检索结果-内蒙古大学图书馆

Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

引用

arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

来源：评论

学校读者我要写书评

暂无评论

Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs

arXiv

引用

arXiv 2021年

作者： Sanders, Lauren M. Yang, Jason H. Scott, Ryan T. Qutub, Amina Ann Martin, Hector Garcia Berrios, Daniel C. Hastings, Jaden J.A. Rask, Jon Mackintosh, Graham Hoarfrost, Adrienne L. Chalk, Stuart Kalantari, John Khezeli, Kia Antonsen, Erik L. Babdor, Joel Barker, Richard Baranzini, Sergio E. Beheshti, Afshin Delgado-Aparicio, Guillermo M. Glicksberg, Benjamin S. Greene, Casey S. Haendel, Melissa Hamid, Arif A. Heller, Philip Jamieson, Daniel Jarvis, Katelyn J. Komarova, Svetlana V. Komorowski, Matthieu Kothiyal, Prachi Mahabal, Ashish Manor, Uri Mason, Christopher E. Matar, Mona Mias, George I. Miller, Jack Myers, Jerry G. Nelson, Charlotte Oribello, Jonathan Park, Seung-Min Parsons-Wingerter, Patricia Prabhu, R.K. Reynolds, Robert J. Saravia-Butler, Amanda Saria, Suchi Sawyer, Aenor Singh, Nitin Kumar Soboczenski, Frank Snyder, Michael Soman, Karthik Theriot, Corey A. van Valen, David Venkateswaran, Kasthuri Warren, Liz Worthey, Liz Zitnik, Marinka Costes, Sylvain V. Blue Marble Space Institute of Science Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Center for Emerging and Re-Emerging Pathogens Department of Microbiology Biochemistry and Molecular Genetics Rutgers New Jersey Medical School NewarkNJ07103 United States KBR Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States AI MATRIX Consortium Department of Biomedical Engineering University of Texas San Antonio and UT Health Sciences San AntonioTX78249 United States Biological Systems and Engineering Division Lawrence Berkeley National Lab. BerkeleyCA94608 United States DOE Agile BioFoundry EmeryvilleCA94608 United States Joint BioEnergy Institute EmeryvilleCA94608 United States Department of Physiology and Biophysics Weill Cornell Medicine New YorkNY10065 United States Office of the Center Director NASA Ames Research Center Moffett Field CA94035 United States Bay Area Environmental Research Institute NASA Ames Research Center Moffett Field CA94035 United States Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Department of Chemistry University of North Florida JacksonvilleFL32224 United States Center for Individualized Medicine Department of Surgery Department of Quantitative Health Sciences Mayo Clinic RochesterMN55905 United States Department of Emergency Medicine Center for Space Medicine Baylor College of Medicine HoustonTX77030 United States Department of Microbiology and Immunology Department of Otolaryngology Head and Neck Surgery University of California San Francisco San FranciscoCA94143 United States The Gilroy AstroBiology Research Group The University of Wisconsin - Madison MadisonWI53706 United States Weill Institute for Neurosciences Department of Neurology University of California San Francisco San FranciscoCA94158 United States Data Science Analytics Georgia Institute of Technology Lima15024

Space biology research aims to understand fundamental effects of spaceflight on organisms, develop foundational knowledge to support deep space exploration, and ultimately bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals, and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data, and model organisms from both spaceborne and ground-analog studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally autonomous, light, agile, and intelligent to expedite knowledge discovery. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning, and modeling applications which offer key solutions toward these space biology challenges. In the next decade, the synthesis of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modeling and analytics, support maximally autonomous and reproducible experiments, and efficiently manage spaceborne data and metadata, all with the goal to enable life to thrive in deep space. © 2021, CC BY.

