Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets.

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第一作者： Abhijeet R,Patil

第一单位： Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Immunology and Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA.

作者： Abhijeet R,Patil ^[1] ; Jonathan,Schug ^[2] ; Chengyang,Liu ^[3] ; Deeksha,Lahori ^[2] ; Hélène C,Descamps ^[2] ; Human Pancreas Analysis Consortium ^[4] ; Ali,Naji ^[5] ; Klaus H,Kaestner ^[2] ; Robert B,Faryabi ^[6] ; Golnaz,Vahedi ^[7]

作者单位： Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Immunology and Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA. ^[1] Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA. ^[2] Institute for Immunology and Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA. ^[3] Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA. ^[4] Institute for Immunology and Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA. ^[5] Institute for Immunology and Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Abramson Family Cancer Research Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA. ^[6] Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Immunology and Immune Health, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Epigenetics Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Institute for Diabetes, Obesity and Metabolism, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA; Abramson Family Cancer Research Institute, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA. Electronic address: vahedi@pennmedicine.upenn.edu. ^[7]

关键词 autoantibody-positive human islets machine learning single-cell RNA-seq type 1 diabetes

主题词人类(Humans);糖尿病, 1型(Diabetes Mellitus, Type 1);单细胞分析(Single-Cell Analysis);胰岛(Islets of Langerhans);疾病恶化(Disease Progression);自身抗体(Autoantibodies);基因表达谱(Gene Expression Profiling);男(雄)性(Male);女(雌)性(Female);胰岛素分泌细胞(Insulin-Secreting Cells);成年人(Adult)

DOI 10.1016/j.xcrm.2024.101535

PMID 38677282

发布时间 2025-01-08

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Cell reports. Medicine

2024年5卷5期

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Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets.

Cell reports. Medicine

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Modeling type 1 diabetes progression using machine learning and single-cell transcriptomic measurements in human islets.

Cell reports. Medicine

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