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DOMMINO 2.0: Integrating structurally resolved protein-, RNA-, and DNA-mediated Macromolecular interactions

Database 2016年第2016期2016卷 bav114页

作者： Kuang, Xingyan Dhroso, Andi Han, Jing Ginger Shyu, Chi-Ren Korkin, Dmitry Informatics Institute University of Missouri Columbia MO United States Department of Computer Science Bioinformatics and Computational Biology Program Worcester Polytechnic Institute Worcester MA United States Department of Electrical and Computer Engineering United States Department of Computer Science University of Missouri Columbia MO United States Ohio State University Comprehensive Cancer Center Columbus OH United States

Macromolecular interactions are formed between proteins, DNA and RNA molecules. Being a principle building block in macromolecular assemblies and pathways, the interactions underlie most of cellular functions. Malfunctioning of macromolecular interactions is also linked to a number of diseases. Structural knowledge of the macromolecular interaction allows one to understand the interaction's mechanism, determine its functional implications and characterize the effects of genetic variations, such as single nucleotide polymorphisms, on the interaction. Unfortunately, until now the interactions mediated by different types of macromolecules, e.g. protein-protein interactions or protein-DNA interactions, are collected into individual and unrelated structural databases. This presents a significant obstacle in the analysis of macromolecular interactions. For instance, the homogeneous structural interaction databases prevent scientists from studying structural interactions of different types but occurring in the same macromolecular complex. Here, we introduce DOMMINO 2.0, a structural Database Of Macro-Molecular INteractiOns. Compared to DOMMINO 1.0, a comprehensive database on protein-protein interactions, DOMMINO 2.0 includes the interactions between all three basic types of macromolecules extracted from PDB files. DOMMINO 2.0 is automatically updated on a weekly basis. It currently includes ∼1 040 000 interactions between two polypeptide subunits (e.g. domains, peptides, termini and interdomain linkers), ∼43 000 RNA-mediated interactions, and ∼12 000 DNA-mediated interactions. All protein structures in the database are annotated using SCOP and SUPERFAMILY family annotation. As a result, protein-mediated interactions involving protein domains, interdomain linkers, C- and N-termini, and peptides are identified. Our database provides an intuitive web interface, allowing one to investigate interactions at three different resolution levels: whole subunit network, binary intera

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26th Annual computational Neuroscience Meeting (CNS*2017) of the Organization for computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROscience 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Author Correction: Identification of genetic effects underlying type 2 diabetes in South Asian and European populations

Communications biology

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Communications biology 2022年第1期5卷 441页