关键词： Predictive analytics

来源：评论

学校读者我要写书评

暂无评论

Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space health

arXiv

引用

arXiv 2021年

作者： Scott, Ryan T. Antonsen, Erik L. Sanders, Lauren M. Hastings, Jaden J.A. Park, Seung-Min Mackintosh, Graham Reynolds, Robert J. Hoarfrost, Adrienne L. Sawyer, Aenor Greene, Casey S. Glicksberg, Benjamin S. Theriot, Corey A. Berrios, Daniel C. Miller, Jack Babdor, Joel Barker, Richard Baranzini, Sergio E. Beheshti, Afshin Chalk, Stuart Delgado-Aparicio, Guillermo M. Haendel, Melissa Hamid, Arif A. Heller, Philip Jamieson, Daniel Jarvis, Katelyn J. Kalantari, John Khezeli, Kia Komarova, Svetlana V. Komorowski, Matthieu Kothiyal, Prachi Mahabal, Ashish Manor, Uri Martin, Hector Garcia Mason, Christopher E. Matar, Mona Mias, George I. Myers, Jerry G. Nelson, Charlotte Oribello, Jonathan Parsons-Wingerter, Patricia Prabhu, R.K. Qutub, Amina Ann Rask, Jon Saravia-Butler, Amanda Saria, Suchi Singh, Nitin Kumar Soboczenski, Frank Snyder, Michael Soman, Karthik van Valen, David Venkateswaran, Kasthuri Warren, Liz Worthey, Liz Yang, Jason H. Zitnik, Marinka Costes, Sylvain V. KBR Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States Department of Emergency Medicine Center for Space Medicine Baylor College of Medicine HoustonTX77030 United States Blue Marble Space Institute of Science Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States Department of Physiology and Biophysics Weill Cornell Medicine New YorkNY10065 United States Department of Urology Department of Radiology Stanford University School of Medicine StanfordCA94305 United States Bay Area Environmental Research Institute NASA Ames Research Center Moffett FieldCA94035 United States Mortality Research & Consulting Inc. HoustonTX77058 United States Space Biosciences Division NASA Ames Research Center Moffett FieldCA94035 United States UC Space Health Department of Orthopaedic Surgery University of California San Francisco San FranciscoCA94143 United States Center for Health AI Department of Biochemistry and Molecular Genetics University of Colorado School of Medicine Anschutz Medical Campus AuroraCO80045 United States Hasso Plattner Institute for Digital Health at Mount Sinai Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New YorkNY10065 United States Department of Preventive Medicine and Community Health UTMB GalvestonTX77551 United States Human Health and Performance Directorate NASA Johnson Space Center HoustonTX77058 United States Department of Microbiology and Immunology Department of Otolaryngology Head and Neck Surgery University of California San Francisco San FranciscoCA94143 United States The Gilroy AstroBiology Research Group The University of Wisconsin Madison MadisonWI53706 United States Weill Institute for Neurosciences Department of Neurology University of California San Francisco San FranciscoCA94158 United States Department of Chemistry University of North Florida JacksonvilleFL32224 United States Data Scienc

Human space exploration beyond low Earth orbit will involve missions of significant distance and duration. To effectively mitigate myriad space health hazards, paradigm shifts in data and space health systems are necessary to enable Earth-independence, rather than Earth-reliance. Promising developments in the fields of artificial intelligence and machine learning for biology and health can address these needs. We propose an appropriately autonomous and intelligent Precision Space health system that will monitor, aggregate, and assess biomedical statuses;analyze and predict personalized adverse health outcomes;adapt and respond to newly accumulated data;and provide preventive, actionable, and timely insights to individual deep space crew members and iterative decision support to their crew medical officer. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration, on future applications of artificial intelligence in space biology and health. In the next decade, biomonitoring technology, biomarker science, spacecraft hardware, intelligent software, and streamlined data management must mature and be woven together into a Precision Space health system to enable humanity to thrive in deep space. © 2021, CC BY.

