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Blood Vessels, Thrombosis & Hemostasis 2025年

作者： Thomas E. Plate Asaad Trabolsi Rachel S. Kronenfeld Leticia E. Campoverde Dan Morgenstern-Kaplan Alyssa J. Mercadel Michael Caballero Wei Zhao Gerald A. Soff Sylvester Comprehensive Cancer Center University of Miami Miller School of Medicine Miami Fl USA Hematology Oncology Fellowship Program Jackson Memorial Health System/ University of Miami Miami Fl USA Division of Pediatric Hematology/Oncology University of Miami/Jackson Memorial Hospital Miami FL Internal Medicine Residency program division of internal medicine Department of Medicine University of Miami/ Jackson Memorial Hospital Miami Division of Gynecologic Oncology Department of Obstetrics Gynecology and Reproductive Sciences University of Miami Leonard M. Miller School of Medicine Miami Data Science and Engineering UHealth Information Technology University of Miami Miami FL Biostatistics and Bioinformatics Shared Resource Sylvester Comprehensive Cancer Center University of Miami Miami FL Division of Hematology Department of Medicine University of Miami Miller School of Medicine Miami Fl USA

Venous thromboembolism (VTE) is a frequent complication in patients with lung cancer, but the risk factors and incidence in different lung cancer subtypes have not been fully characterized. Despite multiple studies supporting the use of VTE prophylaxis in patients with cancer at increased risk of VTE by the Khorana score (KS), routine use of VTE prophylaxis is uncommon in clinical practice for these patients. This study further characterizes the risk factors and incidence of VTE and in patients with lung cancer at a university cancer center. Further, we assessed the association of KS and its individual components with overall survival in this same group of patients with lung cancer. Utilizing natural language processing and human review to detect thrombotic events in the electronic medical record, a 12-month incidence of 10.1% was identified in the 632 lung cancer patients analyzed. Significant risk factors included age <60 years and white blood cell count (WBC) ≥ 11× 10 9 /L, but KS itself was not significantly associated with VTE. The median overall survival was 12 months with VTE. The KS, age ≥ 60 years, stage III-IV, WBC ≥ 11× 10 9 /L, Hgb <10 gm/dL, BMI, surgery and VTE were identified as significant predictors of death. These findings warrant further validation, as the KS and two of its individual components in this study of lung cancer were significantly associated with reduced overall survival.

关键词： Lung cancer thrombosis Khorana Score cancer associated thrombosis

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A structural haplotype in the 17q21.31 MAPT region is associated with increased risk for chronic traumatic encephalopathy endophenotypes

Cell Reports Medicine

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Cell Reports Medicine 2025年第5期6卷 102084-102084页

作者： Han, Xudong Zhang, Yichi Petrosky, Jillian N. Bald, Sarah Sherva, Richard M. Labadorf, Adam Cherry, Jonathan D. Chung, Jaeyoon Farrell, Kurt Abdolmohammadi, Bobak Durape, Shruti Martin, Brett M. Palmisano, Joseph N. Farrell, John J. Alvarez, Victor E. Huber, Bertrand R. Dwyer, Brigid Daneshvar, Daniel H. Jun, Gyungah R. Lunetta, Kathryn L. Goldstein, Lee E. Katz, Douglas I. Cantu, Robert C. Shenton, Martha E. Cummings, Jeffrey L. Reiman, Eric M. Stern, Robert A. Alosco, Michael L. Tripodis, Yorghos Farrer, Lindsay A. Stein, Thor D. Crary, John F. McKee, Ann C. Mez, Jesse Bioinformatics Graduate Program Boston University Boston MA United States Section of Biomedical Genetics Department of Medicine Boston University Chobanian & Avedisian School of Medicine Boston MA United States Department of Neurology Boston University Chobanian & Avedisian School of Medicine Boston MA United States Boston University Alzheimer's Disease Research Center Boston University Chobanian & Avedisian School of Medicine Boston MA United States Boston VA Healthcare System Boston MA United States Boston University Chronic Traumatic Encephalopathy Center Boston University Boston MA United States Department of Pathology and Laboratory Medicine Boston University Chobanian & Avedisian School of Medicine Boston MA United States Departments of Pathology Neuroscience and Artificial Intelligence & Human Health Neuropathology Brain Bank & Research CoRE Friedman Brain Institute Ronald M. Loeb Center for Alzheimer's Disease Icahn School of Medicine at Mount Sinai New York NY United States Biostatistics and Epidemiology Data Analytics Center Boston University School of Public Health Boston MA United States Bedford VA Healthcare System Bedford MA United States Braintree Rehabilitation Hospital Braintree MA United States Department of Physical Medicine and Rehabilitation Harvard Medical School Boston MA United States Department of Rehabilitation and Human Performance Brain Injury Research Center Icahn School of Medicine at Mount Sinai New York NY United States Department of Neurology Icahn School of Medicine at Mount Sinai New York NY United States Department of Biostatistics Boston University School of Public Health Boston MA United States Department of Ophthalmology Boston University Chobanian & Avedisian School of Medicine Boston MA United States Departments of Biomedical Electrical & Computer Engineering Boston University College of Engineering Boston MA United States Departments of Radiology and Psychiatry Boston University Chobanian & Avedisia

