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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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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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Trust in government moderates the association between fear of COVID-19 as well as empathic concern and preventive behaviour

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Communications Psychology 2023年第1期1卷 1-16页

作者： Arzu Karakulak Beyza Tepe Radosveta Dimitrova Mohamed Abdelrahman Azzam Amin Plamen Akaliyski Rana Alaseel Batoul Bakkar Wassim Gharz Edine Fatema Mohsen Yousuf Abdulqader Alkamali Danny A. Lizarzaburu Aguinaga Andrii Andres John Jamir Benzon R. Aruta Marios Assiotis Olga Solomontos-Kountouri Hrant Avanesyan Maria Muradyan Norzihan Ayub Maria Bacikova-Sleskova Raushan Baikanova Aidos Bolatov Telman Seisembekov Sunčica Bartoluci Ksenija Bosnar Anna Janovská Darko Katović Franjo Prot David Benitez Rita Rivera Ivanna Bodnar Iuliia Pavlova Judyta Borchet Maria Kazmierczak Aleksandra Lewandowska-Walter Justyna Michalek-Kwiecien Katarzyna Skrzypińska Yunier Broche-Pérez Carmen Buzea Rosalinda Cassibba Pasquale Musso Fabiola Silletti Marta Martín Carbonell Bin-Bin Chen Gordana Ristevska Dimitrovska Dương Công Doanh Alejandra del Carmen Dominguez Espinosa Nelli Ferenczi Regina Fernández-Morales Jorge Gaete Yiqun Gan Suely Giolo Rubia Carla Formighieri Giordani Camila Muhl José Rasia Maria-Therese Friehs Shahar Gindi Biljana Gjoneska Juan Carlos Godoy Lorena Cecilia López Steinmetz Maria del Pilar Grazioso Marinés Mejía Camellia Hancheva Given Hapunda Shogo Hihara Russell Sarwar Kabir Tinka Delakorda Kawashima Kazumi Sugimura Brett Walter Mohd Saiful Husain Md Saiful Islam Sadia Sultana Nino Javakhishvili Ana Makashvili Veljko Jovanović Nor Ba’yah Abdul Kadir Johannes Karl Zhumaly Kauyzbay Richa Khanna Meetu Khosla Martina Klicperová-Baker Iva Poláčková Šolcová Ana Kozina Steven Eric Krauss Rodrigo Landabur Katharina Lefringhausen Yun-Hsia Liang Sadia Malik Denisse Manrique-Millones Stefanos Mastrotheodoros Breeda McGrath Enkeleint A. Mechili Samson Mhizha Diana Miconi Rodrigo Moreta-Herrera Andrej Naterer Arash Nemat Felix Neto Joana Neto Luz Marina Alonso Palacio Hassan Okati-Aliabad Carlos Iván Orellana Ligia María Orellana Sushanta Kumar Mishra Joonha Park Eddy Peralta Petro Petrytsa Saša Pišot Benedicta Prihatin Dwi Riyanti Laura Francisca Sudarnoto Angela Oktavia Suryani Adil Samekin Danielius Serapinas Rasa Pilkaus Istanbul Policy Center Sabanci University Istanbul Turkey Department of Psychology MEF University Istanbul Turkey Department of Psychology Stockholm University Stockholm Sweden Social Psychology Department Doha Institute for Graduate Studies Doha Qatar Mokhtass for Consultations and Research Doha Qatar Department of Sociology and Social Policy Lingnan University Hong Kong SAR China Faculty of Medicine Syrian Private University Damascus Syrian Arab Republic Ipswich Hospital Ipswich UK United Private School Athaiba Oman Universidad César Vallejo Trujillo Peru Department of Physical Education Lviv Polytechnic National University Lviv Ukraine Department of Psychology De La Salle University Manila Philippines Theological School Church of Cyprus Nicosia Cyprus General Psychology Chair Yerevan State University Yerevan Armenia Faculty of Psychology and Education University of Malaysia Sabah Sabah Malaysia Department of Educational Psychology and Health Psychology Pavol Jozef Šafárik University Košice Slovakia Astana Medical University Astana Kazakhstan University of Zagreb Zagreb Croatia Clinical Psychology Department Albizu University Miami FL USA Counseling & Psychological Services Duke University Durham NC USA Lviv State University of Physical Culture Lviv Ukraine Institute of Psychology University of Gdansk Gdansk Poland Polish Society for the Psychology of Religion University of Gdańsk Gdańsk Poland Department of Psychology Universidad Central Marta Abreu de Las Villas Santa Clara Cuba Department of Social Sciences and Communication Transilvania University of Brasov Brasov Romania Department of Education Psychology Communication University of Bari Bari Italy Faculty of Psychology Cooperative University of Colombia Santa Marta Colombia Psychology Department Fudan University Shanghai China Higher Medical School University St. Kliment Ohridski Bitola North Macedonia PHI Psihomedika Bitola North Macedonia National Economics University