作者： Marie Loh Weihua Zhang Hong Kiat Ng Katharina Schmid Amel Lamri Lin Tong Meraj Ahmad Jung-Jin Lee Maggie C Y Ng Lauren E Petty Cassandra N Spracklen Fumihiko Takeuchi Md Tariqul Islam Farzana Jasmine Anuradhani Kasturiratne Muhammad Kibriya Karen L Mohlke Guillaume Paré Gauri Prasad Mohammad Shahriar Miao Ling Chee H Janaka de Silva James C Engert Hertzel C Gerstein K Radha Mani Charumathi Sabanayagam Marijana Vujkovic Ananda R Wickremasinghe Tien Yin Wong Chittaranjan S Yajnik Salim Yusuf Habibul Ahsan Dwaipayan Bharadwaj Sonia S Anand Jennifer E Below Michael Boehnke Donald W Bowden Giriraj R Chandak Ching-Yu Cheng Norihiro Kato Anubha Mahajan Xueling Sim Mark I McCarthy Andrew P Morris Jaspal S Kooner Danish Saleheen John C Chambers Lee Kong Chian School of Medicine Nanyang Technological University Singapore 308232 Singapore. Department of Epidemiology and Biostatistics Imperial College London London W2 1PG UK. Department of Cardiology Ealing Hospital London North West Healthcare NHS Trust Middlesex UB1 3HW UK. Institute of Computational Biology Deutsches Forschungszentrum für Gesundheit und Umwelt Helmholtz Zentrum München 85764 Neuherberg Germany. Department of Informatics Technical University of Munich 85748 Garching bei München Neuherberg Germany. Department of Medicine McMaster University Hamilton ON Canada. Population Health Research Institute Hamilton Health Sciences and McMaster University Hamilton ON Canada. The University of Chicago Biological Sciences Division Public Health Sciences 5841 South Maryland Avenue MC2000 Chicago IL 60637 USA. Genomic Research on Complex diseases CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB) Hyderabad India. Translational Medicine and Human Genetics Department of Medicine University of Pennsylvania Philadelphia Pennsylvania USA. Department of Medicine Mayo Hospital Lahore Pakistan. Center for Genomics and Personalized Medicine Research Center for Diabetes Research Wake Forest School of Medicine Winston-Salem NC 37215 USA. Vanderbilt Genetics Institute Division of Genetic Medicine Vanderbilt University Medical Center Nashville TN 37232 USA. Human Genetics Center School of Public Health The University of Texas Health Science Center at Houston Houston TX 77030 USA. Department of Genetics University of North Carolina at Chapel Hill Chapel Hill NC 27599 USA. Department of Biostatistics and Epidemiology University of Massachusetts Amherst MA 01003 USA. Department of Gene Diagnostics and Therapeutics Research Institute National Center for Global Health and Medicine Tokyo Japan. U Chicago Research Bangladesh House#4 Road#2b Sector#4 Uttara Dhaka 1230 Bangladesh. Department of Public Health Faculty of Medicine

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Author Correction: The power of genetic diversity in genome-wide association studies of lipids

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Nature 2023年第7965期618卷 E19-E20页

作者： Sarah E Graham Shoa L Clarke Kuan-Han H Wu Stavroula Kanoni Greg J M Zajac Shweta Ramdas Ida Surakka Ioanna Ntalla Sailaja Vedantam Thomas W Winkler Adam E Locke Eirini Marouli Mi Yeong Hwang Sohee Han Akira Narita Ananyo Choudhury Amy R Bentley Kenneth Ekoru Anurag Verma Bhavi Trivedi Hilary C Martin Karen A Hunt Qin Hui Derek Klarin Xiang Zhu Gudmar Thorleifsson Anna Helgadottir Daniel F Gudbjartsson Hilma Holm Isleifur Olafsson Masato Akiyama Saori Sakaue Chikashi Terao Masahiro Kanai Wei Zhou Ben M Brumpton Humaira Rasheed Sanni E Ruotsalainen Aki S Havulinna Yogasudha Veturi QiPing Feng Elisabeth A Rosenthal Todd Lingren Jennifer Allen Pacheco Sarah A Pendergrass Jeffrey Haessler Franco Giulianini Yuki Bradford Jason E Miller Archie Campbell Kuang Lin Iona Y Millwood George Hindy Asif Rasheed Jessica D Faul Wei Zhao David R Weir Constance Turman Hongyan Huang Mariaelisa Graff Anubha Mahajan Michael R Brown Weihua Zhang Ketian Yu Ellen M Schmidt Anita Pandit Stefan Gustafsson Xianyong Yin Jian'an Luan Jing-Hua Zhao Fumihiko Matsuda Hye-Mi Jang Kyungheon Yoon Carolina Medina-Gomez Achilleas Pitsillides Jouke Jan Hottenga Gonneke Willemsen Andrew R Wood Yingji Ji Zishan Gao Simon Haworth Ruth E Mitchell Jin Fang Chai Mette Aadahl Jie Yao Ani Manichaikul Helen R Warren Julia Ramirez Jette Bork-Jensen Line L Kårhus Anuj Goel Maria Sabater-Lleal Raymond Noordam Carlo Sidore Edoardo Fiorillo Aaron F McDaid Pedro Marques-Vidal Matthias Wielscher Stella Trompet Naveed Sattar Line T Møllehave Betina H Thuesen Matthias Munz Lingyao Zeng Jianfeng Huang Bin Yang Alaitz Poveda Azra Kurbasic Claudia Lamina Lukas Forer Markus Scholz Tessel E Galesloot Jonathan P Bradfield E Warwick Daw Joseph M Zmuda Jonathan S Mitchell Christian Fuchsberger Henry Christensen Jennifer A Brody Mary F Feitosa Mary K Wojczynski Michael Preuss Massimo Mangino Paraskevi Christofidou Niek Verweij Jan W Benjamins Jorgen Engmann Rachel L Kember Roderick C Slieker Ken Sin Lo Nuno R Zilhao Phuong Le Marcus E Kleber Graciela E Delgado Shaofeng Huo Dai Department of Internal Medicine Division of Cardiology University of Michigan Ann Arbor MI USA. VA Palo Alto Health Care System Palo Alto CA USA. Department of Medicine Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Department of Biostatistics and Center for Statistics Genetics University of Michigan Ann Arbor MI USA. Department of Genetics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Clinical Pharmacology William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK. Endocrinology Boston Children's Hospital Boston MA USA. Medical and Population Genetics Broad Institute Cambridge MA USA. Department of Genetic Epidemiology University of Regensburg Regensburg Germany. McDonnell Genome Institute and Department of Medicine Washington University St Louis MO USA. Department of Precision Medicine Division of Genome Science National Institute of Health Cheongju-si South Korea. Tohoku Medical Megabank Organization Tohoku University Sendai Japan. Sydney Brenner Institute for Molecular Bioscience Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa. Center for Research on Genomics and Global Health National Human Genome Research Institute National Institutes of Health Bethesda MD USA. Blizard Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Wellcome Sanger Institute Hinxton UK. Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA. Atlanta VA Health Care System Decatur GA USA. Malcolm Randall VA Medical Center Gainesville FL USA. Division of Vascular Sur

