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Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000-17: analysis for the Global Burden of Disease Study 2017 (vol 395, pg 1779, 2020)

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LANCET 2020年第10239期395卷 1762-1762页

作者： Reiner, R. C., Jr. Hay, S., I Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Global Health School of Medicine University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States College of Health and Medical Sciences Haramaya University Harar Ethiopia Department of Epidemiology and Biostatistics Haramaya University Harar Ethiopia Department of Medical Laboratory Sciences Haramaya University Harar Ethiopia School of Nursing and Midwifery Haramaya University Harar Ethiopia School of Pharmacy Haramaya University Harar Ethiopia School of Public Health Haramaya University Harar Ethiopia Haramaya University Harar Ethiopia Advanced Diagnostic and Interventional Radiology Research Center Tehran University of Medical Sciences Tehran Iran Cancer Biology Research Center Tehran University of Medical Sciences Tehran Iran Cancer Research Institute Tehran University of Medical Sciences Tehran Iran Department of Economics and Management Sciences for Health Tehran University of Medical Sciences Tehran Iran Department of Environmental Health Engineering Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran Department of Microbiology Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran Hematology-Oncology and Stem Cell Transplantation Research Center Tehran University of Medical Sciences Tehran Iran Iran National Institute of Health Research Tehran University of Medical Sciences Tehran Iran Metabolomics and

Summary Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood *** We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, to estimate posterior distributions of diarrhoea prevalence, incidence, and mortality from 2000 to 2017. From these data, we estimated the burden of diarrhoea at varying subnational levels (termed units) by spatially aggregating draws, and we investigated the drivers of subnational patterns by creating aggregated risk factor *** The greatest declines in diarrhoeal mortality were seen in south and southeast Asia and South America, where 54·0% (95% uncertainty interval [UI] 38·1-65·8), 17·4% (7·7-28·4), and 59·5% (34·2-86·9) of units, respectively, recorded decreases in deaths from diarrhoea greater than 10%. Although children in much of Africa remain at high risk of death due to diarrhoea, regions with the most deaths were outside Africa, with the highest mortality units located in Pakistan. Indonesia showed the greatest within-country geographical inequality; some regions had mortality rates nearly four times the average country rate. Reductions in mortality were correlated to improvements in water, sanitation, and hygiene (WASH) or reductions in child growth failure (CGF). Similarly, most high-risk areas had poor WASH, high CGF, or low oral rehydration therapy *** By co-analysing geospatial trends in d

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1047. Asymptomatic SARS-CoV-2 Infections, BNT162b2 mRNA COVID 19 Vaccine-Related Symptoms, and Correlates of Immunity in Post-Vaccination Breakthrough Infections in the Prospective Assessment of SARS-CoV-2 Seroconversion (PASS) Study

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Open Forum Infectious Diseases 2022年第SUPPLEMENT_2期9卷

作者： Goguet, Emilie Weiss, Carol D Olsen, Cara Powers, John H Coggins, Si’Ana A Tribble, David Davies, Julian Illinik, Luca Lusvarghi, Sabrina Edwards, Margaret Sanchez Jackson-Thompson, Belinda Hollis-Perry, Monique Pollett, Simon Wang, Gregory Alcorta, Yolanda Wong, Mimi Saunders, David Mohammed, Roshila Ortega, Orlando Parmelee, Edward Lindrose, Alyssa R Haines-Hull, Hannah Moser, Matthew S Samuels, Emily C Tso, Marana S Graydon, Elizabeth Malloy, Allison M Schully, Kevin Burgess, Timothy Broder, Christopher C Laing, Eric D Mitre, Edward HJF USUHS Bethesda Maryland U.S. Food and Drug Administration Silver Spring Maryland Uniformed Services University Bethesda Maryland Leidos Biomedical Research Rockville Maryland HJF/USUHS Rockville Maryland Infectious Disease Clinical Research Program Department of Preventive Medicine and Biostatistics Uniformed Services University of the Health Sciences Bethesda MD USA Bethesda Maryland Infectious Diseases Clinical Research Program Henry M. Jackson Foundation Bethesda Maryland Henry M. Jackson Foundation for the Advancement of Military Medicine Portsmouth Virginia Division of Viral Products Office of Vaccine Research and Review Center for Biologics Evaluation and Research U.S. Food and Drug Admninistration Silver Spring Maryland Infectious Disease Clinical Research Program Department of Preventive Medicine and Biostatistics Uniformed Services University of the Health SciencesHenry M. Jackson Foundation for the Advancement of Military Medicine Bethesda Maryland Naval Medical Research Center Bethesda Maryland CTC NMRC General Dynamics Information Technology Bethesda Maryland Uniformed Services University of the Health Sciences Bethesda MD USA Bethesda Maryland HJF TMU USUHS Bethesda Maryland HJF Infectious Diseases Clinical Research Program Bethesda Maryland Infectious Disease Clinical Research Program Department of Preventive Medicine and Biostatistics Uniformed Services University of the Health Sciences Bethesda Maryland Department of Pediatrics Uniformed Services University of the Health Sciences Bethesda MD USA Bethesda Maryland NMRC/BDRD Frederick Maryland Department of Microbiology and Immunology Uniformed Services University Bethesda MD Bethesda Maryland

