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arXiv 2020年

作者： Lei, Chon Lok Ghosh, Sanmitra Whittaker, Dominic G. Aboelkassem, Yasser Beattie, Kylie A. Cantwell, Chris D. Delhaas, Tammo Houston, Charles Novaes, Gustavo Montes Panfilov, Alexander V. Pathmanathan, Pras Riabiz, Marina Weber dos Santos, Rodrigo Worden, Keith Mirams, Gary R. Wilkinson, Richard D. Computational Biology & Health Informatics Dept. of Computer Science University of Oxford United Kingdom MRC Biostatistics Unit University of Cambridge United Kingdom Centre for Mathematical Medicine & Biology School of Mathematical Sciences University of Nottingham United Kingdom Department of Bioengineering University of California San Diego United States Systems Modeling and Translational Biology GlaxoSmithKline R&D Stevenage United Kingdom ElectroCardioMaths Programme Centre for Cardiac Engineering Imperial College London United Kingdom CARIM School for Cardiovascular Diseases Maastricht University Netherlands Graduate Program in Computational Modeling Universidade Federal de Juiz de Fora Brazil Department of Physics and Astronomy Ghent University Belgium Laboratory of Computational Biology and Medicine Ural Federal University Ekaterinburg Russia U.S. Food and Drug Administration Center for Devices and Radiological Health Office of Science and Engineering Laboratories United States Department of Biomedical Engineering King’s College London Alan Turing Institute United Kingdom Dynamics Research Group Department of Mechanical Engineering University of Sheffield United Kingdom School of Mathematics and Statistics University of Sheffield United Kingdom

Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions. The field of cardiac simulation has begun to explore and adopt UQ methods to characterise uncertainty in model inputs and how that propagates through to outputs or predictions. In this perspective piece we draw attention to an important and under-addressed source of uncertainty in our predictions — that of uncertainty in the model structure or the equations themselves. The difference between imperfect models and reality is termed model discrepancy, and we are often uncertain as to the size and consequences of this discrepancy. Here we provide two examples of the consequences of discrepancy when calibrating models at the ion channel and action potential scales. Furthermore, we attempt to account for this discrepancy when calibrating and validating an ion channel model using different methods, based on modelling the discrepancy using Gaussian processes (GPs) and autoregressive-moving-average (ARMA) models, then highlight the advantages and shortcomings of each approach. Finally, suggestions and lines of enquiry for future work are provided. Copyright © 2020, The Authors. All rights reserved.

关键词： Uncertainty analysis

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Review of the use of mangrove forests in supporting the socio-economic life of fishing communities

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IOP Conference Series: Earth and Environmental science 2020年第1期575卷

作者： Untari R Darma P Betaubun A A Arief PhD. Student on Agricultural System Graduate School Hasanuddin University South Sulawesi Indonesia Department of Agribusiness Faculty of Agriculture Universitas Musamus Papua Indonesia Agribusiness Study Program Faculty of Agriculture Hasanuddin University South Sulawesi Indonesia Department of civil Engineering Faculty of Engineering Universitas Musamus Papua Indonesia Socio Economic of Fisheries Study Program Faculty of Marine Science and Fisheries Hasanuddin University South Sulawesi Indonesia

Mangrove forests have an important function in human life that cannot be replaced by other functions. The existence of mangrove forests has six main functions, namely biological, ecological, physical, social, economic and chemical functions. This article discusses the description of mangrove forest management in meeting the needs of the economic and social functions of the fishing communities on the coast of Merauke Regency, Papua Province, which were reviewed descriptively using relevant literature studies. In terms of economic function, mangrove forests provide economic value for fishing communities because mangrove forests become habitat for crabs, fish and other marine biota that are captured and sold as the main source of family income. In addition, the use of mangrove forests by fishermen on the coast is used as firewood and building materials. The high utilization of mangrove forests by coastal communities that ignores ecological sustainability causes damage to mangrove forests that threatens the sustainability of ecological functions. Damage to mangrove forests in Merauke in the period 2000-2005 was recorded as wide as 2,416 ha while in the 2005-2010 period damage reached 2,233 ha of the total area of the Merauke mangrove forest which reached 216,001.95 Ha or 6.98% of the Merauke forest area. Based on this, the management of mangrove forest utilization needs to get more attention from various parties so that the ecological function of mangrove forests as a condition of sustainable development, especially for fishing communities on the coast, can be realized in Merauke Regency.

