Evidence map›Paper›PMID 35282650›Full record

ArticleInternational journal of general medicine2022

The Key Genes Underlying Pathophysiology Correlation Between the Acute Myocardial Infarction and COVID-19.

Hongjun You, Qianqian Zhao, Mengya Dong

Open access · goldAbstract read
In one paragraph

Article in International journal of general medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. 1-L Transcription of SARS-CoV-2 Spike Protein S1 Subunit.International journal of molecular sciences · 2024
    Article
  3. Review
  4. Article
  5. Article
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 2 institutions in 1 country.

Hongjun YouDepartment of Cardiovascular Medicine, Shaanxi Provincial People's Hospital, Xi'an, 710068, Shaanxi, People's Republic of China.
Qianqian ZhaoDepartment of Clinical Immunology, The First Affiliated Hospital, Air Force Military Medical University, Xi'an, 710032, Shaanxi, People's Republic of China.
Mengya DongDepartment of Cardiovascular Medicine, Shaanxi Provincial People's Hospital, Xi'an, 710068, Shaanxi, People's Republic of China.ORCID 0000-0001-6453-6822
Shanxi Medical University · CNAir Force Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Accumulating evidences disclose that COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has a marked effect on acute myocardial infarction (AMI). Nevertheless, the underlying pathophysiology correlation between the AMI and COVID-19 remains vague. Materials and Methods: Bioinformatics analyses of the altered transcriptional profiling of peripheral blood mononuclear cells (PBMCs) in patients with AMI and COVID-19 were implemented, including identification of differentially expressed genes and common genes between AMI and COVID-19, protein-protein interactions, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses, TF-genes and miRNA coregulatory networks, to explore their biological functions and potential roles in the pathogenesis of COVID-19-related AMI. Conclusion: Our bioinformatic analyses of