Lorenzo, Joseph A; Sanjay, Archana

2014-10-01

Cbl and Cbl-b are E3 ubiquitin ligases and adaptor proteins, which perform regulatory roles in bone remodeling. Cbl-/- mice have delayed bone development due to decreased osteoclast migration. Cbl-b-/- mice are osteopenic due to increased bone resorbing activity of osteoclasts. Unique to Cbl, but not present in Cbl-b, is tyrosine 737 in the YEAM motif, which upon phosphorylation provides a binding site for the regulatory p85 subunit of PI3K. Substitution of tyrosine 737 with phenylalanine (Y737F, CblYF/YF mice) prevents Y737 phosphorylation and abrogates the Cbl-PI3K interaction. We have previously reported that CblYF/YF mice had increased bone volume due to defective bone resorption and increased bone formation. Here we show that the lumbar vertebra from CblYF/YF mice did not have significant bone loss following ovariectomy. Our data also suggests that abrogation of Cbl-PI3K interaction in mice results in the loss of coupling between bone resorption and formation, since ovariectomized CblYF/YF mice did not show significant changes in serum levels of c-terminal telopeptide (CTX), whereas the serum levels of pro-collagen type-1 amino-terminal pro-peptide (P1NP) were decreased. In contrast, following ovariectomy, Cbl-/- and Cbl-b-/- mice showed significant bone loss in the tibiae and L2 vertebrae, concomitant with increased serum CTX and P1NP levels. These data indicate that while lack of Cbl or Cbl-b distinctly affects bone remodeling, only the loss of Cbl-PI3K interaction protects mice from significant bone loss following ovariectomy. Copyright © 2014 Elsevier Inc. All rights reserved.

Identifying the interacting roles of stressors in driving the global loss of canopy-forming to mat-forming algae in marine ecosystems.

PubMed

Strain, Elisabeth M A; Thomson, Russell J; Micheli, Fiorenza; Mancuso, Francesco P; Airoldi, Laura

2014-11-01

Identifying the type and strength of interactions between local anthropogenic and other stressors can help to set achievable management targets for degraded marine ecosystems and support their resilience by identifying local actions. We undertook a meta-analysis, using data from 118 studies to test the hypothesis that ongoing global declines in the dominant habitat along temperate rocky coastlines, forests of canopy-forming algae and/or their replacement by mat-forming algae are driven by the nonadditive interactions between local anthropogenic stressors that can be addressed through management actions (fishing, heavy metal pollution, nutrient enrichment and high sediment loads) and other stressors (presence of competitors or grazers, removal of canopy algae, limiting or excessive light, low or high salinity, increasing temperature, high wave exposure and high UV or CO2 ), not as easily amenable to management actions. In general, the cumulative effects of local anthropogenic and other stressors had negative effects on the growth and survival of canopy-forming algae. Conversely, the growth or survival of mat-forming algae was either unaffected or significantly enhanced by the same pairs of stressors. Contrary to our predictions, the majority of interactions between stressors were additive. There were however synergistic interactions between nutrient enrichment and heavy metals, the presence of competitors, low light and increasing temperature, leading to amplified negative effects on canopy-forming algae. There were also synergistic interactions between nutrient enrichment and increasing CO2 and temperature leading to amplified positive effects on mat-forming algae. Our review of the current literature shows that management of nutrient levels, rather than fishing, heavy metal pollution or high sediment loads, would provide the greatest opportunity for preventing the shift from canopy to mat-forming algae, particularly in enclosed bays or estuaries because of the

Co-morbidity and clinically significant interactions between antiepileptic drugs and other drugs in elderly patients with newly diagnosed epilepsy.

PubMed

Bruun, Emmi; Virta, Lauri J; Kälviäinen, Reetta; Keränen, Tapani

2017-08-01

A study was conducted to investigate the frequency of potential pharmacokinetic drug-to-drug interactions in elderly patients with newly diagnosed epilepsy. We also investigated co-morbid conditions associated with epilepsy. From the register of Kuopio University Hospital (KUH) we identified community-dwelling patients aged 65 or above with newly diagnosed epilepsy and in whom use of the first individual antiepileptic drug (AED) began in 2000-2013 (n=529). Furthermore, register data of the Social Insurance Institution of Finland were used for assessing potential interactions in a nationwide cohort of elderly subjects with newly diagnosed epilepsy. We extracted all patients aged 65 or above who had received special reimbursement for the cost of AEDs prescribed on account of epilepsy in 2012 where their first AED was recorded in 2011-2012 as monotherapy (n=1081). Clinically relevant drug interactions (of class C or D) at the time of starting of the first AED, as assessed via the SFINX-PHARAO database, were analysed. Hypertension (67%), dyslipidemia (45%), and ischaemic stroke (32%) were the most common co-morbid conditions in the hospital cohort of patients. In these patients, excessive polypharmacy (more than 10 concomitant drugs) was identified in 27% of cases. Of the patients started on carbamazepine, 52 subjects (32%) had one class-C or class-D drug interaction and 51 (31%) had two or more C- or D-class interactions. Only 2% of the subjects started on valproate exhibited a class-C interaction. None of the subjects using oxcarbazepine displayed class-C or class-D interactions. Patients with 3-5 (OR 4.22; p=0.05) or over six (OR 8.86; p=0.003) other drugs were more likely to have C- or D-class interaction. The most common drugs with potential interactions with carbamazepine were dihydropyridine calcium-blockers, statins, warfarin, and psychotropic drugs. Elderly patients with newly diagnosed epilepsy are at high risk of clinically relevant pharmacokinetic

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

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

PubMed

Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

2013-03-23

Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

Assessment of the significance of patent-derived information for the early identification of compound-target interaction hypotheses.

PubMed

Senger, Stefan

2017-04-21

Patents are an important source of information for effective decision making in drug discovery. Encouragingly, freely accessible patent-chemistry databases are now in the public domain. However, at present there is still a wide gap between relatively low coverage-high quality manually-curated data sources and high coverage data sources that use text mining and automated extraction of chemical structures. To secure much needed funding for further research and an improved infrastructure, hard evidence is required to demonstrate the significance of patent-derived information in drug discovery. Surprisingly little such evidence has been reported so far. To address this, the present study attempts to quantify the relevance of patents for formulating and substantiating hypotheses for compound-target interactions. A manually-curated set of 130 compound-target interaction pairs annotated with what are considered to be the earliest patent and publication has been produced. The analysis of this set revealed that in stark contrast to what has been reported for novel chemical structures, only about 10% of the compound-target interaction pairs could be found in publications in the scientific literature within one year of being reported in patents. The average delay across all interaction pairs is close to 4 years. In an attempt to benchmark current capabilities, it was also examined how much of the benefit of using patent-derived information can be retained when a bioannotated version of SureChEMBL is used as secondary source for the patent literature. Encouragingly, this approach found the patents in the annotated set for 72% of the compound-target interaction pairs. Similarly, the effect of using the bioactivity database ChEMBL as secondary source for the scientific literature was studied. Here, the publications from the annotated set were only found for 46% of the compound-target interaction pairs. Patent-derived information is a significant enabler for formulating compound

Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool.

PubMed

Auerbach, Raymond K; Chen, Bin; Butte, Atul J

2013-08-01

Biological analysis has shifted from identifying genes and transcripts to mapping these genes and transcripts to biological functions. The ENCODE Project has generated hundreds of ChIP-Seq experiments spanning multiple transcription factors and cell lines for public use, but tools for a biomedical scientist to analyze these data are either non-existent or tailored to narrow biological questions. We present the ENCODE ChIP-Seq Significance Tool, a flexible web application leveraging public ENCODE data to identify enriched transcription factors in a gene or transcript list for comparative analyses. The ENCODE ChIP-Seq Significance Tool is written in JavaScript on the client side and has been tested on Google Chrome, Apple Safari and Mozilla Firefox browsers. Server-side scripts are written in PHP and leverage R and a MySQL database. The tool is available at http://encodeqt.stanford.edu. abutte@stanford.edu Supplementary material is available at Bioinformatics online.

Significance of investigating allelopathic interactions of marine organisms in the discovery and development of cytotoxic compounds.

PubMed

Singh, Anshika; Thakur, Narsinh L

2016-01-05

Marine sessile organisms often inhabit rocky substrata, which are crowded by other sessile organisms. They acquire living space via growth interactions and/or by allelopathy. They are known to secrete toxic compounds having multiple roles. These compounds have been explored for their possible applications in cancer chemotherapy, because of their ability to kill rapidly dividing cells of competitor organisms. As compared to the therapeutic applications of these compounds, their possible ecological role in competition for space has received little attention. To select the potential candidate organisms for the isolation of lead cytotoxic molecules, it is important to understand their chemical ecology with special emphasis on their allelopathic interactions with their competitors. Knowledge of the ecological role of allelopathic compounds will contribute significantly to an understanding of their natural variability and help us to plan effective and sustainable wild harvests to obtain novel cytotoxic chemicals. This review highlights the significance of studying allelopathic interactions of marine invertebrates in the discovery of cytotoxic compounds, by selecting sponge as a model organism. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Temporospatial dynamics and public health significance of bacterial flora identified on a major leatherback turtle (Dermochelys coriacea) nesting beach in the Southern Caribbean

USGS Publications Warehouse

Phillips, Ayanna Carla N.; Couteau, Johanna; Rajh, Stacy; Stewart, Neville; Watson, Antonio; Jehu, Adam; Asmath, Hamish; Unakal, Chandrashekhar; Dziva, Francis; Holder, Ridley; Carthy, Raymond R.

2017-01-01

Grande Riviere beach, on the island of Trinidad, supports the largest nesting population of leatherback turtles in the Caribbean region. Throughout the nesting season, nests are naturally disturbed by newly nesting females, resulting in egg breakage and loss of some nest viability. This environment is ideal for the growth and proliferation of microorganisms. The range of bacterial flora present in beach sand and egg shells was examined, with emphasis on bacteria that may pose a threat to public and animal health. The extent to which the bacterial load and genera on the beach changed throughout the season was also assessed. Twenty-five genera were identified, with Pseudomonas spp. found to be the most predominant environmental bacteria. Four genera identified possess zoonotic potential, while five additional genera are known to be of public and animal health significance. Distinct shifts in the density and distribution of bacteria were observed along the beach from early to peak nesting season. Shifts were seen across heavily traversed zones, thus highlighting the potential exposure threats posed to beach visitors and animals alike. Further studies aimed at speciating this population of bacteria, as well as isolating potential fungal pathogens may mitigate this threat. Identification of bacterial agents that are specifically pathogenic to leatherback turtles, turtle eggs, hatchlings and those who may interact with these animals will serve to enhance and guide efforts to better conserve this species and protect the health of all who visit this ecologically significant site.

A proteomics method using immunoaffinity fluorogenic derivatization-liquid chromatography/tandem mass spectrometry (FD-LC-MS/MS) to identify a set of interacting proteins.

PubMed

Nakata, Katsunori; Saitoh, Ryoichi; Ishigai, Masaki; Imai, Kazuhiro

2018-02-01

Biological functions in organisms are usually controlled by a set of interacting proteins, and identifying the proteins that interact is useful for understanding the mechanism of the functions. Immunoprecipitation is a method that utilizes the affinity of an antibody to isolate and identify the proteins that have interacted in a biological sample. In this study, the FD-LC-MS/MS method, which involves fluorogenic derivatization followed by separation and quantification by HPLC and finally identification of proteins by HPLC-tandem mass spectrometry, was used to identify proteins in immunoprecipitated samples, using heat shock protein 90 (HSP90) as a model of an interacting protein in HepaRG cells. As a result, HSC70 protein, which was known to form a complex with HSP90, was isolated, together with three different types of HSP90-beta. The results demonstrated that the proposed immunoaffinity-FD-LC-MS/MS method could be useful for simultaneously detecting and identifying the proteins that interact with a certain protein. Copyright © 2017 John Wiley & Sons, Ltd.

Displacement of Drugs from Human Serum Albumin: From Molecular Interactions to Clinical Significance.

PubMed

Rimac, Hrvoje; Debeljak, Željko; Bojić, Mirza; Miller, Larisa

2017-01-01

Human serum albumin (HSA) is the most abundant protein in human serum. It has numerous functions, one of which is transport of small hydrophobic molecules, including drugs, toxins, nutrients, hormones and metabolites. HSA has the ability to interact with a wide variety of structurally different compounds. This promiscuous, nonspecific affinity can lead to sudden changes in concentrations caused by displacement, when two or more compounds compete for binding to the same molecular site. It is important to consider drug combinations and their binding to HSA when defining dosing regimens, as this can directly influence drug's free, active concentration in blood. In present paper we review drug interactions with potential for displacement from HSA, situations in which they are likely to occur and their clinical significance. We also offer guidelines in designing drugs with decreased binding to HSA. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Pathway Interaction Network Analysis Identifies Dysregulated Pathways in Human Monocytes Infected by Listeria monocytogenes.

PubMed

Fan, Wufeng; Zhou, Yuhan; Li, Hao

2017-01-01

In our study, we aimed to extract dysregulated pathways in human monocytes infected by Listeria monocytogenes (LM) based on pathway interaction network (PIN) which presented the functional dependency between pathways. After genes were aligned to the pathways, principal component analysis (PCA) was used to calculate the pathway activity for each pathway, followed by detecting seed pathway. A PIN was constructed based on gene expression profile, protein-protein interactions (PPIs), and cellular pathways. Identifying dysregulated pathways from the PIN was performed relying on seed pathway and classification accuracy. To evaluate whether the PIN method was feasible or not, we compared the introduced method with standard network centrality measures. The pathway of RNA polymerase II pretranscription events was selected as the seed pathway. Taking this seed pathway as start, one pathway set (9 dysregulated pathways) with AUC score of 1.00 was identified. Among the 5 hub pathways obtained using standard network centrality measures, 4 pathways were the common ones between the two methods. RNA polymerase II transcription and DNA replication owned a higher number of pathway genes and DEGs. These dysregulated pathways work together to influence the progression of LM infection, and they will be available as biomarkers to diagnose LM infection.

Protein-protein interaction networks identify targets which rescue the MPP+ cellular model of Parkinson’s disease

NASA Astrophysics Data System (ADS)

Keane, Harriet; Ryan, Brent J.; Jackson, Brendan; Whitmore, Alan; Wade-Martins, Richard

2015-11-01

Neurodegenerative diseases are complex multifactorial disorders characterised by the interplay of many dysregulated physiological processes. As an exemplar, Parkinson’s disease (PD) involves multiple perturbed cellular functions, including mitochondrial dysfunction and autophagic dysregulation in preferentially-sensitive dopamine neurons, a selective pathophysiology recapitulated in vitro using the neurotoxin MPP+. Here we explore a network science approach for the selection of therapeutic protein targets in the cellular MPP+ model. We hypothesised that analysis of protein-protein interaction networks modelling MPP+ toxicity could identify proteins critical for mediating MPP+ toxicity. Analysis of protein-protein interaction networks constructed to model the interplay of mitochondrial dysfunction and autophagic dysregulation (key aspects of MPP+ toxicity) enabled us to identify four proteins predicted to be key for MPP+ toxicity (P62, GABARAP, GBRL1 and GBRL2). Combined, but not individual, knockdown of these proteins increased cellular susceptibility to MPP+ toxicity. Conversely, combined, but not individual, over-expression of the network targets provided rescue of MPP+ toxicity associated with the formation of autophagosome-like structures. We also found that modulation of two distinct proteins in the protein-protein interaction network was necessary and sufficient to mitigate neurotoxicity. Together, these findings validate our network science approach to multi-target identification in complex neurological diseases.

Physiological Significance of Low Atmospheric CO 2 for Plant-Climate Interactions

NASA Astrophysics Data System (ADS)

Cowling, Sharon A.; Sykes, Martin T.

1999-09-01

Methods of palaeoclimate reconstruction from pollen are built upon the assumption that plant-climate interactions remain the same through time or that these interactions are independent of changes in atmospheric CO2. The latter may be problematic because air trapped in polar ice caps indicates that atmospheric CO2 has fluctuated significantly over at least the past 400,000 yr, and likely the last 1.6 million yr. Three other points indicate potential biases for vegetation-based climate proxies. First, C3-plant physiological research shows that the processes that determine growth optima in plants (photosynthesis, mitochondrial respiration, photorespiration) are all highly CO2-dependent, and thus were likely affected by the lower CO2 levels of the last glacial maximum. Second, the ratio of carbon assimilation per unit transpiration (called water-use efficiency) is sensitive to changes in atmospheric CO2 through effects on stomatal conductance and may have altered C3-plant responses to drought. Third, leaf gas-exchange experiments indicate that the response of plants to carbon-depleting environmental stresses are strengthened under low CO2 relative to today. This paper reviews the scope of research addressing the consequences of low atmospheric CO2 for plant and ecosystem processes and highlights why consideration of the physiological effects of low atmospheric CO2 on plant function is recommended for any future refinements to pollen-based palaeoclimatic reconstructions.

Gene interactions in the DNA damage-response pathway identified by genome-wide RNA-interference analysis of synthetic lethality

PubMed Central

van Haaften, Gijs; Vastenhouw, Nadine L.; Nollen, Ellen A. A.; Plasterk, Ronald H. A.; Tijsterman, Marcel

2004-01-01

Here, we describe a systematic search for synthetic gene interactions in a multicellular organism, the nematode Caenorhabditis elegans. We established a high-throughput method to determine synthetic gene interactions by genome-wide RNA interference and identified genes that are required to protect the germ line against DNA double-strand breaks. Besides known DNA-repair proteins such as the C. elegans orthologs of TopBP1, RPA2, and RAD51, eight genes previously unassociated with a double-strand-break response were identified. Knockdown of these genes increased sensitivity to ionizing radiation and camptothecin and resulted in increased chromosomal nondisjunction. All genes have human orthologs that may play a role in human carcinogenesis. PMID:15326288

Comparison of Four Views to Single-view Ultrasound Protocols to Identify Clinically Significant Pneumothorax.

PubMed

Helland, Gregg; Gaspari, Romolo; Licciardo, Samuel; Sanseverino, Alexandra; Torres, Ulises; Emhoff, Timothy; Blehar, David

2016-10-01

Ultrasound (US) has been shown to be effective at identifying a pneumothorax (PTX); however, the additional value of adding multiple views has not been studied. Single- and four-view protocols have both been described in the literature. The objective of this study was to compare the diagnostic accuracy of single-view versus four-view lung US to detect clinically significant PTX in trauma patients. This was a randomized, prospective trial on trauma patients. Adult patients with acute traumatic injury undergoing computed tomography (CT) scan of the chest were eligible for enrollment. Patients were randomized to a single view or four views of each hemithorax prior to any imaging. USs were performed and interpreted by credentialed physicians using a 7.5-Mhz linear array transducer on a portable US machine with digital clips recorded for later review. Attending radiologist interpretation of the chest CT was reviewed for presence or absence of PTX with descriptions of small foci of air or minimal PTX categorized as clinically insignificant. A total of 260 patients were enrolled over a 2-year period. A total of 139 patients received a single view of each chest wall and 121 patients received four views. There were a total of 49 patients that had a PTX (19%), and 29 of these were clinically significant (11%). In diagnosis of any PTX, both single-view and four-view techniques showed poor sensitivity (54.2 and 68%) but high specificity (99 and 98%). For clinically significant PTX, single-view US demonstrated a sensitivity of 93% (95% confidence interval [CI] = 64.1% to 99.6%) and a specificity of 99.2% (95% CI = 95.5% to 99.9%), with sensitivity of 93.3% (95% CI = 66% to 99.7%) and specificity of 98% (95% CI = 92.1% to 99.7%) for four views. Single-view and four-view chest wall USs demonstrate comparable sensitivity and specificity for PTX. The additional time to obtain four views should be weighed against the absence of additional diagnostic yield over a single view when

COMPARATIVE DIVERSITY OF FECAL BACTERIA IN AGRICULTURALLY SIGNIFICANT ANIMALS TO IDENTIFY ALTERNATIVE TARGETS FOR MICROBIAL SOURCE TRACKING

EPA Science Inventory

Animals of agricultural significance contribute a large percentage of fecal pollution to waterways via runoff contamination. The premise of microbial source tracking is to utilize fecal bacteria to identify target populations which are directly correlated to specific animal feces...

Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions

DOE PAGES

Shatsky, Maxim; Dong, Ming; Liu, Haichuan; ...

2016-04-20

Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification ofmore » endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.« less

Quantitative Tagless Copurification: A Method to Validate and Identify Protein-Protein Interactions

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

Shatsky, Maxim; Dong, Ming; Liu, Haichuan

Identifying protein-protein interactions (PPIs) at an acceptable false discovery rate (FDR) is challenging. Previously we identified several hundred PPIs from affinity purification - mass spectrometry (AP-MS) data for the bacteria Escherichia coli and Desulfovibrio vulgaris. These two interactomes have lower FDRs than any of the nine interactomes proposed previously for bacteria and are more enriched in PPIs validated by other data than the nine earlier interactomes. To more thoroughly determine the accuracy of ours or other interactomes and to discover further PPIs de novo, here we present a quantitative tagless method that employs iTRAQ MS to measure the copurification ofmore » endogenous proteins through orthogonal chromatography steps. 5273 fractions from a four-step fractionation of a D. vulgaris protein extract were assayed, resulting in the detection of 1242 proteins. Protein partners from our D. vulgaris and E. coli AP-MS interactomes copurify as frequently as pairs belonging to three benchmark data sets of well-characterized PPIs. In contrast, the protein pairs from the nine other bacterial interactomes copurify two- to 20-fold less often. We also identify 200 high confidence D. vulgaris PPIs based on tagless copurification and colocalization in the genome. These PPIs are as strongly validated by other data as our AP-MS interactomes and overlap with our AP-MS interactome for D.vulgaris within 3% of expectation, once FDRs and false negative rates are taken into account. Finally, we reanalyzed data from two quantitative tagless screens of human cell extracts. We estimate that the novel PPIs reported in these studies have an FDR of at least 85% and find that less than 7% of the novel PPIs identified in each screen overlap. Our results establish that a quantitative tagless method can be used to validate and identify PPIs, but that such data must be analyzed carefully to minimize the FDR.« less

SigTree: A Microbial Community Analysis Tool to Identify and Visualize Significantly Responsive Branches in a Phylogenetic Tree.

PubMed

Stevens, John R; Jones, Todd R; Lefevre, Michael; Ganesan, Balasubramanian; Weimer, Bart C

2017-01-01

Microbial community analysis experiments to assess the effect of a treatment intervention (or environmental change) on the relative abundance levels of multiple related microbial species (or operational taxonomic units) simultaneously using high throughput genomics are becoming increasingly common. Within the framework of the evolutionary phylogeny of all species considered in the experiment, this translates to a statistical need to identify the phylogenetic branches that exhibit a significant consensus response (in terms of operational taxonomic unit abundance) to the intervention. We present the R software package SigTree , a collection of flexible tools that make use of meta-analysis methods and regular expressions to identify and visualize significantly responsive branches in a phylogenetic tree, while appropriately adjusting for multiple comparisons.

Multiple Changes to Reusable Solid Rocket Motors, Identifying Hidden Risks

NASA Technical Reports Server (NTRS)

Greenhalgh, Phillip O.; McCann, Bradley Q.

2003-01-01

The Space Shuttle Reusable Solid Rocket Motor (RSRM) baseline is subject to various changes. Changes are necessary due to safety and quality improvements, environmental considerations, vendor changes, obsolescence issues, etc. The RSRM program has a goal to test changes on full-scale static test motors prior to flight due to the unique RSRM operating environment. Each static test motor incorporates several significant changes and numerous minor changes. Flight motors often implement multiple changes simultaneously. While each change is individually verified and assessed, the potential for changes to interact constitutes additional hidden risk. Mitigating this risk depends upon identification of potential interactions. Therefore, the ATK Thiokol Propulsion System Safety organization initiated the use of a risk interaction matrix to identify potential interactions that compound risk. Identifying risk interactions supports flight and test motor decisions. Uncovering hidden risks of a full-scale static test motor gives a broader perspective of the changes being tested. This broader perspective compels the program to focus on solutions for implementing RSRM changes with minimal/mitigated risk. This paper discusses use of a change risk interaction matrix to identify test challenges and uncover hidden risks to the RSRM program.

Kernel Density Surface Modelling as a Means to Identify Significant Concentrations of Vulnerable Marine Ecosystem Indicators

PubMed Central

Kenchington, Ellen; Murillo, Francisco Javier; Lirette, Camille; Sacau, Mar; Koen-Alonso, Mariano; Kenny, Andrew; Ollerhead, Neil; Wareham, Vonda; Beazley, Lindsay

2014-01-01

The United Nations General Assembly Resolution 61/105, concerning sustainable fisheries in the marine ecosystem, calls for the protection of vulnerable marine ecosystems (VME) from destructive fishing practices. Subsequently, the Food and Agriculture Organization (FAO) produced guidelines for identification of VME indicator species/taxa to assist in the implementation of the resolution, but recommended the development of case-specific operational definitions for their application. We applied kernel density estimation (KDE) to research vessel trawl survey data from inside the fishing footprint of the Northwest Atlantic Fisheries Organization (NAFO) Regulatory Area in the high seas of the northwest Atlantic to create biomass density surfaces for four VME indicator taxa: large-sized sponges, sea pens, small and large gorgonian corals. These VME indicator taxa were identified previously by NAFO using the fragility, life history characteristics and structural complexity criteria presented by FAO, along with an evaluation of their recovery trajectories. KDE, a non-parametric neighbour-based smoothing function, has been used previously in ecology to identify hotspots, that is, areas of relatively high biomass/abundance. We present a novel approach of examining relative changes in area under polygons created from encircling successive biomass categories on the KDE surface to identify “significant concentrations” of biomass, which we equate to VMEs. This allows identification of the VMEs from the broader distribution of the species in the study area. We provide independent assessments of the VMEs so identified using underwater images, benthic sampling with other gear types (dredges, cores), and/or published species distribution models of probability of occurrence, as available. For each VME indicator taxon we provide a brief review of their ecological function which will be important in future assessments of significant adverse impact on these habitats here and

Kernel density surface modelling as a means to identify significant concentrations of vulnerable marine ecosystem indicators.

PubMed

Kenchington, Ellen; Murillo, Francisco Javier; Lirette, Camille; Sacau, Mar; Koen-Alonso, Mariano; Kenny, Andrew; Ollerhead, Neil; Wareham, Vonda; Beazley, Lindsay

2014-01-01

The United Nations General Assembly Resolution 61/105, concerning sustainable fisheries in the marine ecosystem, calls for the protection of vulnerable marine ecosystems (VME) from destructive fishing practices. Subsequently, the Food and Agriculture Organization (FAO) produced guidelines for identification of VME indicator species/taxa to assist in the implementation of the resolution, but recommended the development of case-specific operational definitions for their application. We applied kernel density estimation (KDE) to research vessel trawl survey data from inside the fishing footprint of the Northwest Atlantic Fisheries Organization (NAFO) Regulatory Area in the high seas of the northwest Atlantic to create biomass density surfaces for four VME indicator taxa: large-sized sponges, sea pens, small and large gorgonian corals. These VME indicator taxa were identified previously by NAFO using the fragility, life history characteristics and structural complexity criteria presented by FAO, along with an evaluation of their recovery trajectories. KDE, a non-parametric neighbour-based smoothing function, has been used previously in ecology to identify hotspots, that is, areas of relatively high biomass/abundance. We present a novel approach of examining relative changes in area under polygons created from encircling successive biomass categories on the KDE surface to identify "significant concentrations" of biomass, which we equate to VMEs. This allows identification of the VMEs from the broader distribution of the species in the study area. We provide independent assessments of the VMEs so identified using underwater images, benthic sampling with other gear types (dredges, cores), and/or published species distribution models of probability of occurrence, as available. For each VME indicator taxon we provide a brief review of their ecological function which will be important in future assessments of significant adverse impact on these habitats here and elsewhere.

Identifying Best Practices for an Interactive Webinar

ERIC Educational Resources Information Center

Zoumenou, Virginie; Sigman-Grant, Madeleine; Coleman, Gayle; Malekian, Fatemeh; Zee, Julia M. K.; Fountain, Brent J.; Marsh, Akela

2015-01-01

A webinar or web-seminar is a presentation, seminar, lecture, or workshop transmitted over the internet. This emerging technology is becoming increasingly popular due to its convenience and affordability. However, little research has been conducted on best practices for an interactive webinar that engages learners in a professional development or…

Authentic early experience in Medical Education: a socio-cultural analysis identifying important variables in learning interactions within workplaces.

PubMed

Yardley, Sarah; Brosnan, Caragh; Richardson, Jane; Hays, Richard

2013-12-01

This paper addresses the question 'what are the variables influencing social interactions and learning during Authentic Early Experience (AEE)?' AEE is a complex educational intervention for new medical students. Following critique of the existing literature, multiple qualitative methods were used to create a study framework conceptually orientated to a socio-cultural perspective. Study participants were recruited from three groups at one UK medical school: students, workplace supervisors, and medical school faculty. A series of intersecting spectra identified in the data describe dyadic variables that make explicit the parameters within which social interactions are conducted in this setting. Four of the spectra describe social processes related to being in workplaces and developing the ability to manage interactions during authentic early experiences. These are: (1) legitimacy expressed through invited participation or exclusion; (2) finding a role-a spectrum from student identity to doctor mindset; (3) personal perspectives and discomfort in transition from lay to medical; and, (4) taking responsibility for 'risk'-moving from aversion to management through graded progression of responsibility. Four further spectra describe educational consequences of social interactions. These spectra identify how the reality of learning is shaped through social interactions and are (1) generic-specific objectives, (2) parallel-integrated-learning, (3) context specific-transferable learning and (4) performing or simulating-reality. Attention to these variables is important if educators are to maximise constructive learning from AEE. Application of each of the spectra could assist workplace supervisors to maximise the positive learning potential of specific workplaces.

Identifying the regional-scale groundwater-surface water interaction on the Sanjiang Plain, Northeast China.

PubMed

Wang, Xihua; Zhang, Guangxin; Xu, Y Jun; Sun, Guangzhi

2015-11-01

Assessment on the interaction between groundwater and surface water (GW-SW) can generate information that is critical to regional water resource management, especially for regions that are highly dependent on groundwater resources for irrigation. This study investigated such interaction on China's Sanjiang Plain (10.9 × 10(4) km(2)) and produced results to assist sustainable regional water management for intensive agricultural activities. Methods of hierarchical cluster analysis (HCA), principal component analysis (PCA), and statistical analysis were used in this study. One hundred two water samplings (60 from shallow groundwater, 7 from deep groundwater, and 35 from surface water) were collected and grouped into three clusters and seven sub-clusters during the analyses. The PCA analysis identified four principal components of the interaction, which explained 85.9% variance of total database, attributed to the dissolution and evolution of gypsum, feldspar, and other natural minerals in the region that was affected by anthropic and geological (sedimentary rock mineral) activities. The analyses showed that surface water in the upper region of the Sanjiang Plain gained water from local shallow groundwater, indicating that the surface water in the upper region was relatively more resilient to withdrawal for usage, whereas in the middle region, there was only a weak interaction between shallow groundwater and surface water. In the lower region of the Sanjiang Plain, surface water lost water to shallow groundwater, indicating that the groundwater was vulnerable to pollution by pesticides and fertilizers from terrestrial sources.

Enhancing interacting residue prediction with integrated contact matrix prediction in protein-protein interaction.

PubMed

Du, Tianchuan; Liao, Li; Wu, Cathy H

2016-12-01

Identifying the residues in a protein that are involved in protein-protein interaction and identifying the contact matrix for a pair of interacting proteins are two computational tasks at different levels of an in-depth analysis of protein-protein interaction. Various methods for solving these two problems have been reported in the literature. However, the interacting residue prediction and contact matrix prediction were handled by and large independently in those existing methods, though intuitively good prediction of interacting residues will help with predicting the contact matrix. In this work, we developed a novel protein interacting residue prediction system, contact matrix-interaction profile hidden Markov model (CM-ipHMM), with the integration of contact matrix prediction and the ipHMM interaction residue prediction. We propose to leverage what is learned from the contact matrix prediction and utilize the predicted contact matrix as "feedback" to enhance the interaction residue prediction. The CM-ipHMM model showed significant improvement over the previous method that uses the ipHMM for predicting interaction residues only. It indicates that the downstream contact matrix prediction could help the interaction site prediction.

Participant Interaction in Asynchronous Learning Environments: Evaluating Interaction Analysis Methods

ERIC Educational Resources Information Center

Blanchette, Judith

2012-01-01

The purpose of this empirical study was to determine the extent to which three different objective analytical methods--sequence analysis, surface cohesion analysis, and lexical cohesion analysis--can most accurately identify specific characteristics of online interaction. Statistically significant differences were found in all points of…

Genome-wide interaction study identifies RCBTB1 as a modifier for smoking effect on carotid intima-media thickness.

PubMed

Wang, Liyong; Rundek, Tatjana; Beecham, Ashley; Hudson, Barry; Blanton, Susan H; Zhao, Hongyu; Sacco, Ralph L; Dong, Chuanhui

2014-01-01

Carotid intima-media thickness (cIMT), a marker for atherosclerosis, is affected by smoking and has substantial interindividual variation. We sought to identify the genetic moderators influencing the effect of smoking on cIMT. With a multistage design using 722 379 single nucleotide polymorphisms (SNP), a genome-wide interaction study was performed in a discovery sample of 669 Hispanics, followed by replication in 589 subjects (264 Hispanics, 172 non-Hispanic blacks, 153 non-Hispanic whites). Assuming an additive genetic model, regression analysis was performed to test for smoking-SNP interaction on cIMT while controlling for age, sex, and the top 3 principal components of ancestry. The strongest interaction in Hispanics was found with a synonymous splicing SNP (rs3751383) in exon 9 of RCBTB1 (P=2.5e(-6) in discovery sample; P=0.01 in the Hispanic replication sample; P<8.8e(-9) in the combined Hispanic sample). Stratification analysis in the combined Hispanic sample showed that smoking had no effect on cIMT among rs3751383 G homozygote (P=0.15), a moderate effect among rs3751383 heterozygote (P=0.01), and a strong effect among rs3751383 A homozygote (P=2.1e(-7)). A consistent trend was observed in the non-Hispanic white and black data sets, leading to an interaction effect of P<2.9e(-9) in the meta-analysis of all 1258 subjects. Our study represents the first genome-wide smoking-SNP interaction study of cIMT and identifies RCBTB1 as a modifier of the smoking effect on cIMT. Testing for gene-environment interactions can help uncover genetic factors that contribute to the interindividual variation in response to the same environmental exposure.

LNDriver: identifying driver genes by integrating mutation and expression data based on gene-gene interaction network.

PubMed

Wei, Pi-Jing; Zhang, Di; Xia, Junfeng; Zheng, Chun-Hou

2016-12-23

Cancer is a complex disease which is characterized by the accumulation of genetic alterations during the patient's lifetime. With the development of the next-generation sequencing technology, multiple omics data, such as cancer genomic, epigenomic and transcriptomic data etc., can be measured from each individual. Correspondingly, one of the key challenges is to pinpoint functional driver mutations or pathways, which contributes to tumorigenesis, from millions of functional neutral passenger mutations. In this paper, in order to identify driver genes effectively, we applied a generalized additive model to mutation profiles to filter genes with long length and constructed a new gene-gene interaction network. Then we integrated the mutation data and expression data into the gene-gene interaction network. Lastly, greedy algorithm was used to prioritize candidate driver genes from the integrated data. We named the proposed method Length-Net-Driver (LNDriver). Experiments on three TCGA datasets, i.e., head and neck squamous cell carcinoma, kidney renal clear cell carcinoma and thyroid carcinoma, demonstrated that the proposed method was effective. Also, it can identify not only frequently mutated drivers, but also rare candidate driver genes.

Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion

PubMed Central

Luisier, Raphaëlle; Unterberger, Elif B.; Goodman, Jay I.; Schwarz, Michael; Moggs, Jonathan; Terranova, Rémi; van Nimwegen, Erik

2014-01-01

Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesis. PMID:24464994

A hot spot for systemic lupus erythematosus, but not for psoriatic arthritis, identified by spatial analysis suggests an interaction between ethnicity and place of residence.

PubMed

Al-Maini, Mustafa; Jeyalingam, Thurarshen; Brown, Patrick; Lee, Jennifer J Y; Li, Lennon; Su, Jiandong; Gladman, Dafna D; Fortin, Paul R

2013-06-01

To describe the spatial distribution of incident cases of systemic lupus erythematosus (SLE) using geographic information systems (GIS). Spatial analyses were carried out on 890 SLE patients and 541 psoriatic arthritis (PsA) patients (controls). Age- and sex-adjusted rates for SLE/PsA for each census tract were calculated using denominator population values from the Canadian census. Spatial variations in relative risk were estimated by modeling risk as the product of a time effect, an age effect, and a spatially autocorrelated risk surface to identify hot spots. Patients within the detected hot spot were compared to those outside the hot spot to identify explanatory factors. SLE patients were predominantly female (87.75%) and the incidence rate was highest among those 15-19 years of age (2.4 cases/100,000 person-years). In an SLE hot spot containing 59 patients, 100% of the patients were female and 49.1% (n = 29) were Caucasian, while outside of the hot spot, 86.9% (n = 722) of the patients were female and 68.4% (n = 568) were Caucasian. The proportion of cases of Chinese ethnicity was significantly greater within the hot spot. An interaction was found between Chinese ethnicity and residence within the hot spot, with the risk of SLE to the Chinese population found to be twice the risk to the non-Chinese population. GIS was used to map SLE cases and a hot spot was identified after adjustment for age and sex. Ethnicity by itself did not confer an increased risk of SLE, but the interaction of ethnicity with location of residence significantly increased the risk of SLE. Copyright © 2013 by the American College of Rheumatology.

The significance of GW-SW interactions for biogeochemical processes in sandy streambeds

NASA Astrophysics Data System (ADS)

Arnon, Shai; De Falco, Natalie; Fox, Aryeh; Laube, Gerrit; Schmidt, Christian; Fleckenstein, Jan; Boano, Fulvio

2015-04-01

Stream-groundwater interactions have a major impact on hyporheic exchange fluxes in sandy streambeds. However, the physical complexity of natural streams has limited our ability to study these types of interactions systematically, and to evaluate their importance to biogeochemical processes and nutrient cycling. In this work we were able to quantify the effect of losing and gaining fluxes on hyporheic exchange and nutrient cycling in homogeneous and heterogeneous streambeds by combining experiments in laboratory flumes and modeling. Tracer experiments for measuring hyporheic exchange were done using dyes and NaCl under various combinations of overlying water velocity and losing or gaining fluxes. Nutrient cycling experiments were conducted after growing a benthic biofilm by spiking with Sodium Benzoate (as a source of labile dissolved organic carbon, DOC) and measuring DOC and oxygen dynamics. The combination of experimental observations and modeling revealed that interfacial transport increases with the streambed hydraulic conductivity and proportional to the square of the overlying water velocity. Hyporheic exchange fluxes under losing and gaining flow conditions were similar, and became smaller when the losing or gaining flux increases. Increasing in streambed hydraulic conductivity led to higher hyporheic fluxes and reduction in the effects of losing and gaining flow conditions to constrain exchange. Despite the evident effect of flow conditions on hyporheic exchange, labile DOC uptake was positively linked to increasing overlying water velocity but was not affected by losing and gaining fluxes. This is because microbial aerobic activity was taking place at the upper few millimeters of the streambed as shown by local oxygen consumption rates, which was measured using microelectrodes. Based on modeling work, it is expected that GW-SW interaction will be more significant for less labile DOC and anaerobic processes. Our results enable us to study systematically

Emphasizing the Significance of Electrostatic Interactions in Chemical Bonding

ERIC Educational Resources Information Center

Venkataraman, Bhawani

2017-01-01

This paper describes a pedagogical approach to help students understand chemical bonding by emphasizing the importance of electrostatic interactions between atoms. The approach draws on prior studies that have indicated many misconceptions among students in understanding the nature of the chemical bond and energetics associated with bond formation…

Combining a nontargeted and targeted metabolomics approach to identify metabolic pathways significantly altered in polycystic ovary syndrome.

PubMed

Chang, Alice Y; Lalia, Antigoni Z; Jenkins, Gregory D; Dutta, Tumpa; Carter, Rickey E; Singh, Ravinder J; Nair, K Sreekumaran

2017-06-01

Polycystic ovary syndrome (PCOS) is a condition of androgen excess and chronic anovulation frequently associated with insulin resistance. We combined a nontargeted and targeted metabolomics approach to identify pathways and metabolites that distinguished PCOS from metabolic syndrome (MetS). Twenty obese women with PCOS were compared with 18 obese women without PCOS. Both groups met criteria for MetS but could not have diabetes mellitus or take medications that treat PCOS or affect lipids or insulin sensitivity. Insulin sensitivity was derived from the frequently sampled intravenous glucose tolerance test. A nontargeted metabolomics approach was performed on fasting plasma samples to identify differentially expressed metabolites, which were further evaluated by principal component and pathway enrichment analysis. Quantitative targeted metabolomics was then applied on candidate metabolites. Measured metabolites were tested for associations with PCOS and clinical variables by logistic and linear regression analyses. This multiethnic, obese sample was matched by age (PCOS, 37±6; MetS, 40±6years) and body mass index (BMI) (PCOS, 34.6±5.1; MetS, 33.7±5.2kg/m 2 ). Principal component analysis of the nontargeted metabolomics data showed distinct group separation of PCOS from MetS controls. From the subset of 385 differentially expressed metabolites, 22% were identified by accurate mass, resulting in 19 canonical pathways significantly altered in PCOS, including amino acid, lipid, steroid, carbohydrate, and vitamin D metabolism. Targeted metabolomics identified many essential amino acids, including branched-chain amino acids (BCAA) that were elevated in PCOS compared with MetS. PCOS was most associated with BCAA (P=.02), essential amino acids (P=.03), the essential amino acid lysine (P=.02), and the lysine metabolite α-aminoadipic acid (P=.02) in models adjusted for surrogate variables representing technical variation in metabolites. No significant differences between

Combining a Nontargeted and Targeted Metabolomics Approach to Identify Metabolic Pathways Significantly Altered in Polycystic Ovary Syndrome

PubMed Central

Chang, Alice Y.; Lalia, Antigoni Z.; Jenkins, Gregory D.; Dutta, Tumpa; Carter, Rickey E.; Singh, Ravinder J.; Sreekumaran Nair, K.

2017-01-01

Objective Polycystic ovary syndrome (PCOS) is a condition of androgen excess and chronic anovulation frequently associated with insulin resistance. We combined a nontargeted and targeted metabolomics approach to identify pathways and metabolites that distinguished PCOS from metabolic syndrome (MetS). Methods Twenty obese women with PCOS were compared with 18 obese women without PCOS. Both groups met criteria for MetS but could not have diabetes mellitus or take medications that treat PCOS or affect lipids or insulin sensitivity. Insulin sensitivity was derived from the frequently sampled intravenous glucose tolerance test. A nontargeted metabolomics approach was performed on fasting plasma samples to identify differentially expressed metabolites, which were further evaluated by principal component and pathway enrichment analysis. Quantitative targeted metabolomics was then applied on candidate metabolites. Measured metabolites were tested for associations with PCOS and clinical variables by logistic and linear regression analyses. Results This multiethnic, obese sample was matched by age (PCOS, 37 ± 6; MetS, 40 ± 6 years) and body mass index (BMI) (PCOS, 34.6 ± 5.1; MetS, 33.7 ± 5.2 kg/m2). Principal component analysis of the nontargeted metabolomics data showed distinct group separation of PCOS from MetS controls. From the subset of 385 differentially expressed metabolites, 22% were identified by accurate mass, resulting in 19 canonical pathways significantly altered in PCOS, including amino acid, lipid, steroid, carbohydrate, and vitamin D metabolism. Targeted metabolomics identified many essential amino acids, including branched-chain amino acids (BCAA) that were elevated in PCOS compared with MetS. PCOS was most associated with BCAA (P = .02), essential amino acids (P = .03), the essential amino acid lysine (P = .02), and the lysine metabolite α-aminoadipic acid (P = .02) in models adjusted for surrogate variables representing technical variation in

Effectively identifying compound-protein interactions by learning from positive and unlabeled examples.

PubMed

Cheng, Zhanzhan; Zhou, Shuigeng; Wang, Yang; Liu, Hui; Guan, Jihong; Chen, Yi-Ping Phoebe

2016-05-18

Prediction of compound-protein interactions (CPIs) is to find new compound-protein pairs where a protein is targeted by at least a compound, which is a crucial step in new drug design. Currently, a number of machine learning based methods have been developed to predict new CPIs in the literature. However, as there is not yet any publicly available set of validated negative CPIs, most existing machine learning based approaches use the unknown interactions (not validated CPIs) selected randomly as the negative examples to train classifiers for predicting new CPIs. Obviously, this is not quite reasonable and unavoidably impacts the CPI prediction performance. In this paper, we simply take the unknown CPIs as unlabeled examples, and propose a new method called PUCPI (the abbreviation of PU learning for Compound-Protein Interaction identification) that employs biased-SVM (Support Vector Machine) to predict CPIs using only positive and unlabeled examples. PU learning is a class of learning methods that leans from positive and unlabeled (PU) samples. To the best of our knowledge, this is the first work that identifies CPIs using only positive and unlabeled examples. We first collect known CPIs as positive examples and then randomly select compound-protein pairs not in the positive set as unlabeled examples. For each CPI/compound-protein pair, we extract protein domains as protein features and compound substructures as chemical features, then take the tensor product of the corresponding compound features and protein features as the feature vector of the CPI/compound-protein pair. After that, biased-SVM is employed to train classifiers on different datasets of CPIs and compound-protein pairs. Experiments over various datasets show that our method outperforms six typical classifiers, including random forest, L1- and L2-regularized logistic regression, naive Bayes, SVM and k-nearest neighbor (kNN), and three types of existing CPI prediction models. Source code, datasets and

Co-evolutionary Analysis of Domains in Interacting Proteins Reveals Insights into Domain–Domain Interactions Mediating Protein–Protein Interactions

PubMed Central

Jothi, Raja; Cherukuri, Praveen F.; Tasneem, Asba; Przytycka, Teresa M.

2006-01-01

Recent advances in functional genomics have helped generate large-scale high-throughput protein interaction data. Such networks, though extremely valuable towards molecular level understanding of cells, do not provide any direct information about the regions (domains) in the proteins that mediate the interaction. Here, we performed co-evolutionary analysis of domains in interacting proteins in order to understand the degree of co-evolution of interacting and non-interacting domains. Using a combination of sequence and structural analysis, we analyzed protein–protein interactions in F1-ATPase, Sec23p/Sec24p, DNA-directed RNA polymerase and nuclear pore complexes, and found that interacting domain pair(s) for a given interaction exhibits higher level of co-evolution than the noninteracting domain pairs. Motivated by this finding, we developed a computational method to test the generality of the observed trend, and to predict large-scale domain–domain interactions. Given a protein–protein interaction, the proposed method predicts the domain pair(s) that is most likely to mediate the protein interaction. We applied this method on the yeast interactome to predict domain–domain interactions, and used known domain–domain interactions found in PDB crystal structures to validate our predictions. Our results show that the prediction accuracy of the proposed method is statistically significant. Comparison of our prediction results with those from two other methods reveals that only a fraction of predictions are shared by all the three methods, indicating that the proposed method can detect known interactions missed by other methods. We believe that the proposed method can be used with other methods to help identify previously unrecognized domain–domain interactions on a genome scale, and could potentially help reduce the search space for identifying interaction sites. PMID:16949097

Identifying Significant Changes in Cerebrovascular Reactivity to Carbon Dioxide.

PubMed

Sobczyk, O; Crawley, A P; Poublanc, J; Sam, K; Mandell, D M; Mikulis, D J; Duffin, J; Fisher, J A

2016-05-01

Changes in cerebrovascular reactivity can be used to assess disease progression and response to therapy but require discrimination of pathology from normal test-to-test variability. Such variability is due to variations in methodology, technology, and physiology with time. With uniform test conditions, our aim was to determine the test-to-test variability of cerebrovascular reactivity in healthy subjects and in patients with known cerebrovascular disease. Cerebrovascular reactivity was the ratio of the blood oxygen level-dependent MR imaging response divided by the change in carbon dioxide stimulus. Two standardized cerebrovascular reactivity tests were conducted at 3T in 15 healthy men (36.7 ± 16.1 years of age) within a 4-month period and were coregistered into standard space to yield voxelwise mean cerebrovascular reactivity interval difference measures, composing a reference interval difference atlas. Cerebrovascular reactivity interval difference maps were prepared for 11 male patients. For each patient, the test-retest difference of each voxel was scored statistically as z-values of the corresponding voxel mean difference in the reference atlas and then color-coded and superimposed on the anatomic images to create cerebrovascular reactivity interval difference z-maps. There were no significant test-to-test differences in cerebrovascular reactivity in either gray or white matter (mean gray matter, P = .431; mean white matter, P = .857; paired t test) in the healthy cohort. The patient cerebrovascular reactivity interval difference z-maps indicated regions where cerebrovascular reactivity increased or decreased and the probability that the changes were significant. Accounting for normal test-to-test differences in cerebrovascular reactivity enables the assessment of significant changes in disease status (stability, progression, or regression) in patients with time. © 2016 by American Journal of Neuroradiology.