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Concurrent starbursts in molecular gas disks within a pair of colliding galaxies at z = 1.52

arXiv

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arXiv 2018年

作者： Silverman, J.D. Daddi, E. Rujopakarn, W. Renzini, A. Mancini, C. Bournaud, F. Puglisi, A. Rodighiero, G. Liu, D. Sargent, M. Arimoto, N. Béthermin, M. Fensch, J. Hayward, C.C. Kartaltepe, J. Kashino, D. Koekemoer, A. Magdis, G. McCracken, H.J. Nagao, T. Sheth, K. Smolčić, V. Valentino, F. Kavli Institute for the Physics and Mathematics of the Universe University of Tokyo Kashiwa277-8583 Japan Laboratoire AIM CEA/DSM-CNRS-Universite Paris Diderot Irfu/Service d'Astrophysique CEA Saclay Department of Physics Faculty of Science Chulalongkorn University 254 Phayathai Road Pathumwan Bangkok10330 Thailand Don Kaeo Mae Rim Chiang Mai50180 Thailand Kavli Institute for the Physics and Mathematics of the Universe Todai Institutes for Advanced Study University of Tokyo Kashiwa277-8583 Japan Instituto Nazionale de Astrofisica Osservatorio Astronomico di Padova v.co dell'Osservatorio 5 PadovaI-35122 Italy Dipartimento di Fisica e Astronomia Universita di Padova vicolo Osservatorio 3 Padova35122 Italy Astronomy Centre Department of Physics and Astronomy University of Sussex BrightonBN1 9QH United Kingdom Astronomy Program Department of Physics and Astronomy Seoul National University 599 Gwanak-ro Gwanak-gu Seoul151-742 Korea Republic of Subaru Telescope 650 North A'ohoku Place Hilo Hawaii96720 United States European Southern Observatory Karl-Schwarzschild-Str. 2 Garching85748 Germany European Southern Observatory Karl-Schwarzschild-Str. 2 Garching bei München85748 Germany Center for Computational Astrophysics Flatiron Institute 162 Fifth Avenue New YorkNY10010 United States School of Physics and Astronomy Rochester Institute of Technology 84 Lomb Memorial Drive RochesterNY14623 United States Institute of Astronomy ETH Zürich Wolfgang-Pauli-Strasse 27 ZürichCH-8093 Switzerland Space Telescope Science Institute 3700 San Martin Drive BaltimoreMD21218 United States Cosmic DAWN Centre Niels Bohr Institute University of Copenhagen Juliane Mariesvej 30 Copenhagen2100 Denmark Institut d'Astrophysique de Paris CNRS UMR 7095 and UPMC 98bis boulevard Arago ParisF-75014 France Graduate School of Science and Engineering Ehime University 2-5 Bunkyo-cho Matsuyama790-8577 Japan NASA Headquaters 300 E. St SW WashingtonDC2054

