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Erratum to: The real cost of sequencing: scaling computation to keep pace with data generation

Genome biology 2016年第1期17卷 78页

作者： Paul Muir Shantao Li Shaoke Lou Daifeng Wang Daniel J Spakowicz Leonidas Salichos Jing Zhang George M Weinstock Farren Isaacs Joel Rozowsky Mark Gerstein Department of Molecular Cellular and Developmental Biology Yale University New Haven CT 06520 USA. Systems Biology Institute Yale University West Haven CT 06516 USA. Integrated Graduate Program in Physical and Engineering Biology Yale University New Haven CT 06520 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. Department of Molecular Biophysics and Biochemistry Yale University New Haven CT 06520 USA. The Jackson Laboratory for Genomic Medicine Farmington CT 06032 USA. Program in Computational Biology and Bioinformatics Yale University New Haven CT 06520 USA. mark@***. Department of Molecular Biophysics and Biochemistry Yale University New Haven CT 06520 USA. mark@***. Department of Computer Science Yale University New Haven CT 06520 USA. mark@***.

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Author Correction: A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers

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Nature communications 2021年第1期12卷 2986页

作者： Juliette Coignard Michael Lush Jonathan Beesley Tracy A O'Mara Joe Dennis Jonathan P Tyrer Daniel R Barnes Lesley McGuffog Goska Leslie Manjeet K Bolla Muriel A Adank Simona Agata Thomas Ahearn Kristiina Aittomäki Irene L Andrulis Hoda Anton-Culver Volker Arndt Norbert Arnold Kristan J Aronson Banu K Arun Annelie Augustinsson Jacopo Azzollini Daniel Barrowdale Caroline Baynes Heko Becher Marina Bermisheva Leslie Bernstein Katarzyna Białkowska Carl Blomqvist Stig E Bojesen Bernardo Bonanni Ake Borg Hiltrud Brauch Hermann Brenner Barbara Burwinkel Saundra S Buys Trinidad Caldés Maria A Caligo Daniele Campa Brian D Carter Jose E Castelao Jenny Chang-Claude Stephen J Chanock Wendy K Chung Kathleen B M Claes Christine L Clarke J Margriet Collée Don M Conroy Kamila Czene Mary B Daly Peter Devilee Orland Diez Yuan Chun Ding Susan M Domchek Thilo Dörk Isabel Dos-Santos-Silva Alison M Dunning Miriam Dwek Diana M Eccles A Heather Eliassen Christoph Engel Mikael Eriksson D Gareth Evans Peter A Fasching Henrik Flyger Florentia Fostira Eitan Friedman Lin Fritschi Debra Frost Manuela Gago-Dominguez Susan M Gapstur Judy Garber Vanesa Garcia-Barberan Montserrat García-Closas José A García-Sáenz Mia M Gaudet Simon A Gayther Andrea Gehrig Vassilios Georgoulias Graham G Giles Andrew K Godwin Mark S Goldberg David E Goldgar Anna González-Neira Mark H Greene Pascal Guénel Lothar Haeberle Eric Hahnen Christopher A Haiman Niclas Håkansson Per Hall Ute Hamann Patricia A Harrington Steven N Hart Wei He Frans B L Hogervorst Antoinette Hollestelle John L Hopper Darling J Horcasitas Peter J Hulick David J Hunter Evgeny N Imyanitov Agnes Jager Anna Jakubowska Paul A James Uffe Birk Jensen Esther M John Michael E Jones Rudolf Kaaks Pooja Middha Kapoor Beth Y Karlan Renske Keeman Elza Khusnutdinova Johanna I Kiiski Yon-Dschun Ko Veli-Matti Kosma Peter Kraft Allison W Kurian Yael Laitman Diether Lambrechts Loic Le Marchand Jenny Lester Fabienne Lesueur Tricia Lindstrom Adria Lopez-Fernández Jennifer T Loud Craig Luccarini Arto Mannermaa Siranou Genetic Epidemiology of Cancer team Inserm U900 Paris France. Institut Curie Paris Paris France. Mines ParisTech Fontainebleau Paris France. Centre for Cancer Genetic Epidemiology Department of Public Health and Primary Care University of Cambridge Cambridge UK. PSL University Paris Paris France. Paris Sud University Orsay France. Department of Genetics and Computational Biology QIMR Berghofer Medical Research Institute Brisbane QLD Australia. Centre for Cancer Genetic Epidemiology Department of Oncology University of Cambridge Cambridge UK. Family Cancer Clinic The Netherlands Cancer Institute Antoni van Leeuwenhoek hospital Amsterdam The Netherlands. Immunology and Molecular Oncology Unit Veneto Institute of Oncology IOV - IRCCS Padua Italy. Division of Cancer Epidemiology and Genetics National Cancer Institute National Institutes of Health Department of Health and Human Services Bethesda MD USA. Department of Clinical Genetics Helsinki University Hospital University of Helsinki Helsinki Finland. Fred A. Litwin Center for Cancer Genetics Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital Toronto ON Canada. Department of Molecular Genetics University of Toronto Toronto ON Canada. Department of Epidemiology Genetic Epidemiology Research Institute University of California Irvine Irvine CA USA. Division of Clinical Epidemiology and Aging Research German Cancer Research Center (DKFZ) Heidelberg Germany. Department of Gynaecology and Obstetrics University Hospital of Schleswig-Holstein Campus Kiel Christian-Albrechts University Kiel Kiel Germany. Institute of Clinical Molecular Biology University Hospital of Schleswig-Holstein Campus Kiel Christian-Albrechts University Kiel Kiel Germany. Department of Public Health Sciences and Cancer Research Institute Queen's University Kingston ON Canada. Department of Breast Medical Oncology University of Texas MD Anderson Cancer Center Houston TX USA. Department of Cancer Epidemiology Clinical Sciences

