Evidence map›Paper›PMID 41816327›Full record

ArticleFrontiers in immunology2026

Glomerular cell atlas of multi-disease model revealed the characteristic changes of glomerular cell subtypes in diseases.

Yan Huang, Shuo Li, Shuying Li, Shuzhong Duan, Lan Huang, Jing Wang, Liangyan Ma, Ce Liu, Qilin Chen

Abstract read
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Article in Frontiers in immunology, 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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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Yan HuangNephrology Department, The Affiliated Hospital of Chengde Medical University, Chengde, China.
Shuo LiNephrology Department, The Affiliated Hospital of Chengde Medical University, Chengde, China.
Shuying LiDepartment of Nephrology Children's Hospital of Chongqing Medical University, National Clinical Research Center for Children and Adolescents' Health and Diseases, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Disease, Chongqing, China.
Shuzhong DuanNephrology Department, The Affiliated Hospital of Chengde Medical University, Chengde, China.
Lan HuangNephrology Department, The Affiliated Hospital of Chengde Medical University, Chengde, China.
Jing WangNephrology Department, The Affiliated Hospital of Chengde Medical University, Chengde, China.
Liangyan MaNephrology Department, The Affiliated Hospital of Chengde Medical University, Chengde, China.
Ce LiuNephrology Department, The Affiliated Hospital of Chengde Medical University, Chengde, China.
Qilin ChenDepartment of Nephrology Children's Hospital of Chongqing Medical University, National Clinical Research Center for Children and Adolescents' Health and Diseases, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Disease, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although a range of glomerular diseases profoundly affect glomerulus-associated cells, a comprehensive understanding of their molecular alterations is still lacking. Here, we performed in-depth analysis of glomerular data from mouse models of primary and secondary glomerulopathies and constructed a multi-disease cellular landscape of glomerular cells. We identified a putative subset of proliferative glomerular endothelial cells(gECs) that highly expresses genetic susceptibility genes associated with multiple glomerular diseases. Podocytes exhibited shared injury-associated cell types across different disease models. A podocyte subset highly expressing

Indexed as

Endothelial CellsKidney DiseasesKidney GlomerulusPodocytesAnimalsDisease Models, AnimalGene Expression ProfilingGenetic Predisposition to DiseaseHumansMesangial CellsMicecross-disease atlasglomerular diseasemesangial cellpodocytesingle-cell RNA sequencing

Identifiers

PMID41816327
PMCPMC12971660

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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.