We report on the discovery of a merger-driven starburst at z = 1:52, PACS-787, based on high signal-to-noise ALMA observations. CO(5-4) and continuum emission (850μm) at a spatial resolution of 0.3" reveal two compact (r1/2 ∼ 1 kpc) and interacting molecular gas disks at a separation of 8.6 kpc thus indicative of an early stage in a merger. With a SFR of 991 Mo yr-1, this starburst event should occur closer to final coalescence, as usually seen in hydrodynamical simulations. From the CO size, inclination, and velocity profile for both disks, the dynamical mass is calculated through a novel method that incorporates a calibration using simulations of galaxy mergers. Based on the dynamical mass, we measure (1) the molecular gas mass, independent from the CO luminosity, (2) the ratio of the total gas mass and the CO(1 - 0) luminosity (αCO ≡ Mgas/L'CO1-0), and (3) the gas-to-dust ratio, with the latter two being lower than typically assumed. We find that the high star formation, triggered in both galaxies, is caused by a set of optimal conditions: a high gas mass/fraction, a short depletion time (τdepl = 85 and 67 Myrs) to convert gas into stars, and the interaction of likely counter-rotating molecular disks that may accelerate the loss of angular momentum. The state of interaction is further established by the detection of di_use CO and continuum emission, tidal debris that bridges the two nuclei and is associated with stellar emission seen by HST/WFC3. This observation demonstrates the power of ALMA to study the dynamics of galaxy mergers at high redshift. Copyright © 2018, The Authors. All rights reserved.

关键词： Galaxies

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Nat Genet:单细胞分析解开结直肠癌细胞的神秘面纱

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现代生物医学进展 2017年第15期17卷 I0003-I0003页

作者： Huipeng Li, Elise T Courtois, Debarka Sengupta, Yuliana Tan Shyam Prabhakar Elise T Courtois, Yuliana Tan Paul Robson Debarka Sengupta Kok Hao Chen, Jolene Jie Lin Goh Paul Jongjoon Choi Say Li Kong, Axel M Hillmer Iain Beehuat Tan Clarinda Chua Iain Beehuat Tan Lim Kiat Hon Wah Siew Tan Mark Wong Lawrence J K Wee Iain Beehuat Tan Paul Robson Paul Robson Paul Robson Computational and Systems Biology Genome Institute of Singapore Singapore Developmental Cellomics Laboratory Genome Institute of Singapore Singapore Department of Computer Science and Engineering and Center for Computational Biology Indraprastha Institute of Information Technology Delhi India Synthetic Biology Genome Institute of Singapore Singapore Cancer Therapeutics and Stratified Oncology Genome Institute of Singapore Singapore Department of Medical Oncology National Cancer Centre Singapore Singapore Department of Pathology Singapore General Hospital Singapore Department of Colorectal Surgery Singapore General Hospital Singapore Data Analytics Department Institute for Infocomm Research Singapore Program in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore The Jackson Laboratory for Genomic Medicine Farmington Connecticut USA Department of Genetics and Genome Sciences Institute for Systems Genomics University of Connecticut Farmington Connecticut USA Department of Biological Sciences National University of Singapore Singapore.

