ArticleRenal failure2026
Single-cell transcriptomics and machine-learning reveal M1 macrophage-driven progression from minimal change disease to focal segmental glomerulosclerosis.
Article in Renal failure, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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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Who cites it
1 citing paper in PubMed.
- Analyzing the association between ferritin levels and ICP using machine learning algorithms: a retrospective case-control study.Frontiers in medicine · 2026Article
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8 authors.
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Abstract
Minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS) are two key nephrotic syndrome types with significant clinical implications. MCD predominantly affects children, while FSGS is more common in adults, often leading to irreversible kidney dysfunction. Despite shared features like podocyte injury and immune dysregulation, their pathological and clinical presentations differ. Understanding gene expression changes in these diseases could reveal new therapeutic targets. Single-cell transcriptomic datasets (GSE213030 and GSE176465) were analyzed to investigate cellular interactions in MCD and FSGS. Machine learning algorithms developed diagnostic models, and immune subtypes were identified for detailed subtype analysis. Key genes were validated using qRT-PCR and immunohistochemical staining in a mouse model, focusing on their association with M1 macrophage activation. Integrated single-cell analysis identified six key genes (
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