关键词： Earth (planet)

来源：评论

学校读者我要写书评

暂无评论

Evaluating drug targets through human loss-of-function genetic variation (vol 581, pg 459, 2020)

引用

NATURE 2021年第7846期590卷 E56-E56页

作者： Minikel, Eric Vallabh Karczewski, Konrad J. Martin, Hilary C. Cummings, Beryl B. Whiffin, Nicola Rhodes, Daniel Alfoldi, Jessica Trembath, Richard C. van Heel, David A. Daly, Mark J. Schreiber, Stuart L. MacArthur, Daniel G. Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA USA Chemical Biology and Therapeutics Science Program Broad Institute of MIT and Harvard Cambridge MA USA Analytical and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA Henry and Allison McCance Center for Brain Health Massachusetts General Hospital Boston MA USA Department of Neurology Massachusetts General Hospital Boston MA USA Prion Alliance Cambridge MA USA National Heart and Lung Institute and MRC London Institute of Medical Sciences Imperial College London London UK National Heart & Lung Institute and MRC London Institute of Medical Sciences Imperial College London London UK Cardiovascular Research Centre Royal Brompton & Harefield Hospitals NHS Trust London UK European Molecular Biology Laboratory European Bioinformatics Institute Wellcome Genome Campus Hinxton Cambridge UK Center for Genomic Medicine Massachusetts General Hospital Boston MA USA Program in Bioinformatics and Integrative Genomics Harvard Medical School Boston MA USA Broad Genomics Broad Institute of MIT and Harvard Cambridge MA USA Division of Genetics and Genomics Boston Children’s Hospital Boston MA USA Department of Pediatrics Harvard Medical School Boston MA USA Cardiac Arrhythmia Service and Cardiovascular Research Center Massachusetts General Hospital Boston MA USA Estonian Genome Center Institute of Genomics University of Tartu Tartu Estonia Department of Medicine Harvard Medical School Boston MA USA Cardiac Arrhythmia Service Massachusetts General Hospital Boston MA USA Centre for Population Genomics Garvan Institute of Medical Research and UNSW Sydney Sydney Australia Centre for Population Genomics Murdoch Children’s Research Institute Melbourne Australia Divi

来源：评论

学校读者我要写书评

暂无评论

改进实效型试验的报告质量：CONSORT声明的扩充（1）

引用

英国医学杂志中文版 2009年第2期12卷 108-111页

作者： Merrick Zwarenstein Shaun Treweek Joel J Gagnier Douglas G Altman Sean Tunis Brian Haynes Andrew D Oxman David Moher 汪谋岳(译) Health Services Sciences Sunnybrook Hospital Toronto Ontario Canada Institute for Clinical Evaluative Sciences Toronto Depamnent of Health Policy Management and Evaluation University of Toronto Toronto Division of International Health (IHCAR) Karolinska Institute Stockholm Sweden Clinical and Population Sciences and Education University of Dundee Dundee Norwegian Knowledge Centre for the Health Services Oslo Norway Faculty of Medicine University of Toronto Centre for Statistics in Medicine University of Oxford Oxford Center for Medical Technology Policy Baltimore MD USA Division of General Internal Medicine Johns Hopkins School of Medicine Baltimore MD Center for Heahhcare Policy Stanford University School of Medicine Palo Alto CA USA Department of Clinical Epidemiology and Biostatistics and Department of Medicine McMaster University Faculty of Health Sciences Hamilton ON Canada Clinical Epidemiology Program Ottawa Health Research Institute Ottawa Canada Department of Epidemiology and Community Medicine Faculty of Medicine University of Ottawa Ottawa 中华医学杂志英文版编辑部

实效型试验旨在为临床实践决策提供依据，但报告得不好会降低其实用性。CONSORT和Practihc小组描述了对CONSORT指南的修改，帮助读者评估研究结果的适用性。

关键词： CONSORT声明报告质量试验临床实践适用性

来源：评论

学校读者我要写书评

暂无评论

Transcript expression-aware annotation improves rare variant interpretation (vol 581, pg 452, 2020)