结合单细胞基因组学和计算机技术，一个研究团队（包括来自杰克逊实验室（JAx）单细胞生物学主任Paul Robson博士在内）鉴定出了11种结直肠癌肿瘤的癌细胞组成及邻近的非癌细胞。这对于更好的肿瘤靶向诊断和治疗很重要。”使用单细胞测... 详细信息

结合单细胞基因组学和计算机技术，一个研究团队（包括来自杰克逊实验室（JAx）单细胞生物学主任Paul Robson博士在内）鉴定出了11种结直肠癌肿瘤的癌细胞组成及邻近的非癌细胞。这对于更好的肿瘤靶向诊断和治疗很重要。”使用单细胞测序。”JAX科学家、这篇发表在Nature Genetics上的文章共同第一作者Elise Courtois说道。”我们可以根据肿瘤中的细胞组成将结直肠癌进一步分类。因为每种亚型的肿瘤病人生存率存在差别，我们的方法将为肿瘤医生提供更多的关于肿瘤预后和治疗的信息。”

关键词：单细胞分析结直肠癌癌细胞 Nat 细胞组成肿瘤病计算机技术细胞生物学

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Automated, high throughput exploration of process–structure–property relationships using the MapReduce paradigm

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Materials Discovery 2015年 1卷 21-28页

作者： Wodo, Olga Zola, Jaroslaw Sarath Pokuri, Balaji Sesha Du, Pengfei Ganapathysubramanian, Baskar University at Buffalo Materials Design and Innovation Department Buffalo United States University at Buffalo Mechanical and Aerospace Engineering Department Buffalo United States University at Buffalo Computational and Data-Enabled Science and Engineering Program Buffalo United States University at Buffalo Computer Science and Engineering Department Buffalo United States University at Buffalo Biomedical Informatics Department Buffalo United States Iowa State University Mechanical Engineering Department Ames United States Iowa State University Electrical and Computer Engineering Department Ames United States

The microstructure of a material intimately affects the performance of a device made from this material. The microstructure, in turn, is affected by the processing pathway used to fabricate the device. This forms the process–structure–property triangle that is central to material science. There has been increasing interest to comprehensively understand and subsequently exploit process–structure–property (PSP) relationships to design processing pathways that result in tailored microstructures exhibiting optimal properties. However, unraveling process–structure–property relationships usually requires systematic and tedious combinatorial search of process and system variables to identify the microstructures that are produced. This is further complicated by the necessity to interrogate the properties of the huge set of corresponding microstructures. Motivated by this challenge, we focus on developing a generic methodology to establish and explore PSP pathways. We leverage recent advances in high performance computing (HPC) and high throughput computing (HTC) with the premise that a domain expert should be able to focus on domain specific PSP problems while the highly specialized HPC/HTC knowledge needed to approach such problems should be hidden from the domain expert. Our hypothesis is that PSP exploration can be naturally formulated in terms of a standard paradigm in cloud computing, namely the MapReduce programming model. We show how reformulating PSP exploration into a MapReduce workflow enables us to take advantage of advances in cloud computing while requiring minimal specialized knowledge of HPC. We illustrate this generic approach by exploring PSP relationships relevant to organic photovoltaics. We focus on identifying microstructural traits that correlate with specific properties of the photovoltaic process: exciton generation, exciton dissociation and charge generation. We integrate a graph-based microstructure characterization tool, and a microstructure-aware

关键词： Drift diffusion model High throughput analysis MapReduce paradigm Organic solar cells Process–structure–processing Thermal annealing

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Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the Right to Sight: an analysis for the Global Burden of Disease Study (vol 2, pg 144, 2021)

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LANCET GLOBAL HEALTH 2021年第4期9卷 E408-E408页