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Efficient construction method for phase diagrams using uncertainty sampling

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Physical Review Materials 2019年第3期3卷 033802-033802页

作者： Kei Terayama Ryo Tamura Yoshitaro Nose Hidenori Hiramatsu Hideo Hosono Yasushi Okuno Koji Tsuda RIKEN Center for Advanced Intelligence Project Tokyo 103-0027 Japan Medical Sciences Innovation Hub Program RIKEN Cluster for Science Technology and Innovation Hub Kanagawa 230-0045 Japan Graduate School of Medicine Kyoto University Kyoto 606-8507 Japan International Center for Materials Nanoarchitectonics (WPI-MANA) National Institute for Materials Science Ibaraki 305-0044 Japan Research and Services Division of Materials Data and Integrated System National Institute for Materials Science Ibaraki 305-0047 Japan Graduate School of Frontier Sciences University of Tokyo Chiba 277-8568 Japan Department of Materials Science and Engineering Kyoto University Kyoto 606-8501 Japan Laboratory for Materials and Structures Institute of Innovative Research Tokyo Institute of Technology Yokohama 226-8503 Japan Materials Research Center for Element Strategy Tokyo Institute of Technology Yokohama 226-8503 Japan

We develop a method to efficiently construct phase diagrams using machine learning. Uncertainty sampling (US) in active learning is utilized to intensively sample around phase boundaries. Here, we demonstrate constructions of three known experimental phase diagrams by the US approach. Compared with random sampling, the US approach decreases the number of sampling points to about 20%. In particular, the reduction rate is pronounced in more complicated phase diagrams. Furthermore, we show that using the US approach, undetected new phases can be rapidly found, and smaller numbers of initial sampling points are sufficient. Thus, we conclude that the US approach is useful to construct complicated phase diagrams from scratch and will be an essential tool in materials science.

关键词： Phase diagrams

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Comprehensive High Impedance Fault Model for Real-Time Environment

Comprehensive High Impedance Fault Model for Real-Time Envir...

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Annual Conference of Industrial Electronics Society

作者： Aldair Wontroba Adriano Peres de Morais Jean Pereira Rossini Mairon Gallas Ghendy Cardoso João Paulo Abreu Vieira Marcelo Costa Santos Patrick Escalante Farias Federal University of Santa Maria Santa Maria RS Brazil Federal University of Santa Maria Santa Maria Brazil Electrical Engineering Graduate Program Federal university of Pará Belém PA Brazil Distribution System Operation Management CELPA –Electric Distribution Utility of Pará Belém PA Brazil Federal Institute of Education Science and Technology of Rio Grande do Sul IFRS Farroupilha Brazil

This paper presents a comprehensive high impedance fault model for real-time environment. This model offers different types of ground surface and high impedance faults. Experimental results show that it is suitable for relays and algorithms commissioning in closed loop environment. The model is incorporated into OPAL-RT simulator and implemented in Hypersim software. Finally, the performance of the model is validated under a real case of high impedance fault by comparison with real-time simulation.

关键词： Circuit faults Real-time systems Fault currents Impedance Resistance Power cables Surface impedance

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WE-173. Combining excitability and connectivity measures from interictal invasive-EEG estimates the epileptogenic zone, even in the absence of frank epileptiform activity

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Clinical Neurophysiology 2022年 141卷 S81-S82页

作者： Billardello, Roberto Ntolkeras, Georgios Pesce, Matthew Harmon, Joseph Hadjinicolaou, Aristides Madsen, Joseph Taffoni, Fabrizio Pearl, Phillip Papadelis, Christos Grant, Ellen Tamilia, Eleonora Fetal-Neonatal Neuroimaging and Developmental Science Center Boston Children’s Hospital Harvard Medical School Boston USA Research Unit of Advanced Robotics and Human-Centred Technologies Department of Engineering University Bio-Medico Campus of Rome Rome Italy Baystate Children's Hospital Springfield USA Division of Epilepsy and Clinical Neurophysiology Department of Neurology Boston Children’s Hospital Harvard Medical School Boston USA Epilepsy Surgery Program Department of Neurosurgery Boston Children’s Hospital Harvard Medical School Boston USA Jane and John Justin Neurosciences Center Cook Children’s Health Care System Fort Worth USA Department of Bioengineering University of Texas at Arlington Arlington USA