Genome-wide significant localization for working and spatial memory: Identifying genes for psychosis using models of cognition.

PubMed

Knowles, Emma E M; Carless, Melanie A; de Almeida, Marcio A A; Curran, Joanne E; McKay, D Reese; Sprooten, Emma; Dyer, Thomas D; Göring, Harald H; Olvera, Rene; Fox, Peter; Almasy, Laura; Duggirala, Ravi; Kent, Jack W; Blangero, John; Glahn, David C

2014-01-01

It is well established that risk for developing psychosis is largely mediated by the influence of genes, but identifying precisely which genes underlie that risk has been problematic. Focusing on endophenotypes, rather than illness risk, is one solution to this problem. Impaired cognition is a well-established endophenotype of psychosis. Here we aimed to characterize the genetic architecture of cognition using phenotypically detailed models as opposed to relying on general IQ or individual neuropsychological measures. In so doing we hoped to identify genes that mediate cognitive ability, which might also contribute to psychosis risk. Hierarchical factor models of genetically clustered cognitive traits were subjected to linkage analysis followed by QTL region-specific association analyses in a sample of 1,269 Mexican American individuals from extended pedigrees. We identified four genome wide significant QTLs, two for working and two for spatial memory, and a number of plausible and interesting candidate genes. The creation of detailed models of cognition seemingly enhanced the power to detect genetic effects on cognition and provided a number of possible candidate genes for psychosis. © 2013 Wiley Periodicals, Inc.

Large Frequency Change with Thickness in Interlayer Breathing Mode—Significant Interlayer Interactions in Few Layer Black Phosphorus

NASA Astrophysics Data System (ADS)

Luo, Xin; Lu, Xin; Koon, Gavin Kok Wai; Castro Neto, Antonio H.; Özyilmaz, Barbaros; Xiong, Qihua; Quek, Su Ying

2015-06-01

Bulk black phosphorus (BP) consists of puckered layers of phosphorus atoms. Few-layer BP, obtained from bulk BP by exfoliation, is an emerging candidate as a channel material in post-silicon electronics. A deep understanding of its physical properties and its full range of applications are still being uncovered. In this paper, we present a theoretical and experimental investigation of phonon properties in few-layer BP, focusing on the low-frequency regime corresponding to interlayer vibrational modes. We show that the interlayer breathing mode A3g shows a large redshift with increasing thickness; the experimental and theoretical results agreeing well. This thickness dependence is two times larger than that in the chalcogenide materials such as few-layer MoS2 and WSe2, because of the significantly larger interlayer force constant and smaller atomic mass in BP. The derived interlayer out-of-plane force constant is about 50% larger than that in graphene and MoS2. We show that this large interlayer force constant arises from the sizable covalent interaction between phosphorus atoms in adjacent layers, and that interlayer interactions are not merely of the weak van der Waals type. These significant interlayer interactions are consistent with the known surface reactivity of BP, and have been shown to be important for electric-field induced formation of Dirac cones in thin film BP.

Large Frequency Change with Thickness in Interlayer Breathing Mode--Significant Interlayer Interactions in Few Layer Black Phosphorus.

PubMed

Luo, Xin; Lu, Xin; Koon, Gavin Kok Wai; Castro Neto, Antonio H; Özyilmaz, Barbaros; Xiong, Qihua; Quek, Su Ying

2015-06-10

Bulk black phosphorus (BP) consists of puckered layers of phosphorus atoms. Few-layer BP, obtained from bulk BP by exfoliation, is an emerging candidate as a channel material in post-silicon electronics. A deep understanding of its physical properties and its full range of applications are still being uncovered. In this paper, we present a theoretical and experimental investigation of phonon properties in few-layer BP, focusing on the low-frequency regime corresponding to interlayer vibrational modes. We show that the interlayer breathing mode A(3)g shows a large redshift with increasing thickness; the experimental and theoretical results agree well. This thickness dependence is two times larger than that in the chalcogenide materials, such as few-layer MoS2 and WSe2, because of the significantly larger interlayer force constant and smaller atomic mass in BP. The derived interlayer out-of-plane force constant is about 50% larger than that of graphene and MoS2. We show that this large interlayer force constant arises from the sizable covalent interaction between phosphorus atoms in adjacent layers and that interlayer interactions are not merely of the weak van der Waals type. These significant interlayer interactions are consistent with the known surface reactivity of BP and have been shown to be important for electric-field induced formation of Dirac cones in thin film BP.

Physical Interactions and Expression Quantitative Traits Loci Identify Regulatory Connections for Obesity and Type 2 Diabetes Associated SNPs

PubMed Central

Fadason, Tayaza; Ekblad, Cameron; Ingram, John R.; Schierding, William S.; O'Sullivan, Justin M.

2017-01-01

The mechanisms that underlie the association between obesity and type 2 diabetes are not fully understood. Here, we investigated the role of the 3D genome organization in the pathogeneses of obesity and type-2 diabetes. We interpreted the combined and differential impacts of 196 diabetes and 390 obesity associated single nucleotide polymorphisms (SNPs) by integrating data on the genes with which they physically interact (as captured by Hi-C) and the functional [i.e., expression quantitative trait loci (eQTL)] outcomes associated with these interactions. We identified 861 spatially regulated genes (e.g., AP3S2, ELP5, SVIP, IRS1, FADS2, WFS1, RBM6, HORMAD1, PYROXD2), which are enriched in tissues (e.g., adipose, skeletal muscle, pancreas) and biological processes and canonical pathways (e.g., lipid metabolism, leptin, and glucose-insulin signaling pathways) that are important for the pathogenesis of type 2 diabetes and obesity. Our discovery-based approach also identifies enrichment for eQTL SNP-gene interactions in tissues that are not classically associated with diabetes or obesity. We propose that the combinatorial action of active obesity and diabetes spatial eQTL SNPs on their gene pairs within different tissues reduces the ability of these tissues to contribute to the maintenance of a healthy energy metabolism. PMID:29081791

Fast Modeling of Binding Affinities by Means of Superposing Significant Interaction Rules (SSIR) Method

PubMed Central

Besalú, Emili

2016-01-01

The Superposing Significant Interaction Rules (SSIR) method is described. It is a general combinatorial and symbolic procedure able to rank compounds belonging to combinatorial analogue series. The procedure generates structure-activity relationship (SAR) models and also serves as an inverse SAR tool. The method is fast and can deal with large databases. SSIR operates from statistical significances calculated from the available library of compounds and according to the previously attached molecular labels of interest or non-interest. The required symbolic codification allows dealing with almost any combinatorial data set, even in a confidential manner, if desired. The application example categorizes molecules as binding or non-binding, and consensus ranking SAR models are generated from training and two distinct cross-validation methods: leave-one-out and balanced leave-two-out (BL2O), the latter being suited for the treatment of binary properties. PMID:27240346

Clinicopathologic significance of minichromosome maintenance protein 2 and Tat-interacting protein 30 expression in benign and malignant lesions of the gallbladder.

PubMed

Liu, Dong-cai; Yang, Zhu-lin

2011-11-01

Gallbladder cancers are aggressive tumors with a poor prognosis and high mortality rate. To find specific biological markers for early diagnosis and prognosis and to develop possible alternative treatment strategies, we examined minichromosome maintenance protein 2 (MCM2) and Tat-interacting protein 30 (TIP30) expression in 108 gallbladder adenocarcinomas, 15 gallbladder polyps, 35 chronic cholecystitis tissues, and 46 peritumoral tissues using immunohistochemistry. Expression of MCM2 was significantly higher in adenocarcinomas than in peritumoral tissues (χ² = 8.41; P < .01), adenomatous polyps (χ² = 6.81; P < .01), and chronic cholecystitis (χ² = 21.00; P < .01). In contrast, Tat-interacting protein 30 expression was significantly less in adenocarcinomas than in peritumoral tissues (χ² = 13.26; P < .01), adenomatous polyps (χ² = 4.76; P < .05), and chronic cholecystitis (χ² = 18.93; P < .01). The benign lesions in gallbladder epithelium with positive MCM2 or negative Tat-interacting protein 30 expression showed moderate to severe atypical hyperplasia. Expression of MCM2 and absence of Tat-interacting protein 30 were significantly associated with poor differentiation, large tumor mass, lymph node metastasis, and invasion of adenocarcinoma. Univariate Kaplan-Meier analysis showed that either elevated MCM2 (P = .006) or lowered Tat-interacting protein 30 (P = .006) expression was closely associated with shorter overall survival. Multivariate Cox regression analysis revealed that expression of MCM2 (P = .007) or nonexpression of Tat-interacting protein 30 (P = .009) was an independent predictor of a poor prognosis in adenocarcinoma. Our results suggest that overexpression of MCM2 or loss of expression of Tat-interacting protein 30 is closely related to carcinogenesis, progression, biological behavior, and prognosis of gallbladder adenocarcinoma. Copyright © 2011 Elsevier Inc. All rights reserved.

UV-triggered Affinity Capture Identifies Interactions between the Plasmodium falciparum Multidrug Resistance Protein 1 (PfMDR1) and Antimalarial Agents in Live Parasitized Cells*

PubMed Central

Brunner, Ralf; Ng, Caroline L.; Aissaoui, Hamed; Akabas, Myles H.; Boss, Christoph; Brun, Reto; Callaghan, Paul S.; Corminboeuf, Olivier; Fidock, David A.; Frame, Ithiel J.; Heidmann, Bibia; Le Bihan, Amélie; Jenö, Paul; Mattheis, Corinna; Moes, Suzette; Müller, Ingrid B.; Paguio, Michelle; Roepe, Paul D.; Siegrist, Romain; Voss, Till; Welford, Richard W. D.; Wittlin, Sergio; Binkert, Christoph

2013-01-01

A representative of a new class of potent antimalarials with an unknown mode of action was recently described. To identify the molecular target of this class of antimalarials, we employed a photo-reactive affinity capture method to find parasite proteins specifically interacting with the capture compound in living parasitized cells. The capture reagent retained the antimalarial properties of the parent molecule (ACT-213615) and accumulated within parasites. We identified several proteins interacting with the capture compound and established a functional interaction between ACT-213615 and PfMDR1. We surmise that PfMDR1 may play a role in the antimalarial activity of the piperazine-containing compound ACT-213615. PMID:23754276

T Cell Post-Transcriptional miRNA-mRNA Interaction Networks Identify Targets Associated with Susceptibility/Resistance to Collagen-induced Arthritis

PubMed Central

Macedo, Claudia; Cunha, Thiago M.; Nascimento, Daniele C. B.; Sakamoto-Hojo, Elza T.; Donadi, Eduardo A.; Cunha, Fernando Q.; Passos, Geraldo A.

2013-01-01

Background Due to recent studies indicating that the deregulation of microRNAs (miRNAs) in T cells contributes to increased severity of rheumatoid arthritis, we hypothesized that deregulated miRNAs may interact with key mRNA targets controlling the function or differentiation of these cells in this disease. Methodology/Principal Findings To test our hypothesis, we used microarrays to survey, for the first time, the expression of all known mouse miRNAs in parallel with genome-wide mRNAs in thymocytes and naïve and activated peripheral CD3+ T cells from two mouse strains the DBA-1/J strain (MHC-H2q), which is susceptible to collagen induced arthritis (CIA), and the DBA-2/J strain (MHC-H2d), which is resistant. Hierarchical clustering of data showed the several T cell miRNAs and mRNAs differentially expressed between the mouse strains in different stages of immunization with collagen. Bayesian statistics using the GenMir++ algorithm allowed reconstruction of post-transcriptional miRNA-mRNA interaction networks for target prediction. We revealed the participation of miR-500, miR-202-3p and miR-30b*, which established interactions with at least one of the following mRNAs: Rorc, Fas, Fasl, Il-10 and Foxo3. Among the interactions that were validated by calculating the minimal free-energy of base pairing between the miRNA and the 3′UTR of the mRNA target and luciferase assay, we highlight the interaction of miR-30b*-Rorc mRNA because the mRNA encodes a protein implicated in pro-inflammatory Th17 cell differentiation (Rorγt). FACS analysis revealed that Rorγt protein levels and Th17 cell counts were comparatively reduced in the DBA-2/J strain. Conclusions/Significance This result showed that the miRNAs and mRNAs identified in this study represent new candidates regulating T cell function and controlling susceptibility and resistance to CIA. PMID:23359619

The malaria parasite RhopH protein complex interacts with erythrocyte calmyrin identified from a comprehensive erythrocyte protein library.

PubMed

Miura, Toyokazu; Takeo, Satoru; Ntege, Edward H; Otsuki, Hitoshi; Sawasaki, Tatsuya; Ishino, Tomoko; Takashima, Eizo; Tsuboi, Takafumi

2018-06-02

Malaria merozoite apical organelles; microneme and rhoptry secreted proteins play functional roles during and following invasion of host erythrocytes. Among numerous proteins, the rhoptries discharge high molecular weight proteins known as RhopH complex. Recent reports suggest that the RhopH complex is essential for growth and survival of the malaria parasite within erythrocytes. However, an in-depth understanding of the host-parasite molecular interactions is indispensable. Here we utilized a comprehensive mouse erythrocyte protein library consisting of 443 proteins produced by a wheat germ cell-free system, combined with AlphaScreen technology to identify mouse erythrocyte calmyrin as an interacting molecule of the rodent malaria parasite Plasmodium yoelii RhopH complex (PyRhopH). The PyRhopH interaction was dependent on the calmyrin N-terminus and divalent cation capacity. The finding unveils a recommendable and invaluable usefulness of our comprehensive mouse erythrocyte protein library together with the AlphaScreen technology in investigating a wide-range of host-parasite molecular interactions. Copyright © 2018 Elsevier Inc. All rights reserved.

Identifying cases of undiagnosed, clinically significant COPD in primary care: qualitative insight from patients in the target population

PubMed Central

Leidy, Nancy K; Kim, Katherine; Bacci, Elizabeth D; Yawn, Barbara P; Mannino, David M; Thomashow, Byron M; Barr, R Graham; Rennard, Stephen I; Houfek, Julia F; Han, Meilan K; Meldrum, Catherine A; Make, Barry J; Bowler, Russ P; Steenrod, Anna W; Murray, Lindsey T; Walsh, John W; Martinez, Fernando

2015-01-01

Background: Many cases of chronic obstructive pulmonary disease (COPD) are diagnosed only after significant loss of lung function or during exacerbations. Aims: This study is part of a multi-method approach to develop a new screening instrument for identifying undiagnosed, clinically significant COPD in primary care. Methods: Subjects with varied histories of COPD diagnosis, risk factors and history of exacerbations were recruited through five US clinics (four pulmonary, one primary care). Phase I: Eight focus groups and six telephone interviews were conducted to elicit descriptions of risk factors for COPD, recent or historical acute respiratory events, and symptoms to inform the development of candidate items for the new questionnaire. Phase II: A new cohort of subjects participated in cognitive interviews to assess and modify candidate items. Two peak expiratory flow (PEF) devices (electronic, manual) were assessed for use in screening. Results: Of 77 subjects, 50 participated in Phase I and 27 in Phase II. Six themes informed item development: exposure (smoking, second-hand smoke); health history (family history of lung problems, recurrent chest infections); recent history of respiratory events (clinic visits, hospitalisations); symptoms (respiratory, non-respiratory); impact (activity limitations); and attribution (age, obesity). PEF devices were rated easy to use; electronic values were significantly higher than manual (P<0.0001). Revisions were made to the draft items on the basis of cognitive interviews. Conclusions: Forty-eight candidate items are ready for quantitative testing to select the best, smallest set of questions that, together with PEF, can efficiently identify patients in need of diagnostic evaluation for clinically significant COPD. PMID:26028486

Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

DOE PAGES

Larsen, Peter E.; Sreedasyam, Avinash; Trivedi, Geetika; ...

2016-01-19

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensormore » systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.« less

Multi-omics approach identifies molecular mechanisms of plant-fungus mycorrhizal interaction

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

Larsen, Peter E.; Sreedasyam, Avinash; Trivedi, Geetika

In mycorrhizal symbiosis, plant roots form close, mutually beneficial interactions with soil fungi. Before this mycorrhizal interaction can be established however, plant roots must be capable of detecting potential beneficial fungal partners and initiating the gene expression patterns necessary to begin symbiosis. To predict a plant root – mycorrhizal fungi sensor systems, we analyzed in vitro experiments of Populus tremuloides (aspen tree) and Laccaria bicolor (mycorrhizal fungi) interaction and leveraged over 200 previously published transcriptomic experimental data sets, 159 experimentally validated plant transcription factor binding motifs, and more than 120-thousand experimentally validated protein-protein interactions to generate models of pre-mycorrhizal sensormore » systems in aspen root. These sensor mechanisms link extracellular signaling molecules with gene regulation through a network comprised of membrane receptors, signal cascade proteins, transcription factors, and transcription factor biding DNA motifs. Modeling predicted four pre-mycorrhizal sensor complexes in aspen that interact with fifteen transcription factors to regulate the expression of 1184 genes in response to extracellular signals synthesized by Laccaria. Predicted extracellular signaling molecules include common signaling molecules such as phenylpropanoids, salicylate, and, jasmonic acid. Lastly, this multi-omic computational modeling approach for predicting the complex sensory networks yielded specific, testable biological hypotheses for mycorrhizal interaction signaling compounds, sensor complexes, and mechanisms of gene regulation.« less

[From stone-craved genes to Michelangelo: significance and different aspects of gene-environment interaction].

PubMed

Lazary, Judit

2017-12-01

Although genetic studies have improved a lot in recent years, without clinical relevance sometimes their significance is devalued. Reviewing the major milestones of psychogenomics it can be seen that break-through success is just a question of time. Investigations of direct effect of genetic variants on phenotypes have not yielded positive findings. However, an important step was taken by adapting the gene-environment interaction model. In this model genetic vulnerability stepped into the place of "stone craved" pathology. Further progress happened when studies of environmental factors were combined with genetic function (epigenetics). This model provided the possibility for investigation of therapeutic interventions as environmental factors and it was proven that effective treatments exert a modifying effect on gene expression. Moreover, recent developments focus on therapeutic manipulation of gene function (e.g. chemogenetics). Instead of "stone craved" genes up-to-date dynamically interacting gene function became the basis of psychogenomics in which correction of the expression is a potential therapeutic tool. Keeping in mind these trends and developments, there is no doubt that genetics will be a fundamental part of daily clinical routine in the future.

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.

The SADI Personal Health Lens: A Web Browser-Based System for Identifying Personally Relevant Drug Interactions.

PubMed

Vandervalk, Ben; McCarthy, E Luke; Cruz-Toledo, José; Klein, Artjom; Baker, Christopher J O; Dumontier, Michel; Wilkinson, Mark D

2013-04-05

The Web provides widespread access to vast quantities of health-related information that can improve quality-of-life through better understanding of personal symptoms, medical conditions, and available treatments. Unfortunately, identifying a credible and personally relevant subset of information can be a time-consuming and challenging task for users without a medical background. The objective of the Personal Health Lens system is to aid users when reading health-related webpages by providing warnings about personally relevant drug interactions. More broadly, we wish to present a prototype for a novel, generalizable approach to facilitating interactions between a patient, their practitioner(s), and the Web. We utilized a distributed, Semantic Web-based architecture for recognizing personally dangerous drugs consisting of: (1) a private, local triple store of personal health information, (2) Semantic Web services, following the Semantic Automated Discovery and Integration (SADI) design pattern, for text mining and identifying substance interactions, (3) a bookmarklet to trigger analysis of a webpage and annotate it with personalized warnings, and (4) a semantic query that acts as an abstract template of the analytical workflow to be enacted by the system. A prototype implementation of the system is provided in the form of a Java standalone executable JAR file. The JAR file bundles all components of the system: the personal health database, locally-running versions of the SADI services, and a javascript bookmarklet that triggers analysis of a webpage. In addition, the demonstration includes a hypothetical personal health profile, allowing the system to be used immediately without configuration. Usage instructions are provided. The main strength of the Personal Health Lens system is its ability to organize medical information and to present it to the user in a personalized and contextually relevant manner. While this prototype was limited to a single knowledge domain

The SADI Personal Health Lens: A Web Browser-Based System for Identifying Personally Relevant Drug Interactions

PubMed Central

Vandervalk, Ben; McCarthy, E Luke; Cruz-Toledo, José; Klein, Artjom; Baker, Christopher J O; Dumontier, Michel

2013-01-01

Background The Web provides widespread access to vast quantities of health-related information that can improve quality-of-life through better understanding of personal symptoms, medical conditions, and available treatments. Unfortunately, identifying a credible and personally relevant subset of information can be a time-consuming and challenging task for users without a medical background. Objective The objective of the Personal Health Lens system is to aid users when reading health-related webpages by providing warnings about personally relevant drug interactions. More broadly, we wish to present a prototype for a novel, generalizable approach to facilitating interactions between a patient, their practitioner(s), and the Web. Methods We utilized a distributed, Semantic Web-based architecture for recognizing personally dangerous drugs consisting of: (1) a private, local triple store of personal health information, (2) Semantic Web services, following the Semantic Automated Discovery and Integration (SADI) design pattern, for text mining and identifying substance interactions, (3) a bookmarklet to trigger analysis of a webpage and annotate it with personalized warnings, and (4) a semantic query that acts as an abstract template of the analytical workflow to be enacted by the system. Results A prototype implementation of the system is provided in the form of a Java standalone executable JAR file. The JAR file bundles all components of the system: the personal health database, locally-running versions of the SADI services, and a javascript bookmarklet that triggers analysis of a webpage. In addition, the demonstration includes a hypothetical personal health profile, allowing the system to be used immediately without configuration. Usage instructions are provided. Conclusions The main strength of the Personal Health Lens system is its ability to organize medical information and to present it to the user in a personalized and contextually relevant manner. While this

Screening approach for identifying candidate drugs and drug-drug interactions related to hip fracture risk in persons with Alzheimer disease.

PubMed

Tolppanen, Anna-Maija; Taipale, Heidi; Koponen, Marjaana; Tanskanen, Antti; Lavikainen, Piia; Paananen, Jussi; Tiihonen, Jari; Hartikainen, Sirpa

2017-08-01

To assess whether a "drugome-wide" screen with case-crossover design is a feasible approach for identifying candidate drugs and drug-drug interactions. All community-dwelling residents of Finland who received a clinically verified Alzheimer disease diagnosis in 2005 to 2011 and experienced incident hip fracture (HF) afterwards (N = 4851). Three scenarios were used to test the sensitivity of this approach (1) hazard period 0 to 30 and control period 31 to 61 days before HF, (2) hazard period 0 to 30 and control period 336 to 366 days before HF, and (3) hazard period 0 to 14 and control period 16 to 30 days before HF. Nine, 44, and 5 drugs were associated with increased HF risk and 8, 23, and 4 with decreased risk in scenarios 1, 2, and 3, respectively. Six drugs were identified with scenario 1 only and 54 and 1 with scenarios 2 and 3, respectively. Only six drugs (metoprolol, simvastatin, trimethoprim, codeine combinations, fentanyl, and paracetamol) were associated with HF in all scenarios, four with 1 and 2 (cefalexin, buprenorphine, olanzapine, and memantine), and one with 1 and 3 (enalapril) or 2 and 3 (ciprofloxacin). The direction of associations was the same in all/both scenarios. The interaction results were equally versatile, with hydroxocobalamin*oxazepam being the only interaction observed in all scenarios. Case-crossover analysis is a potential approach for identifying candidate drugs and drug-drug interactions associated with adverse events as it implicitly controls for fixed confounders. The results are highly dependent on applied hazard and control periods, but the choice of periods can help in targeting the analyses to different phases of drug use. Copyright © 2017 John Wiley & Sons, Ltd.

The significance of spatial resolution: Identifying forest cover from satellite data

Treesearch

Dumitru Salajanu; Charles E. Olson

2001-01-01

Twenty-five years ago, a National Academy of Sciences report identified species identification as a requirement if satellite data are to reach their full potential in forest inventory and monitoring; the report suggested that improving spatial resolution to 10 meters would probably be required (Committee on Remote Sensing Programs for Earth Resource Surveys [CORSPERS]...

Functional binding interaction identified between the axonal CAM L1 and members of the ERM family

PubMed Central

Dickson, Tracey C.; Mintz, C. David; Benson, Deanna L.; Salton, Stephen R.J.

2002-01-01

Ayeast two-hybrid library was screened using the cytoplasmic domain of the axonal cell adhesion molecule L1 to identify binding partners that may be involved in the regulation of L1 function. The intracellular domain of L1 bound to ezrin, a member of the ezrin, radixin, and moesin (ERM) family of membrane–cytoskeleton linking proteins, at a site overlapping that for AP2, a clathrin adaptor. Binding of bacterial fusion proteins confirmed this interaction. To determine whether ERM proteins interact with L1 in vivo, extracellular antibodies to L1 were used to force cluster the protein on cultured hippocampal neurons and PC12 cells, which were then immunolabeled for ERM proteins. Confocal analysis revealed a precise pattern of codistribution between ERMs and L1 clusters in axons and PC12 neurites, whereas ERMs in dendrites and spectrin labeling remained evenly distributed. Transfection of hippocampal neurons grown on an L1 substrate with a dominant negative ERM construct resulted in extensive and abnormal elaboration of membrane protrusions and an increase in axon branching, highlighting the importance of the ERM–actin interaction in axon development. Together, our data indicate that L1 binds directly to members of the ERM family and suggest this association may coordinate aspects of axonal morphogenesis. PMID:12070130

Functional binding interaction identified between the axonal CAM L1 and members of the ERM family.

PubMed

Dickson, Tracey C; Mintz, C David; Benson, Deanna L; Salton, Stephen R J

2002-06-24

A yeast two-hybrid library was screened using the cytoplasmic domain of the axonal cell adhesion molecule L1 to identify binding partners that may be involved in the regulation of L1 function. The intracellular domain of L1 bound to ezrin, a member of the ezrin, radixin, and moesin (ERM) family of membrane-cytoskeleton linking proteins, at a site overlapping that for AP2, a clathrin adaptor. Binding of bacterial fusion proteins confirmed this interaction. To determine whether ERM proteins interact with L1 in vivo, extracellular antibodies to L1 were used to force cluster the protein on cultured hippocampal neurons and PC12 cells, which were then immunolabeled for ERM proteins. Confocal analysis revealed a precise pattern of codistribution between ERMs and L1 clusters in axons and PC12 neurites, whereas ERMs in dendrites and spectrin labeling remained evenly distributed. Transfection of hippocampal neurons grown on an L1 substrate with a dominant negative ERM construct resulted in extensive and abnormal elaboration of membrane protrusions and an increase in axon branching, highlighting the importance of the ERM-actin interaction in axon development. Together, our data indicate that L1 binds directly to members of the ERM family and suggest this association may coordinate aspects of axonal morphogenesis.

Global Sensitivity Analysis of OnGuard Models Identifies Key Hubs for Transport Interaction in Stomatal Dynamics1[CC-BY

PubMed Central

Vialet-Chabrand, Silvere; Griffiths, Howard

2017-01-01

The physical requirement for charge to balance across biological membranes means that the transmembrane transport of each ionic species is interrelated, and manipulating solute flux through any one transporter will affect other transporters at the same membrane, often with unforeseen consequences. The OnGuard systems modeling platform has helped to resolve the mechanics of stomatal movements, uncovering previously unexpected behaviors of stomata. To date, however, the manual approach to exploring model parameter space has captured little formal information about the emergent connections between parameters that define the most interesting properties of the system as a whole. Here, we introduce global sensitivity analysis to identify interacting parameters affecting a number of outputs commonly accessed in experiments in Arabidopsis (Arabidopsis thaliana). The analysis highlights synergies between transporters affecting the balance between Ca2+ sequestration and Ca2+ release pathways, notably those associated with internal Ca2+ stores and their turnover. Other, unexpected synergies appear, including with the plasma membrane anion channels and H+-ATPase and with the tonoplast TPK K+ channel. These emergent synergies, and the core hubs of interaction that they define, identify subsets of transporters associated with free cytosolic Ca2+ concentration that represent key targets to enhance plant performance in the future. They also highlight the importance of interactions between the voltage regulation of the plasma membrane and tonoplast in coordinating transport between the different cellular compartments. PMID:28432256

Identifying thresholds in pattern-process relationships: a new cross-scale interactions experiment at the Jornada Basin LTER

USDA-ARS?s Scientific Manuscript database

Interactions among ecological patterns and processes at multiple scales play a significant role in threshold behaviors in arid systems. Black grama grasslands and mesquite shrublands are hypothesized to operate under unique sets of feedbacks: grasslands are maintained by fine-scale biotic feedbacks ...

The Use of Chemical-Chemical Interaction and Chemical Structure to Identify New Candidate Chemicals Related to Lung Cancer

PubMed Central

Zheng, Mingyue; Kong, Xiangyin; Huang, Tao; Cai, Yu-Dong

2015-01-01

Lung cancer causes over one million deaths every year worldwide. However, prevention and treatment methods for this serious disease are limited. The identification of new chemicals related to lung cancer may aid in disease prevention and the design of more effective treatments. This study employed a weighted network, constructed using chemical-chemical interaction information, to identify new chemicals related to two types of lung cancer: non-small lung cancer and small-cell lung cancer. Then, a randomization test as well as chemical-chemical interaction and chemical structure information were utilized to make further selections. A final analysis of these new chemicals in the context of the current literature indicates that several chemicals are strongly linked to lung cancer. PMID:26047514

The Significance of Microbe-Mineral-Biomarker Interactions in the Detection of Life on Mars and Beyond.

PubMed

Röling, Wilfred F M; Aerts, Joost W; Patty, C H Lucas; ten Kate, Inge Loes; Ehrenfreund, Pascale; Direito, Susana O L

2015-06-01

The detection of biomarkers plays a central role in our effort to establish whether there is, or was, life beyond Earth. In this review, we address the importance of considering mineralogy in relation to the selection of locations and biomarker detection methodologies with characteristics most promising for exploration. We review relevant mineral-biomarker and mineral-microbe interactions. The local mineralogy on a particular planet reflects its past and current environmental conditions and allows a habitability assessment by comparison with life under extreme conditions on Earth. The type of mineral significantly influences the potential abundances and types of biomarkers and microorganisms containing these biomarkers. The strong adsorptive power of some minerals aids in the preservation of biomarkers and may have been important in the origin of life. On the other hand, this strong adsorption as well as oxidizing properties of minerals can interfere with efficient extraction and detection of biomarkers. Differences in mechanisms of adsorption and in properties of minerals and biomarkers suggest that it will be difficult to design a single extraction procedure for a wide range of biomarkers. While on Mars samples can be used for direct detection of biomarkers such as nucleic acids, amino acids, and lipids, on other planetary bodies remote spectrometric detection of biosignatures has to be relied upon. The interpretation of spectral signatures of photosynthesis can also be affected by local mineralogy. We identify current gaps in our knowledge and indicate how they may be filled to improve the chances of detecting biomarkers on Mars and beyond.

Compensated Sex and Sexual Risk: Sexual, Social and Economic Interactions between Homosexually- and Heterosexually-Identified Men of Low Income in Two Cities of Peru

PubMed Central

Fernández-Dávila, Percy; Salazar, Ximena; Cáceres, Carlos F.; Maiorana, Andre; Kegeles, Susan; Coates, Thomas J.; Martinez, Josefa

2009-01-01

This study describes the complex dynamics of the sexual, economic and social interactions between a group of feminized homosexual men and men who have sex with men and self-identify as heterosexual (‘mostaceros’), in lower-income peripheral urban areas of Lima and Trujillo, Peru. The study examined sexual risk between these two groups of men, and the significance of the economic exchanges involved in their sexual interactions. Using a Grounded Theory approach, 23 individual interviews and 7 focus groups were analyzed. The results reveal that cultural, economic and gender factors mold sexual and social relations among a group of men who have sex with men in Peru. Compensated sex is part of the behaviors of these men, reflecting a complicated construction of sexuality based on traditional conceptions of gender roles, sexual identity and masculinity. Several factors (e.g. difficulty in negotiating condom use, low self-esteem, low risk perception, alcohol and drug consumption), in the context of compensated sex, play a role in risk-taking for HIV infection. PMID:19890491

A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease

PubMed Central

Huan, Tianxiao; Zhang, Bin; Wang, Zhi; Joehanes, Roby; Zhu, Jun; Johnson, Andrew D.; Ying, Saixia; Munson, Peter J.; Raghavachari, Nalini; Wang, Richard; Liu, Poching; Courchesne, Paul; Hwang, Shih-Jen; Assimes, Themistocles L.; McPherson, Ruth; Samani, Nilesh J.; Schunkert, Heribert; Meng, Qingying; Suver, Christine; O'Donnell, Christopher J.; Derry, Jonathan; Yang, Xia; Levy, Daniel

2013-01-01

Objective Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD. Approach and Results We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. 24 coexpression modules were identified including one case-specific and one control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with altered gene expression associated SNPs (eSNPs) and with results of GWAS of CHD and its risk factors, the control-specific DM was implicated as CHD-causal based on its significant enrichment for both CHD and lipid eSNPs. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver (KD) genes. Multi-tissue KDs (SPIB and TNFRSF13C) and tissue-specific KDs (e.g. EBF1) were identified. Conclusions Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk. PMID:23539213

Emory University: MEDICI (Mining Essentiality Data to Identify Critical Interactions) for Cancer Drug Target Discovery and Development | Office of Cancer Genomics

Cancer.gov

The CTD2 Center at Emory University has developed a computational methodology to combine high-throughput knockdown data with known protein network topologies to infer the importance of protein-protein interactions (PPIs) for the survival of cancer cells.  Applying these data to the Achilles shRNA results, the CCLE cell line characterizations, and known and newly identified PPIs provides novel insights for potential new drug targets for cancer therapies and identifies important PPI hubs.

No significant interactions between nitrogen stimulation and ozone inhibition of isoprene emission in Cathay poplar.

PubMed

Yuan, Xiangyang; Shang, Bo; Xu, Yansen; Xin, Yue; Tian, Yuan; Feng, Zhaozhong; Paoletti, Elena

2017-12-01

Isoprene emission from plants subject to a combination of ozone (O 3 ) and nitrogen (N) has never been investigated. Cathay poplar (Populus cathayana) saplings were exposed to O 3 (CF, charcoal-filtered air, NF, non-filtered ambient air and E-O 3 , non-filtered air +40ppb) and N treatments (N0, 0kgNha -1 year -1 , N50, 50kgNha -1 year -1 and N100, 100kgNha -1 year -1 ) for 96days. Increasing O 3 exposure decreased isoprene emission (11.5% in NF and 57.9% in E-O 3 ), as well as light-saturated photosynthetic rate (A sat ) and chlorophyll content, while N load increased isoprene emission (19.6% in N50 and 33.4% in N100) as well as A sat and chlorophyll content. Although O 3 and N interacted significantly in A sat , N did not mitigate the negative effects of O 3 on isoprene emission, i.e. the combined effects were additive and did not interact. These results warrant more research on the combined effects of co-existing global change factors on future isoprene emission and atmospheric chemical processes. Copyright © 2017 Elsevier B.V. All rights reserved.

Ecto-Fc MS identifies ligand-receptor interactions through extracellular domain Fc fusion protein baits and shotgun proteomic analysis

PubMed Central

Savas, Jeffrey N.; De Wit, Joris; Comoletti, Davide; Zemla, Roland; Ghosh, Anirvan

2015-01-01

Ligand-receptor interactions represent essential biological triggers which regulate many diverse and important cellular processes. We have developed a discovery-based proteomic biochemical protocol which couples affinity purification with multidimensional liquid chromatographic tandem mass spectrometry (LCLC-MS/MS) and bioinformatic analysis. Compared to previous approaches, our analysis increases sensitivity, shortens analysis duration, and boosts comprehensiveness. In this protocol, receptor extracellular domains are fused with the Fc region of IgG to generate fusion proteins that are purified from transfected HEK293T cells. These “ecto-Fcs” are coupled to protein A beads and serve as baits for binding assays with prey proteins extracted from rodent brain. After capture, the affinity purified proteins are digested into peptides and comprehensively analyzed by LCLC-MS/MS with ion trap mass spectrometers. In four working days, this protocol can generate shortlists of candidate ligand-receptor protein-protein interactions. Our “Ecto-Fc MS” approach outperforms antibody-based approaches and provides a reproducible and robust framework to identify extracellular ligand – receptor interactions. PMID:25101821

A New Method, "Reverse Yeast Two-Hybrid Array" (RYTHA), Identifies Mutants that Dissociate the Physical Interaction Between Elg1 and Slx5.

PubMed

Lev, Ifat; Shemesh, Keren; Volpe, Marina; Sau, Soumitra; Levinton, Nelly; Molco, Maya; Singh, Shivani; Liefshitz, Batia; Ben Aroya, Shay; Kupiec, Martin

2017-07-01

The vast majority of processes within the cell are carried out by proteins working in conjunction. The Yeast Two-Hybrid (Y2H) methodology allows the detection of physical interactions between any two interacting proteins. Here, we describe a novel systematic genetic methodology, "Reverse Yeast Two-Hybrid Array" (RYTHA), that allows the identification of proteins required for modulating the physical interaction between two given proteins. Our assay starts with a yeast strain in which the physical interaction of interest can be detected by growth on media lacking histidine, in the context of the Y2H methodology. By combining the synthetic genetic array technology, we can systematically screen mutant libraries of the yeast Saccharomyces cerevisiae to identify trans -acting mutations that disrupt the physical interaction of interest. We apply this novel method in a screen for mutants that disrupt the interaction between the N-terminus of Elg1 and the Slx5 protein. Elg1 is part of an alternative replication factor C-like complex that unloads PCNA during DNA replication and repair. Slx5 forms, together with Slx8, a SUMO-targeted ubiquitin ligase (STUbL) believed to send proteins to degradation. Our results show that the interaction requires both the STUbL activity and the PCNA unloading by Elg1, and identify topoisomerase I DNA-protein cross-links as a major factor in separating the two activities. Thus, we demonstrate that RYTHA can be applied to gain insights about particular pathways in yeast, by uncovering the connection between the proteasomal ubiquitin-dependent degradation pathway, DNA replication, and repair machinery, which can be separated by the topoisomerase-mediated cross-links to DNA. Copyright © 2017 by the Genetics Society of America.

Methodology to identify risk-significant components for inservice inspection and testing

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

Anderson, M.T.; Hartley, R.S.; Jones, J.L. Jr.

1992-08-01

Periodic inspection and testing of vital system components should be performed to ensure the safe and reliable operation of Department of Energy (DOE) nuclear processing facilities. Probabilistic techniques may be used to help identify and rank components by their relative risk. A risk-based ranking would allow varied DOE sites to implement inspection and testing programs in an effective and cost-efficient manner. This report describes a methodology that can be used to rank components, while addressing multiple risk issues.

Significance of phytohormones in Siberian larch-bud gall midge interaction

Treesearch

Rida M. Matrenina

1991-01-01

Interrelations of the bud gall midge and the Siberian larch are of scientific and practical interest because of the bud gall midge's role as a plant endoparasite. We know that attack by the gall midge sets off a reaction in the entire plant. Invasion by the insect results in a certain interaction between physiological mechanisms of the insect and the plant which...

Identifying the most significant indicators of the total road safety performance index.

PubMed

Tešić, Milan; Hermans, Elke; Lipovac, Krsto; Pešić, Dalibor

2018-04-01

The review of the national and international literature dealing with the assessment of the road safety level has shown great efforts of the authors who tried to define the methodology for calculating the composite road safety index on a territory (region, state, etc.). The procedure for obtaining a road safety composite index of an area has been largely harmonized. The question that has not been fully resolved yet concerns the selection of indicators. There is a wide range of road safety indicators used to show a road safety situation on a territory. Road safety performance index (RSPI) obtained on the basis of a larger number of safety performance indicators (SPIs) enable decision makers to more precisely define the earlier goal- oriented actions. However, recording a broader comprehensive set of SPIs helps identify the strengths and weaknesses of a country's road safety system. Providing high quality national and international databases that would include comparable SPIs seems to be difficult since a larger number of countries dispose of a small number of identical indicators available for use. Therefore, there is a need for calculating a road safety performance index with a limited number of indicators (RSPI ln n ) which will provide a comparison of a sufficient quality, of as many countries as possible. The application of the Data Envelopment Analysis (DEA) method and correlative analysis has helped to check if the RSPI ln n is likely to be of sufficient quality. A strong correlation between the RSPI ln n and the RSPI has been identified using the proposed methodology. Based on this, the most contributing indicators and methodologies for gradual monitoring of SPIs, have been defined for each country analyzed. The indicator monitoring phases in the analyzed countries have been defined in the following way: Phase 1- the indicators relating to alcohol, speed and protective systems; Phase 2- the indicators relating to roads and Phase 3- the indicators relating to

A Multinomial Model for Identifying Significant Pure-Tone Threshold Shifts

ERIC Educational Resources Information Center

Schlauch, Robert S.; Carney, Edward

2007-01-01

Purpose: Significant threshold differences on retest for pure-tone audiometry are often evaluated by application of ad hoc rules, such as a shift in a pure-tone average or in 2 adjacent frequencies that exceeds a predefined amount. Rules that are so derived do not consider the probability of observing a particular audiogram. Methods: A general…

Identifying Interactions that Determine Fragment Binding at Protein Hotspots.

PubMed

Radoux, Chris J; Olsson, Tjelvar S G; Pitt, Will R; Groom, Colin R; Blundell, Tom L

2016-05-12

Locating a ligand-binding site is an important first step in structure-guided drug discovery, but current methods do little to suggest which interactions within a pocket are the most important for binding. Here we illustrate a method that samples atomic hotspots with simple molecular probes to produce fragment hotspot maps. These maps specifically highlight fragment-binding sites and their corresponding pharmacophores. For ligand-bound structures, they provide an intuitive visual guide within the binding site, directing medicinal chemists where to grow the molecule and alerting them to suboptimal interactions within the original hit. The fragment hotspot map calculation is validated using experimental binding positions of 21 fragments and subsequent lead molecules. The ligands are found in high scoring areas of the fragment hotspot maps, with fragment atoms having a median percentage rank of 97%. Protein kinase B and pantothenate synthetase are examined in detail. In each case, the fragment hotspot maps are able to rationalize a Free-Wilson analysis of SAR data from a fragment-based drug design project.

Homology-based modeling of the Erwinia amylovora type III secretion chaperone DspF used to identify amino acids required for virulence and interaction with the effector DspE.

PubMed

Triplett, Lindsay R; Wedemeyer, William J; Sundin, George W

2010-09-01

The structure of DspF, a type III secretion system (T3SS) chaperone required for virulence of the fruit tree pathogen Erwinia amylovora, was modeled based on predicted structural homology to characterized T3SS chaperones. This model guided the selection of 11 amino acid residues that were individually mutated to alanine via site-directed mutagenesis. Each mutant was assessed for its effect on virulence complementation, dimerization and interaction with the N-terminal chaperone-binding site of DspE. Four amino acid residues were identified that did not complement the virulence defect of a dspF knockout mutant, and three of these residues were required for interaction with the N-terminus of DspE. This study supports the significance of the predicted beta-sheet helix-binding groove in DspF chaperone function. Copyright 2010 Elsevier Masson SAS. All rights reserved.

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency.

PubMed

Yeh, Hsiang-Yuan; Cheng, Shih-Wu; Lin, Yu-Chun; Yeh, Cheng-Yu; Lin, Shih-Fang; Soo, Von-Wun

2009-12-21

Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. We provide a computational framework to reconstruct

Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

PubMed Central

2009-01-01

Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN) algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD) as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2) regulated by RUNX1 and STAT3 is correlated to the pathological stage. Conclusions We provide a

Detecting signals of drug-drug interactions in a spontaneous reports database.

PubMed

Thakrar, Bharat T; Grundschober, Sabine Borel; Doessegger, Lucette

2007-10-01

The spontaneous reports database is widely used for detecting signals of ADRs. We have extended the methodology to include the detection of signals of ADRs that are associated with drug-drug interactions (DDI). In particular, we have investigated two different statistical assumptions for detecting signals of DDI. Using the FDA's spontaneous reports database, we investigated two models, a multiplicative and an additive model, to detect signals of DDI. We applied the models to four known DDIs (methotrexate-diclofenac and bone marrow depression, simvastatin-ciclosporin and myopathy, ketoconazole-terfenadine and torsades de pointes, and cisapride-erythromycin and torsades de pointes) and to four drug-event combinations where there is currently no evidence of a DDI (fexofenadine-ketoconazole and torsades de pointes, methotrexade-rofecoxib and bone marrow depression, fluvastatin-ciclosporin and myopathy, and cisapride-azithromycine and torsade de pointes) and estimated the measure of interaction on the two scales. The additive model correctly identified all four known DDIs by giving a statistically significant (P < 0.05) positive measure of interaction. The multiplicative model identified the first two of the known DDIs as having a statistically significant or borderline significant (P < 0.1) positive measure of interaction term, gave a nonsignificant positive trend for the third interaction (P = 0.27), and a negative trend for the last interaction. Both models correctly identified the four known non interactions by estimating a negative measure of interaction. The spontaneous reports database is a valuable resource for detecting signals of DDIs. In particular, the additive model is more sensitive in detecting such signals. The multiplicative model may further help qualify the strength of the signal detected by the additive model.

Detecting signals of drug–drug interactions in a spontaneous reports database

PubMed Central

Thakrar, Bharat T; Grundschober, Sabine Borel; Doessegger, Lucette

2007-01-01

Aims The spontaneous reports database is widely used for detecting signals of ADRs. We have extended the methodology to include the detection of signals of ADRs that are associated with drug–drug interactions (DDI). In particular, we have investigated two different statistical assumptions for detecting signals of DDI. Methods Using the FDA's spontaneous reports database, we investigated two models, a multiplicative and an additive model, to detect signals of DDI. We applied the models to four known DDIs (methotrexate-diclofenac and bone marrow depression, simvastatin-ciclosporin and myopathy, ketoconazole-terfenadine and torsades de pointes, and cisapride-erythromycin and torsades de pointes) and to four drug-event combinations where there is currently no evidence of a DDI (fexofenadine-ketoconazole and torsades de pointes, methotrexade-rofecoxib and bone marrow depression, fluvastatin-ciclosporin and myopathy, and cisapride-azithromycine and torsade de pointes) and estimated the measure of interaction on the two scales. Results The additive model correctly identified all four known DDIs by giving a statistically significant (P< 0.05) positive measure of interaction. The multiplicative model identified the first two of the known DDIs as having a statistically significant or borderline significant (P< 0.1) positive measure of interaction term, gave a nonsignificant positive trend for the third interaction (P= 0.27), and a negative trend for the last interaction. Both models correctly identified the four known non interactions by estimating a negative measure of interaction. Conclusions The spontaneous reports database is a valuable resource for detecting signals of DDIs. In particular, the additive model is more sensitive in detecting such signals. The multiplicative model may further help qualify the strength of the signal detected by the additive model. PMID:17506784

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

The Significance of Microbe-Mineral-Biomarker Interactions in the Detection of Life on Mars and Beyond

PubMed Central

Aerts, Joost W.; Patty, C.H. Lucas; ten Kate, Inge Loes; Ehrenfreund, Pascale; Direito, Susana O.L.

2015-01-01

Abstract The detection of biomarkers plays a central role in our effort to establish whether there is, or was, life beyond Earth. In this review, we address the importance of considering mineralogy in relation to the selection of locations and biomarker detection methodologies with characteristics most promising for exploration. We review relevant mineral-biomarker and mineral-microbe interactions. The local mineralogy on a particular planet reflects its past and current environmental conditions and allows a habitability assessment by comparison with life under extreme conditions on Earth. The type of mineral significantly influences the potential abundances and types of biomarkers and microorganisms containing these biomarkers. The strong adsorptive power of some minerals aids in the preservation of biomarkers and may have been important in the origin of life. On the other hand, this strong adsorption as well as oxidizing properties of minerals can interfere with efficient extraction and detection of biomarkers. Differences in mechanisms of adsorption and in properties of minerals and biomarkers suggest that it will be difficult to design a single extraction procedure for a wide range of biomarkers. While on Mars samples can be used for direct detection of biomarkers such as nucleic acids, amino acids, and lipids, on other planetary bodies remote spectrometric detection of biosignatures has to be relied upon. The interpretation of spectral signatures of photosynthesis can also be affected by local mineralogy. We identify current gaps in our knowledge and indicate how they may be filled to improve the chances of detecting biomarkers on Mars and beyond. Key Words: DNA—Lipids—Photosynthesis—Extremophiles—Mineralogy—Subsurface. Astrobiology 15, 492–507. PMID:26060985

Integrated genomic and transcriptomic analysis of human brain metastases identifies alterations of potential clinical significance.