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BPS2025 - Single-cell mass-based mixture model for perturbation response characterization in breast cancer

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Biophysical Journal 2025年第3期124卷 639a-639a页

作者： Fakhar U. Singhera Robert Kimmerling Xingyao Chen Leigh Campbell Jonathan Katz Reva Basho Justin Wells Albert Kovatich Michael F. Press Jerry S. Lee Mork Family Department of Chemical Engineering and Materials Science University of Southern California Los Angeles CA USA Travera Inc. Medford MA USA Ellison Institute of Technology Los Angeles CA USA Murtha Cancer Center Research Program Department of Surgery Uniformed Services University of the Health Sciences Bethseda MD USA The Henry M. Jackson Foundation for the Advancement of Military Medicine Inc. Bethseda MD USA Department of Medicine Keck School of Medicine University of Southern California Los Angeles CA USA Division of Surgical Oncology Walter Reed National Military Medical Center Bethseda MD USA Department of Pathology Keck School of Medicine University of Southern California Los Angeles CA USA

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Optogenetic activation of cortical microglia promotes neuronal activity and pain hypersensitivity

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Cell Reports 2025年第5期44卷 115717页

作者： Yi, Min-Hee Liu, Yi Liu, Yong U. Lee, Jinkyung Hanumaihgari, Priyanka Parusel, Sebastian Bosco, Dale B. Wang, Lingxiao Zheng, Jiaying Shi, Wu Eauchai, Lattawat Chompoopong, Supin Hunt, Christine L. Wu, Long-Jun Department of Neurology Mayo Clinic Rochester 55905 MN United States Department of Microbiology and Immunology Chonnam National University Medical School Jeollanam-do Hwasun 58128 South Korea Institute for Biomedical Science (IBS) of Chonnam National University Hwasun Hospital Jeollanam-do Hwasun 58128 South Korea BioMedical Sciences Graduate Program (BMSGP) Chonnam National University Jeollanam-do Hwasun 58128 South Korea Center for Neuroimmunology and Glial Biology Institute of Molecular Medicine University of Texas Health Science Center Houston 77030 TX United States Department of Anesthesiology First Affiliated Hospital of Sun Yat-sen University Guangdong Guangzhou 510080 China Department of Anesthesiology Guangzhou First People's Hospital School of Medicine South China University of Technology Guangzhou China Department of Neuroscience Johns Hopkins Medical Institute Baltimore 21205 MD United States Faculty of Medicine Siriraj Hospital Mahidol University Bangkok 10700 Thailand Department of Pain Medicine Mayo Clinic Jacksonville 32224 FL United States

Chronic pain following peripheral nerve injury is accompanied by increased neuronal activity in the somatosensory cortex. However, whether and how cortical microglia contribute to these changes is less understood. To this end, we applied an optogenetic strategy to specifically target cortical microglia and investigate their function in behavioral pain sensitization. We found that optogenetic activation of microglia in the primary somatosensory cortex (S1) via red-activated channelrhodopsin (ReaChR) triggered pain hypersensitivity and affective-motivational responses in mice. Remarkably, S1-targeted optogenetic stimulation increased microglial landscape changes and ATP release. In addition, optogenetic stimulation altered the microglial proteomic profile, upregulated neuronal c-Fos expression, and enhanced neuronal Ca²⁺ signaling in the S1. Our results provide mechanistic evidence linking cortical microglia with neuronal hyperactivity and chronic pain behaviors. © 2025 The Author(s)