A Correction to this paper has been published: https://***/10.1038/s41467-021-23162-4.

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MetaPathways v2.0: A master-worker model for environmental Pathway/Genome Database construction on grids and clouds

MetaPathways v2.0: A master-worker model for environmental P...

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IEEE Symposium on Computational Intelligence and bioinformatics and Computational Biology (CIBCB)

作者： Niels W. Hanson Kishori M. Konwar Shang-Ju Wu Steven J. Hallam Graduate Program in Bioinformatics University of British Columbia Canada Department of Microbiology & Immunology University of British Columbia Canada

The development of high-throughput sequencing technologies over the past decade has generated a tidal wave of environmental sequence information from a variety of natural and human engineered ecosystems. The resulting flood of information into public databases and archived sequencing projects has exponentially expanded computational resource requirements rendering most local homology-based search methods inefficient. We recently introduced MetaPathways v1.0, a modular annotation and analysis pipeline for constructing environmental Pathway/Genome Databases (ePGDBs) from environmental sequence information capable of using the Sun Grid engine for external resource partitioning. However, a command-line interface and facile task management introduced user activation barriers with concomitant decrease in fault tolerance. Here we present MetaPathways v2.0 incorporating a graphical user interface (GUI) and refined task management methods. The MetaPathways GUI provides an intuitive display for setup and process monitoring and supports interactive data visualization and sub-setting via a custom Knowledge Engine data structure. A master-worker model is adopted for task management allowing users to scavenge computational results from a number of worker grids in an ad hoc, asynchronous, distributed network that dramatically increases fault tolerance. This model facilitates the use of EC2 instances extending ePGDB construction to the Amazon Elastic Cloud.