Chronic traumatic encephalopathy (CTE) is a neurodegenerative tauopathy associated with repetitive head impact (RHI) exposure. Genetic variation in the 17q21.31 region, containing microtubule-associated protein tau (MAPT), has been implicated in tauopathies but has not been investigated in CTE. The region includes a megabase-long inversion (H1/H2) and copy-number variations, including α, β, and γ segments, which can be characterized as nine segregating structural haplotypes. We leveraged array SNP data and a reference panel across the 17q21.31 region to impute structural haplotypes and test their association with CTE endophenotypes in 447 European ancestry brain donors with RHI exposure. The H1β1γ1 haplotype was significantly associated with dementia and semi-quantitative tau burden in multiple cortical and medial temporal regions commonly affected in CTE. H1β1γ1 differential expression analyses in dorsolateral frontal cortex implicated cis-acting genes and inflammatory pathways. Taken together, the H1β1γ1 haplotype may help explain CTE heterogeneity among those with similar RHI exposure. © 2025 The Authors

关键词： 17q21.31 chronic traumatic encephalopathy dementia differential gene expression immune system MAPT repetitive head impacts structural haplotypes tauopathy traumatic brain injury

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Rapid generation of gene-targeted EPS-derived mouse models through tetraploid complementation

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Protein & Cell 2019年第1期10卷 20-30页

作者： Haibo Li Chaoran Zhao Jun Xu Yaxing Xu Chunmei Cheng Yinan Liu Ting Wang Yaqin Du Liangfu Xie Jingru Zhao Yanchuang Han Xiaobao Wang Yun Bai Hongkui Deng Department of Cell Biology School of Basic Medical SciencesPeking University Stem Cell Research CenterState Key Laboratory of Natural and Biomimetic DrugsPeking University Health Science Center and the MOE Key Laboratory of Cell Proliferation and DifferentiationCollege of Life SciencesPeking-Tsinghua Center for Life SciencesPeking UniversityBeijing 100191China Shenzhen Stem Cell Engineering Laboratory Key Laboratory of Chemical GenomicsPeking University Shenzhen Graduate SchoolShenzhen 518055China Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program College of Life SciencesPeking UniversityBeijing 100871China BeiHao Stem Cell and Regenerative Medicine Translational Research Institute BeijingChina

One major strategy to generate genetically modified mouse models is gene targeting in mouse embryonic stem(ES)cells,which is used to produce gene-targeted mice for wide applications in ***,a major bottleneck in this approach is that the robustness of germiine transmission of gene-targeted ES cells can be significantly reduced by their genetic and epigenetic instability after long-term culturing,which impairs the efficiency and robustness of mouse model ***,we have established a new type of pluripotent cells termed extended pluripotent stem(EPS)cells,which have superior developmental potency and robust germline competence compared to conventional mouse ES *** this study,we demonstrate that mouse EPS cells well maintain developmental potency and genetic stability after long-term *** on gene targeting in mouse EPS cells,we established a new approach to directly and rapidly generate gene-targeted mouse models through tetraploid complementation,Haibo Li and Chaoran Zhao contributed equally to this *** supplementary material The online version of this article(https://***/10.1007/s13238-018-0556-1)contains supplementary material,which is available to authorized *** could be accomplished in approximately 2 ***,using this approach,we successfully constructed mouse models in which the human interleukin 3(IL3)or interleukin 6(IL6)gene was knocked into its corresponding locus in the mouse *** study demonstrates the feasibility of using mouse EPS cells to rapidly generate mouse models by gene targeting,which have great application potential in biomedical research.

