ReviewCellular and molecular life sciences : CMLS2026
Molecular mechanisms and therapeutic strategies of glomerular cell senescence in diabetic kidney disease: from heterogeneity to precision intervention.
Review in Cellular and molecular life sciences : CMLS, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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8 authors.
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Abstract
Diabetic kidney disease (DKD) has emerged as a major cause of end-stage renal disease (ESRD) worldwide, with approximately 30%-40% of diabetic patients progressing to DKD and 25% eventually requiring renal replacement therapy. Glomerular cell senescence, a central pathological driver of disease progression, persists throughout the entire course of DKD and involves activation of the complement system, transcription factor regulation, mitochondrial dysfunction, oxidative stress, and DNA damage response (DDR). Despite shared senescence mechanisms, podocytes, endothelial cells, and mesangial cells exhibit distinct senescent heterogeneity. This manuscript explores the core mechanisms regulating glomerular cell senescence and their impact on renal filtration barrier injury, inflammation, and glomerulosclerosis, with a specific focus on the senescent characteristics and interactions of different types of glomerular cells. It also discusses senescence-related diagnostic biomarkers and epigenetic clocks. Our findings highlight the critical role of cell type-specific senescence in the pathogenesis of DKD and propose potential precision therapeutic strategies targeting cellular senescence, offering promising breakthroughs for preventing or alleviating the progression of DKD.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.