PubMed

Saunus, Jodi M; Quinn, Michael C J; Patch, Ann-Marie; Pearson, John V; Bailey, Peter J; Nones, Katia; McCart Reed, Amy E; Miller, David; Wilson, Peter J; Al-Ejeh, Fares; Mariasegaram, Mythily; Lau, Queenie; Withers, Teresa; Jeffree, Rosalind L; Reid, Lynne E; Da Silva, Leonard; Matsika, Admire; Niland, Colleen M; Cummings, Margaret C; Bruxner, Timothy J C; Christ, Angelika N; Harliwong, Ivon; Idrisoglu, Senel; Manning, Suzanne; Nourse, Craig; Nourbakhsh, Ehsan; Wani, Shivangi; Anderson, Matthew J; Fink, J Lynn; Holmes, Oliver; Kazakoff, Stephen; Leonard, Conrad; Newell, Felicity; Taylor, Darrin; Waddell, Nick; Wood, Scott; Xu, Qinying; Kassahn, Karin S; Narayanan, Vairavan; Taib, Nur Aishah; Teo, Soo-Hwang; Chow, Yock Ping; kConFab; Jat, Parmjit S; Brandner, Sebastian; Flanagan, Adrienne M; Khanna, Kum Kum; Chenevix-Trench, Georgia; Grimmond, Sean M; Simpson, Peter T; Waddell, Nicola; Lakhani, Sunil R

2015-11-01

Treatment options for patients with brain metastases (BMs) have limited efficacy and the mortality rate is virtually 100%. Targeted therapy is critically under-utilized, and our understanding of mechanisms underpinning metastatic outgrowth in the brain is limited. To address these deficiencies, we investigated the genomic and transcriptomic landscapes of 36 BMs from breast, lung, melanoma and oesophageal cancers, using DNA copy-number analysis and exome- and RNA-sequencing. The key findings were as follows. (a) Identification of novel candidates with possible roles in BM development, including the significantly mutated genes DSC2, ST7, PIK3R1 and SMC5, and the DNA repair, ERBB-HER signalling, axon guidance and protein kinase-A signalling pathways. (b) Mutational signature analysis was applied to successfully identify the primary cancer type for two BMs with unknown origins. (c) Actionable genomic alterations were identified in 31/36 BMs (86%); in one case we retrospectively identified ERBB2 amplification representing apparent HER2 status conversion, then confirmed progressive enrichment for HER2-positivity across four consecutive metastatic deposits by IHC and SISH, resulting in the deployment of HER2-targeted therapy for the patient. (d) In the ERBB/HER pathway, ERBB2 expression correlated with ERBB3 (r(2)  = 0.496; p < 0.0001) and HER3 and HER4 were frequently activated in an independent cohort of 167 archival BM from seven primary cancer types: 57.6% and 52.6% of cases were phospho-HER3(Y1222) or phospho-HER4(Y1162) membrane-positive, respectively. The HER3 ligands NRG1/2 were barely detectable by RNAseq, with NRG1 (8p12) genomic loss in 63.6% breast cancer-BMs, suggesting a microenvironmental source of ligand. In summary, this is the first study to characterize the genomic landscapes of BM. The data revealed novel candidates, potential clinical applications for genomic profiling of resectable BMs, and highlighted the possibility of therapeutically targeting

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

Enteral feeding: drug/nutrient interaction.

PubMed

Lourenço, R

2001-04-01

Enteral nutrition support via a feeding tube is the first choice for artificial nutrition. Most patients also require simultaneous drug therapy, with the potential risk for drug-nutrient interactions which may become relevant in clinical practice. During enteral nutrition, drug-nutrient interactions are more likely to occur than in patients fed orally. However, there is a lack of awareness about its clinical significance, which should be recognised and prevented in order to optimise nutritional and pharmacological therapeutic goals of safety and efficacy. To raise the awareness of potential drug-nutrient interactions and influence on clinical outcomes. To identify factors that can promote drug-nutrient interactions and contribute to nutrition and/or therapeutic failure. To be aware of different types of drug-nutrient interactions. To understand complex underlying mechanisms responsible for drug-nutrient interactions. To learn basic rules for the administration of medications during tube-feeding. Copyright 2001 Harcourt Publishers Ltd.

Transcriptional Profiling Identifies Functional Interactions of TGFβ and PPARβ/δ Signaling

PubMed Central

Kaddatz, Kerstin; Adhikary, Till; Finkernagel, Florian; Meissner, Wolfgang; Müller-Brüsselbach, Sabine; Müller, Rolf

2010-01-01

Peroxisome proliferator-activated receptors (PPARs) not only play a key role in regulating metabolic pathways but also modulate inflammatory processes, pointing to a functional interaction between PPAR and cytokine signaling pathways. In this study, we show by genome-wide transcriptional profiling that PPARβ/δ and transforming growth factor-β (TGFβ) pathways functionally interact in human myofibroblasts and that a subset of these genes is cooperatively activated by TGFβ and PPARβ/δ. Using the angiopoietin-like 4 (ANGPTL4) gene as a model, we demonstrate that two enhancer regions cooperate to mediate the observed synergistic response. A TGFβ-responsive enhancer located ∼8 kb upstream of the transcriptional start site is regulated by a mechanism involving SMAD3, ETS1, RUNX, and AP-1 transcription factors that interact with multiple contiguous binding sites. A second enhancer (PPAR-E) consisting of three juxtaposed PPAR response elements is located in the third intron ∼3.5 kb downstream of the transcriptional start site. The PPAR-E is strongly activated by all three PPAR subtypes, with a novel type of PPAR response element motif playing a central role. Although the PPAR-E is not regulated by TGFβ, it interacts with SMAD3, ETS1, RUNX2, and AP-1 in vivo, providing a possible mechanistic explanation for the observed synergism. PMID:20595396

Ancestry-specific and sex-specific risk alleles identified in a genome-wide gene-by-alcohol dependence interaction study of risky sexual behaviors.

PubMed

Polimanti, Renato; Zhao, Hongyu; Farrer, Lindsay A; Kranzler, Henry R; Gelernter, Joel

2017-12-01

We previously mapped loci for the genome-wide association studies (GWAS) and genome-wide gene-by-alcohol dependence interaction (GW-GxAD) analyses of risky sexual behaviors (RSB). This study extends those findings by analyzing the ancestry- and sex-specific AD-stratified effects on RSB. We examined the concordance of findings for the AD-stratified GWAS and the GW-GxAD analysis of RSB, with concordance defined as genome-wide significance in one analysis and at least nominal significance in the second analysis. A total of 2,173 African-American (AA) and 1,751 European-American (EA) subjects were investigated. Information regarding RSB (lifetime experiences of unprotected sex and multiple sexual partners) and DSM-IV diagnosis of lifetime AD were derived from the Semi-Structured Assessment for Drug Dependence and Alcoholism (SSADDA). In our ancestry- and sex-specific analyses, we identified four independent genome-wide significant (GWS) loci (p < 5*10 -8 ) and one suggestive locus (p < 6*10 -8 ). In men, we observed a GWS signal in FAM162A (rs2002594, p = 4.96*10 -8 ). In women, there was a suggestive locus in PLGRKT (rs3824435, p = 5.52*10 -8 ). In AAs, there was a GWS signal in GRK5 (rs1316543, p = 1.25*10 -9 ). In AA men, we observed an intergenic GWS signal (rs12898370, p = 4.49*10 -8 ) near LINGO1. In EA men, there was a GWS signal in CCSER1 (rs62313897; p = 7.93*10 -10 ). The loci identified in this GWAS implicate molecular mechanisms related to psychiatric illness and personality features, suggesting that the interplay between AD and RSB is mediated by alleles associated with behavioral traits. © 2017 Wiley Periodicals, Inc.

Comparison of a video-based assessment and a multiple stimulus assessment to identify preferred jobs for individuals with significant intellectual disabilities.

PubMed

Horrocks, Erin L; Morgan, Robert L

2009-01-01

The authors compare two methods of identifying job preferences for individuals with significant intellectual disabilities. Three individuals with intellectual disabilities between the ages of 19 and 21 participated in a video-based preference assessment and a multiple stimulus without replacement (MSWO) assessment. Stimulus preference assessment procedures typically involve giving participants access to the selected stimuli to increase the probability that participants will associate the selected choice with the actual stimuli. Although individuals did not have access to the selected stimuli in the video-based assessment, results indicated that both assessments identified the same highest preference job for all participants. Results are discussed in terms of using a video-based assessment to accurately identify job preferences for individuals with developmental disabilities.

THE IDENTIFICATION AND TESTING OF INTERACTION PATTERNS

EPA Science Inventory

This paper presents a method for identifying and assessing the significance of interaction patterns among various chemicals and chemical classes of importance to regulatory toxicologists. To this end, efforts were made to assemble and evaluate experimental data on toxicologically...

Using the 3-Sigma Limit to Identify Significantly Long Pauses during Composing.

ERIC Educational Resources Information Center

Kelly, Leonard P.; Nolan, Thomas W.

Ten deaf college freshmen and a comparison group of five hearing students participated in a study of a method to identify long pauses in written composition that have important statistical properties. Subjects first wrote two initial drafts of short stories they had viewed on video tape. Later, they revised and recopied their two originals and one…

Identifying medical students at risk of underperformance from significant stressors.

PubMed

Wilkinson, Tim J; McKenzie, Jan M; Ali, Anthony N; Rudland, Joy; Carter, Frances A; Bell, Caroline J

2016-02-02

Stress is associated with poorer academic performance but identifying vulnerable students is less clear. A series of earthquakes and disrupted learning environments created an opportunity to explore the relationships among stress, student factors, support and academic performance within a medical course. The outcomes were deviations from expected performances on end of year written and clinical examinations. The predictors were questionnaire-based measures of connectedness/support, impact of the earthquakes, safety, depression, anxiety, stress, resilience and personality. The response rate was 77%. Poorer than expected performance on all examinations was associated with greater disruptions to living arrangements and fewer years in the country; on the written examination with not having a place to study; and on the clinical examination with relationship status, not having the support of others, less extroversion, and feeling less safe. There was a suggestion of a beneficial association with some markers of stress. We show that academic performance is assisted by students having a secure physical and emotional base. The students who are most vulnerable are those with fewer social networks, and those who are recent immigrants.

Genome-wide significant risk associations for mucinous ovarian carcinoma.

PubMed

Kelemen, Linda E; Lawrenson, Kate; Tyrer, Jonathan; Li, Qiyuan; Lee, Janet M; Seo, Ji-Heui; Phelan, Catherine M; Beesley, Jonathan; Chen, Xiaoqing; Spindler, Tassja J; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia

2015-08-01

Genome-wide association studies have identified several risk associations for ovarian carcinomas but not for mucinous ovarian carcinomas (MOCs). Our analysis of 1,644 MOC cases and 21,693 controls with imputation identified 3 new risk associations: rs752590 at 2q13 (P = 3.3 × 10(-8)), rs711830 at 2q31.1 (P = 7.5 × 10(-12)) and rs688187 at 19q13.2 (P = 6.8 × 10(-13)). We identified significant expression quantitative trait locus (eQTL) associations for HOXD9 at 2q31.1 in ovarian (P = 4.95 × 10(-4), false discovery rate (FDR) = 0.003) and colorectal (P = 0.01, FDR = 0.09) tumors and for PAX8 at 2q13 in colorectal tumors (P = 0.03, FDR = 0.09). Chromosome conformation capture analysis identified interactions between the HOXD9 promoter and risk-associated SNPs at 2q31.1. Overexpressing HOXD9 in MOC cells augmented the neoplastic phenotype. These findings provide the first evidence for MOC susceptibility variants and insights into the underlying biology of the disease.

Identifying significant predictors of head-on conflicts on two-lane rural roads using inductive loop detectors data.

PubMed

Shariat-Mohaymany, Afshin; Tavakoli-Kashani, Ali; Nosrati, Hadi; Ranjbari, Andisheh

2011-12-01

To identify the significant factors that influence head-on conflicts resulting from dangerous overtaking maneuvers on 2-lane rural roads in Iran. A traffic conflict technique was applied to 12 two-lane rural roads in order to investigate the potential situations for accidents to occur and thus to identify the geometric and traffic factors affecting traffic conflicts. Traffic data were collected via the inductive loop detectors installed on these roads, and geometric characteristics were obtained through field observations. Two groups of data were then analyzed independently by Pearson's chi-square test to evaluate their relationship to traffic conflicts. The independent variables were percentage of time spent following (PTSF), percentage of heavy vehicles, directional distribution of traffic (DDT), mean speed, speed standard deviation, section type, road width, longitudinal slope, holiday or workday, and lighting condition. It was indicated that increasing the PTSF, decreasing the percentage of heavy vehicles, increasing the mean speed (up to 75 km/h), increasing DDT in the range of 0 to 60 percent, and decreasing the standard deviation of speed significantly increased the occurrence of traffic conflicts. It was also revealed that traffic conflicts occur more frequently on curve sections and on workdays. The variables road width, slope, and lighting condition were found to have a minor effect on conflict occurrence. To reduce the number of head-on conflicts on the aforementioned roads, some remedial measures are suggested, such as not constructing long "No Passing" zones and constructing passing lanes where necessary; keeping road width at the standard value; constructing roads with horizontal curves and a high radius and using appropriate road markings and overtaking-forbidden signs where it is impossible to modify the radius; providing enough light and installing caution signs/devices on the roads; and intensifying police control and supervision on workdays

Are Mammographically Occult Additional Tumors Identified More Than 2 Cm Away From the Primary Breast Cancer on MRI Clinically Significant?

PubMed

Goodman, Sarah; Mango, Victoria; Friedlander, Lauren; Desperito, Elise; Wynn, Ralph; Ha, Richard

2018-06-08

To evaluate the clinical significance of mammographically occult additional tumors identified more than 2cm away from the primary breast cancer on preoperative magnetic resonance imaging (MRI). An Institutional Review Board approved review of consecutive preoperative breast MRIs performed from 1/1/08 to 12/31/14, yielded 667 patients with breast cancer. These patients underwent further assessment to identify biopsy proven mammographically occult breast tumors located more than 2cm away from the edge of the primary tumor. Additional MRI characteristics of the primary and secondary tumors and pathology were reviewed. Statistical analysis was performed using SPSS (v. 24). Of 667 patients with breast cancer, 129 patients had 150 additional ipsilateral mammographically occult tumors that were more than 2cm away from the edge of the primary tumor. One hundred twelve of 129 (86.8%) patients had one additional tumor and 17/129 (13.2%) had two or more additional tumors. In 71/129 (55.0%), additional tumors were located in a different quadrant and in 58/129 (45.0%) additional tumors were in the same quadrant but ≥2cm away. Overall, primary tumor size was significantly larger (mean 1.87± 1.25 cm) than the additional tumors (mean 0.79 ± 0.61cm, p < 0.001). However, in 20/129 (15.5%) the additional tumor was larger and in 26/129 (20.2%) the additional tumor was ≥1cm. The primary tumor was significantly more likely to be invasive (81.4%, 105/129) compared to additional tumors (70%, 105/150, p = 0.03). In 9/129 (7.0%) patients, additional tumors yielded unsuspected invasive cancer orhigher tumor grade. The additional tumor was more likely to be nonmass lesion type (37.3% vs 24% p = 0.02) and focus lesion type (10% vs 0.08%, p < 0.001) compared to primary tumor. Mammographically occult additional tumors identified more than 2cm away from the primary breast tumor on MRI are unlikely to be surgically treated if undiagnosed and may be clinically significant. Copyright �

Genome-Wide Gene-Environment Study Identifies Glutamate Receptor Gene GRIN2A as a Parkinson's Disease Modifier Gene via Interaction with Coffee

PubMed Central

Hamza, Taye H.; Chen, Honglei; Hill-Burns, Erin M.; Rhodes, Shannon L.; Montimurro, Jennifer; Kay, Denise M.; Tenesa, Albert; Kusel, Victoria I.; Sheehan, Patricia; Eaaswarkhanth, Muthukrishnan; Yearout, Dora; Samii, Ali; Roberts, John W.; Agarwal, Pinky; Bordelon, Yvette; Park, Yikyung; Wang, Liyong; Gao, Jianjun; Vance, Jeffery M.; Kendler, Kenneth S.; Bacanu, Silviu-Alin; Scott, William K.; Ritz, Beate; Nutt, John; Factor, Stewart A.; Zabetian, Cyrus P.; Payami, Haydeh

2011-01-01

Our aim was to identify genes that influence the inverse association of coffee with the risk of developing Parkinson's disease (PD). We used genome-wide genotype data and lifetime caffeinated-coffee-consumption data on 1,458 persons with PD and 931 without PD from the NeuroGenetics Research Consortium (NGRC), and we performed a genome-wide association and interaction study (GWAIS), testing each SNP's main-effect plus its interaction with coffee, adjusting for sex, age, and two principal components. We then stratified subjects as heavy or light coffee-drinkers and performed genome-wide association study (GWAS) in each group. We replicated the most significant SNP. Finally, we imputed the NGRC dataset, increasing genomic coverage to examine the region of interest in detail. The primary analyses (GWAIS, GWAS, Replication) were performed using genotyped data. In GWAIS, the most significant signal came from rs4998386 and the neighboring SNPs in GRIN2A. GRIN2A encodes an NMDA-glutamate-receptor subunit and regulates excitatory neurotransmission in the brain. Achieving P2df = 10−6, GRIN2A surpassed all known PD susceptibility genes in significance in the GWAIS. In stratified GWAS, the GRIN2A signal was present in heavy coffee-drinkers (OR = 0.43; P = 6×10−7) but not in light coffee-drinkers. The a priori Replication hypothesis that “Among heavy coffee-drinkers, rs4998386_T carriers have lower PD risk than rs4998386_CC carriers” was confirmed: ORReplication = 0.59, PReplication = 10−3; ORPooled = 0.51, PPooled = 7×10−8. Compared to light coffee-drinkers with rs4998386_CC genotype, heavy coffee-drinkers with rs4998386_CC genotype had 18% lower risk (P = 3×10−3), whereas heavy coffee-drinkers with rs4998386_TC genotype had 59% lower risk (P = 6×10−13). Imputation revealed a block of SNPs that achieved P2df<5×10−8 in GWAIS, and OR = 0.41, P = 3×10−8 in heavy coffee-drinkers. This study is proof of concept

Tacrolimus interaction with nafcillin resulting in significant decreases in tacrolimus concentrations: A case report.

PubMed

Wungwattana, Minkey; Savic, Marizela

2017-04-01

Tacrolimus (TAC) is subject to many drug interactions as a result of its metabolism primarily via CYP450 isoenzyme 3A4. Numerous case reports of TAC and CYP3A4 inducers and inhibitors have been described including antimicrobials, calcium channel antagonists, and antiepileptic drugs. We present the case of a 13-year-old patient with cystic fibrosis and a history of liver transplantation, where subtherapeutic TAC concentrations were suspected to be a result of concomitant TAC and nafcillin (NAF) therapy. The observed drug interaction occurred on two separate hospital admissions, during both of which the patient exhibited therapeutic TAC concentrations prior to exposure to NAF, a CYP3A4 inducer. Upon discontinuation of NAF, TAC concentrations recovered in both instances. This case represents a drug-drug interaction between TAC and NAF that has not previously been reported to our knowledge. Despite the lack of existing reports of interaction between these two agents, this case highlights the importance of therapeutic drug monitoring and assessing for any potential drug-drug or drug-food interactions in patients receiving TAC therapy. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Identifying Wave-Particle Interactions in the Solar Wind using Statistical Correlations

NASA Astrophysics Data System (ADS)

Broiles, T. W.; Jian, L. K.; Gary, S. P.; Lepri, S. T.; Stevens, M. L.

2017-12-01

Heavy ions are a trace component of the solar wind, which can resonate with plasma waves, causing heating and acceleration relative to the bulk plasma. While wave-particle interactions are generally accepted as the cause of heavy ion heating and acceleration, observations to constrain the physics are lacking. In this work, we statistically link specific wave modes to heavy ion heating and acceleration. We have computed the Fast Fourier Transform (FFT) of transverse and compressional magnetic waves between 0 and 5.5 Hz using 9 days of ACE and Wind Magnetometer data. The FFTs are averaged over plasma measurement cycles to compute statistical correlations between magnetic wave power at each discrete frequency, and ion kinetic properties measured by ACE/SWICS and Wind/SWE. The results show that lower frequency transverse oscillations (< 0.2 Hz) and higher frequency compressional oscillations (> 0.4 Hz) are positively correlated with enhancements in the heavy ion thermal and drift speeds. Moreover, the correlation results for the He2+ and O6+ were similar on most days. The correlations were often weak, but most days had some frequencies that correlated with statistical significance. This work suggests that the solar wind heavy ions are possibly being heated and accelerated by both transverse and compressional waves at different frequencies.

Short-time windowed covariance: A metric for identifying non-stationary, event-related covariant cortical sites

PubMed Central

Blakely, Timothy; Ojemann, Jeffrey G.; Rao, Rajesh P.N.

2014-01-01

Background Electrocorticography (ECoG) signals can provide high spatio-temporal resolution and high signal to noise ratio recordings of local neural activity from the surface of the brain. Previous studies have shown that broad-band, spatially focal, high-frequency increases in ECoG signals are highly correlated with movement and other cognitive tasks and can be volitionally modulated. However, significant additional information may be present in inter-electrode interactions, but adding additional higher order inter-electrode interactions can be impractical from a computational aspect, if not impossible. New method In this paper we present a new method of calculating high frequency interactions between electrodes called Short-Time Windowed Covariance (STWC) that builds on mathematical techniques currently used in neural signal analysis, along with an implementation that accelerates the algorithm by orders of magnitude by leveraging commodity, off-the-shelf graphics processing unit (GPU) hardware. Results Using the hardware-accelerated implementation of STWC, we identify many types of event-related inter-electrode interactions from human ECoG recordings on global and local scales that have not been identified by previous methods. Unique temporal patterns are observed for digit flexion in both low- (10 mm spacing) and high-resolution (3 mm spacing) electrode arrays. Comparison with existing methods Covariance is a commonly used metric for identifying correlated signals, but the standard covariance calculations do not allow for temporally varying covariance. In contrast STWC allows and identifies event-driven changes in covariance without identifying spurious noise correlations. Conclusions: STWC can be used to identify event-related neural interactions whose high computational load is well suited to GPU capabilities. PMID:24211499

Perturbation analyses of intermolecular interactions

NASA Astrophysics Data System (ADS)

Koyama, Yohei M.; Kobayashi, Tetsuya J.; Ueda, Hiroki R.

2011-08-01

Conformational fluctuations of a protein molecule are important to its function, and it is known that environmental molecules, such as water molecules, ions, and ligand molecules, significantly affect the function by changing the conformational fluctuations. However, it is difficult to systematically understand the role of environmental molecules because intermolecular interactions related to the conformational fluctuations are complicated. To identify important intermolecular interactions with regard to the conformational fluctuations, we develop herein (i) distance-independent and (ii) distance-dependent perturbation analyses of the intermolecular interactions. We show that these perturbation analyses can be realized by performing (i) a principal component analysis using conditional expectations of truncated and shifted intermolecular potential energy terms and (ii) a functional principal component analysis using products of intermolecular forces and conditional cumulative densities. We refer to these analyses as intermolecular perturbation analysis (IPA) and distance-dependent intermolecular perturbation analysis (DIPA), respectively. For comparison of the IPA and the DIPA, we apply them to the alanine dipeptide isomerization in explicit water. Although the first IPA principal components discriminate two states (the α state and PPII (polyproline II) + β states) for larger cutoff length, the separation between the PPII state and the β state is unclear in the second IPA principal components. On the other hand, in the large cutoff value, DIPA eigenvalues converge faster than that for IPA and the top two DIPA principal components clearly identify the three states. By using the DIPA biplot, the contributions of the dipeptide-water interactions to each state are analyzed systematically. Since the DIPA improves the state identification and the convergence rate with retaining distance information, we conclude that the DIPA is a more practical method compared with the

Perturbation analyses of intermolecular interactions.

PubMed

Koyama, Yohei M; Kobayashi, Tetsuya J; Ueda, Hiroki R

2011-08-01

Conformational fluctuations of a protein molecule are important to its function, and it is known that environmental molecules, such as water molecules, ions, and ligand molecules, significantly affect the function by changing the conformational fluctuations. However, it is difficult to systematically understand the role of environmental molecules because intermolecular interactions related to the conformational fluctuations are complicated. To identify important intermolecular interactions with regard to the conformational fluctuations, we develop herein (i) distance-independent and (ii) distance-dependent perturbation analyses of the intermolecular interactions. We show that these perturbation analyses can be realized by performing (i) a principal component analysis using conditional expectations of truncated and shifted intermolecular potential energy terms and (ii) a functional principal component analysis using products of intermolecular forces and conditional cumulative densities. We refer to these analyses as intermolecular perturbation analysis (IPA) and distance-dependent intermolecular perturbation analysis (DIPA), respectively. For comparison of the IPA and the DIPA, we apply them to the alanine dipeptide isomerization in explicit water. Although the first IPA principal components discriminate two states (the α state and PPII (polyproline II) + β states) for larger cutoff length, the separation between the PPII state and the β state is unclear in the second IPA principal components. On the other hand, in the large cutoff value, DIPA eigenvalues converge faster than that for IPA and the top two DIPA principal components clearly identify the three states. By using the DIPA biplot, the contributions of the dipeptide-water interactions to each state are analyzed systematically. Since the DIPA improves the state identification and the convergence rate with retaining distance information, we conclude that the DIPA is a more practical method compared with the

Pathway-based discovery of genetic interactions in breast cancer

PubMed Central

Xu, Zack Z.; Boone, Charles; Lange, Carol A.

2017-01-01

Breast cancer is the second largest cause of cancer death among U.S. women and the leading cause of cancer death among women worldwide. Genome-wide association studies (GWAS) have identified several genetic variants associated with susceptibility to breast cancer, but these still explain less than half of the estimated genetic contribution to the disease. Combinations of variants (i.e. genetic interactions) may play an important role in breast cancer susceptibility. However, due to a lack of statistical power, the current tests for genetic interactions from GWAS data mainly leverage prior knowledge to focus on small sets of genes or SNPs that are known to have an association with breast cancer. Thus, many genetic interactions, particularly among novel variants, remain understudied. Reverse-genetic interaction screens in model organisms have shown that genetic interactions frequently cluster into highly structured motifs, where members of the same pathway share similar patterns of genetic interactions. Based on this key observation, we recently developed a method called BridGE to search for such structured motifs in genetic networks derived from GWAS studies and identify pathway-level genetic interactions in human populations. We applied BridGE to six independent breast cancer cohorts and identified significant pathway-level interactions in five cohorts. Joint analysis across all five cohorts revealed a high confidence consensus set of genetic interactions with support in multiple cohorts. The discovered interactions implicated the glutathione conjugation, vitamin D receptor, purine metabolism, mitotic prometaphase, and steroid hormone biosynthesis pathways as major modifiers of breast cancer risk. Notably, while many of the pathways identified by BridGE show clear relevance to breast cancer, variants in these pathways had not been previously discovered by traditional single variant association tests, or single pathway enrichment analysis that does not consider SNP

49 CFR 520.5 - Guidelines for identifying major actions significantly affecting the environment.

Code of Federal Regulations, 2011 CFR

2011-10-01

... impact but which have a potential for significantly affecting the environment; (2) Any proposed action... relating to the environment; (ii) has a significantly detrimental impact on air or water quality or on... vehicles or motor vehicle equipment; and (13) Any other action that causes significant environment impact...

49 CFR 520.5 - Guidelines for identifying major actions significantly affecting the environment.

Code of Federal Regulations, 2010 CFR

2010-10-01

... significantly affecting the environment. 520.5 Section 520.5 Transportation Other Regulations Relating to... significantly affecting the environment. (a) General guidelines. The phrase, “major Federal actions significantly affecting the quality of the human environment,” as used in this part, shall be construed with a...

The Protein Identifier Cross-Referencing (PICR) service: reconciling protein identifiers across multiple source databases.

PubMed

Côté, Richard G; Jones, Philip; Martens, Lennart; Kerrien, Samuel; Reisinger, Florian; Lin, Quan; Leinonen, Rasko; Apweiler, Rolf; Hermjakob, Henning

2007-10-18

Each major protein database uses its own conventions when assigning protein identifiers. Resolving the various, potentially unstable, identifiers that refer to identical proteins is a major challenge. This is a common problem when attempting to unify datasets that have been annotated with proteins from multiple data sources or querying data providers with one flavour of protein identifiers when the source database uses another. Partial solutions for protein identifier mapping exist but they are limited to specific species or techniques and to a very small number of databases. As a result, we have not found a solution that is generic enough and broad enough in mapping scope to suit our needs. We have created the Protein Identifier Cross-Reference (PICR) service, a web application that provides interactive and programmatic (SOAP and REST) access to a mapping algorithm that uses the UniProt Archive (UniParc) as a data warehouse to offer protein cross-references based on 100% sequence identity to proteins from over 70 distinct source databases loaded into UniParc. Mappings can be limited by source database, taxonomic ID and activity status in the source database. Users can copy/paste or upload files containing protein identifiers or sequences in FASTA format to obtain mappings using the interactive interface. Search results can be viewed in simple or detailed HTML tables or downloaded as comma-separated values (CSV) or Microsoft Excel (XLS) files suitable for use in a local database or a spreadsheet. Alternatively, a SOAP interface is available to integrate PICR functionality in other applications, as is a lightweight REST interface. We offer a publicly available service that can interactively map protein identifiers and protein sequences to the majority of commonly used protein databases. Programmatic access is available through a standards-compliant SOAP interface or a lightweight REST interface. The PICR interface, documentation and code examples are available at

The Protein Identifier Cross-Referencing (PICR) service: reconciling protein identifiers across multiple source databases

PubMed Central

Côté, Richard G; Jones, Philip; Martens, Lennart; Kerrien, Samuel; Reisinger, Florian; Lin, Quan; Leinonen, Rasko; Apweiler, Rolf; Hermjakob, Henning

2007-01-01

Background Each major protein database uses its own conventions when assigning protein identifiers. Resolving the various, potentially unstable, identifiers that refer to identical proteins is a major challenge. This is a common problem when attempting to unify datasets that have been annotated with proteins from multiple data sources or querying data providers with one flavour of protein identifiers when the source database uses another. Partial solutions for protein identifier mapping exist but they are limited to specific species or techniques and to a very small number of databases. As a result, we have not found a solution that is generic enough and broad enough in mapping scope to suit our needs. Results We have created the Protein Identifier Cross-Reference (PICR) service, a web application that provides interactive and programmatic (SOAP and REST) access to a mapping algorithm that uses the UniProt Archive (UniParc) as a data warehouse to offer protein cross-references based on 100% sequence identity to proteins from over 70 distinct source databases loaded into UniParc. Mappings can be limited by source database, taxonomic ID and activity status in the source database. Users can copy/paste or upload files containing protein identifiers or sequences in FASTA format to obtain mappings using the interactive interface. Search results can be viewed in simple or detailed HTML tables or downloaded as comma-separated values (CSV) or Microsoft Excel (XLS) files suitable for use in a local database or a spreadsheet. Alternatively, a SOAP interface is available to integrate PICR functionality in other applications, as is a lightweight REST interface. Conclusion We offer a publicly available service that can interactively map protein identifiers and protein sequences to the majority of commonly used protein databases. Programmatic access is available through a standards-compliant SOAP interface or a lightweight REST interface. The PICR interface, documentation and

Drug-nutrient interactions.

PubMed

Chan, Lingtak-Neander

2013-07-01

Drug-nutrient interactions are defined as physical, chemical, physiologic, or pathophysiologic relationships between a drug and a nutrient. The causes of most clinically significant drug-nutrient interactions are usually multifactorial. Failure to identify and properly manage drug-nutrient interactions can lead to very serious consequences and have a negative impact on patient outcomes. Nevertheless, with thorough review and assessment of the patient's history and treatment regimens and a carefully executed management strategy, adverse events associated with drug-nutrient interactions can be prevented. Based on the physiologic sequence of events after a drug or a nutrient has entered the body and the mechanism of interactions, drug-nutrient interactions can be categorized into 4 main types. Each type of interaction can be managed using similar strategies. The existing data that guide the clinical management of most drug-nutrient interactions are mostly anecdotal experience, uncontrolled observations, and opinions, whereas the science in understanding the mechanism of drug-nutrient interactions remains limited. The challenge for researchers and clinicians is to increase both basic and higher level clinical research in this field to bridge the gap between the science and practice. The research should aim to establish a better understanding of the function, regulation, and substrate specificity of the nutrient-related enzymes and transport proteins present in the gastrointestinal tract, as well as assess how the incidence and management of drug-nutrient interactions can be affected by sex, ethnicity, environmental factors, and genetic polymorphisms. This knowledge can help us develop a true personalized medicine approach in the prevention and management of drug-nutrient interactions.

Macrolide drug interactions: an update.

PubMed

Pai, M P; Graci, D M; Amsden, G W

2000-04-01

To describe the current drug interaction profiles for the commonly used macrolides in the US and Europe, and to comment on the clinical impact of these interactions. A MEDLINE search (1975-1998) was performed to identify all pertinent studies, review articles, and case reports. When appropriate information was not available in the literature, data were obtained from the product manufacturers. All available data were reviewed to provide an unbiased account of possible drug interactions. Data for some of the interactions were not available from the literature, but were available from abstracts or company-supplied materials. Although the data were not always explicit, the best attempt was made to deliver pertinent information that clinical practitioners would need to formulate practice opinions. When more in-depth information was supplied in the form of a review or study report, a thorough explanation of pertinent methodology was supplied. Several clinically significant drug interactions have been identified since the approval of erythromycin. These interactions usually were related to the inhibition of the cytochrome P450 enzyme systems, which are responsible for the metabolism of many drugs. The decreased metabolism by the macrolides has in some instances resulted in potentially severe adverse events. The development and marketing of newer macrolides are hoped to improve the drug interaction profile associated with this class. However, this has produced variable success. Some of the newer macrolides demonstrated an interaction profile similar to that of erythromycin; others have improved profiles. The most success in avoiding drug interactions related to the inhibition of cytochrome P450 has been through the development of the azalide subclass, of which azithromycin is the first and only to be marketed. Azithromycin has not been demonstrated to inhibit the cytochrome P450 system in studies using a human liver microsome model, and to date has produced none of the

Genome-wide association study identifies TF as a significant modifier gene of iron metabolism in HFE hemochromatosis.

PubMed

de Tayrac, Marie; Roth, Marie-Paule; Jouanolle, Anne-Marie; Coppin, Hélène; le Gac, Gérald; Piperno, Alberto; Férec, Claude; Pelucchi, Sara; Scotet, Virginie; Bardou-Jacquet, Edouard; Ropert, Martine; Bouvet, Régis; Génin, Emmanuelle; Mosser, Jean; Deugnier, Yves

2015-03-01

Hereditary hemochromatosis (HH) is the most common form of genetic iron loading disease. It is mainly related to the homozygous C282Y/C282Y mutation in the HFE gene that is, however, a necessary but not a sufficient condition to develop clinical and even biochemical HH. This suggests that modifier genes are likely involved in the expressivity of the disease. Our aim was to identify such modifier genes. We performed a genome-wide association study (GWAS) using DNA collected from 474 unrelated C282Y homozygotes. Associations were examined for both quantitative iron burden indices and clinical outcomes with 534,213 single nucleotide polymorphisms (SNP) genotypes, with replication analyses in an independent sample of 748 C282Y homozygotes from four different European centres. One SNP met genome-wide statistical significance for association with transferrin concentration (rs3811647, GWAS p value of 7×10(-9) and replication p value of 5×10(-13)). This SNP, located within intron 11 of the TF gene, had a pleiotropic effect on serum iron (GWAS p value of 4.9×10(-6) and replication p value of 3.2×10(-6)). Both serum transferrin and iron levels were associated with serum ferritin levels, amount of iron removed and global clinical stage (p<0.01). Serum iron levels were also associated with fibrosis stage (p<0.0001). This GWAS, the largest one performed so far in unselected HFE-associated HH (HFE-HH) patients, identified the rs3811647 polymorphism in the TF gene as the only SNP significantly associated with iron metabolism through serum transferrin and iron levels. Because these two outcomes were clearly associated with the biochemical and clinical expression of the disease, an indirect link between the rs3811647 polymorphism and the phenotypic presentation of HFE-HH is likely. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

49 CFR 520.5 - Guidelines for identifying major actions significantly affecting the environment.

Code of Federal Regulations, 2012 CFR

2012-10-01

... indirectly result in a significant increase in the problem of solid waste, as in the disposal of motor... directly or indirectly result in a significant increase in noise levels, either within a motor vehicle's... significant increase in the energy or fuel necessary to operate a motor vehicle, including but not limited to...

49 CFR 520.5 - Guidelines for identifying major actions significantly affecting the environment.

Code of Federal Regulations, 2014 CFR

2014-10-01

... indirectly result in a significant increase in the problem of solid waste, as in the disposal of motor... directly or indirectly result in a significant increase in noise levels, either within a motor vehicle's... significant increase in the energy or fuel necessary to operate a motor vehicle, including but not limited to...

49 CFR 520.5 - Guidelines for identifying major actions significantly affecting the environment.

Code of Federal Regulations, 2013 CFR

2013-10-01

... indirectly result in a significant increase in the problem of solid waste, as in the disposal of motor... directly or indirectly result in a significant increase in noise levels, either within a motor vehicle's... significant increase in the energy or fuel necessary to operate a motor vehicle, including but not limited to...

Identifying seismic electirc signals upon significant periodic data loss. The case of Japan

NASA Astrophysics Data System (ADS)

Varotsos, P.; Skordas, E. S.; Sarlis, N. V.; Lazaridou, M. S.

2011-12-01

In many cases of geophysical interest, it happens that for substantial parts of the time of data collection, high noise prevents any attempt for extracting a useful signal. Data for such time segments are removed from further analysis. This is the case, for example, in the geoelectrical field measurements at some sites in Japan, where high noise - due mainly to leakage currents from DC driven trains - prevails almost during 70% of the 24 hour operational time. In particular, the low noise time occurs from 00:00 to 06:00 and from 22:00 to 24:00 local time (LT) when nearby DC driven trains cease service, i.e., almost only 30% of the 24 h. Thus, the question arises whether it is still possible to identify seismic electric signals [P. Varotsos and K. Alexopoulos, Tectonophysics 110 (1984) 73-98; 99-125] upon removing the noisy data segments lasting for the period 06:00 to 22:00 every day. We show that even in such a case, the identification of seismic electric signals, which are long-range correlated signals [PA Varotsos, NV Sarlis and ES Skordas, Phys. Rev. E 66 (2002), 011902], may be possible[PA Varotsos, NV Sarlis and ES Skordas, Tectonophysics 503 (2011) 189-194]. The key point is the use of the following two modern methods: The natural time analysis [PA Varotsos, NV Sarlis and ES Skordas, Natural Time Analysis: The new view of time (2011) Springer-Verlag Berlin-Heidelberg] of the remaining data and the Detrended Fluctuation Analysis (DFA). Our main conclusion states that the distinction between seismic electric signal activities (critical dynamics) and artificial noise becomes possible even after removing periodically a significant portion of the data.

The binary protein-protein interaction landscape of Escherichia coli

PubMed Central

Rajagopala, Seesandra V.; Vlasblom, James; Arnold, Roland; Franca-Koh, Jonathan; Pakala, Suman B.; Phanse, Sadhna; Ceol, Arnaud; Häuser, Roman; Siszler, Gabriella; Wuchty, Stefan; Emili, Andrew; Babu, Mohan; Aloy, Patrick; Pieper, Rembert; Uetz, Peter

2014-01-01

Efforts to map the Escherichia coli interactome have identified several hundred macromolecular complexes, but direct binary protein-protein interactions (PPIs) have not been surveyed on a large scale. Here we performed yeast two-hybrid screens of 3,305 baits against 3,606 preys (~70% of the E. coli proteome) in duplicate to generate a map of 2,234 interactions, approximately doubling the number of known binary PPIs in E. coli. Integration of binary PPIs and genetic interactions revealed functional dependencies among components involved in cellular processes, including envelope integrity, flagellum assembly and protein quality control. Many of the binary interactions that could be mapped within multi-protein complexes were informative regarding internal topology and indicated that interactions within complexes are significantly more conserved than those interactions connecting different complexes. This resource will be useful for inferring bacterial gene function and provides a draft reference of the basic physical wiring network of this evolutionarily significant model microbe. PMID:24561554

Risk of Clinically Significant Prostate Cancer Associated With Prostate Imaging Reporting and Data System Category 3 (Equivocal) Lesions Identified on Multiparametric Prostate MRI.

PubMed

Sheridan, Alison D; Nath, Sameer K; Syed, Jamil S; Aneja, Sanjay; Sprenkle, Preston C; Weinreb, Jeffrey C; Spektor, Michael

2018-02-01

The objective of this study is to determine the frequency of clinically significant cancer (CSC) in Prostate Imaging Reporting and Data System (PI-RADS) category 3 (equivocal) lesions prospectively identified on multiparametric prostate MRI and to identify risk factors (RFs) for CSC that may aid in decision making. Between January 2015 and July 2016, a total of 977 consecutively seen men underwent multiparametric prostate MRI, and 342 underwent MRI-ultrasound (US) fusion targeted biopsy. A total of 474 lesions were retrospectively reviewed, and 111 were scored as PI-RADS category 3 and were visualized using a 3-T MRI scanner. Multiparametric prostate MR images were prospectively interpreted by body subspecialty radiologists trained to use PI-RADS version 2. CSC was defined as a Gleason score of at least 7 on targeted biopsy. A multivariate logistic regression model was constructed to identify the RFs associated with CSC. Of the 111 PI-RADS category 3 lesions, 81 (73.0%) were benign, 11 (9.9%) were clinically insignificant (Gleason score, 6), and 19 (17.1%) were clinically significant. On multivariate analysis, three RFs were identified as significant predictors of CSC: older patient age (odds ratio [OR], 1.13; p = 0.002), smaller prostate volume (OR, 0.94; p = 0.008), and abnormal digital rectal examination (DRE) findings (OR, 3.92; p = 0.03). For PI-RADS category 3 lesions associated with zero, one, two, or three RFs, the risk of CSC was 4%, 16%, 62%, and 100%, respectively. PI-RADS category 3 lesions for which two or more RFs were noted (e.g., age ≥ 70 years, gland size ≤ 36 mL, or abnormal DRE findings) had a CSC detection rate of 67% with a sensitivity of 53%, a specificity of 95%, a positive predictive value of 67%, and a negative predictive value of 91%. Incorporating clinical parameters into risk stratification algorithms may improve the ability to detect clinically significant disease among PI-RADS category 3 lesions and may aid in the decision to

Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries

PubMed Central

Guo, Xiuqing; Franceschini, Nora; Cheng, Ching-Yu; Sim, Xueling; Vojinovic, Dina; Marten, Jonathan; Musani, Solomon K.; Li, Changwei; Schwander, Karen; Richard, Melissa A.; Noordam, Raymond; Aschard, Hugues; Bartz, Traci M.; Bielak, Lawrence F.; Dorajoo, Rajkumar; Fisher, Virginia; Hartwig, Fernando P.; Horimoto, Andrea R. V. R.; Lohman, Kurt K.; Manning, Alisa K.; Rankinen, Tuomo; Smith, Albert V.; Wojczynski, Mary K.; Alver, Maris; Boissel, Mathilde; Cai, Qiuyin; Divers, Jasmin; Gao, Chuan; Goel, Anuj; Harris, Sarah E.; He, Meian; Hsu, Fang-Chi; Jackson, Anne U.; Kähönen, Mika; Kasturiratne, Anuradhani; Komulainen, Pirjo; Kühnel, Brigitte; Laguzzi, Federica; Luan, Jian'an; Nolte, Ilja M.; Padmanabhan, Sandosh; Robino, Antonietta; Scott, Robert A.; Sofer, Tamar; Stančáková, Alena; Takeuchi, Fumihiko; Tayo, Bamidele O.; Varga, Tibor V.; Vitart, Veronique; Wang, Yajuan; Warren, Helen R.; Wen, Wanqing; Yanek, Lisa R.; Zhang, Weihua; Zhao, Jing Hua; Afaq, Saima; Amin, Najaf; Arking, Dan E.; Aung, Tin; Boerwinkle, Eric; Borecki, Ingrid; Broeckel, Ulrich; Brown, Morris; Brumat, Marco; Burke, Gregory L.; Chakravarti, Aravinda; Charumathi, Sabanayagam; Ida Chen, Yii-Der; Connell, John M.; Correa, Adolfo; de las Fuentes, Lisa; de Mutsert, Renée; de Silva, H. Janaka; Deng, Xuan; Ding, Jingzhong; Duan, Qing; Eaton, Charles B.; Ehret, Georg; Eppinga, Ruben N.; Faul, Jessica D.; Felix, Stephan B.; Forouhi, Nita G.; Forrester, Terrence; Franco, Oscar H.; Friedlander, Yechiel; Gandin, Ilaria; Gao, He; Ghanbari, Mohsen; Gigante, Bruna; Gu, C. Charles; Gu, Dongfeng; Hagenaars, Saskia P.; Hallmans, Göran; Harris, Tamara B.; He, Jiang; Heng, Chew-Kiat; Hirata, Makoto; Howard, Barbara V.; Ikram, M. Arfan; John, Ulrich; Katsuya, Tomohiro; Khor, Chiea Chuen; Kilpeläinen, Tuomas O.; Koh, Woon-Puay; Krieger, José E.; Kritchevsky, Stephen B.; Kubo, Michiaki; Kuusisto, Johanna; Lakka, Timo A.; Langefeld, Carl D.; Langenberg, Claudia; Launer, Lenore J.; Lehne, Benjamin; Lewis, Cora E.; Li, Yize; Lin, Shiow; Liu, Jianjun; Liu, Jingmin; Loh, Marie; Louie, Tin; Mägi, Reedik; McKenzie, Colin A.; Meitinger, Thomas; Milaneschi, Yuri; Milani, Lili; Mohlke, Karen L.; Momozawa, Yukihide; Nalls, Mike A.; Nelson, Christopher P.; Sotoodehnia, Nona; Norris, Jill M.; O'Connell, Jeff R.; Palmer, Nicholette D.; Perls, Thomas; Pedersen, Nancy L.; Peters, Annette; Peyser, Patricia A.; Poulter, Neil; Raffel, Leslie J.; Raitakari, Olli T.; Roll, Kathryn; Rose, Lynda M.; Rosendaal, Frits R.; Rotter, Jerome I.; Schmidt, Carsten O.; Schreiner, Pamela J.; Schupf, Nicole; Scott, William R.; Shi, Yuan; Sidney, Stephen; Sims, Mario; Sitlani, Colleen M.; Smith, Jennifer A.; Snieder, Harold; Starr, John M.; Strauch, Konstantin; Stringham, Heather M.; Tan, Nicholas Y. Q.; Tang, Hua; Taylor, Kent D.; Teo, Yik Ying; Tham, Yih Chung; Turner, Stephen T.; Uitterlinden, André G.; Vollenweider, Peter; Waldenberger, Melanie; Wang, Lihua; Wang, Ya Xing; Wei, Wen Bin; Williams, Christine; Yao, Jie; Yu, Caizheng; Yuan, Jian-Min; Zhao, Wei; Zonderman, Alan B.; Becker, Diane M.; Boehnke, Michael; Bowden, Donald W.; Chambers, John C.; Deary, Ian J.; Esko, Tõnu; Farrall, Martin; Franks, Paul W.; Freedman, Barry I.; Froguel, Philippe; Gasparini, Paolo; Gieger, Christian; Kamatani, Yoichiro; Kato, Norihiro; Kooner, Jaspal S.; Kutalik, Zoltán; Laakso, Markku; Laurie, Cathy C.; Leander, Karin; Lehtimäki, Terho; Study, Lifelines Cohort; Magnusson, Patrik K. E.; Oldehinkel, Albertine J.; Penninx, Brenda W. J. H.; Polasek, Ozren; Porteous, David J.; Rauramaa, Rainer; Samani, Nilesh J.; Scott, James; Shu, Xiao-Ou; van der Harst, Pim; Wagenknecht, Lynne E.; Watkins, Hugh; Weir, David R.; Wickremasinghe, Ananda R.; Wu, Tangchun; Zheng, Wei; Bouchard, Claude; Christensen, Kaare; Evans, Michele K.; Gudnason, Vilmundur; Horta, Bernardo L.; Kardia, Sharon L. R.; Liu, Yongmei; Pereira, Alexandre C.; Psaty, Bruce M.; Ridker, Paul M.; van Dam, Rob M.; Gauderman, W. James; Zhu, Xiaofeng; Mook-Kanamori, Dennis O.; Fornage, Myriam; Rotimi, Charles N.; Cupples, L. Adrienne; Kelly, Tanika N.; Fox, Ervin R.; Hayward, Caroline; van Duijn, Cornelia M.; Tai, E Shyong; Wong, Tien Yin; Kooperberg, Charles; Palmas, Walter; Morrison, Alanna C.; Caulfield, Mark J.; Munroe, Patricia B.; Rao, Dabeeru C.; Province, Michael A.; Levy, Daniel

2018-01-01

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10−5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10−8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10−8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension. PMID:29912962

Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries.

