AIMC Topic: Cellular Senescence
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Identification of diagnostic genes and the miRNA‒mRNA‒TF regulatory network in human oocyte aging via machine learning methods.
Journal of assisted reproduction and genetics
Nov 14, 2024
PURPOSE: Oocyte aging is a significant factor in the negative reproductive outcomes of older women. However, the pathogenesis of oocyte aging remains unclear. This study aimed to identify the hub genes involved in oocyte aging via bioinformatics meth...
Integrated machine learning identifies a cellular senescence-related prognostic model to improve outcomes in uterine corpus endometrial carcinoma.
Frontiers in immunology
Jun 27, 2024
BACKGROUND: Uterine Corpus Endometrial Carcinoma (UCEC) stands as one of the prevalent malignancies impacting women globally. Given its heterogeneous nature, personalized therapeutic approaches are increasingly significant for optimizing patient outc...
D-MAINS: A Deep-Learning Model for the Label-Free Detection of Mitosis, Apoptosis, Interphase, Necrosis, and Senescence in Cancer Cells.
Cells
Jun 8, 2024
BACKGROUND: Identifying cells engaged in fundamental cellular processes, such as proliferation or living/death statuses, is pivotal across numerous research fields. However, prevailing methods relying on molecular biomarkers are constrained by high c...
Identification of key genes and biological pathways associated with vascular aging in diabetes based on bioinformatics and machine learning.
Aging
May 27, 2024
Vascular aging exacerbates diabetes-associated vascular damage, a major cause of microvascular and macrovascular complications. This study aimed to elucidate key genes and pathways underlying vascular aging in diabetes using integrated bioinformatics...
Identification of diagnostic markers related to inflammatory response and cellular senescence in endometriosis using machine learning and in vitro experiment.
Inflammation research : official journal of the European Histamine Research Society ... [et al.]
May 4, 2024
OBJECTIVE: To understand the association between chronic inflammation, cellular senescence, and immunological infiltration in endometriosis.
Single-cell senescence identification reveals senescence heterogeneity, trajectory, and modulators.
Cell metabolism
Apr 10, 2024
Cellular senescence underlies many aging-related pathologies, but its heterogeneity poses challenges for studying and targeting senescent cells. We present here a machine learning program senescent cell identification (SenCID), which accurately ident...
Integrative analysis of potential diagnostic markers and therapeutic targets for glomerulus-associated diabetic nephropathy based on cellular senescence.
Frontiers in immunology
Jan 8, 2024
INTRODUCTION: Diabetic nephropathy (DN), distinguished by detrimental changes in the renal glomeruli, is regarded as the leading cause of death from end-stage renal disease among diabetics. Cellular senescence plays a paramount role, profoundly affec...
Morphology-based deep learning enables accurate detection of senescence in mesenchymal stem cell cultures.
BMC biology
Jan 2, 2024
BACKGROUND: Cell senescence is a sign of aging and plays a significant role in the pathogenesis of age-related disorders. For cell therapy, senescence may compromise the quality and efficacy of cells, posing potential safety risks. Mesenchymal stem c...
Discovery of senolytics using machine learning.
Nature communications
Jun 10, 2023
Cellular senescence is a stress response involved in ageing and diverse disease processes including cancer, type-2 diabetes, osteoarthritis and viral infection. Despite growing interest in targeted elimination of senescent cells, only few senolytics ...
Dynamics of redox signaling in aging via autophagy, inflammation, and senescence.
Biogerontology
May 17, 2023
Review paper attempts to explain the dynamic aspects of redox signaling in aging through autophagy, inflammation, and senescence. It begins with ROS source in the cell, then states redox signaling in autophagy, and regulation of autophagy in aging. N...
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