关键词： Engines Databases Data structures Graphical user interfaces Monitoring Computational modeling Pipelines

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Corrigendum to: Report: NIA Workshop on Measures of Physiologic Resiliencies in Human Aging

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The journals of gerontology. Series A, Biological sciences and medical sciences 2018年第7期73卷 995页

作者： Evan C Hadley George A Kuchel Anne B Newman Heather G Allore Jenna M Bartley Cindy S Bergeman Michael L Blinov Cathleen S Colon-Emeric Firdaus S Dabhar Laura L Dugan Chhanda Dutta Basil A Eldadah Luigi Ferrucci James L Kirkland Stephen B Kritchevsky Lewis A Lipsitz Neelesh K Nadkarni May J Reed Kenneth E Schmader Felipe Sierra Stephanie A Studenski Ravi Varadhan Jeremy D Walston Heather E Whitson Raymond Yung Division of Geriatrics and Clinical Gerontology National Institutes of Health National Institute on Aging Bethesda Maryland. Department of Medicine Center on Aging University of Connecticut Health Center Farmington. Department of Epidemiology University of Pittsburgh Graduate School of Public Health. Department of Medicine Division of Geriatric Medicine University of Pittsburgh School of Medicine Pennsylvania. Department of Internal Medicine Section of Geriatrics Yale University School of Medicine New Haven Connecticut. Department of Immunology Center on Aging University of Connecticut Health Center University of Connecticut Farmington. Department of Psychology University of Notre Dame Indiana. R. D. Berlin Center for Cell Analysis and Modeling University of Connecticut School of Medicine University of Connecticut Farmington. Duke University School of Medicine Duke University Medical Center. Durham VA Geriatric Research Education and Clinical Center North Carolina. Department of Psychiatry and Behavioral Sciences Stanford University School of Medicine Stanford University California. Department of Medicine Division of Geriatric Medicine Vanderbilt University School of Medicine Vanderbilt University Nashville Tennessee. Office of the Scientific Director National Institute on Aging National Institutes of Health Bethesda Maryland. Robert and Arlene Kogod Center on Aging Mayo Clinic College of Medicine Mayo Clinic Rochester Minnesota. Department of Gerontology and Geriatrics Sticht Center on Aging Wake Forest University School of Medicine Winston-Salem North Carolina. Beth Israel Deaconess Medical Center Harvard Medical School Boston. Institute for Aging Research Hebrew Senior Life Boston Massachusetts. Division of Geriatric Medicine Department of Internal Medicine School of Medicine University of Washington Seattle. Division of Geriatric Medicine Department of Medicine School of Medicine Duke University. Department of Veterans Affairs Medical Center Durham No

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Abstracts from the 20th International Symposium on Signal Transduction at the Blood-Brain Barriers Abstracts

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FLUIDS AND BARRIERS OF THE CNS 2017年第SUPPL 2期14卷 27-27页

作者： [Anonymous] The Jerzy Kukuczka Academy of Physical Education Katowice Poland The Institute of Animal Physiology and Food Research Polish Academy of Sciences Olsztyn Poland University of Miami Miami FL USA Institute of Pharmaceutical Science King’s College London London United Kingdom Department of Ophthalmology and Molecular and Integrative Physiology The University of Michigan Ann Arbor MI USA Department of Internal Medicine and Cardiology The University of Michigan Ann Arbor MI USA School of Medicine Department of Cellular and Molecular Medicine Koc University Istanbul Turkey Department of Cellular and Molecular Medicine Medical Faculty Koc University Istanbul Turkey Department of Neuroscience School of Medicine Koc University Istanbul Turkey Department of Neuroscience Medical Faculty Koc University Istanbul Turkey Department of Laboratory Animals Science Aziz Sancar Experimental Medicine Research Institute Istanbul University Istanbul Turkey Department of Neuroscience Aziz Sancar Experimental Medicine Research Institute Istanbul University Istanbul Turkey School of Medicine Koc University Istanbul Turkey Department of Forensic Science Istanbul Faculty of Medicine Istanbul University Istanbul Turkey Department of Histology and Embryology School of Medicine Koc University Istanbul Turkey Department of Histology and Embryology Istanbul Faculty of Medicine Istanbul University Istanbul Turkey Department of Physiology School of Medicine Koc University Istanbul Turkey Theodor Kocher Institute University of Bern Bern Switzerland Institute of Veterinary Physiology Vetsuisse Faculty University of Zurich Zurich Switzerland Zurich Center for Integrative Human Physiology University of Zurich Zurich Switzerland Zurich Center of Integrative Human Physiology University of Zurich Zurich Switzerland Institute for Veterinary Physiology and Zurich Center for Integrative Human Physiology University of Zurich Zurich Switzerland Institute of Veterinary Physiology Univer