PubMed

Feitosa, Mary F; Kraja, Aldi T; Chasman, Daniel I; Sung, Yun J; Winkler, Thomas W; Ntalla, Ioanna; Guo, Xiuqing; Franceschini, Nora; Cheng, Ching-Yu; Sim, Xueling; Vojinovic, Dina; Marten, Jonathan; Musani, Solomon K; Li, Changwei; Bentley, Amy R; Brown, Michael R; Schwander, Karen; Richard, Melissa A; Noordam, Raymond; Aschard, Hugues; Bartz, Traci M; Bielak, Lawrence F; Dorajoo, Rajkumar; Fisher, Virginia; Hartwig, Fernando P; Horimoto, Andrea R V R; Lohman, Kurt K; Manning, Alisa K; Rankinen, Tuomo; Smith, Albert V; Tajuddin, Salman M; Wojczynski, Mary K; Alver, Maris; Boissel, Mathilde; Cai, Qiuyin; Campbell, Archie; Chai, Jin Fang; Chen, Xu; Divers, Jasmin; Gao, Chuan; Goel, Anuj; Hagemeijer, Yanick; Harris, Sarah E; He, Meian; Hsu, Fang-Chi; Jackson, Anne U; Kähönen, Mika; Kasturiratne, Anuradhani; Komulainen, Pirjo; Kühnel, Brigitte; Laguzzi, Federica; Luan, Jian'an; Matoba, Nana; Nolte, Ilja M; Padmanabhan, Sandosh; Riaz, Muhammad; Rueedi, Rico; Robino, Antonietta; Said, M Abdullah; Scott, Robert A; Sofer, Tamar; Stančáková, Alena; Takeuchi, Fumihiko; Tayo, Bamidele O; van der Most, Peter J; Varga, Tibor V; Vitart, Veronique; Wang, Yajuan; Ware, Erin B; Warren, Helen R; Weiss, Stefan; Wen, Wanqing; Yanek, Lisa R; Zhang, Weihua; Zhao, Jing Hua; Afaq, Saima; Amin, Najaf; Amini, Marzyeh; Arking, Dan E; Aung, Tin; Boerwinkle, Eric; Borecki, Ingrid; Broeckel, Ulrich; Brown, Morris; Brumat, Marco; Burke, Gregory L; Canouil, Mickaël; Chakravarti, Aravinda; Charumathi, Sabanayagam; Ida Chen, Yii-Der; Connell, John M; Correa, Adolfo; de Las Fuentes, Lisa; de Mutsert, Renée; de Silva, H Janaka; Deng, Xuan; Ding, Jingzhong; Duan, Qing; Eaton, Charles B; Ehret, Georg; Eppinga, Ruben N; Evangelou, Evangelos; Faul, Jessica D; Felix, Stephan B; Forouhi, Nita G; Forrester, Terrence; Franco, Oscar H; Friedlander, Yechiel; Gandin, Ilaria; Gao, He; Ghanbari, Mohsen; Gigante, Bruna; Gu, C Charles; Gu, Dongfeng; Hagenaars, Saskia P; Hallmans, Göran; Harris, Tamara B; He, Jiang; Heikkinen, Sami; Heng, Chew-Kiat; Hirata, Makoto; Howard, Barbara V; Ikram, M Arfan; John, Ulrich; Katsuya, Tomohiro; Khor, Chiea Chuen; Kilpeläinen, Tuomas O; Koh, Woon-Puay; Krieger, José E; Kritchevsky, Stephen B; Kubo, Michiaki; Kuusisto, Johanna; Lakka, Timo A; Langefeld, Carl D; Langenberg, Claudia; Launer, Lenore J; Lehne, Benjamin; Lewis, Cora E; Li, Yize; Lin, Shiow; Liu, Jianjun; Liu, Jingmin; Loh, Marie; Louie, Tin; Mägi, Reedik; McKenzie, Colin A; Meitinger, Thomas; Metspalu, Andres; Milaneschi, Yuri; Milani, Lili; Mohlke, Karen L; Momozawa, Yukihide; Nalls, Mike A; Nelson, Christopher P; Sotoodehnia, Nona; Norris, Jill M; O'Connell, Jeff R; Palmer, Nicholette D; Perls, Thomas; Pedersen, Nancy L; Peters, Annette; Peyser, Patricia A; Poulter, Neil; Raffel, Leslie J; Raitakari, Olli T; Roll, Kathryn; Rose, Lynda M; Rosendaal, Frits R; Rotter, Jerome I; Schmidt, Carsten O; Schreiner, Pamela J; Schupf, Nicole; Scott, William R; Sever, Peter S; Shi, Yuan; Sidney, Stephen; Sims, Mario; Sitlani, Colleen M; Smith, Jennifer A; Snieder, Harold; Starr, John M; Strauch, Konstantin; Stringham, Heather M; Tan, Nicholas Y Q; Tang, Hua; Taylor, Kent D; Teo, Yik Ying; Tham, Yih Chung; Turner, Stephen T; Uitterlinden, André G; Vollenweider, Peter; Waldenberger, Melanie; Wang, Lihua; Wang, Ya Xing; Wei, Wen Bin; Williams, Christine; Yao, Jie; Yu, Caizheng; Yuan, Jian-Min; Zhao, Wei; Zonderman, Alan B; Becker, Diane M; Boehnke, Michael; Bowden, Donald W; Chambers, John C; Deary, Ian J; Esko, Tõnu; Farrall, Martin; Franks, Paul W; Freedman, Barry I; Froguel, Philippe; Gasparini, Paolo; Gieger, Christian; Jonas, Jost Bruno; Kamatani, Yoichiro; Kato, Norihiro; Kooner, Jaspal S; Kutalik, Zoltán; Laakso, Markku; Laurie, Cathy C; Leander, Karin; Lehtimäki, Terho; Study, Lifelines Cohort; Magnusson, Patrik K E; Oldehinkel, Albertine J; Penninx, Brenda W J H; Polasek, Ozren; Porteous, David J; Rauramaa, Rainer; Samani, Nilesh J; Scott, James; Shu, Xiao-Ou; van der Harst, Pim; Wagenknecht, Lynne E; Wareham, Nicholas J; Watkins, Hugh; Weir, David R; Wickremasinghe, Ananda R; Wu, Tangchun; Zheng, Wei; Bouchard, Claude; Christensen, Kaare; Evans, Michele K; Gudnason, Vilmundur; Horta, Bernardo L; Kardia, Sharon L R; Liu, Yongmei; Pereira, Alexandre C; Psaty, Bruce M; Ridker, Paul M; van Dam, Rob M; Gauderman, W James; Zhu, Xiaofeng; Mook-Kanamori, Dennis O; Fornage, Myriam; Rotimi, Charles N; Cupples, L Adrienne; Kelly, Tanika N; Fox, Ervin R; Hayward, Caroline; van Duijn, Cornelia M; Tai, E Shyong; Wong, Tien Yin; Kooperberg, Charles; Palmas, Walter; Rice, Kenneth; Morrison, Alanna C; Elliott, Paul; Caulfield, Mark J; Munroe, Patricia B; Rao, Dabeeru C; Province, Michael A; Levy, Daniel

2018-01-01

Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.

Laboratory simulation reveals significant impacts of ocean acidification on microbial community composition and host-pathogen interactions between the blood clam and Vibrio harveyi.

PubMed

Zha, Shanjie; Liu, Saixi; Su, Wenhao; Shi, Wei; Xiao, Guoqiang; Yan, Maocang; Liu, Guangxu

2017-12-01

It has been suggested that climate change may promote the outbreaks of diseases in the sea through altering the host susceptibility, the pathogen virulence, and the host-pathogen interaction. However, the impacts of ocean acidification (OA) on the pathogen components of bacterial community and the host-pathogen interaction of marine bivalves are still poorly understood. Therefore, 16S rRNA high-throughput sequencing and host-pathogen interaction analysis between blood clam (Tegillarca granosa) and Vibrio harveyi were conducted in the present study to gain a better understanding of the ecological impacts of ocean acidification. The results obtained revealed a significant impact of ocean acidification on the composition of microbial community at laboratory scale. Notably, the abundance of Vibrio, a major group of pathogens to many marine organisms, was significantly increased under ocean acidification condition. In addition, the survival rate and haemolytic activity of V. harveyi were significantly higher in the presence of haemolymph of OA treated T. granosa, indicating a compromised immunity of the clam and enhanced virulence of V. harveyi under future ocean acidification scenarios. Conclusively, the results obtained in this study suggest that future ocean acidification may increase the risk of Vibrio pathogen infection for marine bivalve species, such as blood clams. Copyright © 2017 Elsevier Ltd. All rights reserved.

Regression Trees Identify Relevant Interactions: Can This Improve the Predictive Performance of Risk Adjustment?

PubMed

Buchner, Florian; Wasem, Jürgen; Schillo, Sonja

2017-01-01

Risk equalization formulas have been refined since their introduction about two decades ago. Because of the complexity and the abundance of possible interactions between the variables used, hardly any interactions are considered. A regression tree is used to systematically search for interactions, a methodologically new approach in risk equalization. Analyses are based on a data set of nearly 2.9 million individuals from a major German social health insurer. A two-step approach is applied: In the first step a regression tree is built on the basis of the learning data set. Terminal nodes characterized by more than one morbidity-group-split represent interaction effects of different morbidity groups. In the second step the 'traditional' weighted least squares regression equation is expanded by adding interaction terms for all interactions detected by the tree, and regression coefficients are recalculated. The resulting risk adjustment formula shows an improvement in the adjusted R 2 from 25.43% to 25.81% on the evaluation data set. Predictive ratios are calculated for subgroups affected by the interactions. The R 2 improvement detected is only marginal. According to the sample level performance measures used, not involving a considerable number of morbidity interactions forms no relevant loss in accuracy. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Identification of significant medium components that affect docosahexaenoic acid production by Schizochytrium sp. SW1

NASA Astrophysics Data System (ADS)

Manikan, Vidyah; Hamid, Aidil A.

2013-11-01

Central composite design (CCD) was employed to investigate the significance of glucose, yeast extract, MSG and sea salt in affecting the amount of docosahexaenoic acid (DHA) accumulated by a locally isolated strain of Schizochytrium. Design Expert software was used to construct a set of experiments where each medium component mentioned above was varied over three levels. Cultivation was carried out in 250mL flasks containing 50mL of medium, incubated at 30°C with 200 rpm agitation for 96 hours. ANOVA was conducted to identify the influential factors and the level of their significance where factors that scored a probability value of less than 0.05 were considered significant. The level of influence for each independent variable was also interpreted using perturbation whereas pattern of interaction between the factors were interpreted using interaction plots. This experiment revealed that yeast extract and monosodium glutamate have significant influence on DHA accumulation process by Schizochytrium sp. SW1.

Ion-dipole interactions and their functions in proteins.

PubMed

Sippel, Katherine H; Quiocho, Florante A

2015-07-01

Ion-dipole interactions in biological macromolecules are formed between atomic or molecular ions and neutral protein dipolar groups through either hydrogen bond or coordination. Since their discovery 30 years ago, these interactions have proven to be a frequent occurrence in protein structures, appearing in everything from transporters and ion channels to enzyme active sites to protein-protein interfaces. However, their significance and roles in protein functions are largely underappreciated. We performed PDB data mining to identify a sampling of proteins that possess these interactions. In this review, we will define the ion-dipole interaction and discuss several prominent examples of their functional roles in nature. © 2015 The Protein Society.

Analysis of protein targets in pathogen-host interaction in infectious diseases: a case study on Plasmodium falciparum and Homo sapiens interaction network.

PubMed

Saha, Sovan; Sengupta, Kaustav; Chatterjee, Piyali; Basu, Subhadip; Nasipuri, Mita

2017-09-23

Infection and disease progression is the outcome of protein interactions between pathogen and host. Pathogen, the role player of Infection, is becoming a severe threat to life as because of its adaptability toward drugs and evolutionary dynamism in nature. Identifying protein targets by analyzing protein interactions between host and pathogen is the key point. Proteins with higher degree and possessing some topologically significant graph theoretical measures are found to be drug targets. On the other hand, exceptional nodes may be involved in infection mechanism because of some pathway process and biologically unknown factors. In this article, we attempt to investigate characteristics of host-pathogen protein interactions by presenting a comprehensive review of computational approaches applied on different infectious diseases. As an illustration, we have analyzed a case study on infectious disease malaria, with its causative agent Plasmodium falciparum acting as 'Bait' and host, Homo sapiens/human acting as 'Prey'. In this pathogen-host interaction network based on some interconnectivity and centrality properties, proteins are viewed as central, peripheral, hub and non-hub nodes and their significance on infection process. Besides, it is observed that because of sparseness of the pathogen and host interaction network, there may be some topologically unimportant but biologically significant proteins, which can also act as Bait/Prey. So, functional similarity or gene ontology mapping can help us in this case to identify these proteins. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

A High-Confidence Interaction Map Identifies SIRT1 as a Mediator of Acetylation of USP22 and the SAGA Coactivator Complex

PubMed Central

Armour, Sean M.; Bennett, Eric J.; Braun, Craig R.; Zhang, Xiao-Yong; McMahon, Steven B.; Gygi, Steven P.; Harper, J. Wade

2013-01-01

Although many functions and targets have been attributed to the histone and protein deacetylase SIRT1, a comprehensive analysis of SIRT1 binding proteins yielding a high-confidence interaction map has not been established. Using a comparative statistical analysis of binding partners, we have assembled a high-confidence SIRT1 interactome. Employing this method, we identified the deubiquitinating enzyme ubiquitin-specific protease 22 (USP22), a component of the deubiquitinating module (DUBm) of the SAGA transcriptional coactivating complex, as a SIRT1-interacting partner. We found that this interaction is highly specific, requires the ZnF-UBP domain of USP22, and is disrupted by the inactivating H363Y mutation within SIRT1. Moreover, we show that USP22 is acetylated on multiple lysine residues and that alteration of a single lysine (K129) within the ZnF-UBP domain is sufficient to alter interaction of the DUBm with the core SAGA complex. Furthermore, USP22-mediated recruitment of SIRT1 activity promotes the deacetylation of individual SAGA complex components. Our results indicate an important role of SIRT1-mediated deacetylation in regulating the formation of DUBm subcomplexes within the larger SAGA complex. PMID:23382074

A high-confidence interaction map identifies SIRT1 as a mediator of acetylation of USP22 and the SAGA coactivator complex.

PubMed

Armour, Sean M; Bennett, Eric J; Braun, Craig R; Zhang, Xiao-Yong; McMahon, Steven B; Gygi, Steven P; Harper, J Wade; Sinclair, David A

2013-04-01

Although many functions and targets have been attributed to the histone and protein deacetylase SIRT1, a comprehensive analysis of SIRT1 binding proteins yielding a high-confidence interaction map has not been established. Using a comparative statistical analysis of binding partners, we have assembled a high-confidence SIRT1 interactome. Employing this method, we identified the deubiquitinating enzyme ubiquitin-specific protease 22 (USP22), a component of the deubiquitinating module (DUBm) of the SAGA transcriptional coactivating complex, as a SIRT1-interacting partner. We found that this interaction is highly specific, requires the ZnF-UBP domain of USP22, and is disrupted by the inactivating H363Y mutation within SIRT1. Moreover, we show that USP22 is acetylated on multiple lysine residues and that alteration of a single lysine (K129) within the ZnF-UBP domain is sufficient to alter interaction of the DUBm with the core SAGA complex. Furthermore, USP22-mediated recruitment of SIRT1 activity promotes the deacetylation of individual SAGA complex components. Our results indicate an important role of SIRT1-mediated deacetylation in regulating the formation of DUBm subcomplexes within the larger SAGA complex.

Identification of structural protein-protein interactions of herpes simplex virus type 1.

PubMed

Lee, Jin H; Vittone, Valerio; Diefenbach, Eve; Cunningham, Anthony L; Diefenbach, Russell J

2008-09-01

In this study we have defined protein-protein interactions between the structural proteins of herpes simplex virus type 1 (HSV-1) using a LexA yeast two-hybrid system. The majority of the capsid, tegument and envelope proteins of HSV-1 were screened in a matrix approach. A total of 40 binary interactions were detected including 9 out of 10 previously identified tegument-tegument interactions (Vittone, V., Diefenbach, E., Triffett, D., Douglas, M.W., Cunningham, A.L., and Diefenbach, R.J., 2005. Determination of interactions between tegument proteins of herpes simplex virus type 1. J. Virol. 79, 9566-9571). A total of 12 interactions involving the capsid protein pUL35 (VP26) and 11 interactions involving the tegument protein pUL46 (VP11/12) were identified. The most significant novel interactions detected in this study, which are likely to play a role in viral assembly, include pUL35-pUL37 (capsid-tegument), pUL46-pUL37 (tegument-tegument) and pUL49 (VP22)-pUS9 (tegument-envelope). This information will provide further insights into the pathways of HSV-1 assembly and the identified interactions are potential targets for new antiviral drugs.

Methodology to explore interactions between the water system and society in order to identify adaptation strategies

NASA Astrophysics Data System (ADS)

Offermans, A. G. E.; Haasnoot, M.

2009-04-01

Development of sustainable water management strategies involves analysing current and future vulnerability, identification of adaptation possibilities, effect analysis and evaluation of the strategies under different possible futures. Recent studies on water management often followed the pressure-effect chain and compared the state of social, economic and ecological functions of the water systems in one or two future situations with the current situation. The future is, however, more complex and dynamic. Water management faces major challenges to cope with future uncertainties in both the water system as well as the social system. Uncertainties in our water system relate to (changes in) drivers and pressures and their effects on the state, like the effects of climate change on discharges. Uncertainties in the social world relate to changing of perceptions, objectives and demands concerning water (management), which are often related with the aforementioned changes in the physical environment. The methodology presented here comprises the 'Perspectives method', derived from the Cultural Theory, a method on analyzing and classifying social response to social and natural states and pressures. The method will be used for scenario analysis and to identify social responses including changes in perspectives and management strategies. The scenarios and responses will be integrated within a rapid assessment tool. The purpose of the tool is to provide users with insight about the interaction of the social and physical system and to identify robust water management strategies by analysing the effectiveness under different possible futures on the physical, social and socio-economic system. This method allows for a mutual interaction between the physical and social system. We will present the theoretical background of the perspectives method as well as a historical overview of perspective changes in the Dutch Meuse area to show how social and physical systems interrelate. We

Interactive Book Reading to Accelerate Word Learning by Kindergarten Children With Specific Language Impairment: Identifying an Adequate Intensity and Variation in Treatment Response.

PubMed

Storkel, Holly L; Voelmle, Krista; Fierro, Veronica; Flake, Kelsey; Fleming, Kandace K; Romine, Rebecca Swinburne

2017-01-01

This study sought to identify an adequate intensity of interactive book reading for new word learning by children with specific language impairment (SLI) and to examine variability in treatment response. An escalation design adapted from nontoxic drug trials (Hunsberger, Rubinstein, Dancey, & Korn, 2005) was used in this Phase I/II preliminary clinical trial. A total of 27 kindergarten children with SLI were randomized to 1 of 4 intensities of interactive book reading: 12, 24, 36, or 48 exposures. Word learning was monitored through a definition task and a naming task. An intensity response curve was examined to identify the adequate intensity. Correlations and classification accuracy were used to examine variation in response to treatment relative to pretreatment and early treatment measures. Response to treatment improved as intensity increased from 12 to 24 to 36 exposures, and then no further improvements were observed as intensity increased to 48 exposures. There was variability in treatment response: Children with poor phonological awareness, low vocabulary, and/or poor nonword repetition were less likely to respond to treatment. The adequate intensity for this version of interactive book reading was 36 exposures, but further development of the treatment is needed to increase the benefit for children with SLI.

Interactive Book Reading to Accelerate Word Learning by Kindergarten Children With Specific Language Impairment: Identifying an Adequate Intensity and Variation in Treatment Response

PubMed Central

Voelmle, Krista; Fierro, Veronica; Flake, Kelsey; Fleming, Kandace K.; Romine, Rebecca Swinburne

2017-01-01

Purpose This study sought to identify an adequate intensity of interactive book reading for new word learning by children with specific language impairment (SLI) and to examine variability in treatment response. Method An escalation design adapted from nontoxic drug trials (Hunsberger, Rubinstein, Dancey, & Korn, 2005) was used in this Phase I/II preliminary clinical trial. A total of 27 kindergarten children with SLI were randomized to 1 of 4 intensities of interactive book reading: 12, 24, 36, or 48 exposures. Word learning was monitored through a definition task and a naming task. An intensity response curve was examined to identify the adequate intensity. Correlations and classification accuracy were used to examine variation in response to treatment relative to pretreatment and early treatment measures. Results Response to treatment improved as intensity increased from 12 to 24 to 36 exposures, and then no further improvements were observed as intensity increased to 48 exposures. There was variability in treatment response: Children with poor phonological awareness, low vocabulary, and/or poor nonword repetition were less likely to respond to treatment. Conclusion The adequate intensity for this version of interactive book reading was 36 exposures, but further development of the treatment is needed to increase the benefit for children with SLI. PMID:28036410

Mining the Immune Cell Proteome to Identify Ovarian Cancer-Specific Biomarkers

DTIC Science & Technology

2012-03-01

data and are in the process of identifying gene signatures that can be used as biomarkers for the identification of ovarian cancer-specific biomarkers...groups. The groups showed significant difference in age as well as gestational age, which is expected when considering the disease process . Isolation of...MUC4 in intracellular signaling.32 Oligosaccharides attached to the extracellular domains of mucins have also been shown to interact with different

Hierarchthis: An Interactive Interface for Identifying Mission-Relevant Components of the Advanced Multi-Mission Operations System

NASA Technical Reports Server (NTRS)

Litomisky, Krystof

2012-01-01

Even though NASA's space missions are many and varied, there are some tasks that are common to all of them. For example, all spacecraft need to communicate with other entities, and all spacecraft need to know where they are. These tasks use tools and services that can be inherited and reused between missions, reducing systems engineering effort and therefore reducing cost.The Advanced Multi-Mission Operations System, or AMMOS, is a collection of multimission tools and services, whose development and maintenance are funded by NASA. I created HierarchThis, a plugin designed to provide an interactive interface to help customers identify mission-relevant tools and services. HierarchThis automatically creates diagrams of the AMMOS database, and then allows users to show/hide specific details through a graphical interface. Once customers identify tools and services they want for a specific mission, HierarchThis can automatically generate a contract between the Multimission Ground Systems and Services Office, which manages AMMOS, and the customer. The document contains the selected AMMOS components, along with their capabilities and satisfied requirements. HierarchThis reduces the time needed for the process from service selections to having a mission-specific contract from the order of days to the order of minutes.

Cutpoints for Low Appendicular Lean Mass That Identify Older Adults With Clinically Significant Weakness

PubMed Central

Peters, Katherine W.; Shardell, Michelle D.; McLean, Robert R.; Dam, Thuy-Tien L.; Kenny, Anne M.; Fragala, Maren S.; Harris, Tamara B.; Kiel, Douglas P.; Guralnik, Jack M.; Ferrucci, Luigi; Kritchevsky, Stephen B.; Vassileva, Maria T.; Studenski, Stephanie A.; Alley, Dawn E.

2014-01-01

Background. Low lean mass is potentially clinically important in older persons, but criteria have not been empirically validated. As part of the FNIH (Foundation for the National Institutes of Health) Sarcopenia Project, this analysis sought to identify cutpoints in lean mass by dual-energy x-ray absorptiometry that discriminate the presence or absence of weakness (defined in a previous report in the series as grip strength <26kg in men and <16kg in women). Methods. In pooled cross-sectional data stratified by sex (7,582 men and 3,688 women), classification and regression tree (CART) analysis was used to derive cutpoints for appendicular lean body mass (ALM) that best discriminated the presence or absence of weakness. Mixed-effects logistic regression was used to quantify the strength of the association between lean mass category and weakness. Results. In primary analyses, CART models identified cutpoints for low lean mass (ALM <19.75kg in men and <15.02kg in women). Sensitivity analyses using ALM divided by body mass index (BMI: ALMBMI) identified a secondary definition (ALMBMI <0.789 in men and ALMBMI <0.512 in women). As expected, after accounting for study and age, low lean mass (compared with higher lean mass) was associated with weakness by both the primary (men, odds ratio [OR]: 6.9 [95% CI: 5.4, 8.9]; women, OR: 3.6 [95% CI: 2.9, 4.3]) and secondary definitions (men, OR: 4.3 [95% CI: 3.4, 5.5]; women, OR: 2.2 [95% CI: 1.8, 2.8]). Conclusions. ALM cutpoints derived from a large, diverse sample of older adults identified lean mass thresholds below which older adults had a higher likelihood of weakness. PMID:24737559

Use of multiple correspondence analysis (MCA) to identify interactive meteorological conditions affecting relative throughfall

NASA Astrophysics Data System (ADS)

Van Stan, John T.; Gay, Trent E.; Lewis, Elliott S.

2016-02-01

Forest canopies alter rainfall reaching the surface by redistributing it as throughfall. Throughfall supplies water and nutrients to a variety of ecohydrological components (soil microbial communities, stream water discharge/chemistry, and stormflow pathways) and is controlled by canopy structural interactions with meteorological conditions across temporal scales. This work introduces and applies multiple correspondence analyses (MCAs) to a range of meteorological thresholds (median intensity, median absolute deviation (MAD) of intensity, median wind-driven droplet inclination angle, and MAD of wind speed) for an example throughfall problem: identification of interacting storm conditions corresponding to temporal concentration in relative throughfall beyond the median observation (⩾73% of rain). MCA results from the example show that equalling or exceeding rain intensity thresholds (median and MAD) corresponded with temporal concentration of relative throughfall across all storms. Under these intensity conditions, two wind mechanisms produced significant correspondences: (1) high, steady wind-driven droplet inclination angles increased surface wetting; and (2) sporadic winds shook entrained droplets from surfaces. A discussion is provided showing that these example MCA findings agree well with previous work relying on more historically common methods (e.g., multiple regression and analytical models). Meteorological threshold correspondences to temporal concentration of relative throughfall at our site may be a function of heavy Tillandsia usneoides coverage. Applications of MCA within other forests may provide useful insights to how temporal throughfall dynamics are affected for drainage pathways dependent on different structures (leaves, twigs, branches, etc.).

The maul of the wild. Animal attacks can produce significant trauma.

PubMed

Conrad, L

1994-03-01

Wild-animal attacks are almost an anachronism in our day and age. They remind us that humans can still be food or prey. Cougar attacks, though rare, produce significant trauma. Characteristic patterns of injury and wound infection should be appropriately identified and treated. As we protect wild-animal species and acknowledge their right to share territory, interactions--and possibly attacks--are likely to increase. Awareness, education, knowledge and prevention, rather than the elimination of animal populations, may be the best way to control wild-animal attacks on humans in the future.

Frequency and severity of potential drug interactions in a cohort of HIV-infected patients Identified through a Multidisciplinary team.

PubMed

Molas, E; Luque, S; Retamero, A; Echeverría-Esnal, D; Guelar, A; Montero, M; Guerri, R; Sorli, L; Lerma, E; Villar, J; Knobel, H

2018-02-01

Interactions between antiretroviral treatment (ART) and comedications are a concern in HIV-infected patients. This study aimed to determine the frequency and severity of potential drug-drug interactions (PDDIs) with ART in our setting. Observational study by a multidisciplinary team in 1259 consecutive HIV patients (March 2015-September 2016). Data on demographics, toxic habits, comorbidities, and current ART were collected. A structured questionnaire recorded concomitant medications (including occasional and over-the-counter drugs). PDDIs were classified into four categories: (1) no interactions, (2) mild (clinically non-significant), (3) moderate (requiring close monitoring or drug modification/dose adjustment), and (4) severe (contraindicated). chi-square test, logistic regression analysis. In total, 881 (70%) patients took comedication, and 563 (44.7%) had ≥ PDDI. Forty-one comedicated patients (4.6%) had severe and 522 (59.2%) moderate PDDIs. Moderate PDDIs mainly involved cardiovascular (53.8%) and central nervous system (40.2%) drugs. Independent risk factors for PDDIs were ART containing a boosted protease inhibitor (odds ratio [OR]=9.11, 95% confidence interval [CI] 5.15-16.11; p = 0.0001) and/or non-nucleoside reverse transcriptase (NNRTI) (OR = 4.34, 95%CI 2.49-7.55; p = 0.0001), HCV co-infection (OR = 3.26, 95%CI 2.15-4.93; p = 0.0001), and use of two or more comedications (OR = 3.36, 95%CI 2.27-4.97; p = 0.0001). Adherence and effectiveness of ART were similar in patients with and without PDDIs. The team made 133 recommendations related to comedications (drug change or dose adjustment) or ART (drug switch or change in administration schedule). Systematic evaluation detected a significant percentage of PDDIs requiring an intervention in HIV patients on ART. Monitoring and advice about drug-drug interactions should be part of routine practice.

Interactive Book Reading to Accelerate Word Learning by Kindergarten Children with Specific Language Impairment: Identifying an Adequate Intensity and Variation in Treatment Response

ERIC Educational Resources Information Center

Storkel, Holly L.; Voelmle, Krista; Fierro, Veronica; Flake, Kelsey; Fleming, Kandace K.; Romine, Rebecca Swinburne

2017-01-01

Purpose: This study sought to identify an adequate intensity of interactive book reading for new word learning by children with specific language impairment (SLI) and to examine variability in treatment response. Method: An escalation design adapted from nontoxic drug trials (Hunsberger, Rubinstein, Dancey, & Korn, 2005) was used in this Phase…

Genome-wide significant risk associations for mucinous ovarian carcinoma

PubMed Central

Kelemen, Linda E.; Lawrenson, Kate; Tyrer, Jonathan; Li, Qiyuan; M. Lee, Janet; Seo, Ji-Heui; Phelan, Catherine M.; Beesley, Jonathan; Chen, Xiaoqin; Spindler, Tassja J.; Aben, Katja K.H.; Anton-Culver, Hoda; Antonenkova, Natalia; Baker, Helen; Bandera, Elisa V.; Bean, Yukie; Beckmann, Matthias W.; Bisogna, Maria; Bjorge, Line; Bogdanova, Natalia; Brinton, Louise A.; Brooks-Wilson, Angela; Bruinsma, Fiona; Butzow, Ralf; Campbell, Ian G.; Carty, Karen; Chang-Claude, Jenny; Chen, Y. Ann; Chen, Zhihua; Cook, Linda S.; Cramer, Daniel W.; Cunningham, Julie M.; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A.; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas T.; Edwards, Robert P.; Eilber, Ursula; Ekici, Arif B.; Engelholm, Svend Aage; Fasching, Peter A.; Fridley, Brooke L.; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G.; Glasspool, Rosalind; Goode, Ellen L.; Goodman, Marc T.; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hasmad, Hanis Nazihah; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A.T.; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus; Hosono, Satoyo; Iversen, Edwin S.; Jakubowska, Anna; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kellar, Melissa; Kelley, Joseph L.; Kiemeney, Lambertus A.; Krakstad, Camilla; Kjaer, Susanne K.; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D.; Lee, Alice W.; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A.; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon F.A.G.; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R.; McNeish, Iain; Menon, Usha; Modugno, Francesmary; Moes-Sosnowska, Joanna; Moysich, Kirsten B.; Narod, Steven A.; Nedergaard, Lotte; Ness, Roberta B.; Nevanlinna, Heli; Azmi, Mat Adenan Noor; Odunsi, Kunle; Olson, Sara H.; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Paul, James; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M.; Permuth-Wey, Jennifer; Pike, Malcolm C.; Poole, Elizabeth M.; Ramus, Susan J.; Risch, Harvey A.; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H.; Rudolph, Anja; Runnebaum, Ingo B.; Rzepecka, Iwona K.; Salvesen, Helga B.; Schildkraut, Joellen M.; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C.; Sucheston, Lara; Tangen, Ingvild L.; Teo, Soo-Hwang; Terry, Kathryn L.; Thompson, Pamela J; Tworoger, Shelley S.; van Altena, Anne M.; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A.; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S.; Wicklund, Kristine G.; Wilkens, Lynne R.; Wlodzimierz, Sawicki; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna H.; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A.; Freedman, Matthew L.; Chenevix-Trench, Georgia; Pharoah, Paul D.; Gayther, Simon A.; Berchuck, Andrew

2015-01-01

Genome-wide association studies have identified several risk associations for ovarian carcinomas (OC) but not for mucinous ovarian carcinomas (MOC). Genotypes from OC cases and controls were imputed into the 1000 Genomes Project reference panel. Analysis of 1,644 MOC cases and 21,693 controls identified three novel risk associations: rs752590 at 2q13 (P = 3.3 × 10−8), rs711830 at 2q31.1 (P = 7.5 × 10−12) and rs688187 at 19q13.2 (P = 6.8 × 10−13). Expression Quantitative Trait Locus (eQTL) analysis in ovarian and colorectal tumors (which are histologically similar to MOC) identified significant eQTL associations for HOXD9 at 2q31.1 in ovarian (P = 4.95 × 10−4, FDR = 0.003) and colorectal (P = 0.01, FDR = 0.09) tumors, and for PAX8 at 2q13 in colorectal tumors (P = 0.03, FDR = 0.09). Chromosome conformation capture analysis identified interactions between the HOXD9 promoter and risk SNPs at 2q31.1. Overexpressing HOXD9 in MOC cells augmented the neoplastic phenotype. These findings provide the first evidence for MOC susceptibility variants and insights into the underlying biology of the disease. PMID:26075790

Identifying parasitic and saprotrophic interactions of freshwater chytrids with a microalga

NASA Astrophysics Data System (ADS)

Ward, C.; Longcore, J. E.; Carney, L. T.; Mayali, X.; Pett-Ridge, J.; Thelen, M. P.; Stuart, R.

2016-12-01

Despite having long been regarded as ecologically insignificant, aquatic fungi may be key regulators of carbon cycling in phytoplankton-dominated freshwater ecosystems. For several decades, it has been known that through infection chytrids and other parasitic fungi can cause major declines in natural algal populations and the release of large quantities of organic matter into the water column. Additionally, as in other environments fungi may be critically important in the decomposition of refractory organic matter, although to our knowledge this has never been investigated in pelagic freshwater ecosystems. We have a limited understanding of how fungi can interact with phytoplankton or phytoplankton-derived organic matter, and logistical difficulties complicate their study in the environment. Here, we have developed a model green alga-chytrid system to characterize the interactions under varying host physiologies and to investigate how these interactions influence the physiological and metabolic outcomes of both members. Chytrid infection was clearly linked to algal growth stage in the fungal isolate belonging to Rhizophydiales with infectivity only in late cyst stage, while the isolate belonging to Paraphysoderma could infect in both early and late cyst stages. To test whether freshwater chytrids can metabolize algal-derived organic matter, fungal isolates were grown axenically in algal spent media from different growth stages. The Rhizophydiales isolate grew on algal exudate from early cyst stage, while the Paraphysodermaisolate grew on exudates from both growth stages. Ongoing work has focused on using biochemical and multi-omic approaches to study the mechanistic underpinnings of algal-fungal interactions and to better understand the factors contributing to growth stage- and strain-specific differences. Together, these findings suggest that fungi may play a dual role in regulating carbon cycling in freshwater ecosystems via parasitic and saprotrophic strategies

Molecular dynamics approach to probe PKCβII-ligand interactions and influence of crystal water molecules on these interactions.

PubMed

Grewal, Baljinder K; Bhat, Jyotsna; Sobhia, Masilamani Elizabeth

2015-01-01

PKCβII is a potential target for therapeutic intervention against pandemic diabetic complications. Present study probes the molecular interactions of PKCβII with its clinically important ligands, viz. ruboxistaurin, enzastaurin and co-crystallized ligand, 2-methyl-1H-indol-3-yl-BIM-1. The essentials of PKCβII-ligand interaction, crystal water-induced alterations in these interactions and key interacting flexible residues are analyzed. Computational methodologies, viz. molecular docking and molecular simulation coupled with molecular mechanics-Poisson-Boltzmann surface area and generalized born surface area (MM-PB[GB]SA) are employed. The structural changes in the presence and absence of crystal water molecules in PKCβII ATP binding site residues, and its interaction with bound ligand, are identified. Difference in interaction of selective and nonselective ligand with ATP binding site residues of PKCβII is reported. The study showed that the nonbonding interactions contribute significantly in PKCβII-ligand binding and presence of crystal water molecules affects the interactions. The findings of present work may integrate the new aspects in the drug design process of PKCβII inhibitors.

Differences and similarities between father-infant interaction and mother-infant interaction.

PubMed

Yago, Satoshi; Hirose, Taiko; Okamitsu, Motoko; Okabayashi, Yukiko; Hiroi, Kayoko; Nakagawa, Nozomi; Omori, Takahide

2014-03-19

The aim of this study was to compare father-infant interaction with mother-infant interaction, and explore differences and similarities between parents. Related factors for quality of father-infant interaction were also examined. Sixteen pairs of parents with infants aged 0 to 36 months were observed for play interaction between parents and their children. Results suggested no significant differences between parents, but children's interactions were significantly more contingent with fathers than mothers (p =.045). Significant correlations between parents were found in socialemotional growth fostering encouragement for children during interaction (ρ =.73, p =.001). Paternal depressive symptoms were significantly correlated to paternal sensitivity to child's cues (ρ =-.59, p =.017).

Affinity purification combined with mass spectrometry to identify herpes simplex virus protein-protein interactions.

PubMed

Meckes, David G

2014-01-01

The identification and characterization of herpes simplex virus protein interaction complexes are fundamental to understanding the molecular mechanisms governing the replication and pathogenesis of the virus. Recent advances in affinity-based methods, mass spectrometry configurations, and bioinformatics tools have greatly increased the quantity and quality of protein-protein interaction datasets. In this chapter, detailed and reliable methods that can easily be implemented are presented for the identification of protein-protein interactions using cryogenic cell lysis, affinity purification, trypsin digestion, and mass spectrometry.

Identifying candidate genes affecting developmental time in Drosophila melanogaster: pervasive pleiotropy and gene-by-environment interaction

PubMed Central

Mensch, Julián; Lavagnino, Nicolás; Carreira, Valeria Paula; Massaldi, Ana; Hasson, Esteban; Fanara, Juan José

2008-01-01

Background Understanding the genetic architecture of ecologically relevant adaptive traits requires the contribution of developmental and evolutionary biology. The time to reach the age of reproduction is a complex life history trait commonly known as developmental time. In particular, in holometabolous insects that occupy ephemeral habitats, like fruit flies, the impact of developmental time on fitness is further exaggerated. The present work is one of the first systematic studies of the genetic basis of developmental time, in which we also evaluate the impact of environmental variation on the expression of the trait. Results We analyzed 179 co-isogenic single P[GT1]-element insertion lines of Drosophila melanogaster to identify novel genes affecting developmental time in flies reared at 25°C. Sixty percent of the lines showed a heterochronic phenotype, suggesting that a large number of genes affect this trait. Mutant lines for the genes Merlin and Karl showed the most extreme phenotypes exhibiting a developmental time reduction and increase, respectively, of over 2 days and 4 days relative to the control (a co-isogenic P-element insertion free line). In addition, a subset of 42 lines selected at random from the initial set of 179 lines was screened at 17°C. Interestingly, the gene-by-environment interaction accounted for 52% of total phenotypic variance. Plastic reaction norms were found for a large number of developmental time candidate genes. Conclusion We identified components of several integrated time-dependent pathways affecting egg-to-adult developmental time in Drosophila. At the same time, we also show that many heterochronic phenotypes may arise from changes in genes involved in several developmental mechanisms that do not explicitly control the timing of specific events. We also demonstrate that many developmental time genes have pleiotropic effects on several adult traits and that the action of most of them is sensitive to temperature during

HyCCAPP as a tool to characterize promoter DNA-protein interactions in Saccharomyces cerevisiae.

PubMed

Guillen-Ahlers, Hector; Rao, Prahlad K; Levenstein, Mark E; Kennedy-Darling, Julia; Perumalla, Danu S; Jadhav, Avinash Y L; Glenn, Jeremy P; Ludwig-Kubinski, Amy; Drigalenko, Eugene; Montoya, Maria J; Göring, Harald H; Anderson, Corianna D; Scalf, Mark; Gildersleeve, Heidi I S; Cole, Regina; Greene, Alexandra M; Oduro, Akua K; Lazarova, Katarina; Cesnik, Anthony J; Barfknecht, Jared; Cirillo, Lisa A; Gasch, Audrey P; Shortreed, Michael R; Smith, Lloyd M; Olivier, Michael

2016-06-01

Currently available methods for interrogating DNA-protein interactions at individual genomic loci have significant limitations, and make it difficult to work with unmodified cells or examine single-copy regions without specific antibodies. In this study, we describe a physiological application of the Hybridization Capture of Chromatin-Associated Proteins for Proteomics (HyCCAPP) methodology we have developed. Both novel and known locus-specific DNA-protein interactions were identified at the ENO2 and GAL1 promoter regions of Saccharomyces cerevisiae, and revealed subgroups of proteins present in significantly different levels at the loci in cells grown on glucose versus galactose as the carbon source. Results were validated using chromatin immunoprecipitation. Overall, our analysis demonstrates that HyCCAPP is an effective and flexible technology that does not require specific antibodies nor prior knowledge of locally occurring DNA-protein interactions and can now be used to identify changes in protein interactions at target regions in the genome in response to physiological challenges. Copyright © 2016 Elsevier Inc. All rights reserved.

Macrolides versus azalides: a drug interaction update.

PubMed

Amsden, G W

1995-09-01

To describe the current drug interaction profiles for all approved and investigational macrolide and azalide antimicrobials, and to comment on the clinical impact of these interactions when appropriate. MEDLINE was searched to identify all pertinent studies, review articles, and case reports from 1975 to 1995. When appropriate information was not available in the literature, data were obtained from the product manufacturers. All available data were reviewed to give an unbiased account of possible drug interactions. Data for some of the interactions were not available from the literature, but were available from abstracts or from company-supplied materials. Although the data were not always entirely explicative, the best attempt was made to deliver the pertinent information that clinical practitioners would need to formulate practice opinions. When more in-depth information was supplied in the form of a review or study report, a thorough explanation of pertinent methodology was supplied. Since the introduction of erythromycin into clinical practice, there have been several clinically significant drug interactions identified throughout the literature associated with this drug. These interactions have been caused mostly by inhibition of the CYP3A subclass of hepatic enzymes, thereby decreasing the metabolism of any other agent given concurrently that is also cleared through this mechanism. With the development and marketing of several new macrolides, it was hoped that the drug interaction profile associated with this class would improve. This has been met with variable success. Although some of the extensions of the 14-membered ring macrolides have shown an incidence of interactions equal to that of erythromycin, others have shown improved profiles. In contrast, the 16-membered ring macrolides have demonstrated a much improved, though not absent, interaction profile. The most success in avoiding drug interactions through structure modification has been accomplished

Modular analysis of the probabilistic genetic interaction network.

PubMed

Hou, Lin; Wang, Lin; Qian, Minping; Li, Dong; Tang, Chao; Zhu, Yunping; Deng, Minghua; Li, Fangting

2011-03-15

Epistatic Miniarray Profiles (EMAP) has enabled the mapping of large-scale genetic interaction networks; however, the quantitative information gained from EMAP cannot be fully exploited since the data are usually interpreted as a discrete network based on an arbitrary hard threshold. To address such limitations, we adopted a mixture modeling procedure to construct a probabilistic genetic interaction network and then implemented a Bayesian approach to identify densely interacting modules in the probabilistic network. Mixture modeling has been demonstrated as an effective soft-threshold technique of EMAP measures. The Bayesian approach was applied to an EMAP dataset studying the early secretory pathway in Saccharomyces cerevisiae. Twenty-seven modules were identified, and 14 of those were enriched by gold standard functional gene sets. We also conducted a detailed comparison with state-of-the-art algorithms, hierarchical cluster and Markov clustering. The experimental results show that the Bayesian approach outperforms others in efficiently recovering biologically significant modules.

The McGill Interactive Pediatric OncoGenetic Guidelines: An approach to identifying pediatric oncology patients most likely to benefit from a genetic evaluation.

PubMed

Goudie, Catherine; Coltin, Hallie; Witkowski, Leora; Mourad, Stephanie; Malkin, David; Foulkes, William D

2017-08-01

Identifying cancer predisposition syndromes in children with tumors is crucial, yet few clinical guidelines exist to identify children at high risk of having germline mutations. The McGill Interactive Pediatric OncoGenetic Guidelines project aims to create a validated pediatric guideline in the form of a smartphone/tablet application using algorithms to process clinical data and help determine whether to refer a child for genetic assessment. This paper discusses the initial stages of the project, focusing on its overall structure, the methodology underpinning the algorithms, and the upcoming algorithm validation process. © 2017 Wiley Periodicals, Inc.

Neuropeptide Y gene-by-psychosocial stress interaction effect is associated with obesity in a Korean population.

PubMed

Kim, Hyun-Jin; Min, Kyoung-Bok; Min, Jin-Young

2016-07-01

Chronic psychosocial stress is a crucial risk factor in the development of many diseases including obesity. Neuropeptide Y (NPY), distributed throughout the peripheral and central nervous system, is believed to pay a role in the pathophysiologic relationship between stress and obesity. Although several animal studies have investigated the impact on obesity of interactions between NPY single nucleotide polymorphisms (SNPs) and stress, the same remains to be analyzed in humans. To identify NPY gene-by-stress interaction effects on human obesity, we analyzed the interaction between four NPY SNPs and stress with obesity-related traits, including visceral adipose tissue (VAT). A total of 1468 adult subjects were included for this analysis. In a SNP-only model without interaction with stress, no significant SNPs were found (pSNP>0.05). However, NPY SNPs-by-stress interaction effects were significantly linked to body mass index (BMI), waist circumference, and VAT (pint<0.05), even though a significant interaction effect for rs16135 on BMI was not identified. These significant interaction effects were also detected in interaction results for the binary traits of obesity. Among the obesity traits, mean changes of VAT by increased stress levels in homozygous risk allele carriers were the greatest (range of mean increases for four SNPs (min-max)=12.57cm(2)-29.86cm(2)). This study suggests that common polymorphisms for NPY were associated with human obesity by interacting with psychosocial stress, emphasizing the need for stress management in obesity prevention. Copyright © 2016 Elsevier Ltd. All rights reserved.

Targeted Resequencing and Functional Testing Identifies Low-Frequency Missense Variants in the Gene Encoding GARP as Significant Contributors to Atopic Dermatitis Risk.

PubMed

Manz, Judith; Rodríguez, Elke; ElSharawy, Abdou; Oesau, Eva-Maria; Petersen, Britt-Sabina; Baurecht, Hansjörg; Mayr, Gabriele; Weber, Susanne; Harder, Jürgen; Reischl, Eva; Schwarz, Agatha; Novak, Natalija; Franke, Andre; Weidinger, Stephan

2016-12-01

Gene-mapping studies have consistently identified a susceptibility locus for atopic dermatitis and other inflammatory diseases on chromosome band 11q13.5, with the strongest association observed for a common variant located in an intergenic region between the two annotated genes C11orf30 and LRRC32. Using a targeted resequencing approach we identified low-frequency and rare missense mutations within the LRRC32 gene encoding the protein GARP, a receptor on activated regulatory T cells that binds latent transforming growth factor-β. Subsequent association testing in more than 2,000 atopic dermatitis patients and 2,000 control subjects showed a significant excess of these LRRC32 variants in individuals with atopic dermatitis. Structural protein modeling and bioinformatic analysis predicted a disruption of protein transport upon these variants, and overexpression assays in CD4 + CD25 - T cells showed a significant reduction in surface expression of the mutated protein. Consistently, flow cytometric (FACS) analyses of different T-cell subtypes obtained from atopic dermatitis patients showed a significantly reduced surface expression of GARP and a reduced conversion of CD4 + CD25 - T cells into regulatory T cells, along with lower expression of latency-associated protein upon stimulation in carriers of the LRRC32 A407T variant. These results link inherited disturbances of transforming growth factor-β signaling with atopic dermatitis risk. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

MIX: a computer program to evaluate interaction between chemicals

Treesearch

Jacqueline L. Robertson; Kimberly C. Smith

1989-01-01

A computer program, MIX, was designed to identify pairs of chemicals whose interaction results in a response that departs significantly from the model predicated on the assumption of independent, uncorrelated joint action. This report describes the MIX program, its statistical basis, and instructions for its use.

An analysis of the gene interaction networks identifying the role of PARP1 in metastasis of non-small cell lung cancer.

PubMed

Chen, Kai; Li, Yajie; Xu, Hui; Zhang, Chunfeng; Li, Zhiqiang; Wang, Wei; Wang, Baofeng

2017-10-20

Though there were many researches about the effects of cancer cells on non-small cell lung cancer (NSCLC) currently, it has been rarely reported completed oncogene and its mechanism in tumors by far. Here, we used biological methods with known oncogene of NSCLC to find new oncogene and explore its functionary mechanism in NSCLC. The study firstly built NSCLC genetic interaction network based on bioinformatics methods and then combined shortest path algorithm with significance test to confirmed core genes that were closely involved with given genes; real-time qPCR was conducted to detect expression levels between patients with NSCLC and normal people; additionally, detection of PARP1's role in migration and invasion was performed by trans-well assays and wound-healing. Through gene interaction network, it was found that, core genes like PARP1, EGFR and ALK had a direct interaction. TCGA database showed that PARP1 presented strong expression in NSCLC and the expression level of metastatic NSCLC was significantly higher than that of non-metastatic NSCLC. Cell migration of NSCLC in accordance to the scratch test was suppressed by PARP1 silence but stimulated noticeably by PARP1 overexpression. According to Kaplan-meier survival curve, the higher PARP1 expression, the poorer patient survival rate and prognosis. Thus, PARP1 expression had a negative correction with patient survival rate and prognosis. New oncogene PARP1 was found from known NSCLC oncogene in terms of gene interaction network, demonstrating PARP1's impact on NSCLC cell migration.