作者： Steinmetz, Jaimie D. Vision and Eye Research Institute Anglia Ruskin University Cambridge United Kingdom Biomedical Informatics Seoul National University Hospital Seoul South Korea Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Institute of Health Services Research Yonsei University Seoul South Korea Department of Ophthalmology University of Washington Seattle WA United States Department of Mathematics Imperial College London London United Kingdom WHO Collaborating Centre for Public Health Education and Training Imperial College London London United Kingdom Department of Primary Care and Public Health Imperial College London London United Kingdom School of Population and Global Health University of Melbourne Carlton VIC Australia School of Optometry and Vision Science UNSW Sydney NSW Australia Brien Holden Vision Institute Sydney Australia Department of Ophthalmology University of Adelaide Adelaide SA Australia Department of Parasitology and Mycology Jahrom University of Medical Sciences Jahrom Iran Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Ophthalmic Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Ophthalmology Shahid Beheshti University of Medical Sciences Tehran Iran Research Institute for Endocrine Sciences Shahid Beheshti University of Medical Sciences Tehran Iran Ophthalmic Epidemiology Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Health Services Management Department Qazvin University of Medical Sciences Qazvin Iran Department of Systems Populations and Leadership University of Michigan Ann Arbor MI United States Department of Medicine Sofia Ismail Memorial Medical Centre Bogura Bangladesh The Fred Hollows Foundation Sydney NSW Australia Berhan Public Health & Eye Care Consultancy Addis A

Hospital El Salvador: a novel paradigm of intensive care in response to COVID-19 in central America. Lancet Glob Health 2021;9: e241?42?In this Comment, the conflict of interest statement should have included the following: ?By virtue of their roles within a public hospital or the Ministry of Health, MB, LC, WH, and XS are government employees. The findings and conclusions in the Comment are only those of the authors.? This correction has been made as of Feb 26, 2021.

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The cluster heritage project with XMM-Newton: Mass assembly and thermodynamics at the endpoint of structure formation I. programme overview

arXiv

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arXiv 2020年

作者： Arnaud, M. Ettori, S. Pratt, Gabriel W. Rossetti, M. Eckert, D. Gastaldello, F. Gavazzi, R. Kay, S.T. Lovisari, L. Maughan, B.J. Pointecouteau, E. Sereno, M. Bartalucci, I. Bonafede, A. Bourdin, H. Cassano, R. Duffy, R.T. Iqbal, A. Maurogordato, S. Rasia, E. Sayers, J. Andrade-Santos, F. Aussel, H. Barnes, D.J. Barrena, R. Borgani, S. Burkutean, S. Clerc, N. Corasaniti, P.-S. Cuillandre, J.-C. de Grandi, S. de Petris, M. Dolag, K. Donahue, M. Ferragamo, A. Gaspari, M. Ghizzardi, S. Gitti, M. Haines, C.P. Jauzac, M. Johnston-Hollitt, M. Jones, C. Kéruzoré, F. LeBrun, A.M.C. Mayet, F. Mazzotta, P. Melin, J.-B. Molendi, S. Nonino, M. Okabe, N. Paltani, S. Perotto, L. Pires, S. Radovich, M. Rubino-Martin, J.-A. Salvati, L. Saro, A. Sartoris, B. Schellenberger, G. Streblyanska, A. Tarrío, P. Tozzi, P. Umetsu, K. van der Burg, R.F.J. Vazza, F. Venturi, T. Yepes, G. Zarattini, S. AIM CEA CNRS Université Paris-Saclay Université Paris Diderot Sorbonne Paris Cité Gif-sur-YvetteF-91191 France INAF Osservatorio di Astrofisica e Scienza dello Spazio via Pietro Gobetti 93/3 Bologna40129 Italy INFN Sezione di Bologna viale Berti Pichat 6/2 BolognaI-40127 Italy INAF IASF-Milano via A. Corti 12 MilanoI-20133 Italy Department of Astronomy University of Geneva ch. d'Écogia 16 VersoixCH-1290 Switzerland CNRS Sorbonne Université UMR 7095 Institut d'Astrophysique de Paris 98 bis Boulevard Arago Paris75014 France Jodrell Bank Centre for Astrophysics Department of Physics and Astronomy School of Natural Sciences The University of Manchester ManchesterM13 9PL United Kingdom Center for Astrophysics | Harvard & Smithsonian 60 Garden Street CambridgeMA02138 United States HH Wills Physics Laboratory University of Bristol Tyndall Ave BristolBS8 1TL United Kingdom IRAP Université de Toulouse CNRS CNES UPS 9 av du colonel Roche BP44346 Toulouse Cedex 431028 France Dipartimento di Fisica e Astronomia Universitá di Bologna Via Gobetti 92/3 Bologna40121 Italy INAF Istituto di Radio Astronomia Via Gobetti 101 Bologna40129 Italy Hamburger Sternwarte Gojenbergsweg 112 Hamburg21029 Germany Università degli studi di Roma Tor Vergata via della ricerca scientifica 1 Roma00133 Italy Université Côte d'Azur Observatoire de la Côte d'Azur CNRS Laboratoire Lagrange Nice France INAF - Osservatorio Astronomico di Trieste via Tiepolo 11 TriesteI-34131 Italy IFPU - Institute for Fundamental Physics of the Universe via Beirut 2 Trieste34151 Italy California Institute of Technology PasadenaCA91125 United States Department of Physics Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology CambridgeMA02139 United States C/ Vía Láctea s/n La Laguna TenerifeE-38205 Spain Universidad de La Laguna Departamento de Astrofísica C/ Astrofísico Francisco Sánchez s/n La Laguna TenerifeE-38206 Spain D