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Polygenic enrichment distinguishes disease associations of individual cells in single-cell RNA-seq data

Research Square

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Research Square 2021年

作者： Zhang, Martin Jinye Hou, Kangcheng Pasaniuc, Bogdan Price, Alkes L. Dey, Kushal K. Jagadeesh, Karthik A. Weinand, Kathryn Sakaue, Saori Taychameekiatchai, Aris Rao, Poorvi Pisco, Angela Oliveira Zou, James Wang, Bruce Gandal, Michael Raychaudhuri, Soumya Harvard University United States Osaka University Japan Department of Epidemiology Harvard T.H. Chan School of Public Health BostonMA United States Program in Medical and Population Genetics Broad Institute of MIT and Harvard CambridgeMA United States Bioinformatics Interdepartmental Program University of California Los Angeles Los AngelesCA United States Department of Pathology and Laboratory Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Department of Computational Medicine David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Center for Data Sciences Brigham and Women’s Hospital BostonMA United States Division of Genetics Department of Medicine Brigham and Women’s Hospital Harvard Medical School BostonMA United States Division of Rheumatology Inflammation and Immunity Department of Medicine Brigham and Women’s Hospital Harvard Medical School BostonMA United States Department of Biomedical Informatics Harvard Medical School BostonMA United States Department of Medicine and Liver Center University of California San Francisco San FranciscoCA United States Developmental and Stem Cell Biology Graduate Program University of California San Francisco San FranciscoCA United States Chan Zuckerberg Biohub San FranciscoCA United States Department of Electrical Engineering Stanford University Palo AltoCA United States Department of Biomedical Data Science Stanford University Palo AltoCA United States Department of Psychiatry David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Program in Neurobehavioral Genetics Semel Institute David Geffen School of Medicine University of California Los Angeles Los AngelesCA United States Versus Arthritis Centre for Genetics and Genomic

Gene expression at the individual cell-level resolution, as quantified by single-cell RNA-sequencing (scRNA-seq), can provide unique insights into the pathology and cellular origin of diseases and complex traits. Here, we introduce single-cell Disease Relevance Score (scDRS), an approach that links scRNA-seq with polygenic risk of disease at individual cell resolution;scDRS identifies individual cells that show excess expression levels for genes in a disease-specific gene set constructed from GWAS data. We determined via simulations that scDRS is well-calibrated and powerful in identifying individual cells associated to disease. We applied scDRS to GWAS data from 74 diseases and complex traits (average N =341K) in conjunction with 16 scRNA-seq data sets spanning 1.3 million cells from 31 tissues and organs. At the cell type level, scDRS broadly recapitulated known links between classical cell types and disease, and also produced novel biologically plausible findings. At the individual cell level, scDRS identified subpopulations of disease-associated cells that are not captured by existing cell type labels, including subpopulations of CD4+ T cells associated with inflammatory bowel disease, partially characterized by their effector-like states;subpopulations of hippocampal CA1 pyramidal neurons associated with schizophrenia, partially characterized by their spatial location at the proximal part of the hippocampal CA1 region;and subpopulations of hepatocytes associated with triglyceride levels, partially characterized by their higher ploidy levels. At the gene level, we determined that genes whose expression across individual cells was correlated with the scDRS score (thus reflecting co-expression with GWAS disease genes) were strongly enriched for gold-standard drug target and Mendelian disease genes. © 2021, CC BY.

