Evidence map›Paper›PMID 29928570›Full record

ArticleFEBS open bio2018

Bioinformatic screening for key miRNAs and genes associated with myocardial infarction.

Ke Wu, Qiang Zhao, Zhengmei Li, Nannan Li, Qiang Xiao, Xiuchang Li, Quanming Zhao

Abstract read
In one paragraph

Article in FEBS open bio, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. HSPA6 and its role in cancers and other diseases.Molecular biology reports · 2022
    Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Identification of key genes involved in myocardial infarction.European journal of medical research · 2019
    Article
  19. 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

7 authors.

Ke WuDepartment of Cardiology Beijing Anzhen Hospital Capital Medical University Beijing China.
Qiang ZhaoDepartment of Cardiology Affiliated Hospital of Taishan Medical University of Shandong Province Taian China.
Zhengmei LiDepartment of Radiology Taishan Medical University of Shandong Province Taian China.
Nannan LiDepartment of Respiration Medicine Central Hospital of Taian of Shandong Province China.
Qiang XiaoDepartment of Cardiology Affiliated Hospital of Taishan Medical University of Shandong Province Taian China.
Xiuchang LiDepartment of Cardiology Affiliated Hospital of Taishan Medical University of Shandong Province Taian China.
Quanming ZhaoDepartment of Cardiology Beijing Anzhen Hospital Capital Medical University Beijing China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite significant advances in understanding of the causes of and treatment of myocardial infarction (MI) in recent years, morbidity and mortality is still high. The aim of this study was to identify miRNA and genes potentially associated with MI. mRNA and miRNA expression datasets were downloaded from the Gene Expression Omnibus database (http://www.ncbi.nlm.nih.gov/geo/). Interactions between miRNA and the expression and function of target genes were analyzed, and a protein-protein interaction network was constructed. The diagnostic value of identified miRNA and genes was assessed. Quantitative RT-PCR was applied to validate the results of the bioinformatics analysis. MiR-27a, miR-31*, miR-1291, miR-139-5p, miR-204, miR-375, and target genes including

Indexed as

diagnostic biomarkersmiRNA‐target networkmyocardial infarctionprotein–protein interaction network

Identifiers

PMID29928570
PMCPMC5985982

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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.