The Cluster HEritage project with XMM-Newton - Mass Assembly and Thermodynamics at the Endpoint of structure formation (CHEX-MATE) is a three-mega-second Multi-Year Heritage programme to obtain X-ray observations of a minimally-biased, signal-to-noise-limited sample of 118 galaxy clusters detected by Planck through the Sunyaev-Zeldovich effect. The programme, described in detail in this paper, aims to study the ultimate products of structure formation in time and mass. It is composed of a census of the most recent objects to have formed (Tier-1: 0.05 14 M 500 14 M), together with a sample of the highest mass objects in the Universe (Tier-2: z 500 > 7.25 × 1014 M). The programme will yield an accurate vision of the statistical properties of the underlying population, measure how the gas properties are shaped by collapse into the dark matter halo, uncover the provenance of non-gravitational heating, and resolve the major uncertainties in mass determination that limit the use of clusters for cosmological parameter estimation. We will acquire X-ray exposures of uniform depth, designed to obtain individual mass measurements accurate to 15 − 20% under the hydrostatic assumption. We present the project motivations, describe the programme definition, and detail the ongoing multi-wavelength observational (lensing, SZ, radio) and theoretical effort that is being deployed in support of the project. Copyright © 2020, The Authors. All rights reserved.

关键词： Thermodynamics

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Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals (vol 52, pg 1314, 2020)

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NATURE GENETICS 2021年第5期53卷 762-762页