引用

NATURE 2021年第7846期590卷 E54-E54页

作者： Cummings, Beryl B. Karczewski, Konrad J. Kosmicki, Jack A. Seaby, Eleanor G. Watts, Nicholas A. Singer-Berk, Moriel Mudge, Jonathan M. Karjalainen, Juha Satterstrom, F. Kyle O'Donnell-Luria, Anne H. Poterba, Timothy Seed, Cotton Solomonson, Matthew Alfoldi, Jessica Daly, Mark J. MacArthur, Daniel G. Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Analytical and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA Program in Bioinformatics and Integrative Genomics Harvard Medical School Boston MA USA Genomic Informatics Group University Hospital Southampton Southampton UK Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard Cambridge MA USA Division of Genetics and Genomics Boston Children’s Hospital Boston MA USA Department of Pediatrics Harvard Medical School Boston MA USA European Molecular Biology Laboratory European Bioinformatics Institute Wellcome Genome Campus Hinxton Cambridge UK Center for Genomic Medicine Massachusetts General Hospital Boston MA USA Broad Genomics Broad Institute of MIT and Harvard Cambridge MA USA National Heart & Lung Institute and MRC London Institute of Medical Sciences Imperial College London London UK Cardiovascular Research Centre Royal Brompton & Harefield Hospitals NHS Trust London UK Cardiac Arrhythmia Service and Cardiovascular Research Center Massachusetts General Hospital Boston MA USA Estonian Genome Center Institute of Genomics University of Tartu Tartu Estonia Department of Medicine Harvard Medical School Boston MA USA Cardiac Arrhythmia Service Massachusetts General Hospital Boston MA USA Division of General Internal Medicine Massachusetts General Hospital Boston MA USA Institute for Molecular Medicine FIMM University of Helsinki Helsinki Finland Department of Public Health Faculty of Medicine University of Helsinki Helsinki Finland Department of Genetics Harvard Medical School Boston MA USA Data Sciences Platform Broad Institute of MIT and Harvard Cambridge MA USA Genomics Platform Broad Institute of MIT and Harvard Cambridge MA USA Wellcome Sanger Institute Hinxton Cambridgeshire UK Unidad de Investigaci

来源：评论

学校读者我要写书评

暂无评论

GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture

引用

Nature genetics 2023年第9期55卷 1471-1482页

作者： Remi Stevelink Dorothee Kasteleijn-Nolst Trenite Bobby P. C. Koeleman Dick Lindhout Anja C. M. Sonsma Ciarán Campbell Gianpiero L. Cavalleri Norman Delanty Hany El-Naggar Austin Lacey Peter Widdess-Walsh Colin P. Doherty Siwei Chen Claire Churchhouse Mark J. Daly Yen-Chen A. Feng Daniel P. Howrigan Mitja I. Kurki Benjamin M. Neale Aarno Palotie Wei Zhou Namrata Gupta Henrike O. Heyne Bassel Abou-Khalil Kevin F. Haas R. S. Taneja Oluyomi M. Adesoji Michael Nothnagel Peter Nürnberg Thomas Sander Zaid Afawi Ilan Blatt Amos D. Korczyn Elisabetta Amadori Ganna Balagura Antonella Riva Marcello Scala Paolo Scudieri Pasquale Striano Federico Zara Michele Iacomino Francesca Madia Alison Anderson Patrick Kwan Terence J. O’Brien Slavé Petrovski K. Meng Tan Marian Todaro Joseph Anderson Danielle M. Andrade Quratulain Zulfiqar Ali Grazia