关键词： tetraploid complementation EPS mouse model CRISPR/Cas9

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Multiomics analysis reveals microbial diversity and activity through spontaneous fermentation of Theobroma cacao

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Heliyon 2024年第23期10卷 e40542页

作者： da Costa Fonseca, Ynara Bahule, Celina Eugenio Herrera, Hector da Silva Martins, Luiza Helena Lopes, Alessandra Santos Cassoli, Juliana Silva Trindade, Felipe Costa Chagas da Costa, Isa Rebecca Henrique de Oliveira Costa, Paulo Oliveira, Guilherme Borges da Silva Valadares, Rafael Graduate Program in Agricultural Applied Biotechnology Federal Rural University of Amazonia President Tancredo Neves Ave 2501 Belém CEP 66.077-830 Brazil Vale Institute of Technology Boaventura da Silva Street 955 Belém CEP 66050-090 Brazil Center of Studies in Science and Technology (NECET) Rovuma University Niassa Branch Lichinga Mozambique Departamento de Ciencias Forestales Facultad de Ciencias Agropecuarias y Medioambiente Universidad de La Frontera Temuco 4811230 Chile Center for Biodiversity and Ecological Sustainability (C-BEST) Facultad de Ciencias Agropecuarias y Medioambiente Universidad de La Frontera Chile Institute of Animal Health and Production Federal Rural University of Amazonia President Tancredo Neves Ave. 2501 Belém CEP 66077-830 Brazil Faculty of Food Engineering Institute of Technology Federal University of Pará Belém CEP 66075-110 Brazil Laboratory of Omics Sciences Institute of Biological Sciences Guamá Campus Federal University of Pará Belém 66075-110 Brazil

To gain insight into the active microbiota during spontaneous fermentation of Theobroma cacao L., this study assessed protein diversity during 120 h using a combined metabarconding and metaproteomics approach. During the first days of fermentation, most of the peptides were associated with T. cacao and yeast (0–72 h). Peptides associated with bacteria became more abundant after 72 h of fermentation, coinciding with a decrease in peptides associated with cocoa (96–120 h). In addition to the known microorganisms involved in fermentation, such as Saccharomyces, Lactobacillus and Acetobacter, novel genera were also metabolically active, including Microvirga, Inquilinus, Candolleomyces and Lasiodiplodia. The results showed a consistency in the main genera detected by both techniques, but the identification of unexplored genera such as Inquilinus, Microvirga, Cyphellophora and Ashbya gossypii, among others, suggests that this omics approach needs to be used together for more comprehensive results on spontaneous fermentation. In conclusion, studies combining techniques such as metabarcoding and metaproteomics should be considered in fermentation studies, as a single technique would result in omissions regarding the activity of certain microorganisms that may be important for the course of spontaneous fermentation. © 2024

关键词： Bacteria Cocoa Metabarcoding Metaproteomics

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Polygenic risk modeling for prediction of epithelial ovarian cancer risk (vol 30, pg 349, 2021)

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EUROPEAN JOURNAL OF HUMAN GENETICS 2022年第5期30卷 630-631页