作者： Surendran, Praveen Feofanova, Elena V. Lahrouchi, Najim Ntalla, Ioanna Karthikeyan, Savita Cook, James Chen, Lingyan Mifsud, Borbala Yao, Chen Kraja, Aldi T. Cartwright, James H. Hellwege, Jacklyn N. Giri, Ayush Tragante, Vinicius Thorleifsson, Gudmar Liu, Dajiang J. Prins, Bram P. Stewart, Isobel D. Cabrera, Claudia P. Eales, James M. Akbarov, Artur Auer, Paul L. Bielak, Lawrence F. Bis, Joshua C. Braithwaite, Vickie S. Brody, Jennifer A. Daw, E. Warwick Warren, Helen R. Drenos, Fotios Nielsen, Sune Fallgaard Faul, Jessica D. Fauman, Eric B. Fava, Cristiano Ferreira, Teresa Foley, Christopher N. Franceschini, Nora Gao, He Giannakopoulou, Olga Giulianini, Franco Gudbjartsson, Daniel F. Guo, Xiuqing Harris, Sarah E. Havulinna, Aki S. Helgadottir, Anna Huffman, Jennifer E. Hwang, Shih-Jen Kanoni, Stavroula Kontto, Jukka Larson, Martin G. Li-Gao, Ruifang Lindstrom, Jaana Lotta, Luca A. Lu, Yingchang Luan, Jian'an Mahajan, Anubha Malerba, Giovanni Masca, Nicholas G. D. Mei, Hao Menni, Cristina Mook-Kanamori, Dennis O. Mosen-Ansorena, David Muller-Nurasyid, Martina Pare, Guillaume Paul, Dirk S. Perola, Markus Poveda, Alaitz Rauramaa, Rainer Richard, Melissa Richardson, Tom G. Sepulveda, Nuno Sim, Xueling Smith, Albert V. Smith, Jennifer A. Staley, James R. Stanakova, Alena Sulem, Patrick Theriault, Sebastien Thorsteinsdottir, Unnur Trompet, Stella Varga, Tibor V. Velez Edwards, Digna R. Veronesi, Giovanni Weiss, Stefan Willems, Sara M. Yao, Jie Young, Robin Yu, Bing Zhang, Weihua Zhao, Jing-Hua Zhao, Wei Zhao, Wei Evangelou, Evangelos Aeschbacher, Stefanie Asllanaj, Eralda Blankenberg, Stefan Bonnycastle, Lori L. Bork-Jensen, Jette Brandslund, Ivan Braund, Peter S. Burgess, Stephen Cho, Kelly Christensen, Cramer Connell, John de Mutsert, Renee Dominiczak, Anna F. Dorr, Marcus Eiriksdottir, Gudny Farmaki, Aliki-Eleni Gaziano, J. Michael Grarup, Niels Grove, Megan L. Hallmans, Goran Hansen, Torben Have, Christian T. Heiss, Gerardo Jorgensen, Marit E. Jousilahti, Pekka Kajantie, Eero Kamat, Mihir Karajamaki, AnneMari Kar British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge UK British Heart Foundation Centre of Research Excellence University of Cambridge Cambridge UK Health Data Research UK Cambridge Wellcome Genome Campus and University of Cambridge Cambridge UK Rutherford Fund Fellow Department of Public Health and Primary Care University of Cambridge Cambridge UK MRC Biostatistics Unit University of Cambridge Cambridge UK National Institute for Health Research Cambridge Biomedical Research Centre University of Cambridge and Cambridge University Hospitals Cambridge UK MRC Integrative Epidemiology Unit (IEU) Population Health Sciences Bristol Medical School University of Bristol Bristol UK Robertson Centre for Biostatistics University of Glasgow Glasgow UK MRC Epidemiology Unit University of Cambridge School of Clinical Medicine Cambridge UK Department of Immunology and Inflammation Imperial College London London UK Centre for Non-communicable Disease Research (CNCR) Dhaka Bangladesh National Institute for Health Research (NIHR) Blood and Transplant Research Unit (BTRU) in Donor Health and Genomics at the University of Cambridge Cambridge UK Department of Human Genetics Wellcome Sanger Institute Wellcome Genome Campus Hinxton Cambridge UK Department of Biostatistics and Epidemiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Center for Non-Communicable Diseases Karachi Pakistan Department of Genetics Novo Nordisk Research Centre Oxford Oxford UK Human Genetics Center Department of Epidemiology Human Genetics and Environmental Sciences School of Public Health University of Texas Health Science Center at Houston Houston TX USA Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA Cardiovascular Research Center Center for Genomic Medicine

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