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Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity (vol 50, pg 765, 2017)

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NATURE GENETICS 2018年第5期50卷 765-766页

作者： Turcot, Valerie Lu, Yingchang Highland, Heather M. Schurmann, Claudia Justice, Anne E. Fine, Rebecca S. Bradfield, Jonathan P. Esko, Tonu Giri, Ayush Graff, Mariaelisa Guo, Xiuqing Hendricks, Audrey E. Karaderi, Tugce Lempradl, Adelheid Locke, Adam E. Mahajan, Anubha Marouli, Eirini Sivapalaratnam, Suthesh Young, Kristin L. Alfred, Tamuno Feitosa, Mary F. Masca, Nicholas G. D. Manning, Alisa K. Medina-Gomez, Carolina Mudgal, Poorva Ng, Maggie C. Y. Reiner, Alex P. Vedantam, Sailaja Willems, Sara M. Winkler, Thomas W. Abecasis, Goncalo Aben, Katja K. Alam, Dewan S. Alharthi, Sameer E. Allison, Matthew Amouyel, Philippe Asselbergs, Folkert W. Auer, Paul L. Balkau, Beverley Bang, Lia E. Barroso, Ines Bastarache, Lisa Benn, Marianne Bergmann, Sven Bielak, Lawrence F. Bluher, Matthias Boehnke, Michael Boeing, Heiner Boerwinkle, Eric Boger, Carsten A. Bork-Jensen, Jette Bots, Michiel L. Bottinger, Erwin P. Bowden, Donald W. Brandslund, Ivan Breen, Gerome Brilliant, Murray H. Broer, Linda Brumat, Marco Burt, Amber A. Butterworth, Adam S. Campbell, Peter T. Cappellani, Stefania Carey, David J. Catamo, Eulalia Caulfield, Mark J. Chambers, John C. Chasman, Daniel I. Chen, Yii-Der I. Chowdhury, Rajiv Christensen, Cramer Chu, Audrey Y. Cocca, Massimiliano Collins, Francis S. Cook, James P. Corley, Janie Galbany, Jordi Corominas Cox, Amanda J. Crosslin, David S. Cuellar-Partida, Gabriel D'Eustacchio, Angela Danesh, John Davies, Gail Bakker, Paul I. W. Groot, Mark C. H. Mutsert, Renee Deary, Ian J. Dedoussis, George Demerath, Ellen W. Heijer, Martin Hollander, Anneke I. Ruijter, Hester M. Dennis, Joe G. Denny, Josh C. Angelantonio, Emanuele Drenos, Fotios Du, Mengmeng Dube, Marie-Pierre Dunning, Alison M. Easton, Douglas F. Edwards, Todd L. Ellinghaus, David Ellinor, Patrick T. Elliott, Paul Evangelou, Evangelos Farmaki, Aliki-Eleni Farooqi, I. Sadaf Faul, Jessica D. Fauser, Sascha Feng, Shuang Ferrannini, Ele Ferrieres, Jean Florez, Jose C. Ford, Ian Fornage, Myriam Franco, Oscar H. Franke, Andre Franks, Paul W. Friedrich, Ne Montreal Heart Institute Université de Montréal Montreal Quebec Canada Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University School of Medicine Nashville TN USA Charles Bronfman Institute for Personalized Medicine Icahn School of Medicine at Mount Sinai New York NY USA Genetics of Obesity and Related Metabolic Traits Program Icahn School of Medicine at Mount Sinai New York NY USA Department of Epidemiology University of North Carolina Chapel Hill NC USA Human Genetics Center University of Texas School of Public Health University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences University of Texas Health Science Center at Houston Houston TX USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Genetics Harvard Medical School Boston MA USA Division of Endocrinology and Center for Basic and Translational Obesity Research Boston Children’s Hospital Boston MA USA Center for Applied Genomics Division of Human Genetics Children’s Hospital of Philadelphia Philadelphia PA USA Quantinuum Research LLC San Diego CA USA Estonian Genome Center University of Tartu Tartu Estonia Division of Epidemiology Department of Medicine Institute for Medicine and Public Health Vanderbilt Genetics Institute Vanderbilt University Nashville TN USA Institute for Translational Genomics and Population Sciences LABioMed at Harbor-UCLA Medical Center Torrance CA USA Wellcome Trust Sanger Institute Hinxton UK Department of Mathematical and Statistical Sciences University of Colorado Denver CO USA Wellcome Trust Centre for Human Genetics University of Oxford Oxford UK Department of Biological Sciences Faculty of Arts and Sciences Eastern Mediterranean University Famagusta Cyprus Max Planck Institute of Immunobiology and Epigenetics Freiburg Germany Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (***35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