关键词： RNA

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Author Correction: Cation-induced intramolecular coil-to-globule transition in poly(ADP-ribose)

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Nature communications 2024年第1期15卷 8617页

作者： Tong Wang Kush Coshic Mohsen Badiee Maranda R McDonald Aleksei Aksimentiev Lois Pollack Anthony K L Leung School of Applied and Engineering Physics Cornell University Ithaca NY 14853 USA. Center for Biophysics and Quantitative Biology University of Illinois Urbana Champaign Urbana IL 61801 USA. Department of Biochemistry and Molecular Biology Bloomberg School of Public Health Johns Hopkins University Baltimore MD 21205 USA. Chemistry-Biology Interface Graduate Program Johns Hopkins University Baltimore MD 21218 USA. Center for Biophysics and Quantitative Biology University of Illinois Urbana Champaign Urbana IL 61801 USA. aksiment@illinois.edu. Beckman Institute for Advanced Science and Technology University of Illinois Urbana Champaign Urbana IL 61801 USA. aksiment@illinois.edu. Department of Physics University of Illinois Urbana Champaign Urbana IL 61801 USA. aksiment@illinois.edu. School of Applied and Engineering Physics Cornell University Ithaca NY 14853 USA. lp26@cornell.edu. Department of Biochemistry and Molecular Biology Bloomberg School of Public Health Johns Hopkins University Baltimore MD 21205 USA. anthony.leung@jhu.edu. Chemistry-Biology Interface Graduate Program Johns Hopkins University Baltimore MD 21218 USA. anthony.leung@jhu.edu. Department of Molecular Biology and Genetics School of Medicine Johns Hopkins University Baltimore MD 21205 USA. anthony.leung@jhu.edu. Department of Oncology School of Medicine Johns Hopkins University Baltimore MD 21205 USA. anthony.leung@jhu.edu. Department of Genetic Medicine School of Medicine Johns Hopkins University Baltimore MD 21205 USA. anthony.leung@jhu.edu.

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Mediation analysis for TNF-α as a mediator between multiple metal exposure and kidney function

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Ecotoxicology and environmental safety 2024年 283卷 116837页

作者： Kuei-Hau Luo Hung-Pin Tu Huang-Chih Chang Chen-Cheng Yang Wei-Chun Weng Tzu-Hua Chen Cheng-Hong Yang Hung-Yi Chuang Graduate Institute of Medicine College of Medicine Kaohsiung Medicine University Kaohsiung City 807 Taiwan. Department of Public Health and Environmental Medicine School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung 807 Taiwan. Divisions of Pulmonary & Critical Care Medicine Department of Internal Medicine Kaohsiung Chang Gung Memorial Hospital Chang Gung University College of Medicine Kaohsiung Taiwan. Graduate Institute of Medicine College of Medicine Kaohsiung Medicine University Kaohsiung City 807 Taiwan Department of Occupational Medicine Kaohsiung Municipal Siaogang Hospital Kaohsiung Medical University Kaohsiung 812 Taiwan. Division of Gastroenterology Department of Internal Medicine Kaohsiung Armed Forces General Hospital Kaohsiung 802 Taiwan. Department of Family Medicine Kaohsiung Municipal Ta-Tung Hospital Kaohsiung 801 Taiwan. Department of Information Management Tainan University of Technology Tainan 71002 Taiwan Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung 80778 Taiwan. Department of Public Health and Environmental Medicine School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung 807 Taiwan Department of Occupational and Environmental Medicine Kaohsiung Medicine University Hospital Kaohsiung Medicine University Kaohsiung 807 Taiwan Ph.D. Program in Environmental and Occupational Medicine College of Medicine and Research Center for Precision Environmental Medicine Kaohsiung Medical University Kaohsiung 807 Taiwan. Electronic address: ericch@kmu.edu.tw.

