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Incidence trends of oral cavity, oropharyngeal, hypopharyngeal and laryngeal cancers among males in Taiwan, 1980-2019: a population-based cancer registry study

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BMC cancer 2023年第1期23卷 213页

作者： Yu-Shiun Tsai Yong-Chen Chen Tzu-I Chen Yu-Kwang Lee Chun-Ju Chiang San-Lin You Wan-Lun Hsu Li-Jen Liao School of Medicine College of Medicine Fu-Jen Catholic University New Taipei City 242 Taiwan. Master Program of Big Data Analysis in Biomedicine College of Medicine Fu Jen Catholic University New Taipei City 242 Taiwan. Data Science Center College of Medicine Fu Jen Catholic University New Taipei City 242 Taiwan. Graduate Institute of Business Administration College of Management Fu Jen Catholic University New Taipei City 242062 Taiwan. Division of General Surgery Department of Surgery National Taiwan University Hospital Taipei 100 Taiwan. Graduate Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei 10055 Taiwan. Master Program of Big Data Analysis in Biomedicine College of Medicine Fu Jen Catholic University New Taipei City 242 Taiwan. 156521@mail.fju.edu.tw. Data Science Center College of Medicine Fu Jen Catholic University New Taipei City 242 Taiwan. 156521@mail.fju.edu.tw. Otolaryngology Head and Neck Surgery Far Eastern Memorial Hospital No. 21 Sec. 2 Nanya S. Rd. Banciao Dist. New Taipei City 220 Taiwan. liaolj@ntu.edu.tw. Head and Neck Cancer Surveillance & Research Group Far Eastern Memorial Hospital New Taipei Taiwan. liaolj@ntu.edu.tw. Department of Electrical Engineering Yuan Ze University Taoyuan Taiwan. liaolj@ntu.edu.tw.

In a country with a high prevalence of cigarette smoking, betel chewing, and alcohol drinking, cancers of the oral cavity, nasopharynx, and larynx were the fourth, twelfth and seventeenth leading causes of cancer death, respectively, for men in 2020. We analyzed patients with head and neck cancer from 1980 to 2019 from the Taiwan Cancer Registration database and discussed the annual average percent change, average percent change, age period, and birth cohort. Obvious period effects and birth effects are seen in oral, oropharyngeal, and hypopharyngeal cancer; however, the most significant period effect was seen between 1990 and 2009, which mainly reflects the consumption of betel nuts per capita. In addition, the period effect lessens after 2010 in oral cancer and hypopharyngeal cancers, while oropharyngeal cancers remain an obvious period effect, which results from the rising prevalence of HPV. Due to the high prevalence rate of betel quid chewing and cigarette smoking in the 1990s, the government executed several acts. As a result, the age-adjusted incidence rates of oral, oropharyngeal, and hypopharyngeal cancers have flattened since 2010, which can be explained by the declining cigarette smoking rate. The strict policy indeed shows an obvious effect on the head and neck cancer incidence rates, and we expect to see a further decline in the future.

关键词： Age-period-cohort effect Head and neck cancers Incidence Secular trend

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Pruritus and Its Association With Cancer and Mortality in Dermatomyositis and Polymyositis: A Nationwide Cohort Study in Taiwan From 2005 to 2022

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Dermatologic Therapy 2025年第1期2025卷

作者： Der-Jr Huang Yu-Hsuan Joni Shao Yi-Hsien Shih Woan-Ruoh Lee Ling-Ya Huang Yu-Min Kuo Quoc Thao Trang Pham Hao-Jui Weng Department of Dermatology Taipei Medical University-Shuang Ho Hospital New Taipei City Taiwan shh.org.tw Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei Taiwan tmu.edu.tw Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan tmuh.org.tw Health Data Analytics and Statistics Center Office of Data Science Taipei Medical University Taipei Taiwan tmu.edu.tw Department of Dermatology School of Medicine College of Medicine Taipei Medical University Taipei Taiwan tmu.edu.tw Graduate Institute of Medical Sciences College of Medicine Taipei Medical University Taipei Taiwan tmu.edu.tw Division of Allergy Immunology and Rheumatology Department of Internal Medicine National Taiwan University Hospital and National Taiwan University Taipei Taiwan ntu.edu.tw Graduate Institute of Clinical Medicine College of Medicine National Taiwan University Taipei Taiwan ntu.edu.tw International Ph.D. Program in Cell Therapy and Regenerative Medicine College of Medicine Taipei Medical University Taipei Taiwan tmu.edu.tw Department of Dermatology Faculty of Medicine University of Medicine and Pharmacy at Ho Chi Minh City Ho Chi Minh City Vietnam hcmut.edu.vn Graduate Institute of Clinical Medicine College of Medicine Taipei Medical University Taipei Taiwan medcol.mw

