ArticleScientific reports2025
Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning.
Article in Scientific reports, 2025. 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.
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Authors and funding
4 authors.
Funding
Abstract
Hepatitis B Virus-associated membranous nephropathy (HBV-MN) significantly impacts renal health, particularly in areas with high HBV prevalence. Understanding the molecular mechanisms underlying HBV-MN is crucial for developing effective therapeutic strategies. This study aims to elucidate the roles of miR-223-3p and CRIM1 in HBV-MN using single-cell RNA sequencing (scRNA-seq) and machine learning. scRNA-seq analysis identified a distinct subcluster of podocytes linked to HBV-MN progression. miR-223-3p emerged as a critical regulatory molecule, with overexpression resulting in decreased CRIM1 expression. Dual-luciferase reporter assays confirmed miR-223-3p targeting CRIM1 at a conserved binding site. These findings were corroborated by machine learning models, which highlighted the significance of miR-223-3p and CRIM1 in disease pathology. miR-223-3p plays a pivotal role in modulating CRIM1 expression in HBV-MN, providing a potential therapeutic target. Integrating scRNA-seq with machine learning offers valuable insights into the molecular landscape of HBV-MN, paving the way for novel interventions.
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