Tumor-stroma interactions a trademark for metastasis.

PubMed

Morales, Monica; Planet, Evarist; Arnal-Estape, Anna; Pavlovic, Milica; Tarragona, Maria; Gomis, Roger R

2011-10-01

We aimed to unravel genes that are significantly associated with metastasis in order to identify functions that support disseminated disease. We identify genes associated with metastasis and verify its clinical correlations using publicly available primary tumor expression profile data sets. We used facilities in R and Bioconductor (GSEA). Specific data structures and functions were imported. Our results show that genes associated with metastasis in primary tumor enriched for pathways associated with immune infiltration or cytokine-cytokine receptor interaction. As an example, we focus on the enrichment of TGFBR2 and TGF|X A set of communication tools capital for tumor-stroma interactions that define metastasis to the lung and support bone colonization. We showed that tumor-stroma communication through cytokine-cytokine receptor interaction pathway is selected in primary tumors with high risk of relapse. High levels of these factors support systemic instigation of the far metastatic nest as well as local metastatic-specific functions that provide solid ground for metastatic development. Copyright © 2011 Elsevier Ltd. All rights reserved.

Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

PubMed Central

Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

2014-01-01

Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

Carboxyl group footprinting mass spectrometry and molecular dynamics identify key interactions in the HER2-HER3 receptor tyrosine kinase interface.

PubMed

Collier, Timothy S; Diraviyam, Karthikeyan; Monsey, John; Shen, Wei; Sept, David; Bose, Ron

2013-08-30

The HER2 receptor tyrosine kinase is a driver oncogene in many human cancers, including breast and gastric cancer. Under physiologic levels of expression, HER2 heterodimerizes with other members of the EGF receptor/HER/ErbB family, and the HER2-HER3 dimer forms one of the most potent oncogenic receptor pairs. Previous structural biology studies have individually crystallized the kinase domains of HER2 and HER3, but the HER2-HER3 kinase domain heterodimer structure has yet to be solved. Using a reconstituted membrane system to form HER2-HER3 kinase domain heterodimers and carboxyl group footprinting mass spectrometry, we observed that HER2 and HER3 kinase domains preferentially form asymmetric heterodimers with HER3 and HER2 monomers occupying the donor and acceptor kinase positions, respectively. Conformational changes in the HER2 activation loop, as measured by changes in carboxyl group labeling, required both dimerization and nucleotide binding but did not require activation loop phosphorylation at Tyr-877. Molecular dynamics simulations on HER2-HER3 kinase dimers identify specific inter- and intramolecular interactions and were in good agreement with MS measurements. Specifically, several intermolecular ionic interactions between HER2 Lys-716-HER3 Glu-909, HER2 Glu-717-HER3 Lys-907, and HER2 Asp-871-HER3 Arg-948 were identified by molecular dynamics. We also evaluated the effect of the cancer-associated mutations HER2 D769H/D769Y, HER3 E909G, and HER3 R948K (also numbered HER3 E928G and R967K) on kinase activity in the context of this new structural model. This study provides valuable insights into the EGF receptor/HER/ErbB kinase structure and interactions, which can guide the design of future therapies.

Teaching Women with Intellectual Disabilities to Identify and Report Inappropriate Staff-to-Resident Interactions

ERIC Educational Resources Information Center

Bollman, Jessica R.; Davis, Paula K.

2009-01-01

This study examined the effectiveness of behavioral skills training in teaching 2 adult women with mild intellectual disabilities to report inappropriate staff-to-resident interactions. The reporting skill included making a self-advocacy response, walking away, and reporting the interaction. Participants' performance was measured during baseline,…

A systems biology strategy to identify molecular mechanisms of action and protein indicators of traumatic brain injury.

PubMed

Yu, Chenggang; Boutté, Angela; Yu, Xueping; Dutta, Bhaskar; Feala, Jacob D; Schmid, Kara; Dave, Jitendra; Tawa, Gregory J; Wallqvist, Anders; Reifman, Jaques

2015-02-01

The multifactorial nature of traumatic brain injury (TBI), especially the complex secondary tissue injury involving intertwined networks of molecular pathways that mediate cellular behavior, has confounded attempts to elucidate the pathology underlying the progression of TBI. Here, systems biology strategies are exploited to identify novel molecular mechanisms and protein indicators of brain injury. To this end, we performed a meta-analysis of four distinct high-throughput gene expression studies involving different animal models of TBI. By using canonical pathways and a large human protein-interaction network as a scaffold, we separately overlaid the gene expression data from each study to identify molecular signatures that were conserved across the different studies. At 24 hr after injury, the significantly activated molecular signatures were nonspecific to TBI, whereas the significantly suppressed molecular signatures were specific to the nervous system. In particular, we identified a suppressed subnetwork consisting of 58 highly interacting, coregulated proteins associated with synaptic function. We selected three proteins from this subnetwork, postsynaptic density protein 95, nitric oxide synthase 1, and disrupted in schizophrenia 1, and hypothesized that their abundance would be significantly reduced after TBI. In a penetrating ballistic-like brain injury rat model of severe TBI, Western blot analysis confirmed our hypothesis. In addition, our analysis recovered 12 previously identified protein biomarkers of TBI. The results suggest that systems biology may provide an efficient, high-yield approach to generate testable hypotheses that can be experimentally validated to identify novel mechanisms of action and molecular indicators of TBI. © 2014 The Authors. Journal of Neuroscience Research Published by Wiley Periodicals, Inc.

Development of Novel Random Network Theory-Based Approaches to Identify Network Interactions among Nitrifying Bacteria

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

Shi, Cindy

2015-07-17

The interactions among different microbial populations in a community could play more important roles in determining ecosystem functioning than species numbers and their abundances, but very little is known about such network interactions at a community level. The goal of this project is to develop novel framework approaches and associated software tools to characterize the network interactions in microbial communities based on high throughput, large scale high-throughput metagenomics data and apply these approaches to understand the impacts of environmental changes (e.g., climate change, contamination) on network interactions among different nitrifying populations and associated microbial communities.

Social significance of community structure: Statistical view

NASA Astrophysics Data System (ADS)

Li, Hui-Jia; Daniels, Jasmine J.

2015-01-01

Community structure analysis is a powerful tool for social networks that can simplify their topological and functional analysis considerably. However, since community detection methods have random factors and real social networks obtained from complex systems always contain error edges, evaluating the significance of a partitioned community structure is an urgent and important question. In this paper, integrating the specific characteristics of real society, we present a framework to analyze the significance of a social community. The dynamics of social interactions are modeled by identifying social leaders and corresponding hierarchical structures. Instead of a direct comparison with the average outcome of a random model, we compute the similarity of a given node with the leader by the number of common neighbors. To determine the membership vector, an efficient community detection algorithm is proposed based on the position of the nodes and their corresponding leaders. Then, using a log-likelihood score, the tightness of the community can be derived. Based on the distribution of community tightness, we establish a connection between p -value theory and network analysis, and then we obtain a significance measure of statistical form . Finally, the framework is applied to both benchmark networks and real social networks. Experimental results show that our work can be used in many fields, such as determining the optimal number of communities, analyzing the social significance of a given community, comparing the performance among various algorithms, etc.

[Quantitative Prediction of Drug-Drug Interaction Caused by CYP Inhibition and Induction from In Vivo Data and Its Application in Daily Clinical Practices-Proposal for the Pharmacokinetic Interaction Significance Classification System (PISCS)].

PubMed

Ohno, Yoshiyuki

2018-01-01

　Drug-drug interactions (DDIs) can affect the clearance of various drugs from the body; however, these effects are difficult to sufficiently evaluate in clinical studies. This article outlines our approach to improving methods for evaluating and providing drug information relative to the effects of DDIs. In a previous study, total exposure changes to many substrate drugs of CYP caused by the co-administration of inhibitor or inducer drugs were successfully predicted using in vivo data. There are two parameters for the prediction: the contribution ratio of the enzyme to oral clearance for substrates (CR), and either the inhibition ratio for inhibitors (IR) or the increase in clearance of substrates produced by induction (IC). To apply these predictions in daily pharmacotherapy, the clinical significance of any pharmacokinetic changes must be carefully evaluated. We constructed a pharmacokinetic interaction significance classification system (PISCS) in which the clinical significance of DDIs was considered in a systematic manner, according to pharmacokinetic changes. The PISCS suggests that many current 'alert' classifications are potentially inappropriate, especially for drug combinations in which pharmacokinetics have not yet been evaluated. It is expected that PISCS would contribute to constructing a reliable system to alert pharmacists, physicians and consumers of a broad range of pharmacokinetic DDIs in order to more safely manage daily clinical practices.

CMDR based differential evolution identifies the epistatic interaction in genome-wide association studies.

PubMed

Yang, Cheng-Hong; Chuang, Li-Yeh; Lin, Yu-Da

2017-08-01

Detecting epistatic interactions in genome-wide association studies (GWAS) is a computational challenge. Such huge numbers of single-nucleotide polymorphism (SNP) combinations limit the some of the powerful algorithms to be applied to detect the potential epistasis in large-scale SNP datasets. We propose a new algorithm which combines the differential evolution (DE) algorithm with a classification based multifactor-dimensionality reduction (CMDR), termed DECMDR. DECMDR uses the CMDR as a fitness measure to evaluate values of solutions in DE process for scanning the potential statistical epistasis in GWAS. The results indicated that DECMDR outperforms the existing algorithms in terms of detection success rate by the large simulation and real data obtained from the Wellcome Trust Case Control Consortium. For running time comparison, DECMDR can efficient to apply the CMDR to detect the significant association between cases and controls amongst all possible SNP combinations in GWAS. DECMDR is freely available at https://goo.gl/p9sLuJ . chuang@isu.edu.tw or e0955767257@yahoo.com.tw. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

MEDICI: Mining Essentiality Data to Identify Critical Interactions for Cancer Drug Target Discovery and Development | Office of Cancer Genomics

Cancer.gov

Protein-protein interactions (PPIs) mediate the transmission and regulation of oncogenic signals that are essential to cellular proliferation and survival, and thus represent potential targets for anti-cancer therapeutic discovery. Despite their significance, there is no method to experimentally disrupt and interrogate the essentiality of individual endogenous PPIs. The ability to computationally predict or infer PPI essentiality would help prioritize PPIs for drug discovery and help advance understanding of cancer biology.

Gene-environment interaction study for BMI reveals interactions between genetic factors and physical activity, alcohol consumption and socioeconomic status

PubMed Central

Karlsson, Torgny; Ek, Weronica E.

2017-01-01

Previous genome-wide association studies (GWAS) have identified hundreds of genetic loci to be associated with body mass index (BMI) and risk of obesity. Genetic effects can differ between individuals depending on lifestyle or environmental factors due to gene-environment interactions. In this study, we examine gene-environment interactions in 362,496 unrelated participants with Caucasian ancestry from the UK Biobank resource. A total of 94 BMI-associated SNPs, selected from a previous GWAS on BMI, were used to construct weighted genetic scores for BMI (GSBMI). Linear regression modeling was used to estimate the effect of gene-environment interactions on BMI for 131 lifestyle factors related to: dietary habits, smoking and alcohol consumption, physical activity, socioeconomic status, mental health, sleeping patterns, as well as female-specific factors such as menopause and childbirth. In total, 15 lifestyle factors were observed to interact with GSBMI, of which alcohol intake frequency, usual walking pace, and Townsend deprivation index, a measure of socioeconomic status, were all highly significant (p = 1.45*10−29, p = 3.83*10−26, p = 4.66*10−11, respectively). Interestingly, the frequency of alcohol consumption, rather than the total weekly amount resulted in a significant interaction. The FTO locus was the strongest single locus interacting with any of the lifestyle factors. However, 13 significant interactions were also observed after omitting the FTO locus from the genetic score. Our analyses indicate that many lifestyle factors modify the genetic effects on BMI with some groups of individuals having more than double the effect of the genetic score. However, the underlying causal mechanisms of gene-environmental interactions are difficult to deduce from cross-sectional data alone and controlled experiments are required to fully characterise the causal factors. PMID:28873402

Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases.

PubMed

Berger, Seth I; Posner, Jeremy M; Ma'ayan, Avi

2007-10-04

In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP), generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

Obesity and Sex Interact in the Regulation of Alzheimer’s Disease

PubMed Central

Moser, V. Alexandra; Pike, Christian J.

2015-01-01

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder, for which a number of genetic, environmental, and lifestyle risk factors have been identified. A significant modifiable risk factor is obesity in mid-life. Interestingly, both obesity and AD exhibit sex differences and are regulated by sex steroid hormones. Accumulating evidence suggests interactions between obesity and sex in regulation of AD risk, although the pathways underlying this relationship are unclear. Inflammation and the E4 allele of apolipoprotein E have been identified as independent risk factors for AD and both interact with obesity and sex steroid hormones. We review the individual and cooperative effects of obesity and sex on development of AD and examine the potential contributions of apolipoprotein E, inflammation, and their interactions to this relationship. PMID:26708713

Multigene interactions and the prediction of depression in the Wisconsin Longitudinal Study

PubMed Central

Roetker, Nicholas S; Yonker, James A; Lee, Chee; Chang, Vicky; Basson, Jacob J; Roan, Carol L; Hauser, Taissa S; Hauser, Robert M

2012-01-01

Objectives Single genetic loci offer little predictive power for the identification of depression. This study examined whether an analysis of gene–gene (G × G) interactions of 78 single nucleotide polymorphisms (SNPs) in genes associated with depression and age-related diseases would identify significant interactions with increased predictive power for depression. Design A retrospective cohort study. Setting A survey of participants in the Wisconsin Longitudinal Study. Participants A total of 4811 persons (2464 women and 2347 men) who provided saliva for genotyping; the group comes from a randomly selected sample of Wisconsin high school graduates from the class of 1957 as well as a randomly selected sibling, almost all of whom are non-Hispanic white. Primary outcome measure Depression as determine by the Composite International Diagnostic Interview–Short-Form. Results Using a classification tree approach (recursive partitioning (RP)), the authors identified a number of candidate G × G interactions associated with depression. The primary SNP splits revealed by RP (ANKK1 rs1800497 (also known as DRD2 Taq1A) in men and DRD2 rs224592 in women) were found to be significant as single factors by logistic regression (LR) after controlling for multiple testing (p=0.001 for both). Without considering interaction effects, only one of the five subsequent RP splits reached nominal significance in LR (FTO rs1421085 in women, p=0.008). However, after controlling for G × G interactions by running LR on RP-specific subsets, every split became significant and grew larger in magnitude (OR (before) → (after): men: GNRH1 novel SNP: (1.43 → 1.57); women: APOC3 rs2854116: (1.28 → 1.55), ACVR2B rs3749386: (1.11 → 2.17), FTO rs1421085: (1.32 → 1.65), IL6 rs1800795: (1.12 → 1.85)). Conclusions The results suggest that examining G × G interactions improves the identification of genetic associations predictive of depression. 4 of the SNPs identified in these interactions

Gene-diet interaction effects on BMI levels in the Singapore Chinese population.

PubMed

Chang, Xuling; Dorajoo, Rajkumar; Sun, Ye; Han, Yi; Wang, Ling; Khor, Chiea-Chuen; Sim, Xueling; Tai, E-Shyong; Liu, Jianjun; Yuan, Jian-Min; Koh, Woon-Puay; van Dam, Rob M; Friedlander, Yechiel; Heng, Chew-Kiat

2018-02-24

Recent genome-wide association studies (GWAS) have identified 97 body-mass index (BMI) associated loci. We aimed to evaluate if dietary intake modifies BMI associations at these loci in the Singapore Chinese population. We utilized GWAS information from six data subsets from two adult Chinese population (N = 7817). Seventy-eight genotyped or imputed index BMI single nucleotide polymorphisms (SNPs) that passed quality control procedures were available in all datasets. Alternative Healthy Eating Index (AHEI)-2010 score and ten nutrient variables were evaluated. Linear regression analyses between z score transformed BMI (Z-BMI) and dietary factors were performed. Interaction analyses were performed by introducing the interaction term (diet x SNP) in the same regression model. Analysis was carried out in each cohort individually and subsequently meta-analyzed using the inverse-variance weighted method. Analyses were also evaluated with a weighted gene-risk score (wGRS) contructed by BMI index SNPs from recent large-scale GWAS studies. Nominal associations between Z-BMI and AHEI-2010 and some dietary factors were identified (P = 0.047-0.010). The BMI wGRS was robustly associated with Z-BMI (P = 1.55 × 10 - 15 ) but not with any dietary variables. Dietary variables did not significantly interact with the wGRS to modify BMI associations. When interaction analyses were repeated using individual SNPs, a significant association between cholesterol intake and rs4740619 (CCDC171) was identified (β = 0.077, adjP interaction  = 0.043). The CCDC171 gene locus may interact with cholesterol intake to increase BMI in the Singaporean Chinese population, however most known obesity risk loci were not associated with dietary intake and did not interact with diet to modify BMI levels.

BCL-2 system analysis identifies high-risk colorectal cancer patients.

PubMed

Lindner, Andreas U; Salvucci, Manuela; Morgan, Clare; Monsefi, Naser; Resler, Alexa J; Cremona, Mattia; Curry, Sarah; Toomey, Sinead; O'Byrne, Robert; Bacon, Orna; Stühler, Michael; Flanagan, Lorna; Wilson, Richard; Johnston, Patrick G; Salto-Tellez, Manuel; Camilleri-Broët, Sophie; McNamara, Deborah A; Kay, Elaine W; Hennessy, Bryan T; Laurent-Puig, Pierre; Van Schaeybroeck, Sandra; Prehn, Jochen H M

2017-12-01

The mitochondrial apoptosis pathway is controlled by an interaction of multiple BCL-2 family proteins, and plays a key role in tumour progression and therapy responses. We assessed the prognostic potential of an experimentally validated, mathematical model of BCL-2 protein interactions (DR_MOMP) in patients with stage III colorectal cancer (CRC). Absolute protein levels of BCL-2 family proteins were determined in primary CRC tumours collected from n=128 resected and chemotherapy-treated patients with stage III CRC. We applied DR_MOMP to categorise patients as high or low risk based on model outputs, and compared model outputs with known prognostic factors (T-stage, N-stage, lymphovascular invasion). DR_MOMP signatures were validated on protein of n=156 patients with CRC from the Cancer Genome Atlas (TCGA) project. High-risk stage III patients identified by DR_MOMP had an approximately fivefold increased risk of death compared with patients identified as low risk (HR 5.2, 95% CI 1.4 to 17.9, p=0.02). The DR_MOMP signature ranked highest among all molecular and pathological features analysed. The prognostic signature was validated in the TCGA colon adenocarcinoma (COAD) cohort (HR 4.2, 95% CI 1.1 to 15.6, p=0.04). DR_MOMP also further stratified patients identified by supervised gene expression risk scores into low-risk and high-risk categories. BCL-2-dependent signalling critically contributed to treatment responses in consensus molecular subtypes 1 and 3, linking for the first time specific molecular subtypes to apoptosis signalling. DR_MOMP delivers a system-based biomarker with significant potential as a prognostic tool for stage III CRC that significantly improves established histopathological risk factors. 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/.

HVint: A Strategy for Identifying Novel Protein-Protein Interactions in Herpes Simplex Virus Type 1*

PubMed Central

Hernandez, Anna; Buch, Anna; Sodeik, Beate; Cristea, Ileana Mihaela

2016-01-01

Human herpesviruses are widespread human pathogens with a remarkable impact on worldwide public health. Despite intense decades of research, the molecular details in many aspects of their function remain to be fully characterized. To unravel the details of how these viruses operate, a thorough understanding of the relationships between the involved components is key. Here, we present HVint, a novel protein-protein intraviral interaction resource for herpes simplex virus type 1 (HSV-1) integrating data from five external sources. To assess each interaction, we used a scoring scheme that takes into consideration aspects such as the type of detection method and the number of lines of evidence. The coverage of the initial interactome was further increased using evolutionary information, by importing interactions reported for other human herpesviruses. These latter interactions constitute, therefore, computational predictions for potential novel interactions in HSV-1. An independent experimental analysis was performed to confirm a subset of our predicted interactions. This subset covers proteins that contribute to nuclear egress and primary envelopment events, including VP26, pUL31, pUL40, and the recently characterized pUL32 and pUL21. Our findings support a coordinated crosstalk between VP26 and proteins such as pUL31, pUS9, and the CSVC complex, contributing to the development of a model describing the nuclear egress and primary envelopment pathways of newly synthesized HSV-1 capsids. The results are also consistent with recent findings on the involvement of pUL32 in capsid maturation and early tegumentation events. Further, they open the door to new hypotheses on virus-specific regulators of pUS9-dependent transport. To make this repository of interactions readily accessible for the scientific community, we also developed a user-friendly and interactive web interface. Our approach demonstrates the power of computational predictions to assist in the design of

Genome-wide gene-asbestos exposure interaction association study identifies a common susceptibility variant on 22q13.31 associated with lung cancer risk

PubMed Central

Liu, Chen-yu; Stücker, Isabelle; Chen, Chu; Goodman, Gary; McHugh, Michelle K.; D’Amelio, Anthony M.; Etzel, Carol J.; Li, Su; Lin, Xihong; Christiani, David C.

2015-01-01

Background Occupational asbestos exposure has been found to increase lung cancer risk in epidemiological studies. Methods We conducted an asbestos exposure-gene interaction analyses among several Caucasian populations who were current or ex-smokers. The discovery phase included 833 Caucasian cases and 739 Caucasian controls, and used a genome-wide association study (GWAS) to identify single nucleotide polymorphisms (SNPs) with gene-asbestos interaction effects. The top ranked SNPs from the discovery phase were replicated within the International Lung and Cancer Consortium (ILCCO). First, in silico replication was conducted in those groups that had GWAS and asbestos exposure data, including 1,548 cases and 1,527 controls. This step was followed by de novo genotyping to replicate the results from the in silico replication, and included 1,539 cases and 1,761 controls. Multiple logistic regression was used to assess the SNP-asbestos exposure interaction effects on lung cancer risk. Results We observed significantly increased lung cancer risk among MIRLET7BHG (MIRLET7B host gene located at 22q13.31) polymorphisms rs13053856, rs11090910, rs11703832, and rs12170325 heterozygous and homozygous variant allele(s) carriers [p<5×10−7 by likelihood ratio test; df=1]. Among the heterozygous and homozygous variant allele(s) carriers of polymorphisms rs13053856, rs11090910, rs11703832, and rs12170325, each unit increase in the natural log-transformed asbestos exposure score was associated with age-, sex-, smoking status- and center-adjusted ORs of 1.34 (95%CI=1.18–1.51), 1.24 (95%CI=1.14–1.35), 1.28 (95%CI=1.17–1.40), and 1.26 (95%CI=1.15–1.38), respectively for lung cancer risk. Conclusion Our findings suggest that MIRLET7BHG polymorphisms may be important predictive markers for asbestos exposure-related lung cancer. Impact To our knowledge, our study is the first report using a systematic genome-wide analysis in combination with detailed asbestos exposure data and

Flash visual evoked potentials are not specific enough to identify parieto-occipital lobe involvement in term neonates after significant hypoglycaemia.

PubMed

Hu, Liyuan; Gu, Qiufang; Zhu, Zhen; Yang, Chenhao; Chen, Chao; Cao, Yun; Zhou, Wenhao

2014-08-01

Hypoglycaemia is a significant problem in high-risk neonates and predominant parieto-occipital lobe involvement has been observed after severe hypoglycaemic insult. We explored the use of flash visual evoked potentials (FVEP) in detecting parieto-occipital lobe involvement after significant hypoglycaemia. Full-term neonates (n = 15) who underwent FVEP from January 2008 to May 2013 were compared with infants (n = 11) without hypoglycaemia or parietal-occipital lobe injury. Significant hypoglycaemia was defined as being symptomatic or needing steroids, glucagon or a glucose infusion rate of ≥12 mg/kg/min. The hypoglycaemia group exhibited delayed latency of the first positive waveform on FVEP. The initial detected time for hypoglycaemia was later in the eight subjects with seizures (median 51-h-old) than those without (median 22-h-old) (P = 0.003). Magnetic resonance imaging showed that 80% of the hypoglycaemia group exhibited occipital-lobe injuries, and they were more likely to exhibit abnormal FVEP morphology (P = 0.007) than the controls. FVEP exhibited 100% sensitivity, but only 25% specificity, for detecting injuries to the parieto-occipital lobes. Flash visual evoked potential (FVEP) was sensitive, but not sufficiently specific, in identifying parieto-occipital lobe injuries among term neonates exposed to significant hypoglycaemia. Larger studies exploring the potential role of FVEP in neonatal hypoglycaemia are required. ©2014 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

A Physical Interaction Network of Dengue Virus and Human Proteins*

PubMed Central

Khadka, Sudip; Vangeloff, Abbey D.; Zhang, Chaoying; Siddavatam, Prasad; Heaton, Nicholas S.; Wang, Ling; Sengupta, Ranjan; Sahasrabudhe, Sudhir; Randall, Glenn; Gribskov, Michael; Kuhn, Richard J.; Perera, Rushika; LaCount, Douglas J.

2011-01-01

Dengue virus (DENV), an emerging mosquito-transmitted pathogen capable of causing severe disease in humans, interacts with host cell factors to create a more favorable environment for replication. However, few interactions between DENV and human proteins have been reported to date. To identify DENV-human protein interactions, we used high-throughput yeast two-hybrid assays to screen the 10 DENV proteins against a human liver activation domain library. From 45 DNA-binding domain clones containing either full-length viral genes or partially overlapping gene fragments, we identified 139 interactions between DENV and human proteins, the vast majority of which are novel. These interactions involved 105 human proteins, including six previously implicated in DENV infection and 45 linked to the replication of other viruses. Human proteins with functions related to the complement and coagulation cascade, the centrosome, and the cytoskeleton were enriched among the DENV interaction partners. To determine if the cellular proteins were required for DENV infection, we used small interfering RNAs to inhibit their expression. Six of 12 proteins targeted (CALR, DDX3X, ERC1, GOLGA2, TRIP11, and UBE2I) caused a significant decrease in the replication of a DENV replicon. We further showed that calreticulin colocalized with viral dsRNA and with the viral NS3 and NS5 proteins in DENV-infected cells, consistent with a direct role for calreticulin in DENV replication. Human proteins that interacted with DENV had significantly higher average degree and betweenness than expected by chance, which provides additional support for the hypothesis that viruses preferentially target cellular proteins that occupy central position in the human protein interaction network. This study provides a valuable starting point for additional investigations into the roles of human proteins in DENV infection. PMID:21911577

Comparative Characterization of the Sindbis Virus Proteome from Mammalian and Invertebrate Hosts Identifies nsP2 as a Component of the Virus Nucleocapsid and Sorting Nexin 5 as a Significant Host Factor for Alphavirus Replication.

PubMed

Schuchman, Ryan; Kilianski, Andy; Piper, Amanda; Vancini, Ricardo; Ribeiro, José M C; Sprague, Thomas R; Nasar, Farooq; Boyd, Gabrielle; Hernandez, Raquel; Glaros, Trevor

2018-05-09

Recent advances in mass spectrometry methods and instrumentation now allow for more accurate identification of proteins in low abundance. This technology was applied to Sindbis virus, the prototypical alphavirus to investigate the viral proteome. To determine if host proteins are specifically packaged into alphavirus virions, Sindbis virus (SINV) was grown in multiple host cells representing vertebrate and mosquito hosts and total protein content of purified virions was determined. This analysis identified host factors not previously associated with alphavirus entry, replication, or egress. One host protein, sorting nexin 5 (SNX5), was shown to be critical for the replication of three different alphaviruses, Sindbis, Mayaro and Chikungunya virus. The most significant finding was that in addition to the host proteins, SINV non-structural protein 2 (nsP2) was detected within virions grown in all host cells examined. The protein and RNA-interacting capabilities of nsP2 coupled with its presence in the virion support a role for nsP2 during packaging and/or entry of progeny virus. This function has not been identified for this protein. Taken together, this strategy identified at least one host factor integrally involved in alphavirus replication. Identification of other host proteins provides insight into alphavirus-host interactions during viral replication in both vertebrate and invertebrate hosts. This method of virus proteome analysis may also be useful for the identification of protein candidates for host-based therapeutics. IMPORTANCE Pathogenic Alphaviruses, such as Chikungunya and Mayaro virus, continue to plague public health in developing and developed countries alike. Alphaviruses belong to a group of viruses vectored in nature by hematophagous (blood-feeding) insects and are termed Arboviruses (arthropod-borne viruses). This group of viruses contains many human pathogens such as dengue fever, West Nile and Yellow fever viruses. With few exceptions there are

Genome-wide transcriptome study in wheat identified candidate genes related to processing quality, majority of them showing interaction (quality x development) and having temporal and spatial distributions.

PubMed

Singh, Anuradha; Mantri, Shrikant; Sharma, Monica; Chaudhury, Ashok; Tuli, Rakesh; Roy, Joy

2014-01-16

The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments. Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT-PCR. Therefore, this study

Genome-wide transcriptome study in wheat identified candidate genes related to processing quality, majority of them showing interaction (quality x development) and having temporal and spatial distributions

PubMed Central

2014-01-01

Background The cultivated bread wheat (Triticum aestivum L.) possesses unique flour quality, which can be processed into many end-use food products such as bread, pasta, chapatti (unleavened flat bread), biscuit, etc. The present wheat varieties require improvement in processing quality to meet the increasing demand of better quality food products. However, processing quality is very complex and controlled by many genes, which have not been completely explored. To identify the candidate genes whose expressions changed due to variation in processing quality and interaction (quality x development), genome-wide transcriptome studies were performed in two sets of diverse Indian wheat varieties differing for chapatti quality. It is also important to understand the temporal and spatial distributions of their expressions for designing tissue and growth specific functional genomics experiments. Results Gene-specific two-way ANOVA analysis of expression of about 55 K transcripts in two diverse sets of Indian wheat varieties for chapatti quality at three seed developmental stages identified 236 differentially expressed probe sets (10-fold). Out of 236, 110 probe sets were identified for chapatti quality. Many processing quality related key genes such as glutenin and gliadins, puroindolines, grain softness protein, alpha and beta amylases, proteases, were identified, and many other candidate genes related to cellular and molecular functions were also identified. The ANOVA analysis revealed that the expression of 56 of 110 probe sets was involved in interaction (quality x development). Majority of the probe sets showed differential expression at early stage of seed development i.e. temporal expression. Meta-analysis revealed that the majority of the genes expressed in one or a few growth stages indicating spatial distribution of their expressions. The differential expressions of a few candidate genes such as pre-alpha/beta-gliadin and gamma gliadin were validated by RT

[Social interactions of preschool children with Down syndrome during extracurricular activities].

PubMed

Lucisano, Renata Valdívia; Pfeifer, Luzia Iara; Pinto, Maria Paula Panuncio; Santos, Jair Lício Ferreira; Anhão, Patrícia Páfaro Gomes

2013-01-01

The aim of this research was to identify the process of social interaction of children with Down Syndrome (DS) during extracurricular activities in the regular early childhood education in Ribeirão Preto-SP, Brazil. Six children aged 3-6 years participated in this study. There were two recordings of each child in situations of social interaction during extracurricular activities, and analyzed by 15 behaviors, divided into two categories of social skills: interpersonal and self-expression. The results demonstrate that, in the interpersonal skill category, the higher occurrence was the behavior "occurs interaction with other children". In the self-expression skills category, only the behaviors "smiles" and "imitates other children" have significant occurrence. The behaviors more frequently identified in this study permit to understand that the school environment is a facilitator for the interaction of child with DS with the typical developmental children, allowing him/her to develop the expected social skills.

Deciphering microbial interactions and detecting keystone species with co-occurrence networks

PubMed Central

Berry, David; Widder, Stefanie

2014-01-01

Co-occurrence networks produced from microbial survey sequencing data are frequently used to identify interactions between community members. While this approach has potential to reveal ecological processes, it has been insufficiently validated due to the technical limitations inherent in studying complex microbial ecosystems. Here, we simulate multi-species microbial communities with known interaction patterns using generalized Lotka-Volterra dynamics. We then construct co-occurrence networks and evaluate how well networks reveal the underlying interactions and how experimental and ecological parameters can affect network inference and interpretation. We find that co-occurrence networks can recapitulate interaction networks under certain conditions, but that they lose interpretability when the effects of habitat filtering become significant. We demonstrate that networks suffer from local hot spots of spurious correlation in the neighborhood of hub species that engage in many interactions. We also identify topological features associated with keystone species in co-occurrence networks. This study provides a substantiated framework to guide environmental microbiologists in the construction and interpretation of co-occurrence networks from microbial survey datasets. PMID:24904535

Deciphering microbial interactions and detecting keystone species with co-occurrence networks.

PubMed

Berry, David; Widder, Stefanie

2014-01-01

Co-occurrence networks produced from microbial survey sequencing data are frequently used to identify interactions between community members. While this approach has potential to reveal ecological processes, it has been insufficiently validated due to the technical limitations inherent in studying complex microbial ecosystems. Here, we simulate multi-species microbial communities with known interaction patterns using generalized Lotka-Volterra dynamics. We then construct co-occurrence networks and evaluate how well networks reveal the underlying interactions and how experimental and ecological parameters can affect network inference and interpretation. We find that co-occurrence networks can recapitulate interaction networks under certain conditions, but that they lose interpretability when the effects of habitat filtering become significant. We demonstrate that networks suffer from local hot spots of spurious correlation in the neighborhood of hub species that engage in many interactions. We also identify topological features associated with keystone species in co-occurrence networks. This study provides a substantiated framework to guide environmental microbiologists in the construction and interpretation of co-occurrence networks from microbial survey datasets.

Interactional Metadiscourse in Turkish Postgraduates' Academic Texts: A Comparative Study of How They Introduce and Conclude

ERIC Educational Resources Information Center

Akbas, Erdem

2012-01-01

This study explores interactional metadiscourse resources in master's dissertations (introductions and conclusions) of Turkish students written in Turkish and English. Interactional resources were identified according to Hyland and Tse's (2004) framework by using WordSmith Tools (5.0). A statistically significant difference between two groups of…

Common Marker Genes Identified from Various Sample Types for Systemic Lupus Erythematosus.

PubMed

Bing, Peng-Fei; Xia, Wei; Wang, Lan; Zhang, Yong-Hong; Lei, Shu-Feng; Deng, Fei-Yan

2016-01-01

Systemic lupus erythematosus (SLE) is a complex auto-immune disease. Gene expression studies have been conducted to identify SLE-related genes in various types of samples. It is unknown whether there are common marker genes significant for SLE but independent of sample types, which may have potentials for follow-up translational research. The aim of this study is to identify common marker genes across various sample types for SLE. Based on four public microarray gene expression datasets for SLE covering three representative types of blood-born samples (monocyte; peripheral blood mononuclear cell, PBMC; whole blood), we utilized three statistics (fold-change, FC; t-test p value; false discovery rate adjusted p value) to scrutinize genes simultaneously regulated with SLE across various sample types. For common marker genes, we conducted the Gene Ontology enrichment analysis and Protein-Protein Interaction analysis to gain insights into their functions. We identified 10 common marker genes associated with SLE (IFI6, IFI27, IFI44L, OAS1, OAS2, EIF2AK2, PLSCR1, STAT1, RNASE2, and GSTO1). Significant up-regulation of IFI6, IFI27, and IFI44L with SLE was observed in all the studied sample types, though the FC was most striking in monocyte, compared with PBMC and whole blood (8.82-251.66 vs. 3.73-74.05 vs. 1.19-1.87). Eight of the above 10 genes, except RNASE2 and GSTO1, interact with each other and with known SLE susceptibility genes, participate in immune response, RNA and protein catabolism, and cell death. Our data suggest that there exist common marker genes across various sample types for SLE. The 10 common marker genes, identified herein, deserve follow-up studies to dissert their potentials as diagnostic or therapeutic markers to predict SLE or treatment response.

Amino Acid Interaction (INTAA) web server.

PubMed

Galgonek, Jakub; Vymetal, Jirí; Jakubec, David; Vondrášek, Jirí

2017-07-03

Large biomolecules-proteins and nucleic acids-are composed of building blocks which define their identity, properties and binding capabilities. In order to shed light on the energetic side of interactions of amino acids between themselves and with deoxyribonucleotides, we present the Amino Acid Interaction web server (http://bioinfo.uochb.cas.cz/INTAA/). INTAA offers the calculation of the residue Interaction Energy Matrix for any protein structure (deposited in Protein Data Bank or submitted by the user) and a comprehensive analysis of the interfaces in protein-DNA complexes. The Interaction Energy Matrix web application aims to identify key residues within protein structures which contribute significantly to the stability of the protein. The application provides an interactive user interface enhanced by 3D structure viewer for efficient visualization of pairwise and net interaction energies of individual amino acids, side chains and backbones. The protein-DNA interaction analysis part of the web server allows the user to view the relative abundance of various configurations of amino acid-deoxyribonucleotide pairs found at the protein-DNA interface and the interaction energies corresponding to these configurations calculated using a molecular mechanical force field. The effects of the sugar-phosphate moiety and of the dielectric properties of the solvent on the interaction energies can be studied for the various configurations. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

PubMed

Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

2015-01-01

Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these

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.

T cell post-transcriptional miRNA-mRNA interaction networks identify targets associated with susceptibility/resistance to collagen-induced arthritis.

PubMed

Donate, Paula B; Fornari, Thais A; Macedo, Claudia; Cunha, Thiago M; Nascimento, Daniele C B; Sakamoto-Hojo, Elza T; Donadi, Eduardo A; Cunha, Fernando Q; Passos, Geraldo A

2013-01-01

Due to recent studies indicating that the deregulation of microRNAs (miRNAs) in T cells contributes to increased severity of rheumatoid arthritis, we hypothesized that deregulated miRNAs may interact with key mRNA targets controlling the function or differentiation of these cells in this disease. To test our hypothesis, we used microarrays to survey, for the first time, the expression of all known mouse miRNAs in parallel with genome-wide mRNAs in thymocytes and naïve and activated peripheral CD3(+) T cells from two mouse strains the DBA-1/J strain (MHC-H2q), which is susceptible to collagen induced arthritis (CIA), and the DBA-2/J strain (MHC-H2d), which is resistant. Hierarchical clustering of data showed the several T cell miRNAs and mRNAs differentially expressed between the mouse strains in different stages of immunization with collagen. Bayesian statistics using the GenMir(++) algorithm allowed reconstruction of post-transcriptional miRNA-mRNA interaction networks for target prediction. We revealed the participation of miR-500, miR-202-3p and miR-30b*, which established interactions with at least one of the following mRNAs: Rorc, Fas, Fasl, Il-10 and Foxo3. Among the interactions that were validated by calculating the minimal free-energy of base pairing between the miRNA and the 3'UTR of the mRNA target and luciferase assay, we highlight the interaction of miR-30b*-Rorc mRNA because the mRNA encodes a protein implicated in pro-inflammatory Th17 cell differentiation (Rorγt). FACS analysis revealed that Rorγt protein levels and Th17 cell counts were comparatively reduced in the DBA-2/J strain. This result showed that the miRNAs and mRNAs identified in this study represent new candidates regulating T cell function and controlling susceptibility and resistance to CIA.

The node-weighted Steiner tree approach to identify elements of cancer-related signaling pathways.

PubMed

Sun, Yahui; Ma, Chenkai; Halgamuge, Saman

2017-12-28

Cancer constitutes a momentous health burden in our society. Critical information on cancer may be hidden in its signaling pathways. However, even though a large amount of money has been spent on cancer research, some critical information on cancer-related signaling pathways still remains elusive. Hence, new works towards a complete understanding of cancer-related signaling pathways will greatly benefit the prevention, diagnosis, and treatment of cancer. We propose the node-weighted Steiner tree approach to identify important elements of cancer-related signaling pathways at the level of proteins. This new approach has advantages over previous approaches since it is fast in processing large protein-protein interaction networks. We apply this new approach to identify important elements of two well-known cancer-related signaling pathways: PI3K/Akt and MAPK. First, we generate a node-weighted protein-protein interaction network using protein and signaling pathway data. Second, we modify and use two preprocessing techniques and a state-of-the-art Steiner tree algorithm to identify a subnetwork in the generated network. Third, we propose two new metrics to select important elements from this subnetwork. On a commonly used personal computer, this new approach takes less than 2 s to identify the important elements of PI3K/Akt and MAPK signaling pathways in a large node-weighted protein-protein interaction network with 16,843 vertices and 1,736,922 edges. We further analyze and demonstrate the significance of these identified elements to cancer signal transduction by exploring previously reported experimental evidences. Our node-weighted Steiner tree approach is shown to be both fast and effective to identify important elements of cancer-related signaling pathways. Furthermore, it may provide new perspectives into the identification of signaling pathways for other human diseases.

Potential Drug-Drug Interactions among Patients prescriptions collected from Medicine Out-patient Setting.

PubMed

Farooqui, Riffat; Hoor, Talea; Karim, Nasim; Muneer, Mehtab

2018-01-01

To identify and evaluate the frequency, severity, mechanism and common pairs of drug-drug interactions (DDIs) in prescriptions by consultants in medicine outpatient department. This cross sectional descriptive study was done by Pharmacology department of Bahria University Medical & Dental College (BUMDC) in medicine outpatient department (OPD) of a private hospital in Karachi from December 2015 to January 2016. A total of 220 prescriptions written by consultants were collected. Medications given with patient's diagnosis were recorded. Drugs were analyzed for interactions by utilizing Medscape drug interaction checker, drugs.com checker and stockley`s drug interactions index. Two hundred eleven prescriptions were selected while remaining were excluded from the study because of unavailability of the prescribed drugs in the drug interaction checkers. In 211 prescriptions, two common diagnoses were diabetes mellitus (28.43%) and hypertension (27.96%). A total of 978 medications were given. Mean number of medications per prescription was 4.6. A total of 369 drug-drug interactions were identified in 211 prescriptions (175%). They were serious 4.33%, significant 66.12% and minor 29.53%. Pharmacokinetic and pharmacodynamic interactions were 37.94% and 51.21% respectively while 10.84% had unknown mechanism. Number wise common pairs of DDIs were Omeprazole-Losartan (S), Gabapentine- Acetaminophen (M), Losartan-Diclofenac (S). The frequency of DDIs is found to be too high in prescriptions of consultants from medicine OPD of a private hospital in Karachi. Significant drug-drug interactions were more and mostly caused by Pharmacodynamic mechanism. Number wise evaluation showed three common pairs of drugs involved in interactions.

Potential Drug-Drug Interactions among Patients prescriptions collected from Medicine Out-patient Setting

PubMed Central

Farooqui, Riffat; Hoor, Talea; Karim, Nasim; Muneer, Mehtab

2018-01-01

Objective: To identify and evaluate the frequency, severity, mechanism and common pairs of drug-drug interactions (DDIs) in prescriptions by consultants in medicine outpatient department. Methods: This cross sectional descriptive study was done by Pharmacology department of Bahria University Medical & Dental College (BUMDC) in medicine outpatient department (OPD) of a private hospital in Karachi from December 2015 to January 2016. A total of 220 prescriptions written by consultants were collected. Medications given with patient's diagnosis were recorded. Drugs were analyzed for interactions by utilizing Medscape drug interaction checker, drugs.com checker and stockley`s drug interactions index. Two hundred eleven prescriptions were selected while remaining were excluded from the study because of unavailability of the prescribed drugs in the drug interaction checkers. Results: In 211 prescriptions, two common diagnoses were diabetes mellitus (28.43%) and hypertension (27.96%). A total of 978 medications were given. Mean number of medications per prescription was 4.6. A total of 369 drug-drug interactions were identified in 211 prescriptions (175%). They were serious 4.33%, significant 66.12% and minor 29.53%. Pharmacokinetic and pharmacodynamic interactions were 37.94% and 51.21% respectively while 10.84% had unknown mechanism. Number wise common pairs of DDIs were Omeprazole-Losartan (S), Gabapentine- Acetaminophen (M), Losartan-Diclofenac (S). Conclusion: The frequency of DDIs is found to be too high in prescriptions of consultants from medicine OPD of a private hospital in Karachi. Significant drug-drug interactions were more and mostly caused by Pharmacodynamic mechanism. Number wise evaluation showed three common pairs of drugs involved in interactions. PMID:29643896

Drug-Target Interactions: Prediction Methods and Applications.

PubMed

Anusuya, Shanmugam; Kesherwani, Manish; Priya, K Vishnu; Vimala, Antonydhason; Shanmugam, Gnanendra; Velmurugan, Devadasan; Gromiha, M Michael

2018-01-01

Identifying the interactions between drugs and target proteins is a key step in drug discovery. This not only aids to understand the disease mechanism, but also helps to identify unexpected therapeutic activity or adverse side effects of drugs. Hence, drug-target interaction prediction becomes an essential tool in the field of drug repurposing. The availability of heterogeneous biological data on known drug-target interactions enabled many researchers to develop various computational methods to decipher unknown drug-target interactions. This review provides an overview on these computational methods for predicting drug-target interactions along with available webservers and databases for drug-target interactions. Further, the applicability of drug-target interactions in various diseases for identifying lead compounds has been outlined. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Experimental evolution of protein–protein interaction networks

PubMed Central

Kaçar, Betül; Gaucher, Eric A.

2013-01-01

The modern synthesis of evolutionary theory and genetics has enabled us to discover underlying molecular mechanisms of organismal evolution. We know that in order to maximize an organism's fitness in a particular environment, individual interactions among components of protein and nucleic acid networks need to be optimized by natural selection, or sometimes through random processes, as the organism responds to changes and/or challenges in the environment. Despite the significant role of molecular networks in determining an organism's adaptation to its environment, we still do not know how such inter- and intra-molecular interactions within networks change over time and contribute to an organism's evolvability while maintaining overall network functions. One way to address this challenge is to identify connections between molecular networks and their host organisms, to manipulate these connections, and then attempt to understand how such perturbations influence molecular dynamics of the network and thus influence evolutionary paths and organismal fitness. In the present review, we discuss how integrating evolutionary history with experimental systems that combine tools drawn from molecular evolution, synthetic biology and biochemistry allow us to identify the underlying mechanisms of organismal evolution, particularly from the perspective of protein interaction networks. PMID:23849056

To be or not to be associated: power study of four statistical modeling approaches to identify parasite associations in cross-sectional studies

PubMed Central

Vaumourin, Elise; Vourc'h, Gwenaël; Telfer, Sandra; Lambin, Xavier; Salih, Diaeldin; Seitzer, Ulrike; Morand, Serge; Charbonnel, Nathalie; Vayssier-Taussat, Muriel; Gasqui, Patrick

2014-01-01

A growing number of studies are reporting simultaneous infections by parasites in many different hosts. The detection of whether these parasites are significantly associated is important in medicine and epidemiology. Numerous approaches to detect associations are available, but only a few provide statistical tests. Furthermore, they generally test for an overall detection of association and do not identify which parasite is associated with which other one. Here, we developed a new approach, the association screening approach, to detect the overall and the detail of multi-parasite associations. We studied the power of this new approach and of three other known ones (i.e., the generalized chi-square, the network and the multinomial GLM approaches) to identify parasite associations either due to parasite interactions or to confounding factors. We applied these four approaches to detect associations within two populations of multi-infected hosts: (1) rodents infected with Bartonella sp., Babesia microti and Anaplasma phagocytophilum and (2) bovine population infected with Theileria sp. and Babesia sp. We found that the best power is obtained with the screening model and the generalized chi-square test. The differentiation between associations, which are due to confounding factors and parasite interactions was not possible. The screening approach significantly identified associations between Bartonella doshiae and B. microti, and between T. parva, T. mutans, and T. velifera. Thus, the screening approach was relevant to test the overall presence of parasite associations and identify the parasite combinations that are significantly over- or under-represented. Unraveling whether the associations are due to real biological interactions or confounding factors should be further investigated. Nevertheless, in the age of genomics and the advent of new technologies, it is a considerable asset to speed up researches focusing on the mechanisms driving interactions between

Drug-nutrient interactions: a broad view with implications for practice.

PubMed

Boullata, Joseph I; Hudson, Lauren M

2012-04-01

The relevance of drug?nutrient interactions in daily practice continues to grow with the widespread use of medication. Interactions can involve a single nutrient, multiple nutrients, food in general, or nutrition status. Mechanistically, drug?nutrient interactions occur because of altered intestinal transport and metabolism, or systemic distribution, metabolism and excretion, as well as additive or antagonistic effects. Optimal patient care includes identifying, evaluating, and managing these interactions. This task can be supported by a systematic approach for categorizing interactions and rating their clinical significance. This review provides such a broad framework using recent examples, as well as some classic drug?nutrient interactions. Pertinent definitions are presented, as is a suggested approach for clinicians. This important and expanding subject will benefit tremendously from further clinician involvement. Copyright © 2012 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Solution structure of Apaf-1 CARD and its interaction with caspase-9 CARD: a structural basis for specific adaptor/caspase interaction.