Annesi Pauls Auce Andreja Avbersek Simona Balestrini Vera Braatz Claudia B. Catarino Krishna Chinthapalli Jennifer Jamnadas-Khoda Dalia Kasperavičiūte Costin Leu Josemir W. Sander Sanjay M. Sisodiya Sara Zagaglia Melanie Bahlo Karen L. Oliver Mark D. Baker Beata Fonferko-Shadrach William O. Pickrell Carmen Barba Claudia Bianchini Viola Doccini Renzo Guerrini Davide Mei Martino Montomoli Elena Parrini Annalisa Vetro Karen Barboza Fabrice Bartolomei Thomas Bast Bernhard J. Steinhoff Larry Baum Stacey S. Cherny Pak Sham Tobias Baumgartner Christian E. Elger Kerstin Hallmann Wolfram S. Kunz Rainer Surges Randi von Wrede Gábor Zsurka Betül Baykan Nerses Bebek Yeşim Kesim Albert J. Becker Susanne Schoch Felicitas Becker Caitlin A. Bennett Samuel F. Berkovic Stephanie L. Leech Brigid M. Regan Ingrid E. Scheffer Bianca Berghuis Ahmad Beydoun Wassim Nasreddine Francesca Bisulli Lidia Di Vito Lorenzo Ferri Tania Giangregorio Laura Licchetta Raffaella Minardi Barbara Mostacci Carlotta Stipa Paolo Tinuper Lorenzo Muccioli Federica Pondrelli Dheeraj R. Bobbili Emadeldin Hassanin Roland Krause Zied Landoulsi Patrick May Ingo Borggraefe Christian Bosselmann Christian Hengsbach Josua Kegele Stephen Lauxmann Department of Genetics University Medical Center Utrecht Utrecht The Netherlands Stichting Epilepsie Instellingen Nederland (SEIN) Heemstede The Netherlands School of Pharmacy and Biomolecular Sciences The Royal College of Surgeons in Ireland Dublin Ireland The FutureNeuro Research Centre Dublin Ireland Department of Neurology Beaumont Hospital Dublin Ireland Department of Neurology St. James’s Hospital Dublin Ireland Analytic and Translational Genetics Unit Department of Medicine Massachusetts General Hospital and Harvard Medical School Boston MA USA Program in Medical and Population Genetics Broad Institute of MIT and Harvard Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of Harvard and M.I.T Cambridge MA USA Institute for Molecular Medicine Finland (FIMM) University of Helsinki Helsinki Finland Psychiatric & Neurodevelopmental Genetics Unit Department of Psychiatry Massachusetts General Hospital and Harvard Medical School Boston MA USA Division of Biostatistics Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei Taiwan Hasso Plattner Institute Digital Health Center University of Potsdam Potsdam Germany Hasso Plattner Institute Mount Sinai School of Medicine New York City NY USA Department of Neurology Vanderbilt University Medical Center Nashville TN USA Cologne Center for Genomics (CCG) University of Cologne Faculty of Medicine and University Hospital Cologne Cologne Germany University Hospital Cologne Cologne Germany Department of Neurology Charité Universitaetsmedizin Berlin Campus Virchow-Clinic Berlin Germany Tel-Aviv University Sackler Faculty of Medicine Ramat Aviv Israel Department of Neurology Sheba Medical Center Ramat Gan Israel Department of Neurosciences Rehabilitation Ophthalmology Genetics Maternal and Child Health University of Genova Genova Italy IRCCS Istituto Giannina Gaslini Genova Italy Department of Medicine University of Melbour