作者： Dareng, Eileen O. Tyrer, Jonathan P. Barnes, Daniel R. Jones, Michelle R. Yang, Xin Aben, Katja K. H. Adank, Muriel A. Agata, Simona Andrulis, Irene L. Anton-Culver, Hoda Antonenkova, Natalia N. Aravantinos, Gerasimos Arun, Banu K. Augustinsson, Annelie Balmana, Judith Bandera, Elisa V. Barkardottir, Rosa B. Barrowdale, Daniel Beckmann, Matthias W. Beeghly-Fadiel, Alicia Benitez, Javier Bermisheva, Marina Bernardini, Marcus Q. Bjorge, Line Black, Amanda Bogdanova, Natalia V. Bonanni, Bernardo Borg, Ake Brenton, James D. Budzilowska, Agnieszka Butzow, Ralf Buys, Saundra S. Cai, Hui Caligo, Maria A. Campbell, Ian Cannioto, Rikki Cassingham, Hayley Chang-Claude, Jenny Chanock, Stephen J. Chen, Kexin Chiew, Yoke-Eng Chung, Wendy K. Claes, Kathleen B. M. Colonna, Sarah Cook, Linda S. Couch, Fergus J. Daly, Mary B. Dao, Fanny Davies, Eleanor de la Hoya, Miguel de Putter, Robin Dennis, Joe DePersia, Allison Devilee, Peter Diez, Orland Ding, Yuan Chun Doherty, Jennifer A. Domchek, Susan M. Dork, Thilo du Bois, Andreas Durst, Matthias Eccles, Diana M. Eliassen, Heather A. Engel, Christoph Evans, Gareth D. Fasching, Peter A. Flanagan, James M. Fortner, Renee T. Machackova, Eva Friedman, Eitan Ganz, Patricia A. Garber, Judy Gensini, Francesca Giles, Graham G. Glendon, Gord Godwin, Andrew K. Goodman, Marc T. Greene, Mark H. Gronwald, Jacek Hahnen, Eric Haiman, Christopher A. Hakansson, Niclas Hamann, Ute Hansen, Thomas V. O. Harris, Holly R. Hartman, Mikael Heitz, Florian Hildebrandt, Michelle A. T. Hogdall, Estrid Hogdall, Claus K. Hopper, John L. Huang, Ruea-Yea Huff, Chad Hulick, Peter J. Huntsman, David G. Imyanitov, Evgeny N. Isaacs, Claudine Jakubowska, Anna James, Paul A. Janavicius, Ramunas Jensen, Allan Johannsson, Oskar Th. John, Esther M. Jones, Michael E. Kang, Daehee Karlan, Beth Y. Karnezis, Anthony Kelemen, Linda E. Khusnutdinova, Elza Kiemeney, Lambertus A. Kim, Byoung-Gie Kjaer, Susanne K. Komenaka, Ian Kupryjanczyk, Jolanta Kurian, Allison W. Kwong, Ava Lambrechts, Diether Larson, Melissa C. Lazaro, Conxi L University of Cambridge Centre for Cancer Genetic Epidemiology Department of Public Health and Primary Care Cambridge UK University of Cambridge Centre for Cancer Genetic Epidemiology Department of Oncology Cambridge UK Center for Bioinformatics and Functional Genomics Cedars-Sinai Medical Center Los Angeles CA USA Radboud University Medical Center Radboud Institute for Health Sciences Nijmegen The Netherlands Netherlands Comprehensive Cancer Organisation Utrecht The Netherlands The Netherlands Cancer Institute—Antoni van Leeuwenhoek hospital Family Cancer Clinic Amsterdam The Netherlands Veneto Institute of Oncology IOV—IRCCS Immunology and Molecular Oncology Unit Padua Italy Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital Fred A. Litwin Center for Cancer Genetics Toronto ON Canada University of Toronto Department of Molecular Genetics Toronto ON Canada University of California Irvine Department of Epidemiology Genetic Epidemiology Research Institute Irvine CA USA N.N. Alexandrov Research Institute of Oncology and Medical Radiology Minsk Belarus ‘Agii Anargiri’ Cancer Hospital Athens Greece University of Texas MD Anderson Cancer Center Department of Breast Medical Oncology Houston TX USA Lund University Department of Cancer Epidemiology Clinical Sciences Lund Sweden Vall d’Hebron Institute of Oncology Hereditary cancer Genetics Group Barcelona Spain University Hospital of Vall d’Hebron Department of Medical Oncology Barcelona Spain Rutgers Cancer Institute of New Jersey Cancer Prevention and Control Program New Brunswick NJ USA Landspitali University Hospital Department of Pathology Reykjavik Iceland University of Iceland BMC (Biomedical Centre) Faculty of Medicine Reykjavik Iceland University Hospital Erlangen Friedrich-Alexander-University Erlangen-Nuremberg Department of Gynecology and Obstetrics Comprehensive Cancer Center ER-EMN Erlangen Germany Vanderbilt University School of Medicine Division of Epidemiology Department

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

关键词： Clinical genetics Genetic markers Risk factors Biomedicine general Human Genetics Bioinformatics Gene Expression Cytogenetics

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AAA + ATPase Thorase inhibits mTOR signaling through the disassembly of the mTOR complex 1

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Nature Communications 2022年第1期13卷 4836页