关键词： ATP chronic pain CP: Neuroscience microglia microglial landscape change optogenetics ReaChR somatosensory cortex two-photon imaging

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BPS2025 - Structure and inhibition of SARS-CoV-2 spike refolding in membranes

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Biophysical Journal 2025年第3期124卷 580a-580a页

作者： Walther Mothes Mikey W. Grunst Zhuan Qin Esteban Dodero-Rojas Shilei Ding Jeremie Prevost Yaozong Chen Yanping Hu Marzena Pazgier Shenping Wu Xuping Xie Andrés Finzi José N. Onuchic Paul C. Whitford Wenwei Li Department of Microbial Pathogenesis Yale University New Haven CT USA Systems Synthetic and Physical Biology PhD Program Rice University Houston TX USA Centre de Recherche du CHUM Montréal QC Canada Département de Microbiologi Université de Montréal Montréal QC Canada School of Medicine Uniformed Services University of the Health Sciences Bethesda MD USA Department of Biochemistry and Molecular Biology University of Texas Medical Branch Galveston TX USA Department of Pharmacology Yale University West Haven CT USA Center for Theoretical Biological Physics Rice University Houston TX USA Department of Physics Northeastern University Boston MA USA

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A global effort to dissect the human genetic basis of resistance to SARS-CoV-2 infection (Oct, 10.1038/s41590-021-01030-z, 2021)

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NATURE IMMUNOLOGY 2022年第2期23卷 341-341页

作者： Andreakos, Evangelos Abel, Laurent Vinh, Donald C. Kaja, Elzbieta Drolet, Beth A. Zhang, Qian O'Farrelly, Cliona Novelli, Giuseppe Rodriguez-Gallego, Carlos Haerynck, Filomeen Prando, Carolina Pujol, Aurora Su, Helen C. Casanova, Jean-Laurent Spaan, Andras N. Laboratory of Immunobiology Center for Clinical Experimental Surgery and Translational Research Biomedical Research Foundation of the Academy of Athens Athens Greece St. Giles Laboratory of Human Genetics of Infectious Diseases Rockefeller Branch The Rockefeller University New York NY USA Laboratory of Human Genetics of Infectious Diseases Necker Branch INSERM U1163 Necker Hospital for Sick Children Paris France University of Paris Imagine Institute Paris France Department of Medicine Division of Infectious Diseases McGill University Health Centre Montréal Québec Canada Infectious Disease Susceptibility Program Research Institute McGill University Health Centre Montréal Québec Canada MNM Diagnostics Inc. Lewes DE USA Department of Dermatology School of Medicine and Public Health University of Wisconsin Madison WI USA Comparative Immunology Group School of Biochemistry and Immunology Trinity Biomedical Sciences Institute Trinity College Dublin Dublin Ireland Department of Biomedicine and Prevention University of Rome Tor Vergata Rome Italy Department of Immunology Hospital Universitario de Gran Canaria Dr. Negrín Canarian Health System Las Palmas de Gran Canaria Las Palmas Spain Department of Clinical Sciences University Fernando Pessoa Canarias Las Palmas de Gran Canaria Las Palmas Spain Department of Pediatric Immunology and Pulmonology Centre for Primary Immunodeficiency Ghent (CPIG) PID Research Laboratory Jeffrey Modell Diagnosis and Research Centre Ghent University Hospital Ghent Belgium Faculdades Pequeno Príncipe Instituto de Pesquisa Pelé Pequeno Príncipe Curitiba Brazil Neurometabolic Diseases Laboratory Bellvitge Biomedical Research Institute (IDIBELL) L’Hospitalet de Llobregat Barcelona Spain Catalan Institution of Research and Advanced Studies (ICREA) Barcelona Spain Center for Biomedical Research on Rare Diseases U759 (CIBERER) ISCIII Barcelona Spain Intramural Research Program National Institute of Allergy and Infectious Disease

SARS-CoV-2 infections display tremendous interindividual variability, ranging from asymptomatic infections to life-threatening disease. Inborn errors of, and autoantibodies directed against, type I interferons (IFNs) account for about 20% of critical COVID-19 cases among SARS-CoV-2-infected individuals. By contrast, the genetic and immunological determinants of resistance to infection per se remain unknown. Following the discovery that autosomal recessive deficiency in the DARC chemokine receptor confers resistance to Plasmodium vivax, autosomal recessive deficiencies of chemokine receptor 5 (CCR5) and the enzyme FUT2 were shown to underlie resistance to HIV-1 and noroviruses, respectively. Along the same lines, we propose a strategy for identifying, recruiting, and genetically analyzing individuals who are naturally resistant to SARS-CoV-2 infection.