关键词： Genome-wide association studies Obesity

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Flor Revisited(Again):eQTL and Mutational Analysis of NB-LRR Mediated Immunity to Powdery Mildew in Barley

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Journal of Integrative Agriculture 2014年第2期13卷 237-243页

作者： Roger Wise Priyanka Surana Greg Fuerst Ruo Xu Divya Mistry Julie Dickerson Dan Nettleton Corn Insects and Crop Genetics Research Unit U.S.Department of Agriculture-Agricultural Research ServiceIowa State UniversityAmesIowa 50011USA Department of Plant Pathology & Microbiology Center for Plant Responses to Environmental StressesIowa State UniversityAmesIowa 50011USA Bioinformatics and Computational Biology Graduate Program Iowa State UniversityAmesIowa 50011USA Department of Statistics Iowa State UniversityAmesIowa 50011USA Department of Electrical and Computer Engineering Iowa State UniversityAmesIowa 50011USA

Genes encoding early signaling events in pathogen defense often are identified only by their phenotype. Such genes involved in barley-powdery mildew interactions include Mla, specifying race-specific resistance; Rarl （Required for Mla12-specified resistance1）, and Roml （Restoration of Mla-specified resistancel）. The HSP90-SGT1-RAR1 complex appears to function as chaperone in MLA-specified resistance, however, much remains to be discovered regarding the precise signaling underlying plant immunity. Genetic analyses of fast-neutron mutants derived from CI 16151 （Mla6） uncovered a novel locus, designated Rar3 （R_equired for Mla6-specified resitance3）. Rar3 segregates independent of Mla6 and Rarl, and rar3 mutants are susceptible to Blumeria graminis f. sp. hordei （Bgh） isolate 5874 （A VRar）, whereas, wild-type progenitor plants are resistant. Comparative expression analyses of the rar3 mutant vs. its wild-type progenitor were conducted via Barleyl GeneChip and GAIIx paired-end RNA-Seq. Whereas Rarl affects transcription of relatively few genes; Rar3 appears to influence thousands, notably in genes controlling ATP binding, catalytic activity, transcription, and phosphorylation; possibly membrane bound or in the nucleus, eQTL analysis of a segregating doubled haploid population identified over two-thousand genes as being regulated by Mla （q value/FDR=0.00001）, a subset of which are significant in Rar3 interactions. The intersection of datasets derived from mla-loss-of-function mutants, Mla-associated eQTL, and rar3-mediated transcriptome reprogramming are narrowing the focus on essential genes required for Mla-specified immunity.

关键词： eQTL transcript profiling immunity resistance signaling barley Blumeria graminis

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Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

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Nature genetics 2019年第7期51卷 1191-1192页