作者： Umanah, George K. E. Abalde-Atristain, Leire Khan, Mohammed Repon Mitra, Jaba Dar, Mohamad Aasif Chang, Melissa Tangella, Kavya McNamara, Amy Bennett, Samuel Chen, Rong Aggarwal, Vasudha Cortes, Marisol Worley, Paul F. Ha, Taekjip Dawson, Ted M. Dawson, Valina L. Neuroregeneration and Stem Cell Programs Institute for Cell Engineering Johns Hopkins University School of Medicine Baltimore 21205 MD United States Department of Neurology Johns Hopkins University School of Medicine Baltimore 21205 MD United States Cellular and Molecular Medicine Graduate Program Johns Hopkins University School of Medicine Baltimore 21205 MD United States Department of Materials Science and Engineering University of Illinois at Urbana-Champaign Urbana 61801 IL United States Department of Biophysics and Biophysical Chemistry Johns Hopkins University Baltimore 21205 MD United States Solomon H. Snyder Department of Neuroscience Johns Hopkins University School of Medicine Baltimore 21205 MD United States Departments of Biophysics and Biophysical Chemistry Biophysics and Biomedical Engineering JHU Howard Hughes Medical Institute Baltimore 21205 MD United States Department of Pharmacology and Molecular Sciences Johns Hopkins University School of Medicine Baltimore 21205 MD United States Department of Physiology Johns Hopkins University School of Medicine Baltimore 21205 MD United States Division of Neuroscience National Institute of Neurological Disorders and Stroke National Institutes of Health Bethesda MD United States Vollum Institute Oregon Health & Science University Portland 97239 OR United States

The mechanistic target of rapamycin (mTOR) signals through the mTOR complex 1 (mTORC1) and the mTOR complex 2 to maintain cellular and organismal homeostasis. Failure to finely tune mTOR activity results in metabolic dysregulation and disease. While there is substantial understanding of the molecular events leading mTORC1 activation at the lysosome, remarkably little is known about what terminates mTORC1 signaling. Here, we show that the AAA + ATPase Thorase directly binds mTOR, thereby orchestrating the disassembly and inactivation of mTORC1. Thorase disrupts the association of mTOR to Raptor at the mitochondria-lysosome interface and this action is sensitive to amino acids. Lack of Thorase causes accumulation of mTOR-Raptor complexes and altered mTORC1 disassembly/re-assembly dynamics upon changes in amino acid availability. The resulting excessive mTORC1 can be counteracted with rapamycin in vitro and in vivo. Collectively, we reveal Thorase as a key component of the mTOR pathway that disassembles and thus inhibits mTORC1. © 2022, The Author(s).

关键词： Cell signalling Lysosomes Mechanisms of disease

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Recent advances in molecularly imprinted polymers toward biomedical healthcare devices

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Biosensors & bioelectronics 2025年 287卷 117637页

作者： Youngjun Seo Yonghwan Kim Jaeheung Kim Hyo Gi Jung Jae Won Jang Hyunji Kim Kyo Seon Hwang Dongtak Lee Sang Won Lee Jeong Hoon Lee Dae Sung Yoon School of Biomedical Engineering Korea University Seoul 02841 Republic of Korea Interdisciplinary Program in Precision Public Health Korea University Seoul 02841 Republic of Korea. Department of Clinical Pharmacology and Therapeutics College of Medicine Kyung Hee University Seoul 02447 Republic of Korea. Department of Bioengineering & Nano-bioengineering Research Center for Bio Materials and Process Development Incheon National University Incheon 22012 Republic of Korea Division of Bioengineering Incheon National University Incheon 22012 Republic of Korea. Terasaki Institute for Biomedical Innovation Los Angeles CA 90064 USA. Electronic address: skylsw5@korea.ac.kr. KU-KIST Graduate School of Converging Science and Technology Korea University Seoul 02841 Republic of Korea Department of Integrative Energy Engineering College of Engineering Korea University Seoul 02841 Republic of Korea. Electronic address: hellojhlee@korea.ac.kr. Interdisciplinary Program in Precision Public Health Korea University Seoul 02841 Republic of Korea Astrion Inc Seoul 02841 Republic of Korea. Electronic address: dsyoon@korea.ac.kr.

Following the increase in the global aging population, the importance of monitoring various disease-related biomarkers at an early stage has increased to ensure the health of the elderly. In an aging society, point-of-care (POC) systems are needed to care for elderly people who have physical and mental disorders. In light of the increasing prominence of POC systems, there is a growing effort to address the limitations associated with conventional receptors in wearable devices by substituting them with molecularly imprinted polymer (MIP). MIPs are well-known synthetic receptors engineered with specific binding cavities based on the "lock and key" principle. They could be synthesized in various configurations depending on specific types of monomers and templates. Compared to conventional receptors such as antibodies and aptamers, MIPs exhibit outstanding advantages, including good stability, cost-effectiveness, ease of synthesis, reusability, and broad applicability. These advantages have led to their extensive application in biomedical healthcare devices. This review summarizes a comparative analysis of sensors utilized for the detection of disease-specific biomarkers through diverse MIP applications and methodologies. Furthermore, we evaluated recent advancements in the miniaturization of MIPs and their integration with wearable biomedical devices for comprehensive healthcare monitoring applications. Finally, we delineated the existing limitations that need to be surmounted for the effective implementation of MIP-based biomedical devices and outlined future objectives for the enhancement of wearable and wireless biomedical healthcare monitoring devices.