PubMed

Zhou, P; Chou, J; Olea, R S; Yuan, J; Wagner, G

1999-09-28

Direct recruitment and activation of caspase-9 by Apaf-1 through the homophilic CARD/CARD (Caspase Recruitment Domain) interaction is critical for the activation of caspases downstream of mitochondrial damage in apoptosis. Here we report the solution structure of the Apaf-1 CARD domain and its surface of interaction with caspase-9 CARD. Apaf-1 CARD consists of six tightly packed amphipathic alpha-helices and is topologically similar to the RAIDD CARD, with the exception of a kink observed in the middle of the N-terminal helix. By using chemical shift perturbation data, the homophilic interaction was mapped to the acidic surface of Apaf-1 CARD centered around helices 2 and 3. Interestingly, a significant portion of the chemically perturbed residues are hydrophobic, indicating that in addition to the electrostatic interactions predicted previously, hydrophobic interaction is also an important driving force underlying the CARD/CARD interaction. On the basis of the identified functional residues of Apaf-1 CARD and the surface charge complementarity, we propose a model of CARD/CARD interaction between Apaf-1 and caspase-9.

Interaction of Carbamazepine with Herbs, Dietary Supplements, and Food: A Systematic Review

PubMed Central

Zuo, Zhong

2013-01-01

Background. Carbamazepine (CBZ) is a first-line antiepileptic drug which may be prone to drug interactions. Systematic review of herb- and food-drug interactions on CBZ is warranted to provide guidance for medical professionals when prescribing CBZ. Method. A systematic review was conducted on six English databases and four Chinese databases. Results. 196 out of 3179 articles fulfilled inclusion criteria, of which 74 articles were reviewed and 33 herbal products/dietary supplement/food interacting with CBZ were identified. No fatal or severe interactions were documented. The majority of the interactions were pharmacokinetic-based (80%). Traditional Chinese medicine accounted for most of the interactions (n = 17), followed by food (n = 10), dietary supplements (n = 3), and other herbs/botanicals (n = 3). Coadministration of 11 and 12 of the studied herbal products/dietary supplement/food significantly decreased or increased the plasma concentrations of CBZ. Regarding pharmacodynamic interaction, Xiao-yao-san, melatonin, and alcohol increased the side effects of CBZ while caffeine lowered the antiepileptic efficacy of CBZ. Conclusion. This review provides a comprehensive summary of the documented interactions between CBZ and herbal products/food/dietary supplements which assists healthcare professionals to identify potential herb-drug and food-drug interactions, thereby preventing potential adverse events and improving patients' therapeutic outcomes when prescribing CBZ. PMID:24023584

Gender interactions and success.

PubMed

Wiggins, Carla; Peterson, Teri

2004-01-01

Does gender by itself, or does gender's interaction with career variables, better explain the difference between women and men's careers in healthcare management? US healthcare managers were surveyed regarding career and personal experiences. Gender was statistically interacted with explanatory variables. Multiple regression with backwards selection systematically removed non-significant variables. All gender interaction variables were non-significant. Much of the literature proposes that work and career factors impact working women differently than working men. We find that while gender alone is a significant predictor of income, it does not significantly interact with other career variables.

Gene-based interaction analysis shows GABAergic genes interacting with parenting in adolescent depressive symptoms.

PubMed

Van Assche, Evelien; Moons, Tim; Cinar, Ozan; Viechtbauer, Wolfgang; Oldehinkel, Albertine J; Van Leeuwen, Karla; Verschueren, Karine; Colpin, Hilde; Lambrechts, Diether; Van den Noortgate, Wim; Goossens, Luc; Claes, Stephan; van Winkel, Ruud

2017-12-01

Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric phenotypes and reduces the risk of false-positive findings. We apply this method focusing on the role of perceived parental support, psychological control, and harsh punishment in depressive symptoms in adolescence. Analyses were conducted on 982 adolescents of Caucasian origin (M age (SD) = 13.78 (.94) years) genotyped for 4,947 SNPs in 263 genes, selected based on a literature survey. The Leuven Adolescent Perceived Parenting Scale (LAPPS) and the Parental Behavior Scale (PBS) were used to assess perceived parental psychological control, harsh punishment, and support. The Center for Epidemiologic Studies Depression Scale (CES-D) was the outcome. We used gene-based testing taking into account linkage disequilibrium to identify genes containing SNPs exhibiting an interaction with environmental factors yielding a p-value per single gene. Significant results at the corrected p-value of p < 1.90 × 10 -4 were examined in an independent replication sample of Dutch adolescents (N = 1354). Two genes showed evidence for interaction with perceived support: GABRR1 (p = 4.62 × 10 -5 ) and GABRR2 (p = 9.05 × 10 -6 ). No genes interacted significantly with psychological control or harsh punishment. Gene-based analysis was unable to confirm the interaction of GABRR1 or GABRR2 with support in the replication sample. However, for GABRR2, but not GABRR1, the correlation of the estimates between the two datasets was significant (r (46) = .32; p = .027) and a gene-based analysis of the combined datasets supported GABRR2 × support interaction (p = 1.63 × 10 -4 ). We present a gene-based method for gene-environment interactions in a polygenic context and show that genes

Exploring the interaction between Salvia miltiorrhiza and human serum albumin: Insights from herb-drug interaction reports, computational analysis and experimental studies

NASA Astrophysics Data System (ADS)

Shao, Xin; Ai, Ni; Xu, Donghang; Fan, Xiaohui

2016-05-01

Human serum albumin (HSA) binding is one of important pharmacokinetic properties of drug, which is closely related to in vivo distribution and may ultimately influence its clinical efficacy. Compared to conventional drug, limited information on this transportation process is available for medicinal herbs, which significantly hampers our understanding on their pharmacological effects, particularly when herbs and drug are co-administrated as polytherapy to the ailment. Several lines of evidence suggest the existence of Salvia miltiorrhiza-Warfarin interaction. Since Warfarin is highly HSA bound in the plasma with selectivity to site I, it is critical to evaluate the possibility of HSA-related herb-drug interaction. Herein an integrated approach was employed to analyze the binding of chemicals identified in S. miltiorrhiza to HSA. Molecular docking simulations revealed filtering criteria for HSA site I compounds that include docking score and key molecular determinants for binding. For eight representative ingredients from the herb, their affinity and specificity to HSA site I was measured and confirmed fluorometrically, which helps to improve the knowledge of interaction mechanisms between this herb and HSA. Our results indicated that several compounds in S. miltiorrhiza were capable of decreasing the binding constant of Warfarin to HSA site I significantly, which may increase free drug concentration in vivo, contributing to the herb-drug interaction observed clinically. Furthermore, the significance of HSA mediated herb-drug interactions was further implied by manual mining on the published literatures on S. miltiorrhiza.

Identifying Features of Bodily Expression As Indicators of Emotional Experience during Multimedia Learning

PubMed Central

Riemer, Valentin; Frommel, Julian; Layher, Georg; Neumann, Heiko; Schrader, Claudia

2017-01-01

The importance of emotions experienced by learners during their interaction with multimedia learning systems, such as serious games, underscores the need to identify sources of information that allow the recognition of learners’ emotional experience without interrupting the learning process. Bodily expression is gaining in attention as one of these sources of information. However, to date, the question of how bodily expression can convey different emotions has largely been addressed in research relying on acted emotion displays. Following a more contextualized approach, the present study aims to identify features of bodily expression (i.e., posture and activity of the upper body and the head) that relate to genuine emotional experience during interaction with a serious game. In a multimethod approach, 70 undergraduates played a serious game relating to financial education while their bodily expression was captured using an off-the-shelf depth-image sensor (Microsoft Kinect). In addition, self-reports of experienced enjoyment, boredom, and frustration were collected repeatedly during gameplay, to address the dynamic changes in emotions occurring in educational tasks. Results showed that, firstly, the intensities of all emotions indeed changed significantly over the course of the game. Secondly, by using generalized estimating equations, distinct features of bodily expression could be identified as significant indicators for each emotion under investigation. A participant keeping their head more turned to the right was positively related to frustration being experienced, whereas keeping their head more turned to the left was positively related to enjoyment. Furthermore, having their upper body positioned more closely to the gaming screen was also positively related to frustration. Finally, increased activity of a participant’s head emerged as a significant indicator of boredom being experienced. These results confirm the value of bodily expression as an indicator

Can the vector space model be used to identify biological entity activities?

PubMed Central

2011-01-01

Background Biological systems are commonly described as networks of entity interactions. Some interactions are already known and integrate the current knowledge in life sciences. Others remain unknown for long periods of time and are frequently discovered by chance. In this work we present a model to predict these unknown interactions from a textual collection using the vector space model (VSM), a well known and established information retrieval model. We have extended the VSM ability to retrieve information using a transitive closure approach. Our objective is to use the VSM to identify the known interactions from the literature and construct a network. Based on interactions established in the network our model applies the transitive closure in order to predict and rank new interactions. Results We have tested and validated our model using a collection of patent claims issued from 1976 to 2005. From 266,528 possible interactions in our network, the model identified 1,027 known interactions and predicted 3,195 new interactions. Iterating the model according to patent issue dates, interactions found in a given past year were often confirmed by patent claims not in the collection and issued in more recent years. Most confirmation patent claims were found at the top 100 new interactions obtained from each subnetwork. We have also found papers on the Web which confirm new inferred interactions. For instance, the best new interaction inferred by our model relates the interaction between the adrenaline neurotransmitter and the androgen receptor gene. We have found a paper that reports the partial dependence of the antiapoptotic effect of adrenaline on androgen receptor. Conclusions The VSM extended with a transitive closure approach provides a good way to identify biological interactions from textual collections. Specifically for the context of literature-based discovery, the extended VSM contributes to identify and rank relevant new interactions even if these

GxE Interactions between FOXO Genotypes and Tea Drinking Are Significantly Associated with Cognitive Disability at Advanced Ages in China

PubMed Central

Zeng, Yi; Chen, Huashuai; Ni, Ting; Ruan, Rongping; Feng, Lei; Nie, Chao; Cheng, Lingguo; Li, Yang; Tao, Wei; Gu, Jun; Land, Kenneth C.; Yashin, Anatoli; Tan, Qihua; Yang, Ze; Bolund, Lars; Yang, Huanming; Hauser, Elizabeth; Willcox, D. Craig; Willcox, Bradley J.; Tian, Xiao-Li; Vaupel, James W.

2015-01-01

Logistic regression analysis based on data from 822 Han Chinese oldest old aged 92+ demonstrated that interactions between carrying FOXO1A-266 or FOXO3-310 or FOXO3-292 and tea drinking at around age 60 or at present time were significantly associated with lower risk of cognitive disability at advanced ages. Associations between tea drinking and reduced cognitive disability were much stronger among carriers of the genotypes of FOXO1A-266 or FOXO3-310 or FOXO3-292 compared with noncarriers, and it was reconfirmed by analysis of three-way interactions across FOXO genotypes, tea drinking at around age 60, and at present time. Based on prior findings from animal and human cell models, we postulate that intake of tea compounds may activate FOXO gene expression, which in turn may positively affect cognitive function in the oldest old population. Our empirical findings imply that the health benefits of particular nutritional interventions, including tea drinking, may, in part, depend upon individual genetic profiles. PMID:24895270

Genome-wide interaction study of smoking and bladder cancer risk

PubMed Central

Figueroa, Jonine D.; Han, Summer S.; Garcia-Closas, Montserrat; Baris, Dalsu; Jacobs, Eric J.; Kogevinas, Manolis; Schwenn, Molly; Malats, Nuria; Johnson, Alison; Purdue, Mark P.; Caporaso, Neil; Landi, Maria Teresa; Prokunina-Olsson, Ludmila; Wang, Zhaoming; Hutchinson, Amy; Burdette, Laurie; Wheeler, William; Vineis, Paolo; Siddiq, Afshan; Cortessis, Victoria K.; Kooperberg, Charles; Cussenot, Olivier; Benhamou, Simone; Prescott, Jennifer; Porru, Stefano; Bueno-de-Mesquita, H.Bas; Trichopoulos, Dimitrios; Ljungberg, Börje; Clavel-Chapelon, Françoise; Weiderpass, Elisabete; Krogh, Vittorio; Dorronsoro, Miren; Travis, Ruth; Tjønneland, Anne; Brenan, Paul; Chang-Claude, Jenny; Riboli, Elio; Conti, David; Gago-Dominguez, Manuela; Stern, Mariana C.; Pike, Malcolm C.; Van Den Berg, David; Yuan, Jian-Min; Hohensee, Chancellor; Rodabough, Rebecca; Cancel-Tassin, Geraldine; Roupret, Morgan; Comperat, Eva; Chen, Constance; De Vivo, Immaculata; Giovannucci, Edward; Hunter, David J.; Kraft, Peter; Lindstrom, Sara; Carta, Angela; Pavanello, Sofia; Arici, Cecilia; Mastrangelo, Giuseppe; Karagas, Margaret R.; Schned, Alan; Armenti, Karla R.; Hosain, G.M.Monawar; Haiman, Chris A.; Fraumeni, Joseph F.; Chanock, Stephen J.; Chatterjee, Nilanjan; Rothman, Nathaniel; Silverman, Debra T.

2014-01-01

Bladder cancer is a complex disease with known environmental and genetic risk factors. We performed a genome-wide interaction study (GWAS) of smoking and bladder cancer risk based on primary scan data from 3002 cases and 4411 controls from the National Cancer Institute Bladder Cancer GWAS. Alternative methods were used to evaluate both additive and multiplicative interactions between individual single nucleotide polymorphisms (SNPs) and smoking exposure. SNPs with interaction P values < 5 × 10− 5 were evaluated further in an independent dataset of 2422 bladder cancer cases and 5751 controls. We identified 10 SNPs that showed association in a consistent manner with the initial dataset and in the combined dataset, providing evidence of interaction with tobacco use. Further, two of these novel SNPs showed strong evidence of association with bladder cancer in tobacco use subgroups that approached genome-wide significance. Specifically, rs1711973 (FOXF2) on 6p25.3 was a susceptibility SNP for never smokers [combined odds ratio (OR) = 1.34, 95% confidence interval (CI) = 1.20–1.50, P value = 5.18 × 10− 7]; and rs12216499 (RSPH3-TAGAP-EZR) on 6q25.3 was a susceptibility SNP for ever smokers (combined OR = 0.75, 95% CI = 0.67–0.84, P value = 6.35 × 10− 7). In our analysis of smoking and bladder cancer, the tests for multiplicative interaction seemed to more commonly identify susceptibility loci with associations in never smokers, whereas the additive interaction analysis identified more loci with associations among smokers—including the known smoking and NAT2 acetylation interaction. Our findings provide additional evidence of gene–environment interactions for tobacco and bladder cancer. PMID:24662972

Identifying Positive Teacher-Student Interactions in a Safe and Engaged Middle School

ERIC Educational Resources Information Center

Zeman, Laura Dreuth

2003-01-01

Research suggests positive interaction between students and teachers is a hallmark of a safe and effective school. Yet to date there is no literature presenting findings or case examples of what constitutes positive engagement or how to measure its frequency. This paper shares observations of a "model" rural middle school in an attempt…

Hierarchical Interactions Model for Predicting Mild Cognitive Impairment (MCI) to Alzheimer's Disease (AD) Conversion

PubMed Central

Li, Han; Liu, Yashu; Gong, Pinghua; Zhang, Changshui; Ye, Jieping

2014-01-01

Identifying patients with Mild Cognitive Impairment (MCI) who are likely to convert to dementia has recently attracted increasing attention in Alzheimer's disease (AD) research. An accurate prediction of conversion from MCI to AD can aid clinicians to initiate treatments at early stage and monitor their effectiveness. However, existing prediction systems based on the original biosignatures are not satisfactory. In this paper, we propose to fit the prediction models using pairwise biosignature interactions, thus capturing higher-order relationship among biosignatures. Specifically, we employ hierarchical constraints and sparsity regularization to prune the high-dimensional input features. Based on the significant biosignatures and underlying interactions identified, we build classifiers to predict the conversion probability based on the selected features. We further analyze the underlying interaction effects of different biosignatures based on the so-called stable expectation scores. We have used 293 MCI subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI) database that have MRI measurements at the baseline to evaluate the effectiveness of the proposed method. Our proposed method achieves better classification performance than state-of-the-art methods. Moreover, we discover several significant interactions predictive of MCI-to-AD conversion. These results shed light on improving the prediction performance using interaction features. PMID:24416143

Evaluation of potential interactions between mycophenolic acid derivatives and proton pump inhibitors.

PubMed

Gabardi, Steven; Olyaei, Ali

2012-01-01

To evaluate the incidence of gastrointestinal (GI) complications in solid organ transplant (SOT) recipients, impact of the complications on transplant outcomes, and the potential interactions between mycophenolic acid (MPA) derivatives and proton pump inhibitors (PPIs). An unrestricted literature search (1980-January 2012) was performed with MEDLINE and EMBASE using the following key words: drug-drug interaction, enteric-coated mycophenolic acid, GI complications, mycophenolate mofetil, solid organ transplant, and proton pump inhibitor, including individual agents within the class. Abstracts from scientific meetings were also evaluated. Additionally, reference citations from identified publications were reviewed. Relevant English-language, original research articles and review articles were evaluated if they focused on any of the topics identified in the search or included substantial content addressing GI complications in SOT recipients or drug interactions. GI complications are frequent among SOT recipients, with some studies showing prevalence rates as high as 70%. Transplant outcomes among renal transplant recipients are significantly impacted by GI complications, especially in patients requiring immunosuppressant dosage reductions or premature discontinuation. To this end, PPI use among patients receiving transplants is common. Recent data demonstrate that PPIs significantly reduce the overall exposure to MPA after oral administration of mycophenolate mofetil. Similar studies show this interaction does not exist between PPIs and enteric-coated mycophenolic acid (EC-MPA). Unfortunately, most of the available data evaluating this interaction are pharmacokinetic analyses that do not investigate the clinical impact of this interaction. A significant interaction exists between PPIs and mycophenolate mofetil secondary to reduced dissolution of mycophenolate mofetil in higher pH environments. EC-MPA is not absorbed in the stomach; therefore, low intragastric acidity

Genotypic variability-based genome-wide association study identifies non-additive loci HLA-C and IL12B for psoriasis.

PubMed

Wei, Wen-Hua; Massey, Jonathan; Worthington, Jane; Barton, Anne; Warren, Richard B

2018-03-01

Genome-wide association studies (GWASs) have identified a number of loci for psoriasis but largely ignored non-additive effects. We report a genotypic variability-based GWAS (vGWAS) that can prioritize non-additive loci without requiring prior knowledge of interaction types or interacting factors in two steps, using a mixed model to partition dichotomous phenotypes into an additive component and non-additive environmental residuals on the liability scale and then the Levene's (Brown-Forsythe) test to assess equality of the residual variances across genotype groups genome widely. The vGWAS identified two genome-wide significant (P < 5.0e-08) non-additive loci HLA-C and IL12B that were also genome-wide significant in an accompanying GWAS in the discovery cohort. Both loci were statistically replicated in vGWAS of an independent cohort with a small sample size. HLA-C and IL12B were reported in moderate gene-gene and/or gene-environment interactions in several occasions. We found a moderate interaction with age-of-onset of psoriasis, which was replicated indirectly. The vGWAS also revealed five suggestive loci (P < 6.76e-05) including FUT2 that was associated with psoriasis with environmental aspects triggered by virus infection and/or metabolic factors. Replication and functional investigation are needed to validate the suggestive vGWAS loci.

Novel whole blood assay for phenotyping platelet reactivity in mice identifies ICAM-1 as a mediator of platelet-monocyte interaction

PubMed Central

Kirkby, Nicholas S.; Chan, Melissa V.; Finsterbusch, Michaela; Hogg, Nancy; Nourshargh, Sussan; Warner, Timothy D.

2015-01-01

Testing of platelet function is central to the cardiovascular phenotyping of genetically modified mice. Traditional platelet function tests have been developed primarily for testing human samples and the volumes required make them highly unsuitable for the testing of mouse platelets. This limits research in this area. To address this problem, we have developed a miniaturized whole blood aggregometry assay, based on a readily accessible 96-well plate format coupled with quantification of single platelet depletion by flow cytometric analysis. Using this approach, we observed a concentration-dependent loss of single platelets in blood exposed to arachidonic acid, collagen, U46619 or protease activated receptor 4 activating peptide. This loss was sensitive to well-established antiplatelet agents and genetic manipulation of platelet activation pathways. Observations were more deeply analyzed by flow cytometric imaging, confocal imaging, and measurement of platelet releasates. Phenotypic analysis of the reactivity of platelets taken from mice lacking intercellular adhesion molecule (ICAM)-1 identified a marked decrease in fibrinogen-dependent platelet-monocyte interactions, especially under inflammatory conditions. Such findings exemplify the value of screening platelet phenotypes of genetically modified mice and shed further light upon the roles and interactions of platelets in inflammation. PMID:26215112

Quality of social interaction in foster dyads at child age 2 and 3 years.

PubMed

Jacobsen, Heidi; Vang, Kristin Alvestad; Lindahl, Karoline Mentzoni; Wentzel-Larsen, Tore; Smith, Lars; Moe, Vibeke

2018-06-30

The main aim of this study was to investigate the quality of social interaction between 60 foster parents and their foster children compared to a group of 55 non-foster families at 2 (T1) and again at 3 (T2) years of age. Video observations were used to investigate child-parent interaction at both time-points. "This is My Baby" interview was administered to investigate foster parents' commitment at T1. The main results revealed significant group differences at T1 on all child-parent social interaction measures, although not at T2. Further, a significant group by time interaction was identified for parental sensitivity, revealing a positive development over time in the foster group. Finally, a significant positive relation was found between commitment at T1 and parental sensitivity. The results convey an optimistic view of the possibilities for foster dyads to develop positive patterns of social interaction over time.

Targeting of Repeated Sequences Unique to a Gene Results in Significant Increases in Antisense Oligonucleotide Potency

PubMed Central

Vickers, Timothy A.; Freier, Susan M.; Bui, Huynh-Hoa; Watt, Andrew; Crooke, Stanley T.

2014-01-01

A new strategy for identifying potent RNase H-dependent antisense oligonucleotides (ASOs) is presented. Our analysis of the human transcriptome revealed that a significant proportion of genes contain unique repeated sequences of 16 or more nucleotides in length. Activities of ASOs targeting these repeated sites in several representative genes were compared to those of ASOs targeting unique single sites in the same transcript. Antisense activity at repeated sites was also evaluated in a highly controlled minigene system. Targeting both native and minigene repeat sites resulted in significant increases in potency as compared to targeting of non-repeated sites. The increased potency at these sites is a result of increased frequency of ASO/RNA interactions which, in turn, increases the probability of a productive interaction between the ASO/RNA heteroduplex and human RNase H1 in the cell. These results suggest a new, highly efficient strategy for rapid identification of highly potent ASOs. PMID:25334092

Substrate co-doping modulates electronic metal–support interactions and significantly enhances single-atom catalysis

DOE PAGES

Shi, Jinlei; Wu, Jinghe; Zhao, Xingju; ...

2016-10-07

Transitional metal nanoparticles or atoms deposited on appropriate substrates can lead to highly economical, efficient, and selective catalysis. One of the greatest challenges is to control the electronic metal–support interactions (EMSI) between the supported metal atoms and the substrate so as to optimize their catalytic performance. Here, from first-principles calculations, we show that an otherwise inactive Pd single adatom on TiO 2(110) can be tuned into a highly effective catalyst, e.g. for O 2 adsorption and CO oxidation, by purposefully selected metal–nonmetal co-dopant pairs in the substrate. Such an effect is proved here to result unambiguously from a significantly enhancedmore » EMSI. A nearly linear correlation is noted between the strength of the EMSI and the activation of the adsorbed O 2 molecule, as well as the energy barrier for CO oxidation. Particularly, the enhanced EMSI shifts the frontier orbital of the deposited Pd atom upward and largely enhances the hybridization and charge transfer between the O 2 molecule and the Pd atom. Upon co-doping, the activation barrier for CO oxidation on the Pd monomer is also reduced to a level comparable to that on the Pd dimer which was experimentally reported to be highly efficient for CO oxidation. The present findings provide new insights into the understanding of the EMSI in heterogeneous catalysis and can open new avenues to design and fabricate cost-effective single-atom-sized and/or nanometer-sized catalysts.« less

Genetic associations with micronutrient levels identified in immune and gastrointestinal networks.

PubMed

Morine, Melissa J; Monteiro, Jacqueline Pontes; Wise, Carolyn; Teitel, Candee; Pence, Lisa; Williams, Anna; Ning, Baitang; McCabe-Sellers, Beverly; Champagne, Catherine; Turner, Jerome; Shelby, Beatrice; Bogle, Margaret; Beger, Richard D; Priami, Corrado; Kaput, Jim

2014-07-01

The discovery of vitamins and clarification of their role in preventing frank essential nutrient deficiencies occurred in the early 1900s. Much vitamin research has understandably focused on public health and the effects of single nutrients to alleviate acute conditions. The physiological processes for maintaining health, however, are complex systems that depend upon interactions between multiple nutrients, environmental factors, and genetic makeup. To analyze the relationship between these factors and nutritional health, data were obtained from an observational, community-based participatory research program of children and teens (age 6-14) enrolled in a summer day camp in the Delta region of Arkansas. Assessments of erythrocyte S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH), plasma homocysteine (Hcy) and 6 organic micronutrients (retinol, 25-hydroxy vitamin D3, pyridoxal, thiamin, riboflavin, and vitamin E), and 1,129 plasma proteins were performed at 3 time points in each of 2 years. Genetic makeup was analyzed with 1 M SNP genotyping arrays, and nutrient status was assessed with 24-h dietary intake questionnaires. A pattern of metabolites (met_PC1) that included the ratio of erythrocyte SAM/SAH, Hcy, and 5 vitamins were identified by principal component analysis. Met_PC1 levels were significantly associated with (1) single-nucleotide polymorphisms, (2) levels of plasma proteins, and (3) multilocus genotypes coding for gastrointestinal and immune functions, as identified in a global network of metabolic/protein-protein interactions. Subsequent mining of data from curated pathway, network, and genome-wide association studies identified genetic and functional relationships that may be explained by gene-nutrient interactions. The systems nutrition strategy described here has thus associated a multivariate metabolite pattern in blood with genes involved in immune and gastrointestinal functions.

Inferring Domain-Domain Interactions from Protein-Protein Interactions with Formal Concept Analysis

PubMed Central

Khor, Susan

2014-01-01

Identifying reliable domain-domain interactions will increase our ability to predict novel protein-protein interactions, to unravel interactions in protein complexes, and thus gain more information about the function and behavior of genes. One of the challenges of identifying reliable domain-domain interactions is domain promiscuity. Promiscuous domains are domains that can occur in many domain architectures and are therefore found in many proteins. This becomes a problem for a method where the score of a domain-pair is the ratio between observed and expected frequencies because the protein-protein interaction network is sparse. As such, many protein-pairs will be non-interacting and domain-pairs with promiscuous domains will be penalized. This domain promiscuity challenge to the problem of inferring reliable domain-domain interactions from protein-protein interactions has been recognized, and a number of work-arounds have been proposed. This paper reports on an application of Formal Concept Analysis to this problem. It is found that the relationship between formal concepts provides a natural way for rare domains to elevate the rank of promiscuous domain-pairs and enrich highly ranked domain-pairs with reliable domain-domain interactions. This piggybacking of promiscuous domain-pairs onto less promiscuous domain-pairs is possible only with concept lattices whose attribute-labels are not reduced and is enhanced by the presence of proteins that comprise both promiscuous and rare domains. PMID:24586450

Gene-Gene and Gene-Environment Interactions in Ulcerative Colitis

PubMed Central

Wang, Ming-Hsi; Fiocchi, Claudio; Zhu, Xiaofeng; Ripke, Stephan; Kamboh, M. Ilyas; Rebert, Nancy; Duerr, Richard H.; Achkar, Jean-Paul

2014-01-01

Genome-wide association studies (GWAS) have identified at least 133 ulcerative colitis (UC) associated loci. The role of genetic factors in clinical practice is not clearly defined. The relevance of genetic variants to disease pathogenesis is still uncertain because of not characterized gene-gene and gene-environment interactions. We examined the predictive value of combining the 133 UC risk loci with genetic interactions in an ongoing inflammatory bowel disease (IBD) GWAS. The Wellcome Trust Case-Control Consortium (WTCCC) IBD GWAS was used as a replication cohort. We applied logic regression (LR), a novel adaptive regression methodology, to search for high order interactions. Exploratory genotype correlations with UC sub-phenotypes (extent of disease, need of surgery, age of onset, extra-intestinal manifestations and primary sclerosing cholangitis (PSC)) were conducted. The combination of 133 UC loci yielded good UC risk predictability (area under the curve [AUC] of 0.86). A higher cumulative allele score predicted higher UC risk. Through LR, several lines of evidence for genetic interactions were identified and successfully replicated in the WTCCC cohort. The genetic interactions combined with the gene-smoking interaction significantly improved predictability in the model (AUC, from 0.86 to 0.89, P=3.26E-05). Explained UC variance increased from 37% to 42% after adding the interaction terms. A within case analysis found suggested genetic association with PSC. Our study demonstrates that the LR methodology allows the identification and replication of high order genetic interactions in UC GWAS datasets. UC risk can be predicted by a 133 loci and improved by adding gene-gene and gene-environment interactions. PMID:24241240

Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies.

PubMed

Smith, Jennifer A; Zhao, Wei; Yasutake, Kalyn; August, Carmella; Ratliff, Scott M; Faul, Jessica D; Boerwinkle, Eric; Chakravarti, Aravinda; Diez Roux, Ana V; Gao, Yan; Griswold, Michael E; Heiss, Gerardo; Kardia, Sharon L R; Morrison, Alanna C; Musani, Solomon K; Mwasongwe, Stanford; North, Kari E; Rose, Kathryn M; Sims, Mario; Sun, Yan V; Weir, David R; Needham, Belinda L

2017-12-18

Inter-individual variability in blood pressure (BP) is influenced by both genetic and non-genetic factors including socioeconomic and psychosocial stressors. A deeper understanding of the gene-by-socioeconomic/psychosocial factor interactions on BP may help to identify individuals that are genetically susceptible to high BP in specific social contexts. In this study, we used a genomic region-based method for longitudinal analysis, Longitudinal Gene-Environment-Wide Interaction Studies (LGEWIS), to evaluate the effects of interactions between known socioeconomic/psychosocial and genetic risk factors on systolic and diastolic BP in four large epidemiologic cohorts of European and/or African ancestry. After correction for multiple testing, two interactions were significantly associated with diastolic BP. In European ancestry participants, outward/trait anger score had a significant interaction with the C10orf107 genomic region ( p = 0.0019). In African ancestry participants, depressive symptom score had a significant interaction with the HFE genomic region ( p = 0.0048). This study provides a foundation for using genomic region-based longitudinal analysis to identify subgroups of the population that may be at greater risk of elevated BP due to the combined influence of genetic and socioeconomic/psychosocial risk factors.

Food-drug interactions.

PubMed

Schmidt, Lars E; Dalhoff, Kim

2002-01-01

Interactions between food and drugs may inadvertently reduce or increase the drug effect. The majority of clinically relevant food-drug interactions are caused by food-induced changes in the bioavailability of the drug. Since the bioavailability and clinical effect of most drugs are correlated, the bioavailability is an important pharmacokinetic effect parameter. However, in order to evaluate the clinical relevance of a food-drug interaction, the impact of food intake on the clinical effect of the drug has to be quantified as well. As a result of quality review in healthcare systems, healthcare providers are increasingly required to develop methods for identifying and preventing adverse food-drug interactions. In this review of original literature, we have tried to provide both pharmacokinetic and clinical effect parameters of clinically relevant food-drug interactions. The most important interactions are those associated with a high risk of treatment failure arising from a significantly reduced bioavailability in the fed state. Such interactions are frequently caused by chelation with components in food (as occurs with alendronic acid, clodronic acid, didanosine, etidronic acid, penicillamine and tetracycline) or dairy products (ciprofloxacin and norfloxacin), or by other direct interactions between the drug and certain food components (avitriptan, indinavir, itraconazole solution, levodopa, melphalan, mercaptopurine and perindopril). In addition, the physiological response to food intake, in particular gastric acid secretion, may reduce the bioavailability of certain drugs (ampicillin, azithromycin capsules, didanosine, erythromycin stearate or enteric coated, and isoniazid). For other drugs, concomitant food intake may result in an increase in drug bioavailability either because of a food-induced increase in drug solubility (albendazole, atovaquone, griseofulvin, isotretinoin, lovastatin, mefloquine, saquinavir and tacrolimus) or because of the secretion of

Assortative and dissortative priorities for game interaction and strategy adaptation significantly bolster network reciprocity in the prisoner’s dilemma

NASA Astrophysics Data System (ADS)

Tanimoto, Jun

2014-05-01

In 2 × 2 prisoner’s dilemma games, network reciprocity is one mechanism for adding social viscosity, which leads to cooperative equilibrium. Here we show that combining the process for selecting a gaming partner with the process for selecting an adaptation partner significantly enhances cooperation, even though such selection processes require additional costs to collect further information concerning which neighbor should be chosen. Based on elaborate investigations of the dynamics generated by our model, we find that high levels of cooperation result from two kinds of behavior: cooperators tend to interact with cooperators to prevent being exploited by defectors and defectors tend to choose cooperators to exploit despite the possibility that some defectors convert to cooperators.

Transethnic genome-wide scan identifies novel Alzheimer's disease loci.

PubMed

Jun, Gyungah R; Chung, Jaeyoon; Mez, Jesse; Barber, Robert; Beecham, Gary W; Bennett, David A; Buxbaum, Joseph D; Byrd, Goldie S; Carrasquillo, Minerva M; Crane, Paul K; Cruchaga, Carlos; De Jager, Philip; Ertekin-Taner, Nilufer; Evans, Denis; Fallin, M Danielle; Foroud, Tatiana M; Friedland, Robert P; Goate, Alison M; Graff-Radford, Neill R; Hendrie, Hugh; Hall, Kathleen S; Hamilton-Nelson, Kara L; Inzelberg, Rivka; Kamboh, M Ilyas; Kauwe, John S K; Kukull, Walter A; Kunkle, Brian W; Kuwano, Ryozo; Larson, Eric B; Logue, Mark W; Manly, Jennifer J; Martin, Eden R; Montine, Thomas J; Mukherjee, Shubhabrata; Naj, Adam; Reiman, Eric M; Reitz, Christiane; Sherva, Richard; St George-Hyslop, Peter H; Thornton, Timothy; Younkin, Steven G; Vardarajan, Badri N; Wang, Li-San; Wendlund, Jens R; Winslow, Ashley R; Haines, Jonathan; Mayeux, Richard; Pericak-Vance, Margaret A; Schellenberg, Gerard; Lunetta, Kathryn L; Farrer, Lindsay A

2017-07-01

Genetic loci for Alzheimer's disease (AD) have been identified in whites of European ancestry, but the genetic architecture of AD among other populations is less understood. We conducted a transethnic genome-wide association study (GWAS) for late-onset AD in Stage 1 sample including whites of European Ancestry, African-Americans, Japanese, and Israeli-Arabs assembled by the Alzheimer's Disease Genetics Consortium. Suggestive results from Stage 1 from novel loci were followed up using summarized results in the International Genomics Alzheimer's Project GWAS dataset. Genome-wide significant (GWS) associations in single-nucleotide polymorphism (SNP)-based tests (P < 5 × 10 -8 ) were identified for SNPs in PFDN1/HBEGF, USP6NL/ECHDC3, and BZRAP1-AS1 and for the interaction of the (apolipoprotein E) APOE ε4 allele with NFIC SNP. We also obtained GWS evidence (P < 2.7 × 10 -6 ) for gene-based association in the total sample with a novel locus, TPBG (P = 1.8 × 10 -6 ). Our findings highlight the value of transethnic studies for identifying novel AD susceptibility loci. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Hamiltonian identifiability assisted by single-probe measurement

NASA Astrophysics Data System (ADS)

Sone, Akira; Cappellaro, Paola; Quantum Engineering Group Team

2017-04-01

We study the Hamiltonian identifiability of a many-body spin- 1 / 2 system assisted by the measurement on a single quantum probe based on the eigensystem realization algorithm (ERA) approach employed in. We demonstrate a potential application of Gröbner basis to the identifiability test of the Hamiltonian, and provide the necessary experimental resources, such as the lower bound in the number of the required sampling points, the upper bound in total required evolution time, and thus the total measurement time. Focusing on the examples of the identifiability in the spin chain model with nearest-neighbor interaction, we classify the spin-chain Hamiltonian based on its identifiability, and provide the control protocols to engineer the non-identifiable Hamiltonian to be an identifiable Hamiltonian.

PodNet, a protein-protein interaction network of the podocyte.

PubMed

Warsow, Gregor; Endlich, Nicole; Schordan, Eric; Schordan, Sandra; Chilukoti, Ravi K; Homuth, Georg; Moeller, Marcus J; Fuellen, Georg; Endlich, Karlhans

2013-07-01

Interactions between proteins crucially determine cellular structure and function. Differential analysis of the interactome may help elucidate molecular mechanisms during disease development; however, this analysis necessitates mapping of expression data on protein-protein interaction networks. These networks do not exist for the podocyte; therefore, we built PodNet, a literature-based mouse podocyte network in Cytoscape format. Using database protein-protein interactions, we expanded PodNet to XPodNet with enhanced connectivity. In order to test the performance of XPodNet in differential interactome analysis, we examined podocyte developmental differentiation and the effect of cell culture. Transcriptomes of podocytes in 10 different states were mapped on XPodNet and analyzed with the Cytoscape plugin ExprEssence, based on the law of mass action. Interactions between slit diaphragm proteins are most significantly upregulated during podocyte development and most significantly downregulated in culture. On the other hand, our analysis revealed that interactions lost during podocyte differentiation are not regained in culture, suggesting a loss rather than a reversal of differentiation for podocytes in culture. Thus, we have developed PodNet as a valuable tool for differential interactome analysis in podocytes, and we have identified established and unexplored regulated interactions in developing and cultured podocytes.

A genome-wide analysis of gene–caffeine consumption interaction on basal cell carcinoma

PubMed Central

Li, Xin; Cornelis, Marilyn C.; Liang, Liming; Song, Fengju; De Vivo, Immaculata; Giovannucci, Edward; Tang, Jean Y.; Han, Jiali

2016-01-01

Animal models have suggested that oral or topical administration of caffeine could inhibit ultraviolet-induced carcinogenesis via the ataxia telangiectasia and rad3 (ATR)-related apoptosis. Previous epidemiological studies have demonstrated that increased caffeine consumption is associated with reduced risk of basal cell carcinoma (BCC). To identify common genetic markers that may modify this association, we tested gene–caffeine intake interaction on BCC risk in a genome-wide analysis. We included 3383 BCC cases and 8528 controls of European ancestry from the Nurses’ Health Study and Health Professionals Follow-up Study. Single nucleotide polymorphism (SNP) rs142310826 near the NEIL3 gene showed a genome-wide significant interaction with caffeine consumption (P = 1.78 × 10–8 for interaction) on BCC risk. There was no gender difference for this interaction (P = 0.64 for heterogeneity). NEIL3, a gene belonging to the base excision DNA repair pathway, encodes a DNA glycosylase that recognizes and removes lesions produced by oxidative stress. In addition, we identified several loci with P value for interaction <5 × 10–7 in gender-specific analyses (P for heterogeneity between genders < 0.001) including those mapping to the genes LRRTM4, ATF3 and DCLRE1C in women and POTEA in men. Finally, we tested the associations between caffeine consumption-related SNPs reported by previous genome-wide association studies and risk of BCC, both individually and jointly, but found no significant association. In sum, we identified a DNA repair gene that could be involved in caffeine-mediated skin tumor inhibition. Further studies are warranted to confirm these findings. PMID:27797824

Identifying hydrodynamic interaction effects in tethered polymers in uniform flow.

PubMed

Kienle, Diego; Rzehak, Roland; Zimmermann, Walter

2011-06-01

Using Brownian dynamics simulations, we investigate how hydrodynamic interaction (HI) affects the behavior of tethered polymers in uniform flow. While it is expected that the HI within the polymer will lead to a dependency of the polymer's drag coefficient on the flow velocity, the interchain HI causes additional screening effects. For the case of two polymers in uniform flow with their tether points a finite distance apart, it is shown that the interchain HI not only causes a further reduction of the drag per polymer with decreasing distance between the tether points but simultaneously induces a polymer-polymer attraction as well. This attraction exhibits a characteristic maximum at intermediate flow velocities when the drag forces are of the order of the entropic forces. The effects uniquely attributed to the presence of HI can be verified experimentally.

Visualizing statistical significance of disease clusters using cartograms.

PubMed

Kronenfeld, Barry J; Wong, David W S

2017-05-15

Health officials and epidemiological researchers often use maps of disease rates to identify potential disease clusters. Because these maps exaggerate the prominence of low-density districts and hide potential clusters in urban (high-density) areas, many researchers have used density-equalizing maps (cartograms) as a basis for epidemiological mapping. However, we do not have existing guidelines for visual assessment of statistical uncertainty. To address this shortcoming, we develop techniques for visual determination of statistical significance of clusters spanning one or more districts on a cartogram. We developed the techniques within a geovisual analytics framework that does not rely on automated significance testing, and can therefore facilitate visual analysis to detect clusters that automated techniques might miss. On a cartogram of the at-risk population, the statistical significance of a disease cluster is determinate from the rate, area and shape of the cluster under standard hypothesis testing scenarios. We develop formulae to determine, for a given rate, the area required for statistical significance of a priori and a posteriori designated regions under certain test assumptions. Uniquely, our approach enables dynamic inference of aggregate regions formed by combining individual districts. The method is implemented in interactive tools that provide choropleth mapping, automated legend construction and dynamic search tools to facilitate cluster detection and assessment of the validity of tested assumptions. A case study of leukemia incidence analysis in California demonstrates the ability to visually distinguish between statistically significant and insignificant regions. The proposed geovisual analytics approach enables intuitive visual assessment of statistical significance of arbitrarily defined regions on a cartogram. Our research prompts a broader discussion of the role of geovisual exploratory analyses in disease mapping and the appropriate

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits.