关键词： Infection Viral infection Biomedicine general Immunology Infectious Diseases

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Author Correction: Multiplexed CRISPR-based microfluidic platform for clinical testing of respiratory viruses and identification of SARS-CoV-2 variants

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Nature medicine 2024年第1期30卷 307页

作者： Nicole L Welch Meilin Zhu Catherine Hua Juliane Weller Marzieh Ezzaty Mirhashemi Tien G Nguyen Sreekar Mantena Matthew R Bauer Bennett M Shaw Cheri M Ackerman Sri Gowtham Thakku Megan W Tse Jared Kehe Marie-Martine Uwera Jacqueline S Eversley Derek A Bielwaski Graham McGrath Joseph Braidt Jeremy Johnson Felecia Cerrato Gage K Moreno Lydia A Krasilnikova Brittany A Petros Gabrielle L Gionet Ewa King Richard C Huard Samantha K Jalbert Michael L Cleary Nicholas A Fitzgerald Stacey B Gabriel Glen R Gallagher Sandra C Smole Lawrence C Madoff Catherine M Brown Matthew W Keller Malania M Wilson Marie K Kirby John R Barnes Daniel J Park Katherine J Siddle Christian T Happi Deborah T Hung Michael Springer Bronwyn L MacInnis Jacob E Lemieux Eric Rosenberg John A Branda Paul C Blainey Pardis C Sabeti Cameron Myhrvold Broad Institute of MIT and Harvard Cambridge MA USA. nicole_welch@g.harvard.edu. Harvard Program in Virology Division of Medical Sciences Harvard Medical School Boston MA USA. nicole_welch@g.harvard.edu. Broad Institute of MIT and Harvard Cambridge MA USA. Department of Biological Engineering Massachusetts Institute of Technology Cambridge MA USA. Division of Infectious Diseases Department of Medicine Massachusetts General Hospital Boston MA USA. Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK. Harvard Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA. Division of Health Sciences and Technology Harvard Medical School and Massachusetts Institute of Technology Cambridge MA USA. Department of Organismic and Evolutionary Biology Harvard University Cambridge MA USA. Harvard/Massachusetts Institute of Technology MD-PhD Program Harvard Medical School Boston MA USA. Department of Systems Biology Harvard Medical School Boston MA USA. State Health Laboratories Rhode Island Department of Health Providence RI USA. Massachusetts Department of Public Health Boston MA USA. Influenza Division National Center for Immunization and Respiratory Diseases Centers for Disease Control and Prevention Atlanta GA USA. African Centre of Excellence for Genomics of Infectious Diseases Redeemer's University Ede Nigeria. Department of Biological Sciences College of Natural Sciences Redeemer's University Ede Nigeria. Molecular Biology Department and Center for Computational and Integrative Biology Massachusetts General Hospital Boston MA USA. Department of Immunology and Infectious Disease Harvard T.H. Chan School of Public Health Harvard University Boston MA USA. Department of Pathology Massachusetts General Hospital and Harvard Medical School Boston MA USA. Koch Institute for Integrative Cancer Research at Massachusetts Institute of Technology Cambridge MA USA. Broad Institute of MIT and Harvard Cambridge MA USA. pardis

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The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions

arXiv

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arXiv 2023年

作者： Ma, Jun Xie, Ronald Ayyadhury, Shamini Ge, Cheng Gupta, Anubha Gupta, Ritu Gu, Song Zhang, Yao Lee, Gihun Kim, Joonkee Lou, Wei Li, Haofeng Upschulte, Eric Dickscheid, Timo de Almeida, José Guilherme Wang, Yixin Han, Lin Yang, Xin Labagnara, Marco Gligorovski, Vojislav Scheder, Maxime Rahi, Sahand Jamal Kempster, Carly Pollitt, Alice Espinosa, Leon Mignot, Tâm Middeke, Jan Moritz Eckardt, Jan-Niklas Li, Wangkai Li, Zhaoyang Cai, Xiaochen Bai, Bizhe Greenwald, Noah F. Van Valen, David Weisbart, Erin Cimini, Beth A. Cheung, Trevor Brück, Oscar Bader, Gary D. Wang, Bo Peter Munk Cardiac Centre University Health Network TorontoON Canada Department of Laboratory Medicine and Pathobiology University of Toronto TorontoON Canada Vector Institute TorontoON Canada Department of Molecular Genetics University of Toronto TorontoON Canada Donnelly Centre University of Toronto TorontoON Canada Princess Margaret Cancer Centre University Health Network TorontoON Canada School of Medicine and Pharmacy Ocean University of China Qingdao China New Delhi India Laboratory Oncology Dr. BRA-IRCH All India Institute of Medical Sciences New Delhi India Department of Image Reconstruction Nanjing Anke Medical Technology Co. Ltd. Nanjing China Shanghai Artificial Intelligence Laboratory Shanghai China Graduate School of AI KAIST Seoul Korea Republic of Shenzhen Research Institute of Big Data Shenzhen China Shenzhen China Helmholtz AI Research Center Jülich Jülich Germany Faculty of Mathematics and Natural Sciences Institute of Computer Science Heinrich Heine University Düsseldorf Düsseldorf Germany Hinxton United Kingdom Champalimaud Foundation - Centre for the Unknown Lisbon Portugal Department of Bioengineering Stanford University Palo AltoCA United States Tandon School of Engineering New York University New YorkNY United States School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen China Lausanne Switzerland School of Biological Sciences University of Reading Reading United Kingdom Laboratoire de Chimie Bactérienne CNRS Université Aix Marseille UMR Institut de Microbiologie de la Méditerranée Marseille France Department of Internal Medicine I University Hospital Dresden Technical University Dresden Dresden Germany Else Kroener Fresenius Center for Digital Health Technical University Dresden Dresden Germany Department of Automation University of Science and Technology of China Hefei China Institute of Advanced Technology University of Science and Technology of China Hefei Chi

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimental settings. Here, we present a multi-modality cell segmentation benchmark, comprising over 1500 labeled images derived from more than 50 diverse biological experiments. The top participants developed a Transformer-based deep-learning algorithm that not only exceeds existing methods but can also be applied to diverse microscopy images across imaging platforms and tissue types without manual parameter adjustments. This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging. © 2023, CC BY-NC-ND.

关键词： Deep learning

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Cell culture-derived extracellular vesicles: Considerations for reporting cell culturing parameters

Journal of Extracellular Biology

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Journal of Extracellular Biology 2023年第10期2卷 e115页

作者： Shekari, Faezeh Alibhai, Faisal J. Baharvand, Hossein Börger, Verena Bruno, Stefania Davies, Owen Giebel, Bernd Gimona, Mario Salekdeh, Ghasem Hosseini Martin-Jaular, Lorena Mathivanan, Suresh Nelissen, Inge Nolte-’t Hoen, Esther Perut, Francesca Pluchino, Stefano Pocsfalvi, Gabriella Salomon, Carlos Soekmadji, Carolina Staubach, Simon Torrecilhas, Ana Claudia Shelke, Ganesh Vilas Tertel, Tobias Zhu, Dandan Théry, Clotilde Witwer, Kenneth Nieuwland, Rienk Department of Stem Cells and Developmental Biology Cell Science Research Center Royan Institute for Stem Cell Biology and Technology ACECR Tehran Iran Advanced Therapy Medicinal Product Technology Development Center (ATMP-TDC) Cell Science Research Center Royan Institute for Stem Cell Biology and Technology ACECR Tehran Iran University Health Network Toronto Canada Department of Developmental Biology School of Basic Sciences and Advanced Technologies in Biology University of Science and Culture Tehran Iran Institute for Transfusion Medicine University Hospital Essen University of Duisburg-Essen Essen Germany Department of Medical Sciences and Molecular Biotechnology Center University of Torino Turin Italy School of Sport Exercise and Health Sciences Loughborough University Loughborough United Kingdom GMP Unit Spinal Cord Injury & Tissue Regeneration Centre Salzburg (SCI-TReCS) and Research Program “Nanovesicular Therapies” Paracelsus Medical University Salzburg Austria Faculty of Natural Sciences Macquarie University North Ryde NSW Australia Institut Curie INSERM U932 and Curie CoreTech Extracellular Vesicles PSL Research University Paris France Department of Biochemistry and Genetics La Trobe Institute for Molecular Science La Trobe University Melbourne VIC Australia VITO (Flemish Institute for Technological Research) Health department Boeretang Belgium Department of Biomolecular Health Sciences Faculty of Veterinary Medicine Utrecht University Utrecht Netherlands School of Pharmacy and Pharmaceutical Sciences & Trinity Biomedical Sciences Institute Trinity College Dublin Dublin Ireland Biomedical Science and Technologies and Nanobiotechnology Lab IRCCS Istituto Ortopedico Rizzoli Bologna Italy Department of Clinical Neurosciences University of Cambridge Cambridge United Kingdom Institute of Biosciences and BioResources National Research Council Naples Italy Translational Extracellular Vesicles in Obstetrics and Gynae-Oncology Group UQ Centre for Cli