关键词： Biomarker healthcare monitoring Molecularly imprinted polymer Point-of-care Wearable biomedical devices

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Publisher Correction: Three-dimensional atomic mapping of ligands on palladium nanoparticles by atom probe tomography

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Nature communications 2021年第1期12卷 5521页

作者： Kyuseon Jang Se-Ho Kim Hosun Jun Chanwon Jung Jiwon Yu Sangheon Lee Pyuck-Pa Choi Department of Materials Science and Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea. Department of Microstructure Physics and Alloy Design Max-Planck-Institut für Eisenforschung GmbH Düsseldorf Germany. Department of Chemical Engineering and Materials Science Ewha Womans University Seoul Republic of Korea. Department of Chemical Engineering and Materials Science Ewha Womans University Seoul Republic of Korea. sang@ewha.ac.kr. Graduate Program in System Health Science and Engineering Ewha Womans University Seoul Republic of Korea. sang@ewha.ac.kr. Department of Materials Science and Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon Republic of Korea. p.choi@kaist.ac.kr.

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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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Development and validation of a novel combinational index of liquid biopsy biomarker for longitudinal lung cancer patient management

The journal of liquid biopsy

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The journal of liquid biopsy 2024年 6卷 100167页

作者： Min-Yi Liao Yun-Jie Hao Ching-Shan Luo Ching-Mei Chen Po-Hao Feng Hsin-Yu Yang Da-Jeng Yao Kang-Yun Lee Fan-Gang Tseng Department of Power Mechanical Engineering National Tsing Hua University Hsinchu 30013 Taiwan. Department of Engineering and System Science National Tsing Hua University Hsinchu 30013 Taiwan. International Ph.D. Program in Cell Therapy and Regeneration Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan. Division of Pulmonary Medicine Department of Internal Medicine Shuang Ho Hospital Taipei Medical University New Taipei City 23561 Taiwan. TMU Research Center of Thoracic Medicine Taipei Medical University Taipei 11031 Taiwan. Division of Pulmonary Medicine Department of Internal Medicine School of Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan. Nano Science and Technology Program National Tsing Hua University Hsinchu 30013 Taiwan. Institute of Nano Engineering and Micro Systems (NEMS) National Tsing Hua University Hsinchu 30013 Taiwan. Graduate Institute of Clinical Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan. Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Hsinchu 30013 Taiwan.

Objectives:Many cancer biomarkers such as the circulating tumor cells/microemboli (CTCs/CTM) have been reported significant associations with clinical outcomes. However, different biomarkers have different sensitivities and specificities for cancer types and cohort patients, and synergistic effects between certain biomarkers have also been observed, leading to the inaccurate, fluctuating, and even controversial results when multiple biomarkers are analyzed together. In this paper, a novel combinational index, P-score, was developed for monitoring and predicting the disease condition of lung cancer patients during follow-up visits. Materials and methods:There were totally 13 return patients with 54 blood samples involved in this study to examine the number of CTC and CTM. Information from one group of 7 patients including 27 blood samples with published clinical data was employed to develop while those from another group of 4 patients containing 14 blood samples with unpublished clinical data were used to validate the P score in prediction. Enumerations were based on immunofluorescent staining images. Distributions of CTC/CTM and their frequencies in stratified patients were carefully examined and analyzed the ROC curve and AUC value to develop the P score and P score-based prediction model. Results and conclusion:We found that the predictive power of P-score was not only comparable to the traditional cancer marker, in comparison with individual CTC/CTM, more false positives could be corrected by using P-score, thereby to improve the accuracy of analysis. From our preliminary validation tests, the prognosis and disease progression monitored longitudinally by P-score were further confirmed by clinical outcome data from physicians and its sensitivity was even better than those from individual biomarkers. We believe that this novel combinational indicator could be a promising tool to interpret clinical outcomes more accurately from multiple factors, particularly useful

关键词： Circulating tumor cells/microemboli Combinational index Disease monitoring and prognosis Drug screening Lung cancer

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