PubMed

Justice, Anne E; Winkler, Thomas W; Feitosa, Mary F; Graff, Misa; Fisher, Virginia A; Young, Kristin; Barata, Llilda; Deng, Xuan; Czajkowski, Jacek; Hadley, David; Ngwa, Julius S; Ahluwalia, Tarunveer S; Chu, Audrey Y; Heard-Costa, Nancy L; Lim, Elise; Perez, Jeremiah; Eicher, John D; Kutalik, Zoltán; Xue, Luting; Mahajan, Anubha; Renström, Frida; Wu, Joseph; Qi, Qibin; Ahmad, Shafqat; Alfred, Tamuno; Amin, Najaf; Bielak, Lawrence F; Bonnefond, Amelie; Bragg, Jennifer; Cadby, Gemma; Chittani, Martina; Coggeshall, Scott; Corre, Tanguy; Direk, Nese; Eriksson, Joel; Fischer, Krista; Gorski, Mathias; Neergaard Harder, Marie; Horikoshi, Momoko; Huang, Tao; Huffman, Jennifer E; Jackson, Anne U; Justesen, Johanne Marie; Kanoni, Stavroula; Kinnunen, Leena; Kleber, Marcus E; Komulainen, Pirjo; Kumari, Meena; Lim, Unhee; Luan, Jian'an; Lyytikäinen, Leo-Pekka; Mangino, Massimo; Manichaikul, Ani; Marten, Jonathan; Middelberg, Rita P S; Müller-Nurasyid, Martina; Navarro, Pau; Pérusse, Louis; Pervjakova, Natalia; Sarti, Cinzia; Smith, Albert Vernon; Smith, Jennifer A; Stančáková, Alena; Strawbridge, Rona J; Stringham, Heather M; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W; van der Most, Peter J; Van Vliet-Ostaptchouk, Jana V; Vedantam, Sailaja L; Verweij, Niek; Vink, Jacqueline M; Vitart, Veronique; Wu, Ying; Yengo, Loic; Zhang, Weihua; Hua Zhao, Jing; Zimmermann, Martina E; Zubair, Niha; Abecasis, Gonçalo R; Adair, Linda S; Afaq, Saima; Afzal, Uzma; Bakker, Stephan J L; Bartz, Traci M; Beilby, John; Bergman, Richard N; Bergmann, Sven; Biffar, Reiner; Blangero, John; Boerwinkle, Eric; Bonnycastle, Lori L; Bottinger, Erwin; Braga, Daniele; Buckley, Brendan M; Buyske, Steve; Campbell, Harry; Chambers, John C; Collins, Francis S; Curran, Joanne E; de Borst, Gert J; de Craen, Anton J M; de Geus, Eco J C; Dedoussis, George; Delgado, Graciela E; den Ruijter, Hester M; Eiriksdottir, Gudny; Eriksson, Anna L; Esko, Tõnu; Faul, Jessica D; Ford, Ian; Forrester, Terrence; Gertow, Karl; Gigante, Bruna; Glorioso, Nicola; Gong, Jian; Grallert, Harald; Grammer, Tanja B; Grarup, Niels; Haitjema, Saskia; Hallmans, Göran; Hamsten, Anders; Hansen, Torben; Harris, Tamara B; Hartman, Catharina A; Hassinen, Maija; Hastie, Nicholas D; Heath, Andrew C; Hernandez, Dena; Hindorff, Lucia; Hocking, Lynne J; Hollensted, Mette; Holmen, Oddgeir L; Homuth, Georg; Jan Hottenga, Jouke; Huang, Jie; Hung, Joseph; Hutri-Kähönen, Nina; Ingelsson, Erik; James, Alan L; Jansson, John-Olov; Jarvelin, Marjo-Riitta; Jhun, Min A; Jørgensen, Marit E; Juonala, Markus; Kähönen, Mika; Karlsson, Magnus; Koistinen, Heikki A; Kolcic, Ivana; Kolovou, Genovefa; Kooperberg, Charles; Krämer, Bernhard K; Kuusisto, Johanna; Kvaløy, Kirsti; Lakka, Timo A; Langenberg, Claudia; Launer, Lenore J; Leander, Karin; Lee, Nanette R; Lind, Lars; Lindgren, Cecilia M; Linneberg, Allan; Lobbens, Stephane; Loh, Marie; Lorentzon, Mattias; Luben, Robert; Lubke, Gitta; Ludolph-Donislawski, Anja; Lupoli, Sara; Madden, Pamela A F; Männikkö, Reija; Marques-Vidal, Pedro; Martin, Nicholas G; McKenzie, Colin A; McKnight, Barbara; Mellström, Dan; Menni, Cristina; Montgomery, Grant W; Musk, Aw Bill; Narisu, Narisu; Nauck, Matthias; Nolte, Ilja M; Oldehinkel, Albertine J; Olden, Matthias; Ong, Ken K; Padmanabhan, Sandosh; Peyser, Patricia A; Pisinger, Charlotta; Porteous, David J; Raitakari, Olli T; Rankinen, Tuomo; Rao, D C; Rasmussen-Torvik, Laura J; Rawal, Rajesh; Rice, Treva; Ridker, Paul M; Rose, Lynda M; Bien, Stephanie A; Rudan, Igor; Sanna, Serena; Sarzynski, Mark A; Sattar, Naveed; Savonen, Kai; Schlessinger, David; Scholtens, Salome; Schurmann, Claudia; Scott, Robert A; Sennblad, Bengt; Siemelink, Marten A; Silbernagel, Günther; Slagboom, P Eline; Snieder, Harold; Staessen, Jan A; Stott, David J; Swertz, Morris A; Swift, Amy J; Taylor, Kent D; Tayo, Bamidele O; Thorand, Barbara; Thuillier, Dorothee; Tuomilehto, Jaakko; Uitterlinden, Andre G; Vandenput, Liesbeth; Vohl, Marie-Claude; Völzke, Henry; Vonk, Judith M; Waeber, Gérard; Waldenberger, Melanie; Westendorp, R G J; Wild, Sarah; Willemsen, Gonneke; Wolffenbuttel, Bruce H R; Wong, Andrew; Wright, Alan F; Zhao, Wei; Zillikens, M Carola; Baldassarre, Damiano; Balkau, Beverley; Bandinelli, Stefania; Böger, Carsten A; Boomsma, Dorret I; Bouchard, Claude; Bruinenberg, Marcel; Chasman, Daniel I; Chen, Yii-DerIda; Chines, Peter S; Cooper, Richard S; Cucca, Francesco; Cusi, Daniele; Faire, Ulf de; Ferrucci, Luigi; Franks, Paul W; Froguel, Philippe; Gordon-Larsen, Penny; Grabe, Hans-Jörgen; Gudnason, Vilmundur; Haiman, Christopher A; Hayward, Caroline; Hveem, Kristian; Johnson, Andrew D; Wouter Jukema, J; Kardia, Sharon L R; Kivimaki, Mika; Kooner, Jaspal S; Kuh, Diana; Laakso, Markku; Lehtimäki, Terho; Marchand, Loic Le; März, Winfried; McCarthy, Mark I; Metspalu, Andres; Morris, Andrew P; Ohlsson, Claes; Palmer, Lyle J; Pasterkamp, Gerard; Pedersen, Oluf; Peters, Annette; Peters, Ulrike; Polasek, Ozren; Psaty, Bruce M; Qi, Lu; Rauramaa, Rainer; Smith, Blair H; Sørensen, Thorkild I A; Strauch, Konstantin; Tiemeier, Henning; Tremoli, Elena; van der Harst, Pim; Vestergaard, Henrik; Vollenweider, Peter; Wareham, Nicholas J; Weir, David R; Whitfield, John B; Wilson, James F; Tyrrell, Jessica; Frayling, Timothy M; Barroso, Inês; Boehnke, Michael; Deloukas, Panagiotis; Fox, Caroline S; Hirschhorn, Joel N; Hunter, David J; Spector, Tim D; Strachan, David P; van Duijn, Cornelia M; Heid, Iris M; Mohlke, Karen L; Marchini, Jonathan; Loos, Ruth J F; Kilpeläinen, Tuomas O; Liu, Ching-Ti; Borecki, Ingrid B; North, Kari E; Cupples, L Adrienne

2017-04-26

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

PubMed Central

Justice, Anne E.; Winkler, Thomas W.; Feitosa, Mary F.; Graff, Misa; Fisher, Virginia A.; Young, Kristin; Barata, Llilda; Deng, Xuan; Czajkowski, Jacek; Hadley, David; Ngwa, Julius S.; Ahluwalia, Tarunveer S.; Chu, Audrey Y.; Heard-Costa, Nancy L.; Lim, Elise; Perez, Jeremiah; Eicher, John D.; Kutalik, Zoltán; Xue, Luting; Mahajan, Anubha; Renström, Frida; Wu, Joseph; Qi, Qibin; Ahmad, Shafqat; Alfred, Tamuno; Amin, Najaf; Bielak, Lawrence F.; Bonnefond, Amelie; Bragg, Jennifer; Cadby, Gemma; Chittani, Martina; Coggeshall, Scott; Corre, Tanguy; Direk, Nese; Eriksson, Joel; Fischer, Krista; Gorski, Mathias; Neergaard Harder, Marie; Horikoshi, Momoko; Huang, Tao; Huffman, Jennifer E.; Jackson, Anne U.; Justesen, Johanne Marie; Kanoni, Stavroula; Kinnunen, Leena; Kleber, Marcus E.; Komulainen, Pirjo; Kumari, Meena; Lim, Unhee; Luan, Jian'an; Lyytikäinen, Leo-Pekka; Mangino, Massimo; Manichaikul, Ani; Marten, Jonathan; Middelberg, Rita P. S.; Müller-Nurasyid, Martina; Navarro, Pau; Pérusse, Louis; Pervjakova, Natalia; Sarti, Cinzia; Smith, Albert Vernon; Smith, Jennifer A.; Stančáková, Alena; Strawbridge, Rona J.; Stringham, Heather M.; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W.; van der Most, Peter J.; Van Vliet-Ostaptchouk, Jana V.; Vedantam, Sailaja L.; Verweij, Niek; Vink, Jacqueline M.; Vitart, Veronique; Wu, Ying; Yengo, Loic; Zhang, Weihua; Hua Zhao, Jing; Zimmermann, Martina E.; Zubair, Niha; Abecasis, Gonçalo R.; Adair, Linda S.; Afaq, Saima; Afzal, Uzma; Bakker, Stephan J. L.; Bartz, Traci M.; Beilby, John; Bergman, Richard N.; Bergmann, Sven; Biffar, Reiner; Blangero, John; Boerwinkle, Eric; Bonnycastle, Lori L.; Bottinger, Erwin; Braga, Daniele; Buckley, Brendan M.; Buyske, Steve; Campbell, Harry; Chambers, John C.; Collins, Francis S.; Curran, Joanne E.; de Borst, Gert J.; de Craen, Anton J. M.; de Geus, Eco J. C.; Dedoussis, George; Delgado, Graciela E.; den Ruijter, Hester M.; Eiriksdottir, Gudny; Eriksson, Anna L.; Esko, Tõnu; Faul, Jessica D.; Ford, Ian; Forrester, Terrence; Gertow, Karl; Gigante, Bruna; Glorioso, Nicola; Gong, Jian; Grallert, Harald; Grammer, Tanja B.; Grarup, Niels; Haitjema, Saskia; Hallmans, Göran; Hamsten, Anders; Hansen, Torben; Harris, Tamara B.; Hartman, Catharina A.; Hassinen, Maija; Hastie, Nicholas D.; Heath, Andrew C.; Hernandez, Dena; Hindorff, Lucia; Hocking, Lynne J.; Hollensted, Mette; Holmen, Oddgeir L.; Homuth, Georg; Jan Hottenga, Jouke; Huang, Jie; Hung, Joseph; Hutri-Kähönen, Nina; Ingelsson, Erik; James, Alan L.; Jansson, John-Olov; Jarvelin, Marjo-Riitta; Jhun, Min A.; Jørgensen, Marit E.; Juonala, Markus; Kähönen, Mika; Karlsson, Magnus; Koistinen, Heikki A.; Kolcic, Ivana; Kolovou, Genovefa; Kooperberg, Charles; Krämer, Bernhard K.; Kuusisto, Johanna; Kvaløy, Kirsti; Lakka, Timo A.; Langenberg, Claudia; Launer, Lenore J.; Leander, Karin; Lee, Nanette R.; Lind, Lars; Lindgren, Cecilia M.; Linneberg, Allan; Lobbens, Stephane; Loh, Marie; Lorentzon, Mattias; Luben, Robert; Lubke, Gitta; Ludolph-Donislawski, Anja; Lupoli, Sara; Madden, Pamela A. F.; Männikkö, Reija; Marques-Vidal, Pedro; Martin, Nicholas G.; McKenzie, Colin A.; McKnight, Barbara; Mellström, Dan; Menni, Cristina; Montgomery, Grant W.; Musk, AW (Bill); Narisu, Narisu; Nauck, Matthias; Nolte, Ilja M.; Oldehinkel, Albertine J.; Olden, Matthias; Ong, Ken K.; Padmanabhan, Sandosh; Peyser, Patricia A.; Pisinger, Charlotta; Porteous, David J.; Raitakari, Olli T.; Rankinen, Tuomo; Rao, D. C.; Rasmussen-Torvik, Laura J.; Rawal, Rajesh; Rice, Treva; Ridker, Paul M.; Rose, Lynda M.; Bien, Stephanie A.; Rudan, Igor; Sanna, Serena; Sarzynski, Mark A.; Sattar, Naveed; Savonen, Kai; Schlessinger, David; Scholtens, Salome; Schurmann, Claudia; Scott, Robert A.; Sennblad, Bengt; Siemelink, Marten A.; Silbernagel, Günther; Slagboom, P Eline; Snieder, Harold; Staessen, Jan A.; Stott, David J.; Swertz, Morris A.; Swift, Amy J.; Taylor, Kent D.; Tayo, Bamidele O.; Thorand, Barbara; Thuillier, Dorothee; Tuomilehto, Jaakko; Uitterlinden, Andre G.; Vandenput, Liesbeth; Vohl, Marie-Claude; Völzke, Henry; Vonk, Judith M.; Waeber, Gérard; Waldenberger, Melanie; Westendorp, R. G. J.; Wild, Sarah; Willemsen, Gonneke; Wolffenbuttel, Bruce H. R.; Wong, Andrew; Wright, Alan F.; Zhao, Wei; Zillikens, M Carola; Baldassarre, Damiano; Balkau, Beverley; Bandinelli, Stefania; Böger, Carsten A.; Boomsma, Dorret I.; Bouchard, Claude; Bruinenberg, Marcel; Chasman, Daniel I.; Chen, Yii-DerIda; Chines, Peter S.; Cooper, Richard S.; Cucca, Francesco; Cusi, Daniele; Faire, Ulf de; Ferrucci, Luigi; Franks, Paul W.; Froguel, Philippe; Gordon-Larsen, Penny; Grabe, Hans- Jörgen; Gudnason, Vilmundur; Haiman, Christopher A.; Hayward, Caroline; Hveem, Kristian; Johnson, Andrew D.; Wouter Jukema, J; Kardia, Sharon L. R.; Kivimaki, Mika; Kooner, Jaspal S.; Kuh, Diana; Laakso, Markku; Lehtimäki, Terho; Marchand, Loic Le; März, Winfried; McCarthy, Mark I.; Metspalu, Andres; Morris, Andrew P.; Ohlsson, Claes; Palmer, Lyle J.; Pasterkamp, Gerard; Pedersen, Oluf; Peters, Annette; Peters, Ulrike; Polasek, Ozren; Psaty, Bruce M.; Qi, Lu; Rauramaa, Rainer; Smith, Blair H.; Sørensen, Thorkild I. A.; Strauch, Konstantin; Tiemeier, Henning; Tremoli, Elena; van der Harst, Pim; Vestergaard, Henrik; Vollenweider, Peter; Wareham, Nicholas J.; Weir, David R.; Whitfield, John B.; Wilson, James F.; Tyrrell, Jessica; Frayling, Timothy M.; Barroso, Inês; Boehnke, Michael; Deloukas, Panagiotis; Fox, Caroline S.; Hirschhorn, Joel N.; Hunter, David J.; Spector, Tim D.; Strachan, David P.; van Duijn, Cornelia M.; Heid, Iris M.; Mohlke, Karen L.; Marchini, Jonathan; Loos, Ruth J. F.; Kilpeläinen, Tuomas O.; Liu, Ching-Ti; Borecki, Ingrid B.; North, Kari E.; Cupples, L Adrienne

2017-01-01

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution. PMID:28443625

Preliminary disposal limits, plume interaction factors, and final disposal limits

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

Flach, G.

In the 2008 E-Area Performance Assessment (PA), each final disposal limit was constructed as the product of a preliminary disposal limit and a plume interaction factor. The following mathematical development demonstrates that performance objectives are generally expected to be satisfied with high confidence under practical PA scenarios using this method. However, radionuclides that experience significant decay between a disposal unit and the 100-meter boundary, such as H-3 and Sr-90, can challenge performance objectives, depending on the disposed-of waste composition, facility geometry, and the significance of the plume interaction factor. Pros and cons of analyzing single disposal units or multiple disposalmore » units as a group in the preliminary disposal limits analysis are also identified.« less

Image Representation and Interactivity: An Exploration of Utility Values, Information-Needs and Image Interactivity

ERIC Educational Resources Information Center

Lewis, Elise C.

2011-01-01

This study was designed to explore the relationships between users and interactive images. Three factors were identified and provided different perspectives on how users interact with images: image utility, information-need, and images with varying levels of interactivity. The study used a mixed methodology to gain a more comprehensive…

Identifying key sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment.

PubMed

Sweetapple, Christine; Fu, Guangtao; Butler, David

2013-09-01

This study investigates sources of uncertainty in the modelling of greenhouse gas emissions from wastewater treatment, through the use of local and global sensitivity analysis tools, and contributes to an in-depth understanding of wastewater treatment modelling by revealing critical parameters and parameter interactions. One-factor-at-a-time sensitivity analysis is used to screen model parameters and identify those with significant individual effects on three performance indicators: total greenhouse gas emissions, effluent quality and operational cost. Sobol's method enables identification of parameters with significant higher order effects and of particular parameter pairs to which model outputs are sensitive. Use of a variance-based global sensitivity analysis tool to investigate parameter interactions enables identification of important parameters not revealed in one-factor-at-a-time sensitivity analysis. These interaction effects have not been considered in previous studies and thus provide a better understanding wastewater treatment plant model characterisation. It was found that uncertainty in modelled nitrous oxide emissions is the primary contributor to uncertainty in total greenhouse gas emissions, due largely to the interaction effects of three nitrogen conversion modelling parameters. The higher order effects of these parameters are also shown to be a key source of uncertainty in effluent quality. Copyright © 2013 Elsevier Ltd. All rights reserved.

Identifying children with specific reading disabilities from listening and reading discrepancy scores.

PubMed

Spring, C; French, L

1990-01-01

A method of identifying children with specific reading disabilities by identifying discrepancies between their reading and listening comprehension scores was validated with disabled and nondisabled readers in Grades 4, 5, and 6. The method is based on a modification of the reading comprehension subtest of the Peabody Individual Achievement Test (Dunn & Markwardt, 1970). In this modification, even-numbered sentences are read by subjects, and odd-numbered sentences are read by the test administrator as subjects listen. The features of this test that reduce demands on working memory, thereby making it suitable for the detection of a discrepancy between reading and listening comprehension in readers with disabilities, are discussed. A significant group-by-modality interaction was obtained. Children with reading disabilities scored significantly lower on reading than on listening comprehension, while nondisabled readers scored slightly higher, but not significantly so, on reading than on listening comprehension. The appropriateness of this method as a substitute for the traditional method, which is based on the detection of a discrepancy between intelligence and reading and which has recently been proscribed in certain school districts, is discussed. Issues concerning the listening comprehension skills of disabled readers are also discussed.

Detecting recurrent gene mutation in interaction network context using multi-scale graph diffusion.

PubMed

Babaei, Sepideh; Hulsman, Marc; Reinders, Marcel; de Ridder, Jeroen

2013-01-23

Delineating the molecular drivers of cancer, i.e. determining cancer genes and the pathways which they deregulate, is an important challenge in cancer research. In this study, we aim to identify pathways of frequently mutated genes by exploiting their network neighborhood encoded in the protein-protein interaction network. To this end, we introduce a multi-scale diffusion kernel and apply it to a large collection of murine retroviral insertional mutagenesis data. The diffusion strength plays the role of scale parameter, determining the size of the network neighborhood that is taken into account. As a result, in addition to detecting genes with frequent mutations in their genomic vicinity, we find genes that harbor frequent mutations in their interaction network context. We identify densely connected components of known and putatively novel cancer genes and demonstrate that they are strongly enriched for cancer related pathways across the diffusion scales. Moreover, the mutations in the clusters exhibit a significant pattern of mutual exclusion, supporting the conjecture that such genes are functionally linked. Using multi-scale diffusion kernel, various infrequently mutated genes are found to harbor significant numbers of mutations in their interaction network neighborhood. Many of them are well-known cancer genes. The results demonstrate the importance of defining recurrent mutations while taking into account the interaction network context. Importantly, the putative cancer genes and networks detected in this study are found to be significant at different diffusion scales, confirming the necessity of a multi-scale analysis.

Differential Occurrence of Interactions and Interaction Domains in Proteins Containing Homopolymeric Amino Acid Repeats

PubMed Central

Pelassa, Ilaria; Fiumara, Ferdinando

2015-01-01

Homopolymeric amino acids repeats (AARs), which are widespread in proteomes, have often been viewed simply as spacers between protein domains, or even as “junk” sequences with no obvious function but with a potential to cause harm upon expansion as in genetic diseases associated with polyglutamine or polyalanine expansions, including Huntington disease and cleidocranial dysplasia. A growing body of evidence indicates however that at least some AARs can form organized, functional protein structures, and can regulate protein function. In particular, certain AARs can mediate protein-protein interactions, either through homotypic AAR-AAR contacts or through heterotypic contacts with other protein domains. It is still unclear however, whether AARs may have a generalized, proteome-wide role in shaping protein-protein interaction networks. Therefore, we have undertaken here a bioinformatics screening of the human proteome and interactome in search of quantitative evidence of such a role. We first identified the sets of proteins that contain repeats of any one of the 20 amino acids, as well as control sets of proteins chosen at random in the proteome. We then analyzed the connectivity between the proteins of the AAR-containing protein sets and we compared it with that observed in the corresponding control networks. We find evidence for different degrees of connectivity in the different AAR-containing protein networks. Indeed, networks of proteins containing polyglutamine, polyglutamate, polyproline, and other AARs show significantly increased levels of connectivity, whereas networks containing polyleucine and other hydrophobic repeats show lower degrees of connectivity. Furthermore, we observed that numerous protein-protein, -nucleic acid, and -lipid interaction domains are significantly enriched in specific AAR protein groups. These findings support the notion of a generalized, combinatorial role of AARs, together with conventional protein interaction domains, in

Identifying and Assessing Interaction Knowledge, Skills, and Attributes for Future Force Soldiers

DTIC Science & Technology

2007-05-01

Research Institute for the Behavioral and Social Sciences (ARI) SBIR request, the Army Interpersonal Skills Assessment ( AISA ) battery consists of five...Army evolves over the coming years, Soldiers will be placed in positions that require increasing interaction effectiveness. The goal of the AISA is...effective interpersonal KSAs may improve performance. In Phase II of this SBIR effort, the AISA battery underwent a full development cycle

Important drug-nutrient interactions.

PubMed

Mason, Pamela

2010-11-01

Drugs have the potential to interact with nutrients potentially leading to reduced therapeutic efficacy of the drug, nutritional risk or increased adverse effects of the drug. Despite significant interest in such interactions going back to over more than 40 years, the occurrence and clinical significance of many drug-nutrient interactions remains unclear. However, interactions involving drugs with a narrow therapeutic margin such as theophylline and digoxin and those that require careful blood monitoring such as warfarin are likely to be those of clinical significance. Drugs can affect nutrition as a result of changes in appetite and taste as well as having an influence on absorption or metabolism of nutrients. Moreover, foods and supplements can also interact with drugs, of which grapefruit juice and St John's wort are key examples. Significant numbers of people take both supplements and medication and are potentially at risk from interactions. Professionals, such as pharmacists, dietitians, nurses and doctors, responsible for the care of patients should therefore check whether supplements are being taken, while for researchers this is an area worthy of significant further study, particularly in the context of increasingly complex drug regimens and the plethora of new drugs.

Identifying consumer-resource population dynamics using paleoecological data.

PubMed

Einarsson, Árni; Hauptfleisch, Ulf; Leavitt, Peter R; Ives, Anthony R

2016-02-01

Ecologists have long been fascinated by cyclic population fluctuations, because they suggest strong interactions between exploiter and victim species. Nonetheless, even for populations showing high-amplitude fluctuations, it is often hard to identify which species are the key drivers of the dynamics, because data are generally only available for a single species. Here, we use a paleoecological approach to investigate fluctuations in the midge population in Lake Mývatn, Iceland, which ranges over several orders of magnitude in irregular, multigeneration cycles. Previous circumstantial evidence points to consumer-resource interactions between midges and their primary food, diatoms, as the cause of these high-amplitude fluctuations. Using a pair of sediment cores from the lake, we reconstructed 26 years of dynamics of midges using egg remains and of algal groups using diagnostic pigments. We analyzed these data using statistical methods that account for both the autocorrelated nature of paleoecological data and measurement error caused by the mixing of sediment layers. The analyses revealed a signature of consumer-resource interactions in the fluctuations of midges and diatoms: diatom abundance (as inferred from biomarker pigment diatoxanthin) increased when midge abundance was low, and midge abundance (inferred from egg capsules) decreased when diatom abundance was low. Similar patterns were not found for pigments characterizing the other dominant primary producer group in the lake (cyanobacteria), subdominant algae (cryptophytes), or ubiquitous but chemically unstable biomarkers of total algal abundance (chlorophyll a); however, a significant but weaker pattern was found for the chemically stable indicator of total algal populations (β-carotene) to which diatoms are the dominant contributor. These analyses provide the first paleoecological evaluation of specific trophic interactions underlying high amplitude population fluctuations in lakes.

The case-only test for gene-environment interaction is not uniformly powerful: an empirical example

PubMed Central

Wu, Chen; Chang, Jiang; Ma, Baoshan; Miao, Xiaoping; Zhou, Yifeng; Liu, Yu; Li, Yun; Wu, Tangchun; Hu, Zhibin; Shen, Hongbing; Jia, Weihua; Zeng, Yixin; Lin, Dongxin; Kraft, Peter

2016-01-01

The case-only test has been proposed as a more powerful approach to detect gene-environment (G×E) interactions. This approach assumes that the genetic and environmental factors are independent. While it is well known that Type I error rate will increase if this assumption is violated, it is less widely appreciated that gene-environment correlation can also lead to power loss. We illustrate this phenomenon by comparing the performance of the case-only test to other approaches to detect G×E interactions in a genome-wide association study of esophageal squamous carcinoma (ESCC) in Chinese populations. Some of these approaches do not use information on the correlation between exposure and genotype (standard logistic regression), while others seek to use this information in a robust fashion to boost power without increasing Type I error (two-step, empirical Bayes and cocktail methods). G×E interactions were identified involving drinking status and two regions containing genes in the alcohol metabolism pathway, 4q23 and 12q24. Although the case-only test yielded the most significant tests of G×E interaction in the 4q23 region, the case-only test failed to identify significant interactions in the 12q24 region which were readily identified using other approaches. The low power of the case-only test in the 12q24 region is likely due to the strong inverse association between the SNPs in this region and drinking status. This example underscores the need to consider multiple approaches to detect gene-environment interactions, as different tests are more or less sensitive to different alternative hypotheses and violations of the gene-environment independence assumption. PMID:23595356

Immunochip Analyses of Epistasis in Rheumatoid Arthritis Confirm Multiple Interactions within MHC and Suggest Novel Non-MHC Epistatic Signals.

PubMed

Wei, Wen-Hua; Loh, Chia-Yin; Worthington, Jane; Eyre, Stephen

2016-05-01

Studying statistical gene-gene interactions (epistasis) has been limited by the difficulties in performance, both statistically and computationally, in large enough sample numbers to gain sufficient power. Three large Immunochip datasets from cohort samples recruited in the United Kingdom, United States, and Sweden with European ancestry were used to examine epistasis in rheumatoid arthritis (RA). A full pairwise search was conducted in the UK cohort using a high-throughput tool and the resultant significant epistatic signals were tested for replication in the United States and Swedish cohorts. A forward selection approach was applied to remove redundant signals, while conditioning on the preidentified additive effects. We detected abundant genome-wide significant (p < 1.0e-13) epistatic signals, all within the MHC region. These signals were reduced substantially, but a proportion remained significant (p < 1.0e-03) in conditional tests. We identified 11 independent epistatic interactions across the entire MHC, each explaining on average 0.12% of the phenotypic variance, nearly all replicated in both replication cohorts. We also identified non-MHC epistatic interactions between RA susceptible loci LOC100506023 and IRF5 with Immunochip-wide significance (p < 1.1e-08) and between 2 neighboring single-nucleotide polymorphism near PTPN22 that were in low linkage disequilibrium with independent interaction (p < 1.0e-05). Both non-MHC epistatic interactions were statistically replicated with a similar interaction pattern in the US cohort only. There are multiple but relatively weak interactions independent of the additive effects in RA and a larger sample number is required to confidently assign additional non-MHC epistasis.

Identifying novel drug indications through automated reasoning.

PubMed

Tari, Luis; Vo, Nguyen; Liang, Shanshan; Patel, Jagruti; Baral, Chitta; Cai, James

2012-01-01

With the large amount of pharmacological and biological knowledge available in literature, finding novel drug indications for existing drugs using in silico approaches has become increasingly feasible. Typical literature-based approaches generate new hypotheses in the form of protein-protein interactions networks by means of linking concepts based on their cooccurrences within abstracts. However, this kind of approaches tends to generate too many hypotheses, and identifying new drug indications from large networks can be a time-consuming process. In this work, we developed a method that acquires the necessary facts from literature and knowledge bases, and identifies new drug indications through automated reasoning. This is achieved by encoding the molecular effects caused by drug-target interactions and links to various diseases and drug mechanism as domain knowledge in AnsProlog, a declarative language that is useful for automated reasoning, including reasoning with incomplete information. Unlike other literature-based approaches, our approach is more fine-grained, especially in identifying indirect relationships for drug indications. To evaluate the capability of our approach in inferring novel drug indications, we applied our method to 943 drugs from DrugBank and asked if any of these drugs have potential anti-cancer activities based on information on their targets and molecular interaction types alone. A total of 507 drugs were found to have the potential to be used for cancer treatments. Among the potential anti-cancer drugs, 67 out of 81 drugs (a recall of 82.7%) are indeed known cancer drugs. In addition, 144 out of 289 drugs (a recall of 49.8%) are non-cancer drugs that are currently tested in clinical trials for cancer treatments. These results suggest that our method is able to infer drug indications (original or alternative) based on their molecular targets and interactions alone and has the potential to discover novel drug indications for existing drugs.

Ethanol-drug absorption interaction: potential for a significant effect on the plasma pharmacokinetics of ethanol vulnerable formulations.

PubMed

Lennernäs, Hans

2009-01-01

Generally, gastric emptying of a drug to the small intestine is controlled by gastric motor activity and is the main factor affecting the onset of absorption. Accordingly, the emptying rate from the stomach is mainly affected by the digestive state, the properties of the pharmaceutical formulation and the effect of drugs, posture and circadian rhythm. Variability in the gastric emptying of drugs is reflected in variability in the absorption rate and the shape of the plasma pharmacokinetic profile. When ethanol interacts with an oral controlled release product, such that the mechanism controlling drug release is impaired, the delivery of the dissolved dose into the small intestine and the consequent absorption may result in dangerously high plasma concentrations. For example, the maximal plasma concentration of hydromorphone has individually been shown to be increased as much as 16 times through in vivo testing as a result of this specific pharmacokinetic ethanol-drug formulation interaction. Thus, a pharmacokinetic ethanol-drug interaction is a very serious safety concern when substantially the entire dose from a controlled release product is rapidly emptied into the small intestine (dose dumping), having been largely dissolved in a strong alcoholic beverage in the stomach during a sufficient lag-time in gastric emptying. Based on the literature, a two hour time frame for screening the in vitro dissolution profile of a controlled release product in ethanol concentrations of up to 40% is strongly supported and may be considered as the absolute minimum standard. It is also evident that the dilution, absorption and metabolism of ethanol in the stomach are processes with a minor effect on the local ethanol concentration and that ethanol exposure will be highly dependent on the volume and ethanol concentration of the fluid ingested, together with the rate of intake and gastric emptying. When and in which patients a clinically significant dose dumping will happen is

A systems wide mass spectrometric based linear motif screen to identify dominant in-vivo interacting proteins for the ubiquitin ligase MDM2.

PubMed

Nicholson, Judith; Scherl, Alex; Way, Luke; Blackburn, Elizabeth A; Walkinshaw, Malcolm D; Ball, Kathryn L; Hupp, Ted R

2014-06-01

Linear motifs mediate protein-protein interactions (PPI) that allow expansion of a target protein interactome at a systems level. This study uses a proteomics approach and linear motif sub-stratifications to expand on PPIs of MDM2. MDM2 is a multi-functional protein with over one hundred known binding partners not stratified by hierarchy or function. A new linear motif based on a MDM2 interaction consensus is used to select novel MDM2 interactors based on Nutlin-3 responsiveness in a cell-based proteomics screen. MDM2 binds a subset of peptide motifs corresponding to real proteins with a range of allosteric responses to MDM2 ligands. We validate cyclophilin B as a novel protein with a consensus MDM2 binding motif that is stabilised by Nutlin-3 in vivo, thus identifying one of the few known interactors of MDM2 that is stabilised by Nutlin-3. These data invoke two modes of peptide binding at the MDM2 N-terminus that rely on a consensus core motif to control the equilibrium between MDM2 binding proteins. This approach stratifies MDM2 interacting proteins based on the linear motif feature and provides a new biomarker assay to define clinically relevant Nutlin-3 responsive MDM2 interactors. Copyright © 2014 Elsevier Inc. All rights reserved.

A Synthetic Interaction Screen Identifies Factors Selectively Required for Proliferation and TERT Transcription in p53-Deficient Human Cancer Cells

PubMed Central

Park, Sung Mi; Zhu, Lihua J.; Debily, Marie-anne; Kittler, Ellen L. W.; Zapp, Maria L.; Lapointe, David; Gobeil, Stephane; Virbasius, Ching-Man; Green, Michael R.

2012-01-01

Numerous genetic and epigenetic alterations render cancer cells selectively dependent on specific genes and regulatory pathways, and represent potential vulnerabilities that can be therapeutically exploited. Here we describe an RNA interference (RNAi)–based synthetic interaction screen to identify genes preferentially required for proliferation of p53-deficient (p53−) human cancer cells. We find that compared to p53-competent (p53+) human cancer cell lines, diverse p53− human cancer cell lines are preferentially sensitive to loss of the transcription factor ETV1 and the DNA damage kinase ATR. In p53− cells, RNAi–mediated knockdown of ETV1 or ATR results in decreased expression of the telomerase catalytic subunit TERT leading to growth arrest, which can be reversed by ectopic TERT expression. Chromatin immunoprecipitation analysis reveals that ETV1 binds to a region downstream of the TERT transcriptional start-site in p53− but not p53+ cells. We find that the role of ATR is to phosphorylate and thereby stabilize ETV1. Our collective results identify a regulatory pathway involving ETV1, ATR, and TERT that is preferentially important for proliferation of diverse p53− cancer cells. PMID:23284306

Groundwater surface water interactions and the role of phreatophytes in identifying recharge zones

USDA-ARS?s Scientific Manuscript database

Groundwater and surface water interactions within riparian corridors impact the distribution of phreatophytes that tap into groundwater stores. The changes in canopy area of phreatophytes over time is related to changes in depth to groundwater, distance from a stream or river, and hydrologic soil gr...

Potential drug interactions in patients given antiretroviral therapy

PubMed Central

dos Santos, Wendel Mombaque; Secoli, Silvia Regina; Padoin, Stela Maris de Mello

2016-01-01

ABSTRACT Objective: to investigate potential drug-drug interactions (PDDI) in patients with HIV infection on antiretroviral therapy. Methods: a cross-sectional study was conducted on 161 adults with HIV infection. Clinical, socio demographic, and antiretroviral treatment data were collected. To analyze the potential drug interactions, we used the software Micromedex(r). Statistical analysis was performed by binary logistic regression, with a p-value of ≤0.05 considered statistically significant. Results: of the participants, 52.2% were exposed to potential drug-drug interactions. In total, there were 218 potential drug-drug interactions, of which 79.8% occurred between drugs used for antiretroviral therapy. There was an association between the use of five or more medications and potential drug-drug interactions (p = 0.000) and between the time period of antiretroviral therapy being over six years and potential drug-drug interactions (p < 0.00). The clinical impact was prevalent sedation and cardiotoxicity. Conclusions: the PDDI identified in this study of moderate and higher severity are events that not only affect the therapeutic response leading to toxicity in the central nervous and cardiovascular systems, but also can interfere in tests used for detection of HIV resistance to antiretroviral drugs. PMID:27878224

How Aboriginal Peer Interactions in Upper Primary School Sport Support Aboriginal Identity

ERIC Educational Resources Information Center

Kickett-Tucker, Cheryl S.

2008-01-01

This ethnographic study tested the hypothesis that positive social interactions in sport will contribute positively to the Aboriginal identity of urban, Australian Aboriginal children. Nine male and female children aged 11-12 years were observed and interviewed. Significant responses were extracted and meanings were identified and grouped into…

Spectroscopic studies on the interaction of cimetidine drug with biologically significant σ- and π-acceptors

NASA Astrophysics Data System (ADS)

Pandeeswaran, M.; Elango, K. P.

2010-05-01

Spectroscopic studies revealed that the interaction of cimetidine drug with electron acceptors iodine and 2,3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ) resulted through the initial formation of ionic intermediate to charge transfer (CT) complex. The CT-complexes of the interactions have been characterized using UV-vis, 1H NMR, FT-IR and GC-MS techniques. The formation of triiodide ion, I 3-, is further confirmed by the observation of the characteristic bands in the far IR spectrum for non-linear I 3- ion with C s symmetry at 156 and 131 cm -1 assigned to νas(I-I) and νs(I-I) of the I-I bond and at 73 cm -1 due to bending δ(I 3-). The rate of formation of the CT-complexes has been measured and discussed as a function of relative permittivity of solvent and temperature. The influence of relative permittivity of the medium on the rate indicated that the intermediate is more polar than the reactants and this observation was further supported by spectral studies. Based on the spectroscopic results plausible mechanisms for the interaction of the drug with the chosen acceptors were proposed and discussed and the point of attachment of the multifunctional cimetidine drug with these acceptors during the formation of CT-complex has been established.

Human-directed social behaviour in dogs shows significant heritability.

PubMed

Persson, M E; Roth, L S V; Johnsson, M; Wright, D; Jensen, P

2015-04-01

Through domestication and co-evolution with humans, dogs have developed abilities to attract human attention, e.g. in a manner of seeking assistance when faced with a problem solving task. The aims of this study were to investigate within breed variation in human-directed contact seeking in dogs and to estimate its genetic basis. To do this, 498 research beagles, bred and kept under standardized conditions, were tested in an unsolvable problem task. Contact seeking behaviours recorded included both eye contact and physical interactions. Behavioural data was summarized through a principal component analysis, resulting in four components: test interactions, social interactions, eye contact and physical contact. Females scored significantly higher on social interactions and physical contact and age had an effect on eye contact scores. Narrow sense heritabilities (h(2) ) of the two largest components were estimated at 0.32 and 0.23 but were not significant for the last two components. These results show that within the studied dog population, behavioural variation in human-directed social behaviours was sex dependent and that the utilization of eye contact seeking increased with age and experience. Hence, heritability estimates indicate a significant genetic contribution to the variation found in human-directed social interactions, suggesting that social skills in dogs have a genetic basis, but can also be shaped and enhanced through individual experiences. This research gives the opportunity to further investigate the genetics behind dogs' social skills, which could also play a significant part into research on human social disorders such as autism. © 2015 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Thematic content analysis of work-family interactions: Retired cosmonauts’ reflections

NASA Astrophysics Data System (ADS)

Johnson, Phyllis J.; Asmaro, Deyar; Suedfeld, Peter; Gushin, Vadim

2012-12-01

Anecdotal evidence and qualitative research attest to the importance of work-family interactions pre-, during and post-missions. This study uses thematic content analysis to quantify characteristics of work-family interactions and how these changed by stage of cosmonauts' career, identifying the effect of space career variables (e.g., time in space and station) on such interactions during and post-career. Using a thematic scoring scheme developed for this study, we coded work-family interactions identified from interviews with 20 retired male cosmonauts. The majority of work-family interactions were ones in which work overlapped into family life and work hindered or interfered with the family situation. The most common resolution was that family adjusted to work, and the mood or tone about this outcome was almost equally divided among negative, positive and neutral. Changes in work-family interactions and their resolution over the cosmonaut's life showed that the significant interactions were most evident during the cosmonaut career. Although the cosmonaut career has high work demands, it did adjust for family when the need arose. The Russian Space Agency (RKS) eased the impact of the periodic absences, especially through regular communication sessions. Positive work-family interactions, i.e., work or family helping the opposite role, were more likely for those who had been on ISS, not Mir, and for those whose last flight was after 2000. Our data reflect retired cosmonauts' recollections of work-family interactions during their career. Examples of work overlapping into family life and work viewed as interfering with family life were possibly more salient or better remembered than work or family helping the other role.

A Systematic Study of Sustainable Development Goal (SDG) Interactions

NASA Astrophysics Data System (ADS)

Pradhan, Prajal; Costa, Luís.; Rybski, Diego; Lucht, Wolfgang; Kropp, Jürgen P.

2017-11-01

Sustainable development goals (SDGs) have set the 2030 agenda to transform our world by tackling multiple challenges humankind is facing to ensure well-being, economic prosperity, and environmental protection. In contrast to conventional development agendas focusing on a restricted set of dimensions, the SDGs provide a holistic and multidimensional view on development. Hence, interactions among the SDGs may cause diverging results. To analyze the SDG interactions we systematize the identification of synergies and trade-offs using official SDG indicator data for 227 countries. A significant positive correlation between a pair of SDG indicators is classified as a synergy while a significant negative correlation is classified as a trade-off. We rank synergies and trade-offs between SDGs pairs on global and country scales in order to identify the most frequent SDG interactions. For a given SDG, positive correlations between indicator pairs were found to outweigh the negative ones in most countries. Among SDGs the positive and negative correlations between indicator pairs allowed for the identification of particular global patterns. SDG 1 (No poverty) has synergetic relationship with most of the other goals, whereas SDG 12 (Responsible consumption and production) is the goal most commonly associated with trade-offs. The attainment of the SDG agenda will greatly depend on whether the identified synergies among the goals can be leveraged. In addition, the highlighted trade-offs, which constitute obstacles in achieving the SDGs, need to be negotiated and made structurally nonobstructive by deeper changes in the current strategies.

Evaluation of knowledge of Health care professionals on warfarin interactions with drug and herb medicinal in Central Saudi Arabia

PubMed Central

Al-Arifi, Mohamed N.; Wajid, Syed; Al-Manie, Nawaf K.; Al-Saker, Faisal M.; Babelgaith, Salmeen D.; Asiri, Yousif A.; Sales, Ibrahim

2016-01-01

Objectives: To evaluate health care professionals’ knowledge on warfarin interactions with drugs and herbs. Methods: A self-administered questionnaire was developed to assess health care professionals’ knowledge on warfarin interactions with drug and herb. Respondents were asked to classify 15 drugs that may effect on warfarin action as “enhance”, “inhibit “, “no effect”. The study sample involved health care professionals (physicians, pharmacists and nurses) from king Salman hospital, Saudi Arabia. Results: About 92.2% of health care professionals identified warfarin interactions with aspirin, 4.4% for warfarin and fluoxetine. Warfarin and cardiac agents (atenolol) was correctly identified by 11.1% of respondents. In warfarin –herb interactions section, the majority of respondents (66.7%) identified the interaction between green tea and warfarin. Approximately one-third of respondents (n=33) correctly classified warfarin interactions with cardamom. No significant difference was found between the health care professionals (p=0.49) for warfarin-drug interactions knowledge score and p= 0.52 for warfarin- herb interactions knowledge score. Conclusion: This study suggests that health care professionals’ knowledge of warfarin- drug-herb interactions was inadequate. Therefore, health care professionals should receive more education programs about drug-drug/herb interactions to provide appropriate patient counseling and optimal therapeutic outcomes. PMID:27022381

Proteins that interact with calgranulin B in the human colon cancer cell line HCT-116.

PubMed

Myung, Jae Kyung; Yeo, Seung-Gu; Kim, Kyung Hee; Baek, Kwang-Soo; Shin, Daye; Kim, Jong Heon; Cho, Jae Youl; Yoo, Byong Chul

2017-01-24

Calgranulin B is released from immune cells and can be internalized into colon cancer cells to prevent proliferation. The present study aimed to identify proteins that interact with calgranulin B to suppress the proliferation of colon cancer cells, and to obtain information on the underlying anti-tumor mechanism(s) of calgranulin B. Calgranulin B expression was induced in colon cancer cell line HCT-116 by infection with calgranulin B-FLAG expressing lentivirus, and it led to a significant suppression of cell proliferation. Proteins that interacted with calgranulin B were obtained by immunoprecipitation using whole homogenate of lentivirus-infected HCT-116 cells which expressing calgranulin B-FLAG, and identified using liquid chromatography-mass spectrometry/mass spectrometry analysis. A total of 454 proteins were identified that potentially interact with calgranulin B, and most identified proteins were associated with RNA processing, post-transcriptional modifications and the EIF2 signaling pathway. Direct interaction of calgranulin B with flotillin-1, dynein intermediate chain 1, and CD59 glycoprotein has been confirmed, and the molecules N-myc proto-oncogene protein, rapamycin-insensitive companion of mTOR, and myc proto-oncogene protein were shown to regulate calgranulin B-interacting proteins. Our results provide new insight and useful information to explain the possible mechanism(s) underlying the role of calgranulin B as an anti-tumor effector in colon cancer cells.

Proteomic analysis of a compatible interaction between sugarcane and Sporisorium scitamineum.

PubMed

Barnabas, Leonard; Ashwin, N M R; Kaverinathan, K; Trentin, Anna Rita; Pivato, Micaela; Sundar, A Ramesh; Malathi, P; Viswanathan, R; Rosana, O B; Neethukrishna, K; Carletti, Paolo; Arrigoni, Giorgio; Masi, Antonio; Agrawal, Ganesh Kumar; Rakwal, Randeep

2016-04-01

Smut caused by Sporisorium scitamineum is one of the important diseases of sugarcane with global significance. Despite the intriguing nature of sugarcane, S. scitamineum interaction, several pertinent aspects remain unexplored. This study investigates the proteome level alterations occurring in the meristem of a S. scitamineum infected susceptible sugarcane cultivar at whip emergence stage. Differentially abundant proteins were identified by 2DE coupled with MALDI-TOF/TOF-MS. Comprehensively, 53 sugarcane proteins identified were related to defence, stress, metabolism, protein folding, energy, and cell division; in addition, a putative effector of S. scitamineum, chorismate mutase, was identified. Transcript expression vis-à-vis the activity of phenylalanine ammonia lyase was relatively higher in the infected meristem. Abundance of seven candidate proteins in 2D gel profiles was in correlation with its corresponding transcript expression levels as validated by qRT-PCR. Furthermore, this study has opened up new perspectives on the interaction between sugarcane and S. scitamineum. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Significance of stress transfer in time-dependent earthquake probability calculations

USGS Publications Warehouse

Parsons, T.

2005-01-01

A sudden change in stress is seen to modify earthquake rates, but should it also revise earthquake probability? Data used to derive input parameters permits an array of forecasts; so how large a static stress change is require to cause a statistically significant earthquake probability change? To answer that question, effects of parameter and philosophical choices are examined through all phases of sample calculations, Drawing at random from distributions of recurrence-aperiodicity pairs identifies many that recreate long paleoseismic and historic earthquake catalogs. Probability density funtions built from the recurrence-aperiodicity pairs give the range of possible earthquake forecasts under a point process renewal model. Consequences of choices made in stress transfer calculations, such as different slip models, fault rake, dip, and friction are, tracked. For interactions among large faults, calculated peak stress changes may be localized, with most of the receiving fault area changed less than the mean. Thus, to avoid overstating probability change on segments, stress change values should be drawn from a distribution reflecting the spatial pattern rather than using the segment mean. Disparity resulting from interaction probability methodology is also examined. For a fault with a well-understood earthquake history, a minimum stress change to stressing rate ratio of 10:1 to 20:1 is required to significantly skew probabilities with >80-85% confidence. That ratio must be closer to 50:1 to exceed 90-95% confidence levels. Thus revision to earthquake probability is achievable when a perturbing event is very close to the fault in question or the tectonic stressing rate is low.

Predicting Pharmacodynamic Drug-Drug Interactions through Signaling Propagation Interference on Protein-Protein Interaction Networks.

PubMed

Park, Kyunghyun; Kim, Docyong; Ha, Suhyun; Lee, Doheon

2015-01-01

As pharmacodynamic drug-drug interactions (PD DDIs) could lead to severe adverse effects in patients, it is important to identify potential PD DDIs in drug development. The signaling starting from drug targets is propagated through protein-protein interaction (PPI) networks. PD DDIs could occur by close interference on the same targets or within the same pathways as well as distant interference through cross-talking pathways. However, most of the previous approaches have considered only close interference by measuring distances between drug targets or comparing target neighbors. We have applied a random walk with restart algorithm to simulate signaling propagation from drug targets in order to capture the possibility of their distant interference. Cross validation with DrugBank and Kyoto Encyclopedia of Genes and Genomes DRUG shows that the proposed method outperforms the previous methods significantly. We also provide a web service with which PD DDIs for drug pairs can be analyzed at http://biosoft.kaist.ac.kr/targetrw.

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.

A genome-wide gene–environment interaction analysis for tobacco smoke and lung cancer susceptibility

PubMed Central

Zhang, Ruyang; Chu, Minjie; Zhao, Yang; Wu, Chen; Guo, Huan; Shi, Yongyong; Dai, Juncheng; Wei, Yongyue; Jin, Guangfu; Ma, Hongxia; Dong, Jing; Yi, Honggang; Bai, Jianling; Gong, Jianhang; Sun, Chongqi; Zhu, Meng; Wu, Tangchun; Hu, Zhibin; Lin, Dongxin; Shen, Hongbing; Chen, Feng

2014-01-01

Tobacco smoke is the major environmental risk factor underlying lung carcinogenesis. However, approximately one-tenth smokers develop lung cancer in their lifetime indicating there is significant individual variation in susceptibility to lung cancer. And, the reasons for this are largely unknown. In particular, the genetic variants discovered in genome-wide association studies (GWAS) account for only a small fraction of the phenotypic variations for lung cancer, and gene–environment interactions are thought to explain the missing fraction of disease heritability. The ability to identify smokers at high risk of developing cancer has substantial preventive implications. Thus, we undertook a gene–smoking interaction analysis in a GWAS of lung cancer in Han Chinese population using a two-phase designed case–control study. In the discovery phase, we evaluated all pair-wise (591 370) gene–smoking interactions in 5408 subjects (2331 cases and 3077 controls) using a logistic regression model with covariate adjustment. In the replication phase, promising interactions were validated in an independent population of 3023 subjects (1534 cases and 1489 controls). We identified interactions between two single nucleotide polymorphisms and smoking. The interaction P values are 6.73 × 10− 6 and 3.84 × 10− 6 for rs1316298 and rs4589502, respectively, in the combined dataset from the two phases. An antagonistic interaction (rs1316298–smoking) and a synergetic interaction (rs4589502–smoking) were observed. The two interactions identified in our study may help explain some of the missing heritability in lung cancer susceptibility and present strong evidence for further study of these gene–smoking interactions, which are benefit to intensive screening and smoking cessation interventions. PMID:24658283

Content and Usability Evaluation of Patient Oriented Drug-Drug Interaction Websites.

PubMed

Adam, Terrence J; Vang, Joseph

Drug-Drug Interactions (DDI) are an important source of preventable adverse drug events and a common reason for hospitalization among patients on multiple drug therapy regimens. DDI information systems are important patient safety tools with the capacity to identify and warn health professionals of clinically significant DDI risk. While substantial research has been completed on DDI information systems in professional settings such as community, hospital, and independent pharmacies; there has been limited research on DDI systems offered through online websites directly for use by ambulatory patients. The focus of this project is to test patient oriented website capacity to correctly identify drug interactions among well established and clinically significant medication combinations and convey clinical risk data to patients. The patient education capability was assessed by evaluating website Information Capacity, Patient Usability and Readability. The study results indicate that the majority of websites identified which met the inclusion and exclusion criteria operated similarly, but vary in risk severity assessment and are not optimally patient oriented to effectively deliver risk information. The limited quality of information and complex medical term content complicate DDI risk data conveyance and the sites may not provide optimal information delivery to allow medication consumers to understand and manage their medication regimens.