Cell culture-conditioned medium (CCM) is a valuable source of extracellular vesicles (EVs) for basic scientific, therapeutic and diagnostic applications. Cell culturing parameters affect the biochemical composition, release and possibly the function of CCM-derived EVs (CCM-EV). The CCM-EV task force of the Rigor and Standardization Subcommittee of the International Society for Extracellular Vesicles aims to identify relevant cell culturing parameters, describe their effects based on current knowledge, recommend reporting parameters and identify outstanding questions. While some recommendations are valid for all cell types, cell-specific recommendations may need to be established for non-mammalian sources, such as bacteria, yeast and plant cells. Current progress towards these goals is summarized in this perspective paper, along with a checklist to facilitate transparent reporting of cell culturing parameters to improve the reproducibility of CCM-EV research. © 2023 The Authors. Journal of Extracellular Biology published by Wiley Periodicals LLC on behalf of International Society for Extracellular Vesicles.

关键词： cell culture-conditioned medium cellular therapy ectosomes exosomes extracellular vesicles in vitro reproducibility rigor standardization

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OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials

arXiv

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arXiv 2023年

作者： Eastman, Peter Galvelis, Raimondas Peláez, Raúl P. Abreu, Charlles R.A. Farr, Stephen E. Gallicchio, Emilio Gorenko, Anton Henry, Michael M. Hu, Frank Huang, Jing Krämer, Andreas Michel, Julien Mitchell, Joshua A. Pande, Vijay S. Rodrigues, João P.G.L.M. Rodriguez-Guerra, Jaime Simmonett, Andrew C. Singh, Sukrit Swails, Jason Turner, Philip Wang, Yuanqing Zhang, Ivy Chodera, John D. De Fabritiis, Gianni Markland, Thomas E. Department of Chemistry Stanford University StanfordCA94305 United States Acellera Labs C Dr Trueta 183 Barcelona08005 Spain C Dr. Aiguader 88 Barcelona08003 Spain Chemical Engineering Department School of Chemistry Federal University of Rio de Janeiro Rio de Janeiro68542 Brazil Redesign Science Inc. 180 Varick St. New YorkNY10014 United States EaStCHEM School of Chemistry University of Edinburgh EH9 3FJ United Kingdom Department of Chemistry and Biochemistry Brooklyn College The City University of New York NY United States Ph.D. Program in Chemistry Ph.D. Program in Biochemistry The Graduate Center of the City University of New York New YorkNY United States Stream HPC Koningin Wilhelminaplein 1 - 40601 Amsterdam1062 HG Netherlands Computational and Systems Biology Program Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New YorkNY10065 United States Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University 18 Shilongshan Road Zhejiang Hangzhou310024 China Department of Mathematics and Computer Science Freie Universität Berlin Arnimallee 12 Berlin14195 Germany The Open Force Field Initiative Open Molecular Software Foundation DavisCA95616 United States Andreessen Horowitz 2865 Sand Hill Rd Menlo ParkCA94025 United States Department of Structural Biology Stanford University StanfordCA94305 United States Charité Universitätsmedizin Berlin In silico Toxicology and Structural Bioinformatics Virchowweg 6 Berlin10117 Germany Laboratory of Computational Biology National Heart Lung and Blood Institute National Institutes of Health BethesdaMD20892 United States Entos Inc. 9310 Athena Circle La Jolla CA92037 United States College of Engineering Virginia Polytechnic Institute State University BlacksburgVA24061 United States Simons Center for Computational Physical Chemistry Center for Data Science New York University 24 Waverly Place New YorkNY10004 United States T

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUDA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features on simulations of cyclin-dependent kinase 8 (CDK8) and the green fluorescent protein (GFP) chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations at only a modest increase in cost. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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