Evidence map›Paper›PMID 30174600›Full record

ReviewFrontiers in pharmacology2018

miR-133: A Suppressor of Cardiac Remodeling?

Ning Li, Heng Zhou, Qizhu Tang

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 101 papers.

0numbers the graph read from it
0cells of the map it votes in
101citing papers in PubMed
5.9field-weighted citation impact, top 3% 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

101 citing papers in PubMed, 147 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Impact ofJournal of cardiovascular development and disease · 2026
    Review
  5. Review
  6. Genes · 2026
    Review
  7. Review
  8. Article
  9. Review
  10. Review
  11. Review
  12. Review
  13. Review
  14. Review
  15. Review
  16. RNA Therapeutics in Heart Failure.Journal of cardiovascular translational research · 2025
    Review
  17. Article
  18. Review
  19. Review
  20. Review

41 more citing papers are in PubMed but not listed here.

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

3 authors at 1 institution in 1 country.

Ning LiDepartment of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China.
Heng ZhouDepartment of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China.
Qizhu TangDepartment of Cardiology, Renmin Hospital of Wuhan University, Wuhan, China.
Renmin Hospital of Wuhan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiac remodeling, which is characterized by mechanical and electrical remodeling, is a significant pathophysiological process involved in almost all forms of heart diseases. MicroRNAs (miRNAs) are a group of non-coding RNAs of 20-25 nucleotides in length that primarily regulate gene expression by promoting mRNA degradation or post-transcriptional repression in a sequence-specific manner. Three miR-133 genes have been identified in the human genome, miR-133a-1, miR-133a-2, and miR-133b, which are located on chromosomes 18, 20, and 6, respectively. These miRNAs are mainly expressed in muscle tissues and appear to repress the expression of non-muscle genes. Based on accumulating evidence, miR-133 participates in the proliferation, differentiation, survival, hypertrophic growth, and electrical conduction of cardiac cells, which are essential for cardiac fibrosis, cardiac hypertrophy, and arrhythmia. Nevertheless, the roles of miR-133 in cardiac remodeling are ambiguous, and the mechanisms are also sophisticated, involving many target genes and signaling pathways, such as RhoA, MAPK, TGFβ/Smad, and PI3K/Akt. Therefore, in this review, we summarize the critical roles of miR-133 and its potential mechanisms in cardiac remodeling.

Indexed as

electrical remodelingfibrosishypertrophymiR-133reprogram

Identifiers

PMID30174600
PMCPMC6107689
OpenAlexW2887676634

What OpenQuestion holds

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Registered trials

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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.