Epilepsy is a highly heritable disorder affecting over 50 million people worldwide, of which about one-third are resistant to current treatments. Here we report a multi-ancestry genome-wide association study including 29,944 cases, stratified into three broad categories and seven subtypes of epilepsy, and 52,538 controls. We identify 26 genome-wide significant loci, 19 of which are specific to genetic generalized epilepsy (GGE). We implicate 29 likely causal genes underlying these 26 loci. SNP-based heritability analyses show that common variants explain between 39.6% and 90% of genetic risk for GGE and its subtypes. Subtype analysis revealed markedly different genetic architectures between focal and generalized epilepsies. Gene-set analyses of GGE signals implicate synaptic processes in both excitatory and inhibitory neurons in the brain. Prioritized candidate genes overlap with monogenic epilepsy genes and with targets of current antiseizure medications. Finally, we leverage our results to identify alternate drugs with predicted efficacy if repurposed for epilepsy treatment.

关键词：

来源：评论

学校读者我要写书评

暂无评论

31st Annual Meeting and Associated programs of the Society for Immunotherapy of Cancer (SITC 2016): part two Abstracts

引用

JOURNAL FOR IMMUNOTHERAPY OF CANCER 2016年第SUPPL 1期4卷 107-221页

作者： [Anonymous] Department of Immunology University of Texas MD Anderson Cancer Center Houston TX USA Department of Cancer Medicine University of Texas MD Anderson Cancer Center Houston TX USA Immune Design Seattle WA USA Innate Pharma Marseille Provence-Alpes-Cote d’Azur France MedImmune Cambridge England UK Georgetown-Lombardi Comprehensive Cancer Center Washington DC USA Westmead and Blacktown Hospitals Melanoma Institute Australia and the University of Sydney Westmead New South Wales Australia University of California Los Angeles CA USA University of Washington Seattle WA USA Dana-Farber Cancer Institute/Brigham and Women’s Hospital Harvard University Boston MA USA University of Texas MD Anderson Cancer Center Houston TX USA Beth Israel Deaconess Medical Center Boston MA USA Gallipoli Medical Research Foundation Greenslopes Private Hospital and the University of Queensland Greenslopes Queensland Australia Olivia Newton-John Cancer Research Institute Heidelberg Victoria Australia Canterbury District Health Board Christchurch Hospital Christchurch New Zealand Waikato Hospital Regional Cancer Centre Hamilton New Zealand Royal Prince Alfred Hospital Melanoma Institute Australia the University of Sydney and Chris O’Brien Lifehouse Camperdown New South Wales Australia Tasman Oncology Research Southport Gold Coast Queensland Australia Merck & Co. Inc. Kenilworth NJ USA Quantitative Solutions A Certara Company Oss Netherlands Melanoma Institute Australia the University of Sydney Mater Hospital and Royal North Shore Hospital Wollstonecraft New South Wales Australia Columbia University Medical Center New York NY USA Institut d’Investigacions Biomediques August Pi i Sunyer Barcelona Catalonia Spain Icahn School of Medicine at Mount Sinai New York NY USA New York Presbyterian/Columbia University Medical Center New York NY USA Memorial Sloan Kettering Cancer Center New York NY USA Peregrine Pharmaceuticals Inc. Tustin CA USA Regeneron Tarrytown NY USA University of

来源：评论

学校读者我要写书评

暂无评论

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

引用

BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

来源：评论

学校读者我要写书评

暂无评论

Association between GWAS-identified lung adenocarcinoma susceptibility loci and EGFR mutations in never-smoking Asian women, and comparison with findings from Western populations

