Evidence map›Paper›PMID 34604208›Full record

ReviewFrontiers in cell and developmental biology2021

The Roles of lncRNA in Myocardial Infarction: Molecular Mechanisms, Diagnosis Biomarkers, and Therapeutic Perspectives.

Luhan Xie, Qingqing Zhang, Jun Mao, Jun Zhang, Lianhong Li

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
3.5field-weighted citation impact, top 5% of its field
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

27 citing papers in PubMed, 45 citations in OpenAlex.

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  7. Human mtDNA-Encoded Long ncRNAs: Knotty Molecules and Complex Functions.International journal of molecular sciences · 2024
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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 at 1 institution in 1 country.

Luhan XieDepartment of Pathology and Forensic Medicine, College of Basic Medical Sciences, Dalian Medical University, Dalian, China.
Qingqing ZhangDepartment of Pathology and Forensic Medicine, College of Basic Medical Sciences, Dalian Medical University, Dalian, China.
Jun MaoDepartment of Pathology and Forensic Medicine, College of Basic Medical Sciences, Dalian Medical University, Dalian, China.
Jun ZhangDepartment of Teaching Affairs, Dalian Medical University, Dalian, China.
Lianhong LiDepartment of Pathology and Forensic Medicine, College of Basic Medical Sciences, Dalian Medical University, Dalian, China.
Dalian Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, long non-coding RNAs (lncRNAs) have been demonstrated to be associated with many physiological and pathological processes in cardiac. Recent studies have shown that lncRNAs are expressed dynamically in cardiovascular diseases and participate in regulation through a variety of molecular mechanisms, which have become a critical part of the epigenetic and transcriptional regulatory pathways in heart development, as well as the initiation and progress of myocardial infarction. In this review, we summarized some current research about the roles of lncRNAs in heart development and myocardial infarction, with the emphasis on molecular mechanisms of pathological responses, and highlighted their functions in the secondary changes of myocardial infarction. We also discussed the possibility of lncRNAs as novel diagnostic biomarkers and potential therapeutic targets for myocardial infarction.

Indexed as

biomarkerceRNAexosomelong non-coding RNAsmyocardial infarction

Identifiers

PMID34604208
PMCPMC8481623
OpenAlexW3199044236

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.