Evidence map›Paper›PMID 42668808›Full record

ArticlePeerJ2026

Identification and validation of novel platelet-related genes in ulcerative colitis using bioinformatics and machine learning strategies.

Jin Huang, Ying Dai, Shuangshuang Lu, Xue Li, Ruihong Sun, Ben Huang, Chunmei Ma

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PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 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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0cells of the map it votes in
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

7 authors.

Jin Huang *The Second People's Hospital of Changzhou, Changzhou Medical Center, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, China.
Ying Dai *Department of Immunology, Nanjing Medical University, Nanjing, China.
Shuangshuang LuThe Second People's Hospital of Changzhou, Changzhou Medical Center, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, China.
Xue LiDepartment of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Ruihong SunThe First School of Clinical Medicine, Nanjing Medical University, Nanjing, China.
Ben HuangDepartment of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Chunmei MaThe Second People's Hospital of Changzhou, Changzhou Medical Center, The Third Affiliated Hospital of Nanjing Medical University, Changzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ulcerative colitis (UC) is a chronic, relapsing inflammatory disorder of the colonic mucosa. Although colonoscopy remains the diagnostic cornerstone for UC, its invasive nature highlights the need for additional biomarkers. This study used differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine-learning algorithms to identify three key platelet-related genes (PRGs)-TRIM22, TIMP1, and RAC2-that are involved in UC development. Immune cell analysis and single-cell analyses indicated that the expression of these key genes was significantly correlated with macrophages, neutrophils, and mast cells. Moreover, these key PRGs were mainly involved in pathways related to UC, such as chemokine signaling and leukocyte transendothelial migration. The expression levels of the key PRGs were further validated in independent datasets, dextran sulfate sodium (DSS)-induced colitis tissues, and peripheral blood mononuclear cells (PBMC) samples from UC patients. Collectively, these findings support a platelet-related three-gene signature with potential diagnostic and biological relevance in UC.

Indexed as

Blood PlateletsColitis, UlcerativeComputational BiologyMachine Learningrac GTP-Binding ProteinsBiomarkersGene Expression ProfilingHumansRAC2 GTP-Binding ProteinTissue Inhibitor of Metalloproteinase-1BiomarkersRAC2 GTP-Binding Proteinrac GTP-Binding ProteinsTissue Inhibitor of Metalloproteinase-1Immune cell infiltrationMachine learningPlatelet-related genesSingle cell analysisUlcerative colitisWGCNA

Identifiers

PMID42668808
PMCPMC13525761

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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.