引用

Human molecular genetics 2017年第2期26卷 454-465页

作者： Wei Jie Seow Keitaro Matsuo Chao Agnes Hsiung Kouya Shiraishi Minsun Song Hee Nam Kim Maria Pik Wong Yun-Chul Hong H Dean Hosgood Zhaoming Wang I-Shou Chang Jiu-Cun Wang Nilanjan Chatterjee Margaret Tucker Hu Wei Tetsuya Mitsudomi Wei Zheng Jin Hee Kim Baosen Zhou Neil E Caporaso Demetrius Albanes Min-Ho Shin Lap Ping Chung She-Juan An Ping Wang Hong Zheng Yasushi Yatabe Xu-Chao Zhang Young Tae Kim Xiao-Ou Shu Young-Chul Kim Bryan A Bassig Jiang Chang James Chung Man Ho Bu-Tian Ji Michiaki Kubo Yataro Daigo Hidemi Ito Yukihide Momozawa Kyota Ashikawa Yoichiro Kamatani Takayuki Honda Hiromi Sakamoto Hideo Kunitoh Koji Tsuta Shun-Ichi Watanabe Hiroshi Nokihara Yohei Miyagi Haruhiko Nakayama Shingo Matsumoto Masahiro Tsuboi Koichi Goto Zhihua Yin Jianxin Shi Atsushi Takahashi Akiteru Goto Yoshihiro Minamiya Kimihiro Shimizu Kazumi Tanaka Tangchun Wu Fusheng Wei Jason Y Y Wong Fumihiko Matsuda Jian Su Yeul Hong Kim In-Jae Oh Fengju Song Victor Ho Fun Lee Wu-Chou Su Yuh-Min Chen Gee-Chen Chang Kuan-Yu Chen Ming-Shyan Huang Pan-Chyr Yang Hsien-Chih Lin Yong-Bing Xiang Adeline Seow Jae Yong Park Sun-Seog Kweon Chien-Jen Chen Haixin Li Yu-Tang Gao Chen Wu Biyun Qian Daru Lu Jianjun Liu Hyo-Sung Jeon Chin-Fu Hsiao Jae Sook Sung Ying-Huang Tsai Yoo Jin Jung Huan Guo Zhibin Hu Wen-Chang Wang Charles C Chung Charles Lawrence Laurie Burdett Meredith Yeager Kevin B Jacobs Amy Hutchinson Sonja I Berndt Xingzhou He Wei Wu Junwen Wang Yuqing Li Jin Eun Choi Kyong Hwa Park Sook Whan Sung Li Liu Chang Hyun Kang Lingmin Hu Chung-Hsing Chen Tsung-Ying Yang Jun Xu Peng Guan Wen Tan Chih-Liang Wang Alan Dart Loon Sihoe Ying Chen Yi Young Choi Jen-Yu Hung Jun Suk Kim Ho-Il Yoon Qiuyin Cai Chien-Chung Lin In Kyu Park Ping Xu Jing Dong Christopher Kim Qincheng He Reury-Perng Perng Chih-Yi Chen Roel Vermeulen Junjie Wu Wei-Yen Lim Kun-Chieh Chen John K C Chan Minjie Chu Yao-Jen Li Jihua Li Hongyan Chen Chong-Jen Yu Li Jin Yen-Li Lo Ying-Hsiang Chen Joseph F Fraumeni Jie Liu Taiki Yamaji Yang Yang Belynda Hicks Kathleen Wyatt Shengchao A Li Division of Cancer Epidemiology and Genetics National Cancer Institute Bethesda MD USA. Saw Swee Hock School of Public Health National University of Singapore and National University Health System Singapore. Division of Molecular Medicine Aichi Cancer Center Research Institute Nagoya Japan. Institute of Population Health Sciences National Health Research Institutes Zhunan Taiwan. Division of Genome Biology National Cancer Center Research Institute Tokyo Japan. Department of Statistics Sookmyung Women's University Seoul Republic of Korea. Department of Preventive Medicine Chonnam National University Medical School Gwangju Republic of Korea. Department of Pathology The University of Hong Kong Queen Mary Hospital Hong Kong. Department of Preventive Medicine Seoul National University College of Medicine Seoul Republic of Korea. Department of Epidemiology and Population Health Albert Einstein College of Medicine Bronx NY USA. Department of Computational Biology St. Jude Children's Research Hospital Memphis TN 38105 USA. National Institute of Cancer Research National Health Research Institutes Zhunan Taiwan. Ministry of Education Key Laboratory of Contemporary Anthropology School of Life Sciences Fudan University Shanghai People's Republic of China. State Key Laboratory of Genetic Engineering School of Life Sciences Fudan University Shanghai People's Republic of China. Division of Thoracic Surgery Kinki University School of Medicine Sayama Japan. Division of Epidemiology Department of Medicine Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center Nashville TN USA. Department of Integrative Bioscience & Biotechnology Sejong University Seoul Republic of Korea. Department of Epidemiology School of Public Health China Medical University Shenyang People's Republic of China. Guangdong Lung Cancer Institute Medical Research Center and Cancer Center of Guangdong General Hospital Guangdong Academy of Medical Sciences Guangzhou People's Republic

To evaluate associations by EGFR mutation status for lung adenocarcinoma risk among never-smoking Asian women, we conducted a meta-analysis of 11 loci previously identified in genome-wide association studies (GWAS). Genotyping in an additional 10,780 never-smoking cases and 10,938 never-smoking controls from Asia confirmed associations with eight known single nucleotide polymorphisms (SNPs). Two new signals were observed at genome-wide significance (P < 5 × 10-8), namely, rs7216064 (17q24.3, BPTF), for overall lung adenocarcinoma risk, and rs3817963 (6p21.3, BTNL2) which is specific to cases with EGFR mutations. In further sub-analyses by EGFR status, rs9387478 (ROS1/DCBLD1) and rs2179920 (HLA-DPB1) showed stronger estimated associations in EGFR-positive compared to EGFR-negative cases. Comparison of the overall associations with published results in Western populations revealed that the majority of these findings were distinct, underscoring the importance of distinct contributing factors for smoking and non-smoking lung cancer. Our results extend the catalogue of regions associated with lung adenocarcinoma in non-smoking Asian women and highlight the importance of how the germline could inform risk for specific tumour mutation patterns, which could have important translational implications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：