The association between metal mixtures and kidney function has been reported. However, reports on the mechanism of metal toxicity were limited. Oxidative stress was reported as a possible cause. This study aimed to determine the association between of kidney function and metals, such as arsenic (As), cadmium (Cd), cobalt (Co), copper (Cu), lead (Pb), selenium (Se), and zinc (Zn), and to explore the possible mediating role of tumor necrosis factor alpha (TNF-α) between metal toxicity and kidney function. In this study, we recruited 421 adults from a health examination. The concentration of blood metals was analyzed using inductively coupled plasma mass spectrometry. We used linear regression models to assess the association between metals and TNF-α. Then, mediation analysis was applied to investigate the relationship between metal exposure, TNF-α, and kidney function. In univariate linear regression, blood As, Cd, Co, Cu, Pb, and Zn levels significantly increased TNF-α and decreased kidney function. Higher blood As and Pb levels significantly increased TNF-α in multivariable linear regressions after adjusting for covariates. We found that blood levels of As (coefficients = -0.021, p = 0.011), Pb (coefficients = -0.060, p < 0.001), and Zn (coefficients = -0.230, p < 0.001) showed a significant negative association with eGFR in the multiple-metal model. Furthermore, mediation analysis showed that TNF-α mediated 41.7 %, 38.8 %, and 20.8 % of blood Cd, As and Pb, respectively. Among the essential elements, TNF-α mediated 24.5 %, 21.5 % and 19.9 % in the effects of blood Co, Cu, and Zn on kidney function, respectively. TNF-α, acting as a mediator, accounted for 20.1 % of the contribution between the WQS score of metal mixtures and the eGFR (p < 0.001). This study suggested that TNF-α may be a persuasive pathway mediating the association between metals and kidney function. Inflammation and kidney injury could be the underlying mechanisms of metal exposure. However, there i

关键词： Kidney function Mediation analysis Metals Pb TNF-α

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The autocrine glycosylated-GREM1 interacts with TGFB1 to suppress TGFβ/BMP/SMAD-mediated EMT partially by inhibiting MYL9 transactivation in urinary carcinoma

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Cellular oncology (Dordrecht, Netherlands) 2023年第4期46卷 933-951页

作者： Ti-Chun Chan Cheng-Tang Pan Hsin-Yu Hsieh Pichpisith Pierre Vejvisithsakul Ren-Jie Wei Bi-Wen Yeh Wen-Jeng Wu Lih-Ren Chen Meng-Shin Shiao Chien-Feng Li Yow-Ling Shiue Department of Medical Research Chi-Mei Medical Center Tainan 71004 Taiwan. National Institute of Cancer Research National Health Research Institutes Tainan 71004 Taiwan. Institute of Precision Medicine College of Medicine National Sun Yat-Sen University Kaohsiung 80424 Taiwan. Department of Mechanical and Electro-Mechanical Engineering National Sun Yat-Sen University Kaohsiung 80424 Taiwan. Institute of Advanced Semiconductor Packaging and Testing College of Semiconductor and Advanced Technology Research National Sun Yat-Sen University Kaohsiung 80424 Taiwan. Institute of Biomedical Sciences College of Medicine National Sun Yat-Sen University Kaohsiung 80424 Taiwan. Program in Translational Medicine Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok 10400 Thailand. Department of Pathology Kaohsiung Armed Forces General Hospital Kaohsiung 80284 Taiwan. Institute of Medical Science and Technology School of Medicine National Sun Yat-Sen University Kaohsiung 80424 Taiwan. Department of Medical Laboratory Sciences and Biotechnology Fooyin University Kaohsiung 83102 Taiwan. Department of Urology School of Medicine College of Medicine Kaohsiung Medical University Kaohsiung 80708 Taiwan. Department of Urology Kaohsiung Medical University Hospital Kaohsiung 80708 Taiwan. Graduate Institute of Clinical Medicine College of Medicine Kaohsiung Medical University Kaohsiung 80708 Taiwan. Regenerative Medicine and Cell Therapy Research Center Kaohsiung Medical University Kaohsiung 80708 Taiwan. Division of Physiology Livestock Research Institute Tainan 71246 Taiwan. Research Center Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok 10400 Thailand. Department of Medical Research Chi-Mei Medical Center Tainan 71004 Taiwan. angelo.p@yahoo.com.tw. National Institute of Cancer Research National Health Research Institutes Tainan 71004 Taiwan. angelo.p@yahoo.com.tw. Institute of Precision Medicine College of Medicine Nat