Background: Pruritus is the most common initial symptom reported by patients with dermatomyositis (DM) and polymyositis (PM). However, there is limited data regarding the impact of pruritus on cancer and mortality in patients with DM and PM. In this study, we aimed to investigate how pruritus is associated with cancer and mortality in patients with DM and PM. Methods: This nationwide, population-based retrospective cohort study included adult DM and PM patients from Taiwan’s National Health Insurance Research database between 2005 and 2022. Sex- and age-matched pruritic patients, identified by over 6 weeks of antipruritic medication use, and nonpruritic patients were analyzed. The primary outcome was cancer occurrence or all-cause mortality. The association between pruritus and these outcomes was estimated using Cox proportional hazards models. Results: Among 919 matched pairs of pruritic and nonpruritic patients, cancer was observed in 19.96% in the long-term pruritic group (LPG), 14.63% in the short-term pruritic group (SPG), and 10.34% in the non-pruritic group (NPG) ( p < 0.0001). All-cause mortality was documented as 30.37% in the LPG, 29.69% in the SPG, and 37.76% in the NPG ( p < 0.0001). After adjusting for sex, age, and other comorbidities, pruritus was associated with an increased risk of cancer (hazard ratio (HR) 1.708, 95% confidence interval (CI) 1.229–2.374) and a lower risk of all-cause mortality (HR 0.483, 95% CI 0.409–0.569). Conclusion: This population-based study revealed that pruritus appeared to be associated with increased risks of cancer and decreased all-cause mortality. Thus, pruritus may serve as a pragmatic factor for risk stratification and tailored treatment strategies in DM and PM. Cancer screening, particularly for nasopharyngeal and breast cancers in East Asian populations, is recommended for patients with DM or PM, especially those presenting with pruritus. Meanwhile, patients without pruritus may require vigilant management for pote

关键词： cancer dermatomyositis idiopathic inflammatory myopathies mortality polymyositis pruritus

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Automatic Extraction of Medication Mentions from Tweets-Overview of the BioCreative VII Shared Task 3 Competition

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database : the journal of biological databases and curation 2023年第2023期2023卷 baac108页

作者： Davy Weissenbacher Karen O'Connor Siddharth Rawal Yu Zhang Richard Tzong-Han Tsai Timothy Miller Dongfang Xu Carol Anderson Bo Liu Qing Han Jinfeng Zhang Igor Kulev Berkay Köprü Raul Rodriguez-Esteban Elif Ozkirimli Ammer Ayach Roland Roller Stephen Piccolo Peijin Han V G Vinod Vydiswaran Ramya Tekumalla Juan M Banda Parsa Bagherzadeh Sabine Bergler João F Silva Tiago Almeida Paloma Martinez Renzo Rivera-Zavala Chen-Kai Wang Hong-Jie Dai Luis Alberto Robles Hernandez Graciela Gonzalez-Hernandez Department of Computational Biomedicine Cedars-Sinai Medical Center Los Angeles CA USA. DBEI The Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Computer Science and Information Engineering National Central University No. 300 Zhongda Rd Zhongli District Taoyuan 320 Taiwan. IoX Center National Taiwan University Da'an District Section 4 Roosevelt Rd No. 1 Barry Lam Hall Taipei 106 Taiwan. Research Center for Humanities and Social Sciences Academia Sinica No. 128 Section 2 Academia Rd Nangang District Taipei 115 Taiwan. Computational Health Informatics Program Boston Children's Hospital Boston MA USA. Department of Pediatrics Harvard Medical School Boston MA USA. NVIDIA Santa Clara CA USA. Department of Statistics Florida State University Tallahassee FL USA. Data and Analytics Chapter F. Hoffmann-La Roche Ltd Switzerland. Pharmaceutical Research and Early Development Roche Innovation Center Basel Switzerland. Speech and Language Technology Lab DFKI Berlin Germany. Department of Biology Brigham Young University Provo UT USA. Department of Computational Medicine and Bioinformatics Medical School University of Michigan Ann Arbor MI USA. Department of Learning Health Sciences Medical School University of Michigan Ann Arbor MI USA. School of Information University of Michigan Ann Arbor MI USA. Department of Computer Science Georgia State University Atlanta GA USA. CLaC Labs Concordia University Montreal Canada. DETI Institute of Electronics and Informatics Engineering of Aveiro University of Aveiro Portugal. Department of Computation University of A Coruña Spain. Computer Science and Engineering Department Universidad Carlos III de Madrid Madrid Spain. Big Data Laboratory Chunghwa Telecom Laboratories Taoyuan Taiwan. Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan. Department of Electrical Engineering College of Electrical Engineering and Computer Sci

