Evidence map›Paper›PMID 42058121›Full record

ArticleIBRO neuroscience reports2026

The role of serum exosomal miR-23a-3p and miR-375-3p in acute ischemic stroke.

Peng Ou, Lin Liu, Xia Zhou, Wenyi Huang, Jiangmin Li, Yulan Chen, Qiying Tan, Rui Gao, Kejie Chen, Danni Zheng and 5 more

Abstract read
In one paragraph

Article in IBRO neuroscience reports, 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

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2 · The registry

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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

15 authors.

Peng OuSchool of Biomedical Sciences and Technology, Chengdu Medical College, Chengdu, China; Sichuan Higher Education Institute Key Laboratory of Major Disease Target Discovery and Protein Drug Development; Disease Biomarker Research Center of Chengdu Medical College, China.
Lin LiuSchool of Biomedical Sciences and Technology, Chengdu Medical College, Chengdu, China; Sichuan Higher Education Institute Key Laboratory of Major Disease Target Discovery and Protein Drug Development; Disease Biomarker Research Center of Chengdu Medical College, China.
Xia ZhouSchool of Pharmacy, Chengdu Medical College, Chengdu, China.
Wenyi HuangSchool of Biomedical Sciences and Technology, Chengdu Medical College, Chengdu, China; Sichuan Higher Education Institute Key Laboratory of Major Disease Target Discovery and Protein Drug Development; Disease Biomarker Research Center of Chengdu Medical College, China.
Jiangmin LiSchool of Biomedical Sciences and Technology, Chengdu Medical College, Chengdu, China; Sichuan Higher Education Institute Key Laboratory of Major Disease Target Discovery and Protein Drug Development; Disease Biomarker Research Center of Chengdu Medical College, China.
Yulan ChenSchool of Biomedical Sciences and Technology, Chengdu Medical College, Chengdu, China; Sichuan Higher Education Institute Key Laboratory of Major Disease Target Discovery and Protein Drug Development; Disease Biomarker Research Center of Chengdu Medical College, China.
Qiying TanSchool of Biomedical Sciences and Technology, Chengdu Medical College, Chengdu, China; Sichuan Higher Education Institute Key Laboratory of Major Disease Target Discovery and Protein Drug Development; Disease Biomarker Research Center of Chengdu Medical College, China.
Rui GaoSchool of Biomedical Sciences and Technology, Chengdu Medical College, Chengdu, China; Sichuan Higher Education Institute Key Laboratory of Major Disease Target Discovery and Protein Drug Development; Disease Biomarker Research Center of Chengdu Medical College, China.
Kejie ChenSchool of Public Health, Chengdu Medical College, Chengdu, China.
Danni ZhengBiomedical Informatics and Digital Health, School of Medical Sciences, University of Sydney, Sydney, NSW, Australia.
Quandan TanDepartment of Neurology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Yapeng LinDepartment of Neurology, The First Affiliated Hospital of Chengdu Medical College, Chengdu, China.
Dan WangSchool of Biomedical Sciences and Technology, Chengdu Medical College, Chengdu, China; Sichuan Higher Education Institute Key Laboratory of Major Disease Target Discovery and Protein Drug Development; Disease Biomarker Research Center of Chengdu Medical College, China.
Jie YangDepartment of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Junli HaoSchool of Biomedical Sciences and Technology, Chengdu Medical College, Chengdu, China; Sichuan Higher Education Institute Key Laboratory of Major Disease Target Discovery and Protein Drug Development; Disease Biomarker Research Center of Chengdu Medical College, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives:Serum exosomal miRNAs are promising biomarkers and therapeutic targets for multiple diseases, but their expression profiles and functions in acute ischemic stroke (AIS) remain unclear. This study aimed to clarify the expression characteristics of serum exosomal miRNAs in AIS and explore the regulatory roles of key miRNAs in AIS progression.Methods:We first detected serum exosomal miRNA expression profiles of AIS patients and healthy controls via RNA-seq, then validated candidate miRNA levels using qRT-PCR. Enzyme-linked immunosorbent assay (ELISA) was employed to measure serum levels of antithrombotic proteins [thrombomodulin (TM), endothelial NO synthase (eNOS), tissue plasminogen activator (t-PA)]. The regulatory effects of differentially expressed miRNAs on these proteins were verified in human umbilical vein endothelial cells (HUVEC) via transfection assays. Statistical analyses were performed using SPSS 26 and GraphPad Prism 8.Results:Compared with healthy controls, AIS patients exhibited significantly decreased serum exosomal levels of miR-23a-3p, miR-375-3p, and miR-122-5p, along with elevated serum TM, eNOS, and t-PA levels. miR-23a-3p and miR-375-3p could modulate the expression of TM, eNOS, and t-PA in HUVEC, and this regulatory relationship may be direct or indirect. The combination of these miRNAs and proteins achieved moderate predictive efficacy for AIS occurrence.Discussion:This study identifies serum exosomal miR-23a-3p and miR-375-3p as potential biomarkers for AIS and reveals their regulatory role in antithrombotic protein expression, providing novel insights into AIS's molecular mechanism and diagnostic strategies.

Indexed as

Acute ischemic stroke (AIS)BiomarkersMiR-23a-3pMiR-375–3pRNA-seqSerum exosomal miRNAs

Identifiers

PMID42058121
PMCPMC13123579

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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.