With the COVID-19 pandemic, behavioural scientists aimed to illuminate reasons why people comply with (or not) large-scale cooperative activities. Here we investigated the motives that underlie support for COVID-19 preventive behaviours in a sample of 12,758 individuals from 34 countries. We hypothesized that the associations of empathic prosocial concern and fear of disease with support towards preventive COVID-19 behaviours would be moderated by trust in the government. Results suggest that the association between fear of disease and support for COVID-19 preventive behaviours was strongest when trust in the government was weak (both at individual- and country-level). Conversely, the association with empathic prosocial concern was strongest when trust in the government was high, but this moderation was only found at individual-level scores of governmental trust. We discuss how motivations may be shaped by socio-cultural context, and outline how findings may contribute to a better understanding of collective action during global crises.

关键词： Human behaviour Infectious diseases

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Highly accurate model for prediction of lung nodule malignancy with ct scans

arXiv

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arXiv 2018年

作者： Causey, Jason Zhang, Junyu Ma, Shiqian Jiang, Bo Qualls, Jake Politte, David G. Prior, Fred Zhang, Shuzhong Huang, Xiuzhen Department of Computer Science Arkansas State University JonesboroAR72467 United States Department of Industrial and Systems Engineering University of Minnesota MinneapolisMN55455 United States Department of Systems Engineering and Engineering Management Chinese University of Hong Kong Shatin N.T. Hong Kong Research Center for Management Science and Data Analytics School of Information Management and Engineering Shanghai University of Finance and Economics Shanghai200433 China Mallinckrodt Institute of Radiology Washington University St. LouisMO63110 United States Department of Biomedical Informatics University of Arkansas for Medical Sciences Little RockAR72205 United States UALR/UAMS Joint Graduate Program in Bioinformatics Little RockAR72204 United States

Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It remains challenging for computational approaches to achieve performance comparable to experienced radiologists. Here we present NoduleX, a systematic approach to predict lung nodule malignancy from CT data, based on deep learning convolutional neural networks (CNN). For training and validation, we analyze >1000 lung nodules in images from the LIDC/IDRI cohort. All nodules were identified and classified by four experienced thoracic radiologists who participated in the LIDC project. NoduleX achieves high accuracy for nodule malignancy classification, with an AUC of ~0.99. This is commensurate with the analysis of the dataset by experienced radiologists. Our approach, NoduleX, provides an effective framework for highly accurate nodule malignancy prediction with the model trained on a large patient population. Our results are replicable with software available at http://***/NoduleX. Copyright © 2018, The Authors. All rights reserved.

关键词： Forecasting

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Quantum computing at the frontiers of biological sciences

arXiv

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arXiv 2019年

作者： Emani, Prashant S. Warrell, Jonathan Anticevic, Alan Bekiranov, Stefan Gandal, Michael McConnell, Michael J. Sapiro, Guillermo Aspuru-Guzik, Alán Baker, Justin Bastiani, Matteo McClure, Patrick Murray, John Sotiropoulos, Stamatios N. Taylor, Jacob Senthil, Geetha Lehner, Thomas Gerstein, Mark B. Harrow, Aram W. Program in Computational Biology and Bioinformatics Yale University New HavenCT06520 United States Department of Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States Yale School of Medicine Department of Psychiatry New HavenCT06511 United States University of Virginia School of Medicine Department of Biochemistry and Molecular Genetics CharlottesvilleVA22903 United States Department of Psychiatry Semel Institute David Geffen School of Medicine University of California–Los Angeles 695 Charles E. Young Drive South Los AngelesCA90095 United States Univ. of Virginia School of Medicine Department of Neuroscience CharlottesvilleVA22903 United States Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States Department of Chemistry University of Toronto 80 St. George Street TorontoONM5S 3H6 Canada TorontoONM5S 1M1 Canada CIFAR Artificial Intelligence Research Chair Vector Institute TorontoONM5S 1M1 Canada Department of Computer Science University of Toronto 40 St. George Street TorontoONM5S 2E4 Canada Schizophrenia and Bipolar Disorder Program McLean Hospital BelmontMA02478 United States Department of Psychiatry Harvard Medical School BostonMA02114 United States Sir Peter Mansfield Imaging Centre School of Medicine University of Nottingham NottinghamNG7 2RD United Kingdom Machine Learning Team National Institute of Mental Health BethesdaMD20892 United States Section on Functional Imaging Methods National Institute of Mental Health BethesdaMD20892 United States Department of Psychiatry Yale University School of Medicine New HavenCT06511 United States Department of Physics Yale University New HavenCT06511 United States Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD20742 United States National Institute of Standards and Technology GaithersburgMD20899 United States Office of Genomics Research Coordination N

The search for meaningful structure in biological data has relied on cutting-edge advances in computational technology and data science methods. However, challenges arise as we push the limits of scale and complexity in biological problems. Innovation in massively parallel, classical computing hardware and algorithms continues to address many of these challenges, but there is a need to simultaneously consider new paradigms to circumvent current barriers to processing speed. Accordingly, we articulate a view towards quantum computation and quantum information science, where algorithms have demonstrated potential polynomial and exponential computational speedups in certain applications, such as machine learning. The maturation of the field of quantum computing, in hardware and algorithm development, also coincides with the growth of several collaborative efforts to address questions across length and time scales, and scientific disciplines. We use this coincidence to explore the potential for quantum computing to aid in one such endeavor: the merging of insights from genetics, genomics, neuroimaging and behavioral phenotyping. By examining joint opportunities for computational innovation across fields, we highlight the need for a common language between biological data analysis and quantum computing. Ultimately, we consider current and future prospects for the employment of quantum computing algorithms in the biological sciences. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Author Correction: Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer's disease risk

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Nature genetics 2020年第3期52卷 354页

作者： Iris E Jansen Jeanne E Savage Kyoko Watanabe Julien Bryois Dylan M Williams Stacy Steinberg Julia Sealock Ida K Karlsson Sara Hägg Lavinia Athanasiu Nicola Voyle Petroula Proitsi Aree Witoelar Sven Stringer Dag Aarsland Ina S Almdahl Fred Andersen Sverre Bergh Francesco Bettella Sigurbjorn Bjornsson Anne Brækhus Geir Bråthen Christiaan de Leeuw Rahul S Desikan Srdjan Djurovic Logan Dumitrescu Tormod Fladby Timothy J Hohman Palmi V Jonsson Steven J Kiddle Arvid Rongve Ingvild Saltvedt Sigrid B Sando Geir Selbæk Maryam Shoai Nathan G Skene Jon Snaedal Eystein Stordal Ingun D Ulstein Yunpeng Wang Linda R White John Hardy Jens Hjerling-Leffler Patrick F Sullivan Wiesje M van der Flier Richard Dobson Lea K Davis Hreinn Stefansson Kari Stefansson Nancy L Pedersen Stephan Ripke Ole A Andreassen Danielle Posthuma Department of Complex Trait Genetics Center for Neurogenomics and Cognitive Research Amsterdam Neuroscience VU University Amsterdam the Netherlands. Alzheimer Center Amsterdam Department of Neurology Amsterdam Neuroscience Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam the Netherlands. Department of Medical Epidemiology and Biostatistics Karolinska Institutet Stockholm Sweden. deCODE Genetics/ Amgen Reykjavik Iceland. Interdisciplinary Graduate Program Vanderbilt University Nashville TN USA. Institute of Gerontology and Aging Research Network-Jönköping (ARN-J) School of Health and Welfare Jönköping University Jönköping Sweden. NORMENT K.G. Jebsen Centre for Psychosis Research Institute of Clinical Medicine University of Oslo Oslo Norway. Division of Mental Health and Addiction Oslo University Hospital Oslo Norway. Institute of Psychiatry Psychology and Neuroscience King's College London London UK. Institute of Clinical Medicine University of Oslo Oslo Norway. Center for Age-Related Diseases Stavanger University Hospital Stavanger Norway. Department of Neurology Akershus University Hospital Lørenskog Norway. AHUS Campus University of Oslo Oslo Norway. Department of Psychiatry of Old Age Oslo University Hospital Oslo Norway. Department of Community Medicine University of Tromsø Tromsø Norway. Norwegian National Advisory Unit on Ageing and Health Vestfold Hospital Trust Tønsberg Norway. Centre for Old Age Psychiatry Research Innlandet Hospital Trust Ottestad Norway. Department of Geriatric Medicine Landspitali University Hospital Reykjavik Iceland. Geriatric Department Oslo University Hospital Oslo Norway. Department of Neuromedicine and Movement Science Norwegian University of Science and Technology Trondheim Norway. Department of Neurology St Olav's Hospital Trondheim University Hospital Trondheim Norway. Neuroradiology Section Department of Radiology and Biomedical Imaging University of California San Francisco CA USA. Department

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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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 2018年第5期50卷 766-767页

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.

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SciPy 1.0—Fundamental algorithms for scientific computing in python

arXiv

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arXiv 2019年

作者： Virtanen, Pauli Gommers, Ralf Oliphant, Travis E. Haberland, Matt Reddy, Tyler Cournapeau, David Burovski, Evgeni Peterson, Pearu Weckesser, Warren Bright, Jonathan van der Walt, Stéfan J. Brett, Matthew Wilson, Joshua Millman, K. Jarrod Mayorov, Nikolay Nelson, Andrew R.J. Jones, Eric Kern, Robert Larson, Eric Carey, C.J. Polat, Ilhan Feng, Yu Moore, Eric W. VanderPlas, Jake Laxalde, Denis Perktold, Josef Cimrman, Robert Henriksen, Ian Quintero, E.A. Harris, Charles R. Archibald, Anne M. Ribeiro, Antônio H. Pedregosa, Fabian van Mulbregt, Paul University of Jyväskylä University of Jyväskylä FI-40014 Finland Quansight LLC AustinTX United States Ultrasound Imaging Mayo Clinic RochesterMN55902 United States Electrical Engineering Brigham Young University ProvoUT84604 United States Enthought Inc. AustinTX78701 United States Anaconda Inc AustinTX78701 United States BioResource and Agricultural Engineering Department California Polytechnic State University San Luis ObispoCA93407 United States Department of Mathematics University of California Los AngelesCA90025 United States Los Alamos National Laboratory Los AlamosNM87544 United States Independent Researcher Higher School of Economics Myasnitskaya 20 Moscow101000 Russia Independent Researcher Saue Estonia Department of Mechanics and Applied Mathematics Institute of Cybernetics Tallinn Technical University Akadeemia Rd 21 Tallinn Estonia Independent Researcher NY United States Berkeley Institute for Data Science University of California BerkeleyCA94720 United States School of Psychology University of Birmingham Edgbaston BirmighamB15 2TT United Kingdom Division of Biostatistics University of California BerkeleyCA94720 United States WayRay LLC Skolkovo Innovation Center Moscow143026 Russia Australian Nuclear Science and Technology Organisation Locked Bag 2001 Kirrawee DCNSW2232 Australia Institute for Learning and Brain Sciences University of Washington SeattleWA98195 United States College of Information and Computing Sciences University of Massachusetts Amherst AmherstMA01002 United States Berkeley Center for Cosmological Physics University of California BerkeleyCA94720 United States Bruker Biospin Corp. 15 Fortune Drive BillericaMA01821 United States University of Washington SeattleWA98195 United States New Technologies - Research Centre University of West Bohemia Univerzitní 8 Plzeň306 14 Czech Republic Oden Institute for Computational Engineering and Sciences University of Texas at Austin AustinTX7

SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release. SciPy has become a de facto standard for leveraging scientific algorithms in the Python programming language, with more than 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories, and millions of downloads per year. This includes usage of SciPy in almost half of all machine learning projects on GitHub, and usage by high profile projects including LIGO gravitational wave analysis and creation of the first-ever image of a black hole (M87). The library includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics. In this work, we provide an overview of the capabilities and development practices of the SciPy library and highlight some recent technical developments. Copyright © 2019, The Authors. All rights reserved.

关键词： Open source software

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

arXiv

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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

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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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