Transcriptome profiling identified differentially expressed genes and pathways associated with tamoxifen resistance in human breast cancer

PubMed Central

Men, Xin; Ma, Jun; Wu, Tong; Pu, Junyi; Wen, Shaojia; Shen, Jianfeng; Wang, Xun; Wang, Yamin; Chen, Chao; Dai, Penggao

2018-01-01

Tamoxifen (TAM) resistance is an important clinical problem in the treatment of breast cancer. In order to identify the mechanism of TAM resistance for estrogen receptor (ER)-positive breast cancer, we screened the transcriptome using RNA-seq and compared the gene expression profiles between the MCF-7 mamma carcinoma cell line and the TAM-resistant cell line TAMR/MCF-7, 52 significant differential expression genes (DEGs) were identified including SLIT2, ROBO, LHX, KLF, VEGFC, BAMBI, LAMA1, FLT4, PNMT, DHRS2, MAOA and ALDH. The DEGs were annotated in the GO, COG and KEGG databases. Annotation of the function of the DEGs in the KEGG database revealed the top three pathways enriched with the most DEGs, including pathways in cancer, the PI3K-AKT pathway, and focal adhesion. Then we compared the gene expression profiles between the Clinical progressive disease (PD) and the complete response (CR) from the cancer genome altas (TCGA). 10 common DEGs were identified through combining the clinical and cellular analysis results. Protein-protein interaction network was applied to analyze the association of ER signal pathway with the 10 DEGs. 3 significant genes (GFRA3, NPY1R and PTPRN2) were closely related to ER related pathway. These significant DEGs regulated many biological activities such as cell proliferation and survival, motility and migration, and tumor cell invasion. The interactions between these DEGs and drug resistance phenomenon need to be further elucidated at a functional level in further studies. Based on our findings, we believed that these DEGs could be therapeutic targets, which can be explored to develop new treatment options. PMID:29423105

Exploring the Interaction Natures in Plutonyl (VI) Complexes with Topological Analyses of Electron Density

PubMed Central

Du, Jiguang; Sun, Xiyuan; Jiang, Gang

2016-01-01

The interaction natures between Pu and different ligands in several plutonyl (VI) complexes are investigated by performing topological analyses of electron density. The geometrical structures in both gaseous and aqueous phases are obtained with B3LYP functional, and are generally in agreement with available theoretical and experimental results when combined with all-electron segmented all-electron relativistic contracted (SARC) basis set. The Pu–Oyl bond orders show significant linear dependence on bond length and the charge of oxygen atoms in plutonyl moiety. The closed-shell interactions were identified for Pu-Ligand bonds in most complexes with quantum theory of atoms in molecules (QTAIM) analyses. Meanwhile, we found that some Pu–Ligand bonds, like Pu–OH−, show weak covalent. The interactive nature of Pu–ligand bonds were revealed based on the interaction quantum atom (IQA) energy decomposition approach, and our results indicate that all Pu–Ligand interactions is dominated by the electrostatic attraction interaction as expected. Meanwhile it is also important to note that the quantum mechanical exchange-correlation contributions can not be ignored. By means of the non-covalent interaction (NCI) approach it has been found that some weak and repulsion interactions existed in plutonyl(VI) complexes, which can not be distinguished by QTAIM, can be successfully identified. PMID:27077844

Bioinformatic analysis of neurotropic HIV envelope sequences identifies polymorphisms in the gp120 bridging sheet that increase macrophage-tropism through enhanced interactions with CCR5

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

Mefford, Megan E., E-mail: megan_mefford@hms.harvard.edu; Kunstman, Kevin, E-mail: kunstman@northwestern.edu; Wolinsky, Steven M., E-mail: s-wolinsky@northwestern.edu

Macrophages express low levels of the CD4 receptor compared to T-cells. Macrophage-tropic HIV strains replicating in brain of untreated patients with HIV-associated dementia (HAD) express Envs that are adapted to overcome this restriction through mechanisms that are poorly understood. Here, bioinformatic analysis of env sequence datasets together with functional studies identified polymorphisms in the β3 strand of the HIV gp120 bridging sheet that increase M-tropism. D197, which results in loss of an N-glycan located near the HIV Env trimer apex, was detected in brain in some HAD patients, while position 200 was estimated to be under positive selection. D197 andmore » T/V200 increased fusion and infection of cells expressing low CD4 by enhancing gp120 binding to CCR5. These results identify polymorphisms in the HIV gp120 bridging sheet that overcome the restriction to macrophage infection imposed by low CD4 through enhanced gp120–CCR5 interactions, thereby promoting infection of brain and other macrophage-rich tissues. - Highlights: • We analyze HIV Env sequences and identify amino acids in beta 3 of the gp120 bridging sheet that enhance macrophage tropism. • These amino acids at positions 197 and 200 are present in brain of some patients with HIV-associated dementia. • D197 results in loss of a glycan near the HIV Env trimer apex, which may increase exposure of V3. • These variants may promote infection of macrophages in the brain by enhancing gp120–CCR5 interactions.« less

Exploring Wave-Wave Interactions in a General Circulation Model

NASA Astrophysics Data System (ADS)

Nystrom, Virginia; Gasperini, Federico; Forbes, Jeffrey M.; Hagan, Maura E.

2018-01-01

Nonlinear interactions involving Kelvin waves with (periods, zonal wave numbers) = (3.7d, s =- 1) (UFKW1) and = (2.4d, s =- 1) (UFKW2) and s = 0 and s = 1 quasi 9 day waves (Q9DW) with diurnal tides DW1, DW2, DW3, DE2, and DE3 are explored within a National Center for Atmospheric Research (NCAR) thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM) simulation driven at its ˜30 km lower boundary by interpolated 3-hourly output from Modern-Era Retrospective Analysis for Research and Applications (MERRA). The existence of nonlinear wave-wave interactions between the above primary waves is determined by the presence of secondary waves (SWs) with frequencies and zonal wave numbers that are the sums and differences of those of the primary (interacting) waves. Focus is on 10-21 April 2009, when the nontidal dynamics in the mesosphere-lower thermosphere (MLT) region is dominated by UFKW and when identification of SW is robust. Fifteen SWs are identified in all. An interesting triad is identified involving UFKW1, DE3, and a secondary UFKW4 = (1.5d, s =- 2): The UFKW1-DE3 interaction produces UFKW4, the UFKW4-DE3 interaction produces UFKW1, and the UFKW1 interaction with UFKW4 produces DE3. At 120 km the dynamic range of the reconstructed latitude-longitude zonal wind field due to all of the SW is roughly half that of the primary waves, which produced them. This suggests that nonlinear wave-wave interactions could significantly modify the way that the lower atmosphere couples with the ionosphere.

The heritable basis of gene-environment interactions in cardiometabolic traits.

PubMed

Poveda, Alaitz; Chen, Yan; Brändström, Anders; Engberg, Elisabeth; Hallmans, Göran; Johansson, Ingegerd; Renström, Frida; Kurbasic, Azra; Franks, Paul W

2017-03-01

Little is known about the heritable basis of gene-environment interactions in humans. We therefore screened multiple cardiometabolic traits to assess the probability that they are influenced by genotype-environment interactions. Fourteen established environmental risk exposures and 11 cardiometabolic traits were analysed in the VIKING study, a cohort of 16,430 Swedish adults from 1682 extended pedigrees with available detailed genealogical, phenotypic and demographic information, using a maximum likelihood variance decomposition method in Sequential Oligogenic Linkage Analysis Routines software. All cardiometabolic traits had statistically significant heritability estimates, with narrow-sense heritabilities (h 2 ) ranging from 24% to 47%. Genotype-environment interactions were detected for age and sex (for the majority of traits), physical activity (for triacylglycerols, 2 h glucose and diastolic BP), smoking (for weight), alcohol intake (for weight, BMI and 2 h glucose) and diet pattern (for weight, BMI, glycaemic traits and systolic BP). Genotype-age interactions for weight and systolic BP, genotype-sex interactions for BMI and triacylglycerols and genotype-alcohol intake interactions for weight remained significant after multiple test correction. Age, sex and alcohol intake are likely to be major modifiers of genetic effects for a range of cardiometabolic traits. This information may prove valuable for studies that seek to identify specific loci that modify the effects of lifestyle in cardiometabolic disease.

A Genome-wide Trans-ethnic Interaction Study Links the PIGR ...

EPA Pesticide Factsheets

Air pollution is a worldwide contributor to cardiovascular disease mortality and morbidity. Traffic air pollution is a ubiquitous source of air pollution in developed nations, and is associated with multiple cardiovascular outcomes such as: coronary atherosclerosis, peripheral arterial disease, and myocardial infarction. Despite the recognition of the importance of both genetic and environmental exposures to the pathogenesis of cardiovascular disease, studies of these two contributors jointly are rare. We performed a genome-wide interaction study (GWIS) to examine gene-traffic exposure interactions associated with coronary atherosclerosis. Using race-stratified cohorts of 554 African-Americans (AA) and 1623 European-Americans (EA) from a cardiac catheterization cohort (CATHGEN), we identify gene-by-traffic exposure interactions associated with the number of significantly diseased coronary vessels as a measure of chronic atherosclerosis. We found five suggestive (P<1x10-5) interactions in the AA GWIS, of which two (rs1856746 and rs2791713) replicated in the EA cohort (P < 0.05). Both SNPs are in the PIGR-FCAMR locus and are eQTLs in lymphocytes. The protein products of both PIGR and FCAMR are implicated in inflammatory processes. In the EA GWIS, there were three suggestive interactions; none of these replicated in the AA GWIS. All three were intergenic; the most significant interaction was in a regulatory region associated with SAMSN1, a gene previously associate

diffHic: a Bioconductor package to detect differential genomic interactions in Hi-C data.

PubMed

Lun, Aaron T L; Smyth, Gordon K

2015-08-19

Chromatin conformation capture with high-throughput sequencing (Hi-C) is a technique that measures the in vivo intensity of interactions between all pairs of loci in the genome. Most conventional analyses of Hi-C data focus on the detection of statistically significant interactions. However, an alternative strategy involves identifying significant changes in the interaction intensity (i.e., differential interactions) between two or more biological conditions. This is more statistically rigorous and may provide more biologically relevant results. Here, we present the diffHic software package for the detection of differential interactions from Hi-C data. diffHic provides methods for read pair alignment and processing, counting into bin pairs, filtering out low-abundance events and normalization of trended or CNV-driven biases. It uses the statistical framework of the edgeR package to model biological variability and to test for significant differences between conditions. Several options for the visualization of results are also included. The use of diffHic is demonstrated with real Hi-C data sets. Performance against existing methods is also evaluated with simulated data. On real data, diffHic is able to successfully detect interactions with significant differences in intensity between biological conditions. It also compares favourably to existing software tools on simulated data sets. These results suggest that diffHic is a viable approach for differential analyses of Hi-C data.

Factors associated with social interaction anxiety among Chinese adolescents.

PubMed

Peng, Z W; Lam, L T; Jin, J

2011-12-01

To investigate potential risk factors for social anxiety, particularly social interaction anxiety among the Chinese adolescents. A cross-sectional health survey was conducted in Guangzhou city of the Guangdong Province where high school students aged 13 to 18 years were recruited. The sample was selected from all high schools in the city using a 2-stage random cluster sampling technique. Social interaction anxiety was assessed using the Social Interaction Anxiety Scale. Information collected in the survey included: demographics, self-perception on school performance, relationship with teachers and peers, satisfaction with self-image, achievements, and parenting style of the mother. The parent-child relationship, specifically the relationship between respondents and their mothers, was assessed using the mother attachment subscale of the Inventory of Parent and Peer Attachment. Self-esteem was assessed using the Rosenberg Self-Esteem Scale. The multiple linear regression technique was applied to investigate associations between selected potential risk factors and social interaction anxiety, with adjustments for cluster sampling. Lower family income, lower self-esteem, and hostility were significantly associated with social interaction anxiety among adolescents. Variables identified as risk factors of anxiety disorder in the literature, such as gender, were not associated with social interaction anxiety in this sample. These results were consistent with those of other studies conducted mainly in the United States and Europe. Regarding non-significant results related to gender, they need viewing in the context of parenting styles of Chinese mothers.

Rheumatoid arthritis significantly increased recurrence risk after ischemic stroke/transient ischemic attack.

PubMed

Chen, Yih-Ru; Hsieh, Fang-I; Lien, Li-Ming; Hu, Chaur-Jong; Jeng, Jiann-Shing; Peng, Giia-Sheun; Tang, Sung-Chun; Chi, Nai-Fang; Sung, Yueh-Feng; Chiou, Hung-Yi

2018-06-02

The effect of RA on recurrent stroke is unknown. Therefore, we examined effects of rheumatoid arthritis (RA) on risk of stroke recurrence and investigated the interaction between RA and traditional cardiovascular risk factors on recurrence risk after ischemic stroke (IS) or transient ischemic attack (TIA). Of 3190 patients with IS or TIA recruited in this cohort study, 638 were comorbid with RA and 2552 without RA. Stroke recurrence, RA, lifestyle, lipid variables and other comorbidities were identified through linkage between a nationwide stroke database in Taiwan and the National Health Insurance claims database. Cox proportional hazard models with competing risk adjustment were used to evaluate the relationship between RA and recurrent stroke. Patients with RA showed a significantly increased risk of recurrent stroke, particular in recurrent IS/TIA. The increased risk of recurrent IS/TIA in RA patients may through the changes of triglycerides (TG)/high-density lipoprotein cholesterol (HDL-C) ratio. A positive additive interaction was observed between RA and current smoking on the risk of recurrent IS/TIA. Significantly increased risks for recurrent IS/TIA were observed among RA patients who smoked > 40 years or those who smoked > 20 cigarettes/day. This study provides the first evidence that RA significantly increased recurrence IS/TIA risk. The changes of TG/HDL-C ratio may play some roles in the recurrence IS/TIA risk in RA patients. In addition, our results suggest that smoking increases the risk of recurrent IS/TIA in RA patients and reinforces the need for aggressive smoking cessation efforts in RA patients.

Comparative analysis of Leishmania exoproteomes: implication for host-pathogen interactions.

PubMed

Peysselon, Franck; Launay, Guillaume; Lisacek, Frédérique; Duclos, Bertrand; Ricard-Blum, Sylvie

2013-12-01

Leishmaniasis is a vector-borne disease caused by the protozoa Leishmania. We have analyzed and compared the sequences of three experimental exoproteomes of Leishmania promastigotes from different species to determine their specific features and to identify new candidate proteins involved in interactions of Leishmania with the host. The exoproteomes differ from the proteomes by a decrease in the average molecular weight per protein, in disordered amino acid residues and in basic proteins. The exoproteome of the visceral species is significantly enriched in sites predicted to be phosphorylated as well as in features frequently associated with molecular interactions (intrinsic disorder, number of disordered binding regions per protein, interaction and/or trafficking motifs) compared to the other species. The visceral species might thus have a larger interaction repertoire with the host than the other species. Less than 10% of the exoproteomes contain heparin-binding and RGD sequences, and ~30% the host targeting signal RXLXE/D/Q. These latter proteins might thus be exported inside the host cell during the intracellular stage of the infection. Furthermore we have identified nine protein families conserved in the three exoproteomes with specific combinations of Pfam domains and selected eleven proteins containing at least three interaction and/or trafficking motifs including two splicing factors, phosphomannomutase, 2,3-bisphosphoglycerate-independent phosphoglycerate mutase, the paraflagellar rod protein-1D and a putative helicase. Their role in host-Leishmania interactions warrants further investigation but the putative ATP-dependent DEAD/H RNA helicase, which contains numerous interaction motifs, a host targeting signal and two disordered regions, is a very promising candidate. © 2013.

Identifying autism from neural representations of social interactions: neurocognitive markers of autism.

PubMed

Just, Marcel Adam; Cherkassky, Vladimir L; Buchweitz, Augusto; Keller, Timothy A; Mitchell, Tom M

2014-01-01

Autism is a psychiatric/neurological condition in which alterations in social interaction (among other symptoms) are diagnosed by behavioral psychiatric methods. The main goal of this study was to determine how the neural representations and meanings of social concepts (such as to insult) are altered in autism. A second goal was to determine whether these alterations can serve as neurocognitive markers of autism. The approach is based on previous advances in fMRI analysis methods that permit (a) the identification of a concept, such as the thought of a physical object, from its fMRI pattern, and (b) the ability to assess the semantic content of a concept from its fMRI pattern. These factor analysis and machine learning methods were applied to the fMRI activation patterns of 17 adults with high-functioning autism and matched controls, scanned while thinking about 16 social interactions. One prominent neural representation factor that emerged (manifested mainly in posterior midline regions) was related to self-representation, but this factor was present only for the control participants, and was near-absent in the autism group. Moreover, machine learning algorithms classified individuals as autistic or control with 97% accuracy from their fMRI neurocognitive markers. The findings suggest that psychiatric alterations of thought can begin to be biologically understood by assessing the form and content of the altered thought's underlying brain activation patterns.

Identifying Autism from Neural Representations of Social Interactions: Neurocognitive Markers of Autism

PubMed Central

Just, Marcel Adam; Cherkassky, Vladimir L.; Buchweitz, Augusto; Keller, Timothy A.; Mitchell, Tom M.

2014-01-01

Autism is a psychiatric/neurological condition in which alterations in social interaction (among other symptoms) are diagnosed by behavioral psychiatric methods. The main goal of this study was to determine how the neural representations and meanings of social concepts (such as to insult) are altered in autism. A second goal was to determine whether these alterations can serve as neurocognitive markers of autism. The approach is based on previous advances in fMRI analysis methods that permit (a) the identification of a concept, such as the thought of a physical object, from its fMRI pattern, and (b) the ability to assess the semantic content of a concept from its fMRI pattern. These factor analysis and machine learning methods were applied to the fMRI activation patterns of 17 adults with high-functioning autism and matched controls, scanned while thinking about 16 social interactions. One prominent neural representation factor that emerged (manifested mainly in posterior midline regions) was related to self-representation, but this factor was present only for the control participants, and was near-absent in the autism group. Moreover, machine learning algorithms classified individuals as autistic or control with 97% accuracy from their fMRI neurocognitive markers. The findings suggest that psychiatric alterations of thought can begin to be biologically understood by assessing the form and content of the altered thought’s underlying brain activation patterns. PMID:25461818

Genome-wide Mapping of Cellular Protein–RNA Interactions Enabled by Chemical Crosslinking

PubMed Central

Li, Xiaoyu; Song, Jinghui; Yi, Chengqi

2014-01-01

RNA–protein interactions influence many biological processes. Identifying the binding sites of RNA-binding proteins (RBPs) remains one of the most fundamental and important challenges to the studies of such interactions. Capturing RNA and RBPs via chemical crosslinking allows stringent purification procedures that significantly remove the non-specific RNA and protein interactions. Two major types of chemical crosslinking strategies have been developed to date, i.e., UV-enabled crosslinking and enzymatic mechanism-based covalent capture. In this review, we compare such strategies and their current applications, with an emphasis on the technologies themselves rather than the biology that has been revealed. We hope such methods could benefit broader audience and also urge for the development of new methods to study RNA−RBP interactions. PMID:24747191

Assessment of healthcare professionals' knowledge about warfarin-vitamin K drug-nutrient interactions.

PubMed

Couris, R R; Tataronis, G R; Dallal, G E; Blumberg, J B; Dwyer, J T

2000-08-01

Dietary vitamin K can interact with oral anticoagulant drugs and interfere with their therapeutic safety and efficacy. Therefore, knowledge about drug-nutrient interactions involving vitamin K possessed by physicians, pharmacists, dietitians and nurses practicing anticoagulant therapy was assessed. Healthcare practitioners were surveyed using a 30-question, 98-item questionnaire on the most common and/or important food interactions with warfarin, drug interactions with warfarin and general drug-nutrient interactions involving vitamin K. The study sample included 160 randomly selected healthcare providers (40 physicians, pharmacists, dietitians and nurses) from 10 hospitals with 200 to 1000 beds from six Massachusetts regions. Random selection was conducted from a pool of selected healthcare providers practicing anticoagulant therapy who counsel patients receiving warfarin. All surveys were completed within three months of the start of the study, and all participants provided usable data for statistical analysis. The mean scores (+/- SD) on the overall test were 72.5+/-9.0 for pharmacists, 62.51+/-10.6 for physicians, 56.9+/-8.8 for dietitians and 50.2+/-9.3 for nurses, with 100 being a perfect score. Pharmacists scored significantly higher in the area of drug interactions (75.9+/-11.3, p<0.05). Dietitians scored higher in the area of food interactions (73.0+/-10.3). No significant differences between physicians and pharmacists were evident on general drug-nutrient interactions. While over 87% of the healthcare professionals correctly identified some common foods containing large amounts of vitamin K, such as broccoli and spinach, fewer than 25% were able to identify others such as pea soup, coleslaw and dill pickles. Although the healthcare professionals surveyed in this study appear to have demonstrated some proficiency in their respective areas of expertise, they exhibited less knowledge in others. Therefore, additional training and integration of knowledge and

Proteins interacting with cloning scars: a source of false positive protein-protein interactions.

PubMed

Banks, Charles A S; Boanca, Gina; Lee, Zachary T; Florens, Laurence; Washburn, Michael P

2015-02-23

A common approach for exploring the interactome, the network of protein-protein interactions in cells, uses a commercially available ORF library to express affinity tagged bait proteins; these can be expressed in cells and endogenous cellular proteins that copurify with the bait can be identified as putative interacting proteins using mass spectrometry. Control experiments can be used to limit false-positive results, but in many cases, there are still a surprising number of prey proteins that appear to copurify specifically with the bait. Here, we have identified one source of false-positive interactions in such studies. We have found that a combination of: 1) the variable sequence of the C-terminus of the bait with 2) a C-terminal valine "cloning scar" present in a commercially available ORF library, can in some cases create a peptide motif that results in the aberrant co-purification of endogenous cellular proteins. Control experiments may not identify false positives resulting from such artificial motifs, as aberrant binding depends on sequences that vary from one bait to another. It is possible that such cryptic protein binding might occur in other systems using affinity tagged proteins; this study highlights the importance of conducting careful follow-up studies where novel protein-protein interactions are suspected.

Proteins interacting with cloning scars: a source of false positive protein-protein interactions

PubMed Central

Banks, Charles A. S.; Boanca, Gina; Lee, Zachary T.; Florens, Laurence; Washburn, Michael P.

2015-01-01

A common approach for exploring the interactome, the network of protein-protein interactions in cells, uses a commercially available ORF library to express affinity tagged bait proteins; these can be expressed in cells and endogenous cellular proteins that copurify with the bait can be identified as putative interacting proteins using mass spectrometry. Control experiments can be used to limit false-positive results, but in many cases, there are still a surprising number of prey proteins that appear to copurify specifically with the bait. Here, we have identified one source of false-positive interactions in such studies. We have found that a combination of: 1) the variable sequence of the C-terminus of the bait with 2) a C-terminal valine “cloning scar” present in a commercially available ORF library, can in some cases create a peptide motif that results in the aberrant co-purification of endogenous cellular proteins. Control experiments may not identify false positives resulting from such artificial motifs, as aberrant binding depends on sequences that vary from one bait to another. It is possible that such cryptic protein binding might occur in other systems using affinity tagged proteins; this study highlights the importance of conducting careful follow-up studies where novel protein-protein interactions are suspected. PMID:25704442

Identifying Nodes of Transmission in Disease Diffusion Through Social Media

NASA Astrophysics Data System (ADS)

Lamb, David Sebastian

The spread of infectious diseases can be described in terms of three interrelated components: interaction, movement, and scale. Transmission between individuals requires some form of interaction, which is dependent on the pathogen, to occur. Diseases spread through the movement of their hosts; they spread across many spatial scales from local neighborhoods to countries, or temporal scales from days to years, or periodic intervals. Prior research into the spread of disease have examined diffusion processes retrospectively at regional or country levels, or developed differential equation or simulation models of the dynamics of disease transmission. While some of the more recent models incorporate all three components, they are limited in the way they understand where interactions occur. The focus has been on home or work, including contact with family or coworkers. The models reflect a lack of knowledge about how transmissions are made at specific locations in time, so-called nodes of transmission. That is, how individuals' intersections in time and space function in disease transmission. This project sought to use the three factors of interaction, movement, and scale to better understand the spread of disease in terms of the place of interaction called the node of transmission. The overarching objective of this research was: how can nodes of transmission be identified through individual activity spaces incorporating the three factors of infectious disease spread: interaction, movement, and scale?. This objective fed into three main sub-objectives: defining nodes of transmission, developing an appropriate methodology to identifying nodes of transmission, and applying it using geotagged social media data from Twitter. To develop an appropriate framework, this research relied on time geography, and traditional disease. This particularly relied on the idea of bundling to create the nodes, and a nesting effect that integrated scale. The data source used to identify nodes

CONCEPTUAL APPROACHES TO IDENTIFY AND ASSESS MULTPLE STRESSORS, SECTION 1.1

EPA Science Inventory

Every ecosystem is subject to multiple stressors arising from the interactions of biological, physical, and socioeconomic processes (e.g. exploitation and development). These stressors and their interactions need to be identified if risks associated with a planned activity are to...

Designing learning environments to teach interactive Quantum Physics

NASA Astrophysics Data System (ADS)

Gómez Puente, Sonia M.; Swagten, Henk J. M.

2012-10-01

This study aims at describing and analysing systematically an interactive learning environment designed to teach Quantum Physics, a second-year physics course. The instructional design of Quantum Physics is a combination of interactive lectures (using audience response systems), tutorials and self-study in unit blocks, carried out with small groups. Individual formative feedback was introduced as a rapid assessment tool to provide an overview on progress and identify gaps by means of questioning students at three levels: conceptual; prior knowledge; homework exercises. The setup of Quantum Physics has been developed as a result of several loops of adjustments and improvements from a traditional-like type of teaching to an interactive classroom. Results of this particular instructional arrangement indicate significant gains in students' achievements in comparison with the traditional structure of this course, after recent optimisation steps such as the implementation of an individual feedback system.

Identifying intrinsically disordered protein regions likely to undergo binding-induced helical transitions.

PubMed

Glover, Karen; Mei, Yang; Sinha, Sangita C

2016-10-01

Many proteins contain intrinsically disordered regions (IDRs) lacking stable secondary and ordered tertiary structure. IDRs are often implicated in macromolecular interactions, and may undergo structural transitions upon binding to interaction partners. However, as binding partners of many protein IDRs are unknown, these structural transitions are difficult to verify and often are poorly understood. In this study we describe a method to identify IDRs that are likely to undergo helical transitions upon binding. This method combines bioinformatics analyses followed by circular dichroism spectroscopy to monitor 2,2,2-trifluoroethanol (TFE)-induced changes in secondary structure content of these IDRs. Our results demonstrate that there is no significant change in the helicity of IDRs that are not predicted to fold upon binding. IDRs that are predicted to fold fall into two groups: one group does not become helical in the presence of TFE and includes examples of IDRs that form β-strands upon binding, while the other group becomes more helical and includes examples that are known to fold into helices upon binding. Therefore, we propose that bioinformatics analyses combined with experimental evaluation using TFE may provide a general method to identify IDRs that undergo binding-induced disorder-to-helix transitions. Copyright © 2016 Elsevier B.V. All rights reserved.

Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis.

PubMed

Holland, David O; Johnson, Margaret E

2018-03-01

Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that 'leftover' proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module

Faculty Professional Development Focused on Identifying Funding Opportunities: An Interactive Tool

ERIC Educational Resources Information Center

Moore, Alison L.; Reiser, Robert A.; Bradley, Terra W.; Zhao, Weinan

2016-01-01

In an effort to help faculty members learn about and obtain external funding for their research, a team of scholar-practitioners within a College of Education at a large southeastern university developed a database tool that enables faculty to identify grant opportunities aligned with their research interests and provides faculty with easy access…

Identifying key genes associated with acute myocardial infarction.

PubMed

Cheng, Ming; An, Shoukuan; Li, Junquan

2017-10-01

This study aimed to identify key genes associated with acute myocardial infarction (AMI) by reanalyzing microarray data. Three gene expression profile datasets GSE66360, GSE34198, and GSE48060 were downloaded from GEO database. After data preprocessing, genes without heterogeneity across different platforms were subjected to differential expression analysis between the AMI group and the control group using metaDE package. P < .05 was used as the cutoff for a differentially expressed gene (DEG). The expression data matrices of DEGs were imported in ReactomeFIViz to construct a gene functional interaction (FI) network. Then, DEGs in each module were subjected to pathway enrichment analysis using DAVID. MiRNAs and transcription factors predicted to regulate target DEGs were identified. Quantitative real-time polymerase chain reaction (RT-PCR) was applied to verify the expression of genes. A total of 913 upregulated genes and 1060 downregulated genes were identified in the AMI group. A FI network consists of 21 modules and DEGs in 12 modules were significantly enriched in pathways. The transcription factor-miRNA-gene network contains 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p. RT-PCR validations showed that expression levels of FOXO3 and MYBL2 were significantly increased in AMI, and expression levels of hsa-miR-21-5p and hsa-miR-30c-5p were obviously decreased in AMI. A total of 41 DEGs, such as SOCS3, VAPA, and COL5A2, are speculated to have roles in the pathogenesis of AMI; 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p may be involved in the regulation of the expression of these DEGs.

Prevalence of Potential and Clinically Relevant Statin-Drug Interactions in Frail and Robust Older Inpatients.

PubMed

Thai, Michele; Hilmer, Sarah; Pearson, Sallie-Anne; Reeve, Emily; Gnjidic, Danijela

2015-10-01

A significant proportion of older people are prescribed statins and are also exposed to polypharmacy, placing them at increased risk of statin-drug interactions. To describe the prevalence rates of potential and clinically relevant statin-drug interactions in older inpatients according to frailty status. A cross-sectional study of patients aged ≥65 years who were prescribed a statin and were admitted to a teaching hospital between 30 July and 10 October 2014 in Sydney, Australia, was conducted. Data on socio-demographics, comorbidities and medications were collected using a standardized questionnaire. Potential statin-drug interactions were defined if listed in the Australian Medicines Handbook and three international drug information sources: the British National Formulary, Drug Interaction Facts and Drug-Reax(®). Clinically relevant statin-drug interactions were defined as interactions with the highest severity rating in at least two of the three international drug information sources. Frailty was assessed using the Reported Edmonton Frail Scale. A total of 180 participants were recruited (median age 78 years, interquartile range 14), 35.0% frail and 65.0% robust. Potential statin-drug interactions were identified in 10% of participants, 12.7% of frail participants and 8.5% of robust participants. Clinically relevant statin-drug interactions were identified in 7.8% of participants, 9.5% of frail participants and 6.8% of robust participants. Depending on the drug information source used, the prevalence rates of potential and clinically relevant statin-drug interactions ranged between 14.4 and 35.6% and between 14.4 and 20.6%, respectively. In our study of frail and robust older inpatients taking statins, the overall prevalence of potential statin-drug interactions was low and varied significantly according to the drug information source used.

The connectomes of males and females with autism spectrum disorder have significantly different white matter connectivity densities

PubMed Central

Irimia, Andrei; Torgerson, Carinna M.; Jacokes, Zachary J.; Van Horn, John D.

2017-01-01

Autism spectrum disorder (ASD) encompasses a set of neurodevelopmental conditions whose striking sex-related disparity (with an estimated male-to-female ratio of 4:1) remains unknown. Here we use magnetic resonance imaging (MRI) and diffusion weighted imaging (DWI) to identify the brain structure correlates of the sex-by-ASD diagnosis interaction in a carefully selected cohort of 110 ASD patients (55 females) and 83 typically-developing (TD) subjects (40 females). The interaction was found to be predicated primarily upon white matter connectivity density innervating, bilaterally, the lateral aspect of the temporal lobe, the temporo-parieto-occipital junction and the medial parietal lobe. By contrast, regional gray matter (GM) thickness and volume are not found to modulate this interaction significantly. When interpreted in the context of previous studies, our findings add considerable weight to three long-standing hypotheses according to which the sex disparity of ASD incidence is (A) due to WM connectivity rather than to GM differences, (B) modulated to a large extent by temporoparietal connectivity, and (C) accompanied by brain function differences driven by these effects. Our results contribute substantially to the task of unraveling the biological mechanisms giving rise to the sex disparity in ASD incidence, whose clinical implications are significant. PMID:28397802

Recent Empirical Studies of the Pedagogical Effects of Interactive Video Instruction in "Soft Skill" Areas.

ERIC Educational Resources Information Center

Cronin, Michael W.; Cronin, Karen A.

1992-01-01

Recent empirical research has identified significant advantages for interactive video instruction over traditional teaching methods in "soft skill" (humanities and social sciences) areas, including cognitive achievement, transfer of learning to performance, learning motivation, student achievement across uncontrolled student characteristics, user…

Hemiclonal analysis of interacting phenotypes in male and female Drosophila melanogaster

PubMed Central

2014-01-01

Background Identifying the sources of variation in mating interactions between males and females is important because this variation influences the strength and/or the direction of sexual selection that populations experience. While the origins and effects of variation in male attractiveness and ornamentation have received much scrutiny, the causes and consequences of intraspecific variation in females have been relatively overlooked. We used cytogenetic cloning techniques developed for Drosophila melanogaster to create “hemiclonal” males and females with whom we directly observed sexual interaction between individuals of different known genetic backgrounds and measured subsequent reproductive outcomes. Using this approach, we were able to quantify the genetic contribution of each mate to the observed phenotypic variation in biologically important traits including mating speed, copulation duration, and subsequent offspring production, as well as measure the magnitude and direction of intersexual genetic correlation between female choosiness and male attractiveness. Results We found significant additive genetic variation contributing to mating speed that can be attributed to male genetic identity, female genetic identity, but not their interaction. Furthermore we found that phenotypic variation in copulation duration had a significant male-associated genetic component. Female genetic identity and the interaction between male and female genetic identity accounted for a substantial amount of the observed phenotypic variation in egg size. Although previous research predicts a trade-off between egg size and fecundity, this was not evident in our results. We found a strong negative genetic correlation between female choosiness and male attractiveness, a result that suggests a potentially important role for sexually antagonistic alleles in sexual selection processes in our population. Conclusion These results further our understanding of sexual selection because they

Multifactor-Dimensionality Reduction Reveals High-Order Interactions among Estrogen-Metabolism Genes in Sporadic Breast Cancer

PubMed Central

Ritchie, Marylyn D.; Hahn, Lance W.; Roodi, Nady; Bailey, L. Renee; Dupont, William D.; Parl, Fritz F.; Moore, Jason H.

2001-01-01

One of the greatest challenges facing human geneticists is the identification and characterization of susceptibility genes for common complex multifactorial human diseases. This challenge is partly due to the limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes and with environmental exposures. We introduce multifactor-dimensionality reduction (MDR) as a method for reducing the dimensionality of multilocus information, to improve the identification of polymorphism combinations associated with disease risk. The MDR method is nonparametric (i.e., no hypothesis about the value of a statistical parameter is made), is model-free (i.e., it assumes no particular inheritance model), and is directly applicable to case-control and discordant-sib-pair studies. Using simulated case-control data, we demonstrate that MDR has reasonable power to identify interactions among two or more loci in relatively small samples. When it was applied to a sporadic breast cancer case-control data set, in the absence of any statistically significant independent main effects, MDR identified a statistically significant high-order interaction among four polymorphisms from three different estrogen-metabolism genes. To our knowledge, this is the first report of a four-locus interaction associated with a common complex multifactorial disease. PMID:11404819

Molecular Ecological Insights into Neotropical Bird–Tick Interactions

PubMed Central

Esser, Helen J.; Loaiza, Jose R.; Herre, Edward Allen; Aguilar, Celestino; Quintero, Diomedes; Alvarez, Eric; Bermingham, Eldredge

2016-01-01

In the tropics, ticks parasitize many classes of vertebrate hosts. However, because many tropical tick species are only identifiable in the adult stage, and these adults usually parasitize mammals, most attention on the ecology of tick-host interactions has focused on mammalian hosts. In contrast, immature Neotropical ticks are often found on wild birds, yet difficulties in identifying immatures hinder studies of birds’ role in tropical tick ecology and tick-borne disease transmission. In Panama, we found immature ticks on 227 out of 3,498 individually–sampled birds representing 93 host species (24% of the bird species sampled, and 13% of the Panamanian land bird fauna). Tick parasitism rates did not vary with rainfall or temperature, but did vary significantly with several host ecological traits. Likewise, Neotropical–Nearctic migratory birds were significantly less likely to be infested than resident species. Using a molecular library developed from morphologically–identified adult ticks specifically for this study, we identified eleven tick species parasitizing birds, indicating that a substantial portion of the Panamanian avian species pool is parasitized by a diversity of tick species. Tick species that most commonly parasitized birds had the widest diversity of avian hosts, suggesting that immature tick species are opportunistic bird parasites. Although certain avian ecological traits are positively associated with parasitism, we found no evidence that individual tick species show specificity to particular avian host ecological traits. Finally, our data suggest that the four principal vectors of Rocky Mountain Spotted Fever in the Neotropics rarely, if ever, parasitize Panamanian birds. However, other tick species that harbor newly–discovered rickettsial parasites of unknown pathogenicity are frequently found on these birds. Given our discovery of broad interaction between Panamanian tick and avian biodiversity, future work on tick ecology and the

Can Australians identify snakes?

PubMed

Morrison, J J; Pearn, J H; Covacevich, J; Nixon, J

1983-07-23

A study of the ability of Australians to identify snakes was undertaken, in which 558 volunteers (primary and secondary schoolchildren, doctors and university science and medical students) took part. Over all, subjects correctly identified an average of 19% of snakes; 28% of subjects could identify a taipan, 59% could identify a death adder, 18% a tiger snake, 23% an eastern (or common) brown snake, and 0.5% a rough-scaled snake. Eighty-six per cent of subjects who grew up in rural areas could identify a death adder; only 4% of those who grew up in an Australian capital city could identify a nonvenomous python. Male subjects identified snakes more accurately than did female subjects. Doctors and medical students correctly identified an average of 25% of snakes. The ability to identify medically significant Australian snakes was classified according to the observer's background, education, sex, and according to the individual snake species. Australians need to be better educated about snakes indigenous to this country.

iLOCi: a SNP interaction prioritization technique for detecting epistasis in genome-wide association studies

PubMed Central

2012-01-01

Background Genome-wide association studies (GWAS) do not provide a full account of the heritability of genetic diseases since gene-gene interactions, also known as epistasis are not considered in single locus GWAS. To address this problem, a considerable number of methods have been developed for identifying disease-associated gene-gene interactions. However, these methods typically fail to identify interacting markers explaining more of the disease heritability over single locus GWAS, since many of the interactions significant for disease are obscured by uninformative marker interactions e.g., linkage disequilibrium (LD). Results In this study, we present a novel SNP interaction prioritization algorithm, named iLOCi (Interacting Loci). This algorithm accounts for marker dependencies separately in case and control groups. Disease-associated interactions are then prioritized according to a novel ranking score calculated from the difference in marker dependencies for every possible pair between case and control groups. The analysis of a typical GWAS dataset can be completed in less than a day on a standard workstation with parallel processing capability. The proposed framework was validated using simulated data and applied to real GWAS datasets using the Wellcome Trust Case Control Consortium (WTCCC) data. The results from simulated data showed the ability of iLOCi to identify various types of gene-gene interactions, especially for high-order interaction. From the WTCCC data, we found that among the top ranked interacting SNP pairs, several mapped to genes previously known to be associated with disease, and interestingly, other previously unreported genes with biologically related roles. Conclusion iLOCi is a powerful tool for uncovering true disease interacting markers and thus can provide a more complete understanding of the genetic basis underlying complex disease. The program is available for download at http://www4a.biotec.or.th/GI/tools/iloci. PMID:23281813

Using a Drug Interaction Program (Drug Interactions Advisor™) in a Community Hospital

PubMed Central

Harvey, A. C.; Diehl, G. R.; Finlayson, W. B.

1987-01-01

To test the usefulness of a drugs-interaction program in a community hospital one hundred patients in three medical wards were surveyed with respect to their drug regime. The drugs listed for each patient were entered into Drug Interactions Advisor™ a commercial interactions program running on an Apple IIE. Interacting drugs were listed with the severity of the interaction in each case. Of one hundred patients fifty-one had drugs which could potentially interact and in fifty-one percent of cases a change in therapy would have been advised by Drug Interactions Advisor™. The completeness of the data base was assessed as to its inclusion of drugs actually given and it dealt with eighty-nine percent. The program was tested against ten known interactions and it identified six. Multiple drug therapy is a major problem nowadays and will increase with the aging of the population. Drug interactions programs exploit computer technology to make drug surveillance easier. Without computers such surveillance is difficult if not impossible.

Significant Centers of Tectonic Activity as Identified by Wrinkle Ridges for the Western Hemisphere of Mars

NASA Technical Reports Server (NTRS)

Anderson, R.C.; Haldemann, A. F. C.; Golombek, M. P.; Franklin, B. J.; Dohm, J. M.; Lias, J.

2000-01-01

The western hemisphere region of Mars has been the site of numerous scientific investigations regarding its tectonic evolution. For this region of Mars, the dominant tectonic region is the Tharsis province. Tharsis is characterized by an enormous system of radiating grabens and a circumferential system of wrinkle ridges. Past investigations of grabens associated with Tharsis have identified specific centers of tectonic activity. A recent structural analysis of the western hemisphere region of Mars which includes the Tharsis region, utilized 25,000 structures to determine the history of local and regional centers of tectonic activity based primarily on the spatial and temporal relationships of extensional features. This investigation revealed that Tharsis is more structurally complex (heterogeneous) than has been previously identified: it consists of numerous regional and local centers of tectonic activity (some are more dominant and/or more long lived than others). Here we use the same approach as Anderson et al. to determine whether the centers of tectonic activity that formed the extensional features also contributed to wrinkle ridge (compressional) formation.

Pre-Clinical Drug Prioritization via Prognosis-Guided Genetic Interaction Networks

PubMed Central

Xiong, Jianghui; Liu, Juan; Rayner, Simon; Tian, Ze; Li, Yinghui; Chen, Shanguang

2010-01-01

The high rates of failure in oncology drug clinical trials highlight the problems of using pre-clinical data to predict the clinical effects of drugs. Patient population heterogeneity and unpredictable physiology complicate pre-clinical cancer modeling efforts. We hypothesize that gene networks associated with cancer outcome in heterogeneous patient populations could serve as a reference for identifying drug effects. Here we propose a novel in vivo genetic interaction which we call ‘synergistic outcome determination’ (SOD), a concept similar to ‘Synthetic Lethality’. SOD is defined as the synergy of a gene pair with respect to cancer patients' outcome, whose correlation with outcome is due to cooperative, rather than independent, contributions of genes. The method combines microarray gene expression data with cancer prognostic information to identify synergistic gene-gene interactions that are then used to construct interaction networks based on gene modules (a group of genes which share similar function). In this way, we identified a cluster of important epigenetically regulated gene modules. By projecting drug sensitivity-associated genes on to the cancer-specific inter-module network, we defined a perturbation index for each drug based upon its characteristic perturbation pattern on the inter-module network. Finally, by calculating this index for compounds in the NCI Standard Agent Database, we significantly discriminated successful drugs from a broad set of test compounds, and further revealed the mechanisms of drug combinations. Thus, prognosis-guided synergistic gene-gene interaction networks could serve as an efficient in silico tool for pre-clinical drug prioritization and rational design of combinatorial therapies. PMID:21085674

Assessment of Gene-by-Sex Interaction Effect on Bone Mineral Density

PubMed Central

Liu, Ching-Ti; Estrada, Karol; Yerges-Armstrong, Laura M.; Amin, Najaf; Evangelou, Evangelos; Li, Guo; Minster, Ryan L.; Carless, Melanie A.; Kammerer, Candace M.; Oei, Ling; Zhou, Yanhua; Alonso, Nerea; Dailiana, Zoe; Eriksson, Joel; García-Giralt, Natalia; Giroux, Sylvie; Husted, Lise Bjerre; Khusainova, Rita I.; Koromila, Theodora; Kung, Annie WaiChee; Lewis, Joshua R.; Masi, Laura; Mencej-Bedrac, Simona; Nogues, Xavier; Patel, Millan S.; Prezelj, Janez; Richards, J Brent; Sham, Pak Chung; Spector, Timothy; Vandenput, Liesbeth; Xiao, Su-Mei; Zheng, Hou-Feng; Zhu, Kun; Balcells, Susana; Brandi, Maria Luisa; Frost, Morten; Goltzman, David; González-Macías, Jesús; Karlsson, Magnus; Khusnutdinova, Elza K.; Kollia, Panagoula; Langdahl, Bente Lomholt; Ljunggren, Östen; Lorentzon, Mattias; Marc, Janja; Mellström, Dan; Ohlsson, Claes; Olmos, José M.; Ralston, Stuart H.; Riancho, José A.; Rousseau, François; Urreizti, Roser; Van Hul, Wim; Zarrabeitia, María T.; Castano-Betancourt, Martha; Demissie, Serkalem; Grundberg, Elin; Herrera, Lizbeth; Kwan, Tony; Medina-Gómez, Carolina; Pastinen, Tomi; Sigurdsson, Gunnar; Thorleifsson, Gudmar; vanMeurs, Joyce B.J.; Blangero, John; Hofman, Albert; Liu, Yongmei; Mitchell, Braxton D.; O’Connell, Jeffrey R.; Oostra, Ben A.; Rotter, Jerome I; Stefansson, Kari; Streeten, Elizabeth A.; Styrkarsdottir, Unnur; Thorsteinsdottir, Unnur; Tylavsky, Frances A.; Uitterlinden, Andre; Cauley, Jane A.; Harris, Tamara B.; Ioannidis, John P.A.; Psaty, Bruce M.; Robbins, John A; Zillikens, M. Carola; vanDuijn, Cornelia M.; Prince, Richard L.; Karasik, David; Rivadeneira, Fernando; Kiel, Douglas P.; Cupples, L. Adrienne; Hsu, Yi-Hsiang

2012-01-01

Background Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and performed eQTL analysis and bioinformatics network analysis. Methods We conducted an autosomal genome-wide meta-analysis of gene-by-sex interaction on lumbar spine (LS-) and femoral neck (FN-) BMD, in 25,353 individuals from eight cohorts. In a second stage, we followed up the 12 top SNPs (P<1×10−5) in an additional set of 24,763 individuals. Gene-by-sex interaction and sex-specific effects were examined in these 12 SNPs. Results We detected one novel genome-wide significant interaction associated with LS-BMD at the Chr3p26.1-p25.1 locus, near the GRM7 gene (male effect = 0.02 & p-value = 3.0×10−5; female effect = −0.007 & p-value=3.3×10−2) and eleven suggestive loci associated with either FN- or LS-BMD in discovery cohorts. However, there was no evidence for genome-wide significant (P<5×10−8) gene-by-sex interaction in the joint analysis of discovery and replication cohorts. Conclusion Despite the large collaborative effort, no genome-wide significant evidence for gene-by-sex interaction was found influencing BMD variation in this screen of autosomal markers. If they exist, gene-by-sex interactions for BMD probably have weak effects, accounting for less than 0.08% of the variation in these traits per implicated SNP. PMID:22692763

Genome-wide association study meta-analysis identifies five new loci for systemic lupus erythematosus.

PubMed

Julià, Antonio; López-Longo, Francisco Javier; Pérez Venegas, José J; Bonàs-Guarch, Silvia; Olivé, Àlex; Andreu, José Luís; Aguirre-Zamorano, Mª Ángeles; Vela, Paloma; Nolla, Joan M; de la Fuente, José Luís Marenco; Zea, Antonio; Pego-Reigosa, José María; Freire, Mercedes; Díez, Elvira; Rodríguez-Almaraz, Esther; Carreira, Patricia; Blanco, Ricardo; Taboada, Víctor Martínez; López-Lasanta, María; Corbeto, Mireia López; Mercader, Josep M; Torrents, David; Absher, Devin; Marsal, Sara; Fernández-Nebro, Antonio

2018-05-30

Systemic lupus erythematosus (SLE) is a common systemic autoimmune disease with a complex genetic inheritance. Genome-wide association studies (GWAS) have significantly increased the number of significant loci associated with SLE risk. To date, however, established loci account for less than 30% of the disease heritability and additional risk variants have yet to be identified. Here we performed a GWAS followed by a meta-analysis to identify new genome-wide significant loci for SLE. We genotyped a cohort of 907 patients with SLE (cases) and 1524 healthy controls from Spain and performed imputation using the 1000 Genomes reference data. We tested for association using logistic regression with correction for the principal components of variation. Meta-analysis of the association results was subsequently performed on 7,110,321 variants using genetic data from a large cohort of 4036 patients with SLE and 6959 controls of Northern European ancestry. Genetic association was also tested at the pathway level after removing the effect of known risk loci using PASCAL software. We identified five new loci associated with SLE at the genome-wide level of significance (p < 5 × 10 - 8 ): GRB2, SMYD3, ST8SIA4, LAT2 and ARHGAP27. Pathway analysis revealed several biological processes significantly associated with SLE risk: B cell receptor signaling (p = 5.28 × 10 - 6 ), CTLA4 co-stimulation during T cell activation (p = 3.06 × 10 - 5 ), interleukin-4 signaling (p = 3.97 × 10 - 5 ) and cell surface interactions at the vascular wall (p = 4.63 × 10 - 5 ). Our results identify five novel loci for SLE susceptibility, and biologic pathways associated via multiple low-effect-size loci.

Matrix metalloproteinase 20-dentin sialophosphoprotein interaction in oral cancer.

PubMed

Saxena, G; Koli, K; de la Garza, J; Ogbureke, K U E

2015-04-01

Matrix metalloproteinase 20 (MMP-20), widely regarded as tooth specific, participates with MMP-2 in processing dentin sialophosphoprotein (DSPP) into dentin sialoprotein, dentin phosphoprotein, and dentin glycoprotein. In biochemical system, MMP-2, MMP-3, and MMP-9 bind with high affinity to, and are activated by, specific small integrin-binding ligand N-linked glycoproteins (SIBLINGs): bone sialoprotein, osteopontin, and dentin matrix protein 1, respectively. Subsequent reports documented possible biological relevance of SIBLING-MMP interaction in vivo by showing that SIBLINGs are always coexpressed with their MMP partners. However, the cognate MMPs for 2 other SIBLINGs-DSPP and matrix extracellular phosphogylcoprotein-are yet to be identified. Our goal was to investigate MMP-20 expression and to explore preliminary evidence of its interaction with DSPP in oral squamous cell carcinomas (OSCCs). Immunohistochemistry analysis of sections from 21 cases of archived human OSCC tissues showed immunoreactivity for MMP-20 in 18 (86%) and coexpression with DSPP in all 15 cases (71%) positive for DSPP. Similarly, 28 (93%) of 30 cases of oral epithelial dysplasia were positive for MMP-20. Western blot and quantitative real-time polymerase chain reaction analysis on OSCC cell lines showed upregulation of MMP-20 protein and mRNA, respectively, while immunofluorescence showed coexpression of MMP-20 and DSPP. Colocalization and potential interaction of MMP-20 with dentin sialoprotein was confirmed by coimmunoprecipitation and mass spectrometry analysis of immunoprecipitation product from OSCC cell lysate, and in situ proximity ligation assays. Significantly, results of chromatin immunoprecipation revealed a 9-fold enrichment of DSPP at MMP-20 promoter-proximal elements. Our data provide evidence that MMP-20 has a wider tissue distribution than previously acknowledged. MMP-20-DSPP specific interaction, excluding other MMP-20-SIBLING pairings, identifies MMP-20 as DSPP cognate MMP

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm.

PubMed

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene x gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene x gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms.