Evidence map›Paper›PMID 42436397›Full record

ArticleBMC neurology2026

Identification of potential biological biomarkers for acute ischemic stroke based on integrated bioinformatics analyses.

Linling Ji, Lin Zhu, Yiran Zhu, Kaiqi Ren, Jingyan Liang, Yingge Wang

Abstract read
In one paragraph

Article in BMC neurology, 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

6 authors.

Linling JiDepartment of Neurology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China.
Lin ZhuDepartment of Neurology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China.
Yiran ZhuDepartment of Neurology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China.
Kaiqi RenNorthern Jiangsu Peoples Hospital, Clinical Medical College, Yangzhou University, Yangzhou, China.
Jingyan LiangThe First School of Clinical Medicine, Faculty of Medicine, Yangzhou University, Yangzhou, China.
Yingge WangDepartment of Neurology, The Affiliated Hospital of Yangzhou University, Yangzhou University, Yangzhou, China. yinggewang279@hotmail.com.

Funding

the National Natural Science Foundation of China 82370517the Postgraduate Research and Practice Innovation Program of Jiangsu Province SJCX24_2352the Social Development Project Fund of Yangzhou City YZ2023067
6 · The paper itself

Abstract

Ischemic stroke is a major cause of disability and mortality worldwide, accounting for approximately 66% of all stroke cases. Stroke has been reported to cause approximately 6.5 million deaths annually, and the global disability-adjusted life years attributable to stroke are projected to exceed 200 million by 2030. Therefore, identifying reliable diagnostic biomarkers for acute ischemic stroke (AIS) and exploring their underlying molecular mechanisms are of great importance for early disease recognition and clinical intervention. Transglutaminases (TGases) are widely distributed in the central nervous system and play important roles in inflammatory responses, neural repair, and vascular regulation. In this study, multiple bioinformatics approaches were used to identify TGM2 as a candidate gene associated with AIS. Single-cell RNA sequencing (scRNA-seq) data were further integrated to analyze the expression pattern of TGM2 across different cell types and to explore its potential intercellular communication context. Finally, TGM2 expression was validated in peripheral blood samples from patients with AIS. This study provides new evidence supporting the potential involvement of TGM2 in AIS and its value as a candidate biomarker.

Indexed as

Brain IschemiaComputational BiologyIschemic StrokeBiomarkersHumansProtein Glutamine gamma Glutamyltransferase 2BiomarkersProtein Glutamine gamma Glutamyltransferase 2TGM2 protein, humanAcute ischemic strokeBiomarkersCell–cell communicationSingle-cell RNA sequencingTGM2

Identifiers

PMID42436397
PMCPMC13640342

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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.