This study presents the outcomes of the shared task competition BioCreative VII (Task 3) focusing on the extraction of medication names from a Twitter user's publicly available tweets (the user's 'timeline'). In general, detecting health-related tweets is notoriously challenging for natural language processing tools. The main challenge, aside from the informality of the language used, is that people tweet about any and all topics, and most of their tweets are not related to health. Thus, finding those tweets in a user's timeline that mention specific health-related concepts such as medications requires addressing extreme imbalance. Task 3 called for detecting tweets in a user's timeline that mentions a medication name and, for each detected mention, extracting its span. The organizers made available a corpus consisting of 182 049 tweets publicly posted by 212 Twitter users with all medication mentions manually annotated. The corpus exhibits the natural distribution of positive tweets, with only 442 tweets (0.2%) mentioning a medication. This task was an opportunity for participants to evaluate methods that are robust to class imbalance beyond the simple lexical match. A total of 65 teams registered, and 16 teams submitted a system run. This study summarizes the corpus created by the organizers and the approaches taken by the participating teams for this challenge. The corpus is freely available at https://***/tasks/biocreative-vii/track-3/. The methods and the results of the competing systems are analyzed with a focus on the approaches taken for learning from class-imbalanced data.

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Correction: A COVID-19 Pandemic Artificial Intelligence-Based System With Deep Learning Forecasting and Automatic Statistical data Acquisition: Development and Implementation Study

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Journal of medical Internet research 2021年第7期23卷 e31085页

作者： Cheng-Sheng Yu Shy-Shin Chang Tzu-Hao Chang Jenny L Wu Yu-Jiun Lin Hsiung-Fei Chien Ray-Jade Chen Department of Family Medicine School of Medicine College of Medicine Taipei Medical University Taipei Taiwan. Department of Family Medicine Taipei Medical University Hospital Taipei Taiwan. Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei Taiwan. Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan. Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan. Division of Plastic Surgery Department of Surgery Taipei Medical University Hospital and School of Medicine College of Medicine Taipei Medical University Taipei Taiwan. Department of Surgery School of Medicine College of Medicine Taipei Medical University Taipei Taiwan. Division of General Surgery Department of Surgery Taipei Medical University Hospital Taipei Taiwan.

[This corrects the article DOI: 10.2196/27806.].

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The evolutionary history of 2,658 cancers (vol 578, pg 122, 2020)

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NATURE 2023年第7948期614卷 E42-E42页

作者： Gerstung, Moritz Jolly, Clemency Leshchiner, Ignaty Dentro, Stefan C. Gonzalez, Santiago Rosebrock, Daniel Mitchell, Thomas J. Rubanova, Yulia Anur, Pavana Yu, Kaixian Tarabichi, Maxime Deshwar, Amit Wintersinger, Jeff Kleinheinz, Kortine Vazquez-Garcia, Ignacio Haase, Kerstin Jerman, Lara Sengupta, Subhajit Macintyre, Geoff Malikic, Salem Donmez, Nilgun Livitz, Dimitri G. Cmero, Marek Demeulemeester, Jonas Schumacher, Steven Fan, Yu Yao, Xiaotong Lee, Juhee Schlesner, Matthias Boutros, Paul C. Bowtell, David D. Zhu, Hongtu Getz, Gad Imielinski, Marcin Beroukhim, Rameen Sahinalp, S. Cenk Ji, Yuan Peifer, Martin Markowetz, Florian Mustonen, Ville Yuan, Ke Wang, Wenyi Morris, Quaid D. Spellman, Paul T. Wedge, David C. Van Loo, Peter European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Wellcome Sanger Institute Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany University of Ljubljana Ljubljana Slovenia The Francis Crick Institute London UK Big Data Institute University of Oxford Oxford UK Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Big Data Institute Li Ka Shing Centre University of Oxford Oxford UK University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Department of Applied Mathematics and Theoretical Physics Centre for Mathematical Sciences University of Cambridge Cambridge UK Department of Epidemiology and Biostatistics Memorial Sloan Kettering Cancer Center New York NY USA Department of Statistics Columbia University New York NY USA Department of Haematology University of Cambridge Cambridge UK University of Leuven Leuven Belgium Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Charlestown MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Dana-Farber Cancer Institute Boston MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Oxford NIHR Biomedical Research Centre Oxford UK Oxford NIHR Biomedical Research Centre University of Oxford Oxford UK University of Toronto Toronto Ontario Canada Vector Institute Toronto Ontario Canada Vector Institute Toronto ON Canada Department of Computer Science University of Toronto Toronto ON Canada Ontario Institute for Cancer Research Toronto Ontario Canada University of California Los Angeles

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The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

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NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

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Genomic basis for RNA alterations in cancer (vol 578, pg 129, 2020)

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NATURE 2023年第7948期614卷 E37-E37页

作者： Calabrese, Claudia Davidson, Natalie R. Demircioglu, Deniz Fonseca, Nuno A. He, Yao Lehmann, Kjong-Van Liu, Fenglin Shiraishi, Yuichi Soulette, Cameron M. Urban, Lara Greger, Liliana Li, Siliang Liu, Dongbing Perry, Marc D. Xiang, Qian Zhang, Fan Zhang, Junjun Bailey, Peter Erkek, Serap Hoadley, Katherine A. Hou, Yong Huska, Matthew R. Kilpinen, Helena Korbel, Jan O. Marin, Maximillian G. Markowski, Julia Nandi, Tannistha Pan-Hammarstrom, Qiang Pedamallu, Chandra Sekhar Siebert, Reiner Stark, Stefan G. Su, Hong Tan, Patrick Waszak, Sebastian M. Yung, Christina Zhu, Shida Awadalla, Philip Creighton, Chad J. Meyerson, Matthew Ouellette, B. F. Francis Wu, Kui Yang, Huanming Brazma, Alvis Brooks, Angela N. Goke, Jonathan Ratsch, Gunnar Schwarz, Roland F. Stegle, Oliver Zhang, Zemin European Molecular Biology Laboratory European Bioinformatics Institute Hinxton UK European Molecular Biology Laboratory European Bioinformatics Institute (EMBL-EBI) Cambridge UK Genome Biology Unit European Molecular Biology Laboratory (EMBL) Heidelberg Germany CIBIO/InBIO - Research Center in Biodiversity and Genetic Resources Universidade do Porto Vairão Portugal Berlin Institute for Medical Systems Biology Max Delbruck Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) partner site Berlin Germany German Cancer Research Center (DKFZ) Heidelberg Germany Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine Berlin Germany German Cancer Consortium (DKTK) Partner site Berlin Berlin Germany European Molecular Biology Laboratory Genome Biology Unit Heidelberg Germany Division of Computational Genomics and Systems Genetics German Cancer Research Center (DKFZ) Heidelberg Germany ETH Zurich Zurich Switzerland Memorial Sloan Kettering Cancer Center New York NY USA Weill Cornell Medical College New York NY USA SIB Swiss Institute of Bioinformatics Lausanne Switzerland University Hospital Zurich Zurich Switzerland Computational Biology Center Memorial Sloan Kettering Cancer Center New York NY USA Department of Biology ETH Zurich Zürich Switzerland Department of Computer Science ETH Zurich Zurich Switzerland Korea University Seoul South Korea Computational and Systems Biology Program Memorial Sloan Kettering Cancer Center New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine New York NY USA National University of Singapore Singapore Singapore Genome Institute of Singapore Singapore Singapore Computational and Systems Biology Genome Institute of Singap