PURPOSE:Urothelial carcinoma (UC) is a common disease in developed counties. This study aimed to identify autocrine roles and signaling pathways of gremlin 1, DAN family BMP antagonist (GREM1), which inhibits tumor growth and epithelial-mesenchymal transition (EMT) in UC. METHODS:systematic in vitro and in vivo studies using genetic engineering, different urinary bladder urothelial carcinoma (UBUC)-derived cell lines, and mouse models were performed, respectively. Further, primary upper tract urothelial carcinoma (UTUC) and UBUC specimens were evaluated by immunohistochemistry. RESULTS:GREM1 protein levels conferred better disease-specific and metastasis-free survival rates and played an independent prognostic factor in UTUC and UBUC. Hypermethylation is the primary cause of low GREM1 levels. In different UBUC-derived cell lines, the autocrine/secreted and glycosylated GREM1 interacted with transforming growth factor beta 1 (TGFB1) and inhibited TGFβ/BMP/SMAD signaling and myosin light chain 9 (MYL9) transactivation, subsequently cell proliferation and epithelial-mesenchymal transition (EMT). Secreted and glycosylated GREM1 also suppressed tumor growth, metastasis, and MYL9 levels in the mouse model. Instead, cytosolic GREM1 promoted cell proliferation and EMT by activating the tumor necrosis factor (TNF)/AKT/nuclear factor kappa B (NFκB) axis. CONCLUSIONS:Clinical associations, animal models, and in vitro indications provided solid evidence to show that the epithelial autocrine GREM1 is a novel tumor suppressor in UCs. The glycosylated-GREM1 hampered cell proliferation, migration, invasion, and in vitro angiogenesis through interaction with TGFB1 to inactivate TGFβ/BMP/SMAD-mediated EMT in an autocrine manner.

关键词： Autocrine Epithelial-mesenchymal transition GREM1 TGFβ Urothelial carcinoma

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Adverse events following the first, second and third doses of a COVID-19 vaccine in hemodialysis patients

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Renal failure 2023年第1期45卷 2172432页

作者： Mei-Fen Pai Kuei-Ting Tung Shih-Ping Hsu Yu-Sen Peng Wan-Yu Lin Ju-Yeh Yang Hon-Yen Wu Yen-Ling Chiu Kai-Hsiang Shu Wan-Chuan Tsai Division of Nephrology Department of Internal Medicine Far Eastern Memorial Hospital New Taipei City Taiwan. Department of Internal Medicine National Taiwan University Hospital and College of Medicine Taipei City Taiwan. School of Life Science National Taiwan Normal University Taipei City Taiwan. Department of Applied Cosmetology Lee-Ming Institute of Technology New Taipei City Taiwan. Department of Electrical Engineering Yuan Ze University Taoyuan City Taiwan. Institute of Epidemiology and Preventive Medicine College of Public Health National Taiwan University Taipei City Taiwan. Center for General Education Lee-Ming Institute of Technology New Taipei City Taiwan. Faculty of Medicine School of Medicine National Yang-Ming University Taipei City Taiwan. Graduate Program in Biomedical Informatics Yuan Ze University Taoyuan City Taiwan.

BACKGROUND:This study aimed to identify adverse events following the first three doses of COVID-19 vaccines in hemodialysis (HD) patients. Risk factors associated with postvaccination adverse events were explored. METHODS:Postvaccination adverse events in 438 HD patients who received 3 doses of COVID-19 vaccines were prospectively assessed. The adverse events among three doses were compared using generalized linear mixed models. Factors associated with adverse events were assessed with multivariate analyses. RESULTS:The vast majority of participants received Oxford/AstraZeneca ChAdOx1 as their first two doses and Moderna mRNA-1273 as their third dose. Overall, 79%, 50% and 84% of the participants experienced at least one adverse event after their first, second, and third doses, respectively. These adverse events were mostly minor, short-lived and less than 5% reported daily activities being affected. Compared with the first dose, the second dose caused a lower rate of adverse events. Compared with the first dose, the third dose elicited a higher rate of injection site reactions and a lower rate of systemic reactions. Multivariate analyses showed that every 10-year increase of age (odds ratio 0.67, 95% confidence intervals 0.57-0.79) was associated with decreased risk of adverse events, while female sex (2.82, 1.90-4.18) and arteriovenous fistula (1.73, 1.05-2.84) were associated with increased risk of adverse events. Compared with Oxford/AstraZeneca ChAdOx1, Moderna mRNA-1273 was associated with an increased risk of injection site reactions. CONCLUSIONS:COVID-19 vaccination was well tolerated in HD patients. Age, sex, dialysis vascular access and vaccine types were associated with postvaccination adverse events.

关键词： COVID-19 ChAdOx1 Hemodialysis adverse event mRNA-1273 vaccination

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