Evidence map›Paper›PMID 40442195›Full record

ArticleScientific reports2025

Identification of novel therapeutic targets in hepatitis-B virus-associated membranous nephropathy using scRNA-seq and machine learning.

Yongzheng Hu, Qian An, Xinxin Yu, Wei Jiang

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yongzheng HuDepartment of Nephrology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Qian AnDepartment of Nephrology, Qingdao Central Hospital, Qingdao, Shandong, China.
Xinxin YuDepartment of Nephrology, Qingdao Eighth People's Hospital, Qingdao, Shandong, China.
Wei JiangDepartment of Nephrology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China. jiangwei866@qdu.edu.cn.

Funding

National Natural Science Foundation of China 82370724
6 · The paper itself

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.

Indexed as

Glomerulonephritis, MembranousHepatitis BHepatitis B virusMachine LearningMicroRNAsHumansPodocytesRNA-SeqSingle-Cell AnalysisSingle-Cell Gene Expression AnalysisMicroRNAsCRIM1HBV-MNMachine learningMiR-223-3pScRNA-seq

Identifiers

PMID40442195
PMCPMC12123029

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.