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The Past, Present, and Future of the Brain Imaging data Structure (BIDS)

arXiv

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arXiv 2023年

作者： Poldrack, Russell A. Markiewicz, Christopher J. Appelhoff, Stefan Ashar, Yoni K. Auer, Tibor Baillet, Sylvain Bansal, Shashank Beltrachini, Leandro Bénar, Christian G. Bertazzoli, Giacomo Bhogawar, Suyash Blair, Ross W. Bortoletto, Marta Boudreau, Mathieu Brooks, Teon L. Calhoun, Vince D. Castelli, Filippo Maria Clement, Patricia Cohen, Alexander L. Cohen-Adad, Julien D'Ambrosio, Sasha de Hollander, Gilles de la Iglesia-Vayá, María de la Vega, Alejandro Delorme, Arnaud Devinsky, Orrin Draschkow, Dejan Duff, Eugene Paul DuPre, Elizabeth Earl, Eric Esteban, Oscar Feingold, Franklin W. Flandin, Guillaume Galassi, Anthony Gallitto, Giuseppe Ganz, Melanie Gau, Rémi Gholam, James Ghosh, Satrajit S. Giacomel, Alessio Gillman, Ashley G. Gleeson, Padraig Gramfort, Alexandre Guay, Samuel Guidali, Giacomo Halchenko, Yaroslav O. Handwerker, Daniel A. Hardcastle, Nell Herholz, Peer Hermes, Dora Honey, Christopher J. Innis, Robert B. Ioanas, Horea-Ioan Jahn, Andrew Karakuzu, Agah Keator, David B. Kiar, Gregory Kincses, Balint Laird, Angela R. Lau, Jonathan C. Lazari, Alberto Legarreta, Jon Haitz Li, Adam Li, Xiangrui Love, Bradley C. Lu, Hanzhang Maumet, Camille Mazzamuto, Giacomo Meisler, Steven L. Mikkelsen, Mark Mutsaerts, Henk Nichols, Thomas E. Nikolaidis, Aki Nilsonne, Gustav Niso, Guiomar Norgaard, Martin Okell, Thomas W. Oostenveld, Robert Ort, Eduard Park, Patrick J. Pawlik, Mateusz Pernet, Cyril R. Pestilli, Franco Petr, Jan Phillips, Christophe Poline, Jean-Baptiste Pollonini, Luca Raamana, Pradeep Reddy Ritter, Petra Rizzo, Gaia Robbins, Kay A. Rockhill, Alexander P. Rogers, Christine Rokem, Ariel Rorden, Chris Routier, Alexandre Saborit-Torres, Jose Manuel Salo, Taylor Schirner, Michael Smith, Robert E. Spisak, Tamas Sprenger, Julia Swann, Nicole C. Szinte, Martin Takerkart, Sylvain Thirion, Bertrand Thomas, Adam G. Torabian, Sajjad Varoquaux, Gael Voytek, Bradley Welzel, Julius Wilson, Martin Yarkoni, Tal Gorgolewski, Krzysztof J. Department of Psychology Stanford University StanfordCA United States Max Planck Institute for Human Development Berlin Germany University of Colorado Anschutz Medical Campus AuroraCO United States School of Psychology University of Surrey Guildford United Kingdom McConnell Brain Imaging Centre Montréal Neurological Institute McGill University Montréal Canada Department of Bioengineering University of California San Diego La Jolla CA United States School of Physics Astronomy Cardiff University Wales United Kingdom Institut de Neurosciences des Systèmes Marseille France Neurophysiology Lab IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli Brescia Italy Center for Mind/Brain Sciences - CIMeC University of Trento TN Rovereto Italy Brigham and Women’s Hospital BostonMA United States Massachusetts General Hospital BostonMA United States Harvard Medical School BostonMA United States Rackspace Technology San AntonioTX United States NeuroPoly Lab Polytechnique Montréal MontréalQC Canada Georgia State Georgia Tech Emory AtlantaGA United States University of Florence Sesto Fiorentino Italy Bioretics srl Cesena Italy Department of Medical Imaging Ghent University Hospital Ghent Belgium Department of Diagnostic Sciences Ghent University Ghent Belgium Department of Neurology Boston Children's Hospital BostonMA United States Dipartimento di Scienze della Salute dell'Università degli Studi di Milano Milan Italy Department of Clinical and Experimental Epilepsy University College London United Kingdom Zurich Center for Neuroeconomics Department of Economics University of Zurich Zurich Switzerland UMIB-FISABIO Valencia Spain The University of Texas at Austin AustinTX United States SCCN University of California San Diego La Jolla CA United States Department of Neurology NYU Langone Medical Center New YorkNY United States Department of Experimental Psychology University of Oxford Oxford United Kingdom UK Dementia Research Ins

The Brain Imaging data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS. © 2023, CC BY.

关键词： data structures

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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

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NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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Diversity and longitudinal records: Genetic architecture of disease associations and polygenic risk in the Taiwanese Han population

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science Advances 2025年第23期11卷

作者： Ting-Yuan Liu Hsing-Fang Lu Yu-Chia Chen Chi-Chou Liao Ying-Ju Lin Jai-Sing Yang Wen-Ling Liao Wei-De Lin Shih-Yin Chen Yu-Chuen Huang Wei-Yong Lin Yu-Huei Liu Kai-Cheng Hsu Shih-Sheng Chang Hong-Da Chen Yu-Pao Chou Jan-Gowth Chang Chung-Hsing Wang Chwen-Tzuei Chang Chung-Ming Huang Kai-Jieh Yeo Tzu-Yuan Wang Chin-Chung Yeh Jiunn-Horng Chen Chi-Ping Huang Hsueh-Chou Lai Rong-Hsing Chen Hui-Ju Lin Po-Yuan Wu Jiu-Yao Wang Chin-Chi Kuo Der-Yang Cho Chang-Hai Tsai Fuu-Jen Tsai Million-person precision medicine initiative Department of Medical Research China Medical University Hospital Taichung 40402 Taiwan. Master Program for Digital Health Innovation China Medical University Taichung 406040 Taiwan. Department of Medical Research China Medical University Hospital Taichung 40402 Taiwan. Genetic Center Department of Medical Research China Medical University Hospital Taichung 40402 Taiwan. School of Post Baccalaureate Chinese Medicine China Medical University Taichung 404333 Taiwan. Graduate Institute of Integrated Medicine College of Chinese Medicine China Medical University Taichung 406040 Taiwan. Center for Personalized Medicine Department of Medical Research China Medical University Hospital Taichung 406040 Taiwan. School of Chinese Medicine China Medical University Taichung 406040 Taiwan. Drug Development Center China Medical University Taichung 406040 Taiwan. Artificial Intelligence Center China Medical University Hospital Taichung 40402 Taiwan. Department of Neurology China Medical University Hospital Taichung 40402 Taiwan. Department of Medicine China Medical University Taichung 406040 Taiwan. Department of Laboratory Medicine China Medical University Hospital Taichung 40402 Taiwan. Department of Bioinformatics and Medical Engineering Asia University Taichung 41300 Taiwan. Department of Medical Laboratory Science and Biotechnology China Medical University Taichung Taiwan. Division of Genetics and Metabolism Children's Hospital of China Medical University Taichung 404447 Taiwan. Intelligent Diabetes Metabolism and Exercise Center Department of Internal Medicine China Medical University Hospital Taichung 40402 Taiwan. Division of Immunology and Rheumatology Department of Internal Medicine China Medical University Hospital Taichung 40402 Taiwan. Division of Endocrine and Metabolism China Medical University Hospital Taichung 40402 Taiwan. Department of Urology China Medical University Hospital Taichung 40402 Taiwan. Cen

We addressed the underrepresentation of non-European populations in genome-wide association studies (GWASs) by building HiGenome, a large-scale genetic resource for the Taiwanese Han population. Using a custom genotyping array, we integrated deidentified electronic medical records (2003 to 2021) with genomic data to enable GWASs, phenome-wide association studies, and polygenic risk score (PRS) analysis. Among 413,000 participants, 323,397 passed ancestry and quality control filtering. GWASs covered 1085 traits, focusing on diseases prevalent in Taiwan such as type 2 diabetes, chronic kidney disease, gout, and alcoholic liver damage. PRSs were calculated for 238 traits, with the strongest associations observed in musculoskeletal disorders. Incorporating PRS into clinical practice supports early risk prediction and personalized prevention. To further expand translational value, we also conducted pharmacogenomic analysis and human leukocyte antigen typing. HiGenome offers a large-scale genetic and clinical dataset from the Taiwanese Han population, supporting population-specific analyses and precision medicine development in East Asia. The hospital-based design enables continuous follow-up and longitudinal data expansion.

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