Evidence map›Paper›PMID 41483378›Full record

ArticleHuman cell2026

A p53-responsive microRNA-100 released from cardiomyoblasts serves as an early biomarker for acute coronary syndrome.

Cheng-I Cheng, Ming-Huei Chou, Kuang-Den Chen, Po-Han Chen, Ying-Hsien Kao

Abstract read
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In one paragraph

Article in Human cell, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

5 authors.

Cheng-I ChengDivision of Cardiology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital, No. 123, Ta-Pei Road, Niao-Song District, Kaohsiung City, 83301, Taiwan. chris.chengi.cheng@gmail.com.
Ming-Huei ChouGraduate Institute of Clinical Medical Sciences, Chang Gung University College of Medicine, Kaohsiung, Taiwan.
Kuang-Den ChenInstitute for Translational Research in Biomedicine, Chang Gung Memorial Hospital, Kaohsiung, Taiwan.
Po-Han ChenDepartment of Medical Research, E-Da Hospital, I-Shou University, No. 1, Yida Rd., Yanchau District, Kaohsiung, 82445, Taiwan.
Ying-Hsien KaoDepartment of Medical Research, E-Da Hospital, I-Shou University, No. 1, Yida Rd., Yanchau District, Kaohsiung, 82445, Taiwan. ed105156@edah.org.tw.ORCID http://orcid.org/0000-0001-7803-9384

Funding

Chang Gung Memorial Hospital CMRPG8B0751Chang Gung Memorial Hospital CMRPG8H1191E-Da Hospital EDAHT109033
6 · The paper itself

Abstract

Coronary artery disease, a leading cause of mortality, underscores the need for biomarkers that can predict acute coronary syndrome (ACS) occurrence and outcomes. MicroRNAs (miRNAs) are increasingly recognized as potential markers. This study aimed to identify a plasma miRNA signature in ACS patients undergoing elective cardiac catheterization and to investigate miR-100's potential as an ACS prognostic biomarker. Plasma samples from 100 patients with suspected ACS were analyzed. qPCR revealed significantly elevated plasma miR-29a-3p, miR-100, miR-192, and miR-194-5p in ACS patients, and multiplex ELISA showed increased myeloperoxidase. Sub-network enrichment analysis identified TP53 as a central regulator of the miRNA-gene interaction network. In H9c2 cardiomyoblasts, hypoxic treatment (1% O

Indexed as

Acute Coronary SyndromeMicroRNAsMyoblasts, CardiacTumor Suppressor Protein p53AnimalsBiomarkersFemaleHumansMaleMiddle AgedNF-kappa BPrognosisRatsBiomarkersMicroRNAsMIRN100 microRNA, humanNF-kappa BTP53 protein, humanTumor Suppressor Protein p53Acute coronary syndromeCardiomyoblastsHypoxiamicroRNATP53

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.