Evidence map›Paper›PMID 40850945›Full record

ArticleInternational journal of legal medicine2026

Differential diagnosis of acute myocardial infarction based on plasma Exosomal MicroRNA.

Peng Zhou, Jia Zhang, Xiangjun Wu, Leilei Zhang, Qinlai Liu, Ruotong Xiong, Yujie Wang, Min Li, Ran Wei, Xiaoqun Xu and 4 more

Abstract read
PubMed Publisher
In one paragraph

Article in International journal of legal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

14 authors.

Peng Zhou *Binzhou People's Hospital, Shandong First Medical University, Binzhou, 256600, PR China.
Jia Zhang *Binzhou People's Hospital, Shandong First Medical University, Binzhou, 256600, PR China.
Xiangjun Wu *Binzhou People's Hospital, Shandong First Medical University, Binzhou, 256600, PR China.
Leilei ZhangPhysical Evidence Appraisal Center of Shandong Provincial Public Security Department, Jinan, PR China.
Qinlai LiuBinzhou People's Hospital, Shandong First Medical University, Binzhou, 256600, PR China.
Ruotong XiongBinzhou People's Hospital, Shandong First Medical University, Binzhou, 256600, PR China.
Yujie WangBinzhou People's Hospital, Shandong First Medical University, Binzhou, 256600, PR China.
Min LiBinzhou People's Hospital, Shandong First Medical University, Binzhou, 256600, PR China.
Ran WeiBinzhou People's Hospital, Shandong First Medical University, Binzhou, 256600, PR China.
Xiaoqun XuBinzhou People's Hospital, Shandong First Medical University, Binzhou, 256600, PR China.
Deping MengBinzhou People's Hospital, Shandong First Medical University, Binzhou, 256600, PR China.
Chunjiang YuBinzhou People's Hospital, Shandong First Medical University, Binzhou, 256600, PR China.
Jiangwei YanShanxi Medical University, Taiyuan, 030001, PR China. yanjw@sxmu.edu.cn.
Chen FangBinzhou People's Hospital, Shandong First Medical University, Binzhou, 256600, PR China. chenfangyulix@126.com.ORCID http://orcid.org/0000-0003-2441-4470

Funding

National Natural Science Foundation of China 82002006
6 · The paper itself

Abstract

objectThe differentiation of acute myocardial infarction (AMI) has long been a challenging problem in clinical diagnosis and forensic identification. Recent studies have shown that microRNAs (miRNAs) in exosomes are involved in the development and progression of AMI. results indicated that plasma exosomal miRNAs can be considered as novel biomarkers for early AMI recognition.

methodIn this study, exosomal miRNAs in plasma associated with the pathogenesis of AMI was explored and AMI identification model based on these miRNAs were established using machine learning technology.

resultFollowing the analysis of differentially expressed miRNAs in plasma-derived exosomes, the expression levels of 36 miRNAs increase with the passage of time, including miR-3473, miR-504, miR-490-5p, miR-218a-2-3p, and miR-760-3p, showed an increasing trend over time in the plasma exosomes of AMI rats. Based on machine learning techniques, miR-3473, miR-504, miR-490-5p, miR-218a-2-3p were used to construct a model for recognizing early AMI. The precision of the AMI identification model reached 0.955.

conclusionThe results indicated that plasma exosomal miRNAs can be considered as novel biomarkers for early AMI recognition.

Indexed as

ExosomesMicroRNAsMyocardial InfarctionAnimalsBiomarkersDiagnosis, DifferentialHumansMachine LearningMaleRatsRats, Sprague-DawleyBiomarkersMicroRNAsAcute myocardial infarctionExosomesMassively parallel sequencingMicroRNAsPlasma

Identifiers

PMID40850945

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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.