Evidence map›Paper›PMID 39959271›Full record

ArticleWorld journal of diabetes2025

Transcriptome and single-cell profiling of the mechanism of diabetic kidney disease.

Ying Zhou, Xiao Fang, Lin-Jing Huang, Pei-Wen Wu

Abstract read
In one paragraph

Article in World journal of diabetes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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.

Ying ZhouDepartment of Endocrinology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China.
Xiao FangDepartment of Kidney Transplantation, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350001, Fujian Province, China.
Lin-Jing HuangDepartment of Endocrinology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China.
Pei-Wen WuDepartment of Endocrinology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, Fujian Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe NOD-like receptor thermal protein domain associated protein 3 (NLRP3) inflammasome may play an important role in diabetic kidney disease (DKD). However, the exact link remains unclear.

aimTo investigate the role of the NLRP3 inflammasome in DKD.

methodsUsing datasets from the Gene Expression Omnibus database, 30 NLRP3 inflammasome-related genes were identified. Differentially expressed genes were selected using differential expression analysis, whereas intersecting genes were selected based on overlapping differentially expressed genes and NLRP3 inflammasome-related genes. Subsequently, three machine learning algorithms were used to screen genes, and biomarkers were identified by overlapping the genes from the three algorithms. Potential biomarkers were validated by western blotting in a db/db mouse model of diabetes.

resultsTwo biomarkers, sirtuin 2 (SIRT2) and caspase 1 (CASP1), involved in the Leishmania infection pathway were identified. Both biomarkers were expressed in endothelial cells. Pseudo-temporal analysis based on endothelial cells showed that DKD mostly occurs during the mid-differentiation stage. Western blotting results showed that CASP1 expression was higher in the DKD group than in the control group (

conclusionSIRT2 and CASP1 provide a potential theoretical basis for DKD treatment.

Indexed as

Caspase 1Diabetic kidney diseaseNOD-like receptor thermal protein domain associated protein 3Single-cell RNA sequencing analysisSirtuin 2

Identifiers

PMID39959271
PMCPMC11718477

What Socratic holds

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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.