作者： Valérie Turcot Yingchang Lu Heather M Highland Claudia Schurmann Anne E Justice Rebecca S Fine Jonathan P Bradfield Tõnu Esko Ayush Giri Mariaelisa Graff Xiuqing Guo Audrey E Hendricks Tugce Karaderi Adelheid Lempradl Adam E Locke Anubha Mahajan Eirini Marouli Suthesh Sivapalaratnam Kristin L Young Tamuno Alfred Mary F Feitosa Nicholas G D Masca Alisa K Manning Carolina Medina-Gomez Poorva Mudgal Maggie C Y Ng Alex P Reiner Sailaja Vedantam Sara M Willems Thomas W Winkler Gonçalo Abecasis Katja K Aben Dewan S Alam Sameer E Alharthi Matthew Allison Philippe Amouyel Folkert W Asselbergs Paul L Auer Beverley Balkau Lia E Bang Inês Barroso Lisa Bastarache Marianne Benn Sven Bergmann Lawrence F Bielak Matthias Blüher Michael Boehnke Heiner Boeing Eric Boerwinkle Carsten A Böger Jette Bork-Jensen Michiel L Bots Erwin P Bottinger Donald W Bowden Ivan Brandslund Gerome Breen Murray H Brilliant Linda Broer Marco Brumat Amber A Burt Adam S Butterworth Peter T Campbell Stefania Cappellani David J Carey Eulalia Catamo Mark J Caulfield John C Chambers Daniel I Chasman Yii-Der I Chen Rajiv Chowdhury Cramer Christensen Audrey Y Chu Massimiliano Cocca Francis S Collins James P Cook Janie Corley Jordi Corominas Galbany Amanda J Cox David S Crosslin Gabriel Cuellar-Partida Angela D'Eustacchio John Danesh Gail Davies Paul I W Bakker Mark C H Groot Renée Mutsert Ian J Deary George Dedoussis Ellen W Demerath Martin Heijer Anneke I Hollander Hester M Ruijter Joe G Dennis Josh C Denny Emanuele Di Angelantonio Fotios Drenos Mengmeng Du Marie-Pierre Dubé Alison M Dunning Douglas F Easton Todd L Edwards David Ellinghaus Patrick T Ellinor Paul Elliott Evangelos Evangelou Aliki-Eleni Farmaki I Sadaf Farooqi Jessica D Faul Sascha Fauser Shuang Feng Ele Ferrannini Jean Ferrieres Jose C Florez Ian Ford Myriam Fornage Oscar H Franco Andre Franke Paul W Franks Nele Friedrich Ruth Frikke-Schmidt Tessel E Galesloot Wei Gan Ilaria Gandin Paolo Gasparini Jane Gibson Vilmantas Giedraitis Anette P Gjesing Penny Gordon-Larsen Mathias Gorski Hans-Jörgen Montreal Heart Institute Université de Montréal Montreal Quebec Canada. Division of Epidemiology Department of Medicine Vanderbilt-Ingram Cancer Center Vanderbilt Epidemiology Center Vanderbilt University School of Medicine Nashville TN USA. Charles Bronfman Institute for Personalized Medicine Icahn School of Medicine at Mount Sinai New York NY USA. Genetics of Obesity and Related Metabolic Traits Program Icahn School of Medicine at Mount Sinai New York NY USA. Department of Epidemiology University of North Carolina Chapel Hill NC USA. Human Genetics Center University of Texas School of Public Health University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences University of Texas Health Science Center at Houston Houston TX USA. Broad Institute of MIT and Harvard Cambridge MA USA. Department of Genetics Harvard Medical School Boston MA USA. Division of Endocrinology and Center for Basic and Translational Obesity Research Boston Children's Hospital Boston MA USA. Center for Applied Genomics Division of Human Genetics Children's Hospital of Philadelphia Philadelphia PA USA. Quantinuum Research LLC San Diego CA USA. Estonian Genome Center University of Tartu Tartu Estonia. Division of Epidemiology Department of Medicine Institute for Medicine and Public Health Vanderbilt Genetics Institute Vanderbilt University Nashville TN USA. Institute for Translational Genomics and Population Sciences LABioMed at Harbor-UCLA Medical Center Torrance CA USA. Wellcome Trust Sanger Institute Hinxton UK. Department of Mathematical and Statistical Sciences University of Colorado Denver CO USA. Wellcome Trust Centre for Human Genetics University of Oxford Oxford UK. Department of Biological Sciences Faculty of Arts and Sciences Eastern Mediterranean University Famagusta Cyprus. Max Planck Institute of Immunobiology and Epigenetics Freiburg Germany. Department of Biostatistics and Center for Statistical Genetics University of M

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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A web-based, hospital-wide health care-associated bloodstream infection surveillance and classification system: Development and evaluation

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JMIR Medical Informatics 2015年第3期3卷 e31页

作者： Tseng, Yi-Ju Wu, Jung-Hsuan Lin, Hui-Chi Chen, Ming-Yuan Ping, Xiao-Ou Sun, Chun-Chuan Shang, Rung-Ji Sheng, Wang-Huei Chen, Yee-Chun Lai, Feipei Chang, Shan-Chwen Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Computational Health Informatics Program Boston Children's Hospital Boston MA United States Department of Electrical Engineering National Taiwan University Taipei Taiwan Center for Infection Control National Taiwan University Hospital Taipei Taiwan National Taiwan University Hospital Information Systems Office Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Department of Internal Medicine National Taiwan University Hospital and College of Medicine Taipei Taiwan National Health Research Institutes National Institute of Infectious Diseases and Vaccinology Miaoli Taiwan

Background: Surveillance of health care-associated infections is an essential component of infection prevention programs, but conventional systems are labor intensive and performance dependent. Objective: To develop an automatic surveillance and classification system for health care-associated bloodstream infection (HABSI), and to evaluate its performance by comparing it with a conventional infection control personnel (ICP)-based surveillance system. Methods: We developed a Web-based system that was integrated into the medical information system of a 2200-bed teaching hospital in Taiwan. The system automatically detects and classifies HABSIs. Results: In this study, the number of computer-detected HABSIs correlated closely with the number of HABSIs detected by ICP by department (n=20;r=.999 P<.001) and by time (n=14;r=.941;P<.001). Compared with reference standards, this system performed excellently with regard to sensitivity (98.16%), specificity (99.96%), positive predictive value (95.81%), and negative predictive value (99.98%). The system enabled decreasing the delay in confirmation of HABSI cases, on average, by 29 days. Conclusions: This system provides reliable and objective HABSI data for quality indicators, improving the delay caused by a conventional surveillance system. © 2020 JMIR Publications Inc. All rights reserved.

关键词： Health care-associated infection Infection control Information systems Surveillance Web-based services

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Trends and factors associated with initial and recurrent methicillin-resistant Staphylococcus aureus (MRSA) skin and soft-tissue infections among HIV-infected persons: An 18-year study

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Journal of the International Association of Providers of AIDS Care 2014年第3期13卷 206-213页

作者： Vyas, Kartavya J. Shadyab, Aladdin H. Lin, Chii-Dean Crum-Cianflone, Nancy F. Infectious Disease Clinical Research Program Uniformed Services University of the Health Sciences Bethesda MD United States Infectious Disease Clinic Naval Medical Center San Diego San Diego CA United States Department of Bioinformatics and Medical Informatics San Diego State University San Diego CA United States Graduate School of Public Health San Diego State University San Diego CA United States Deployment Health Research Department Naval Health Research Center San Diego CA United States

Background: Factors associated with initial methicillin-resistant Staphylococcus aureus (MRSA) skin and soft-tissue infections (SSTIs) and their recurrence have not been fully elucidated among HIV-infected persons. Methods: We retrospectively evaluated a large cohort of HIV-infected patients from 1993 to 2010 for culture-proven MRSA SSTIs. Separate logistic regression models evaluated factors associated with initial and recurrent infections. Results: Of the 794 patients, 63 (8%) developed an initial infection (19.8 infections/1000 person years [PY]);risk factors included CD4 count <500 cells/mm3 and HIV RNA level ≥400 copies/mL (P < .01), US Centers for Disease Control and Prevention (CDC) stage C versus A/B (P < .01), and injection drug use (IDU, P < .01). In all, 27% developed recurrence (206 infections/1000 PY);risk factors included hospital admission (P = .02). Minocycline for treatment of the initial infection was associated with an 80% decreased odds for recurrence (P = .03). Conclusion: HIV control and avoidance of IDU may be useful in reducing rates of MRSA SSTIs among HIV-infected persons. © The Author(s) 2013.

关键词： epidemiology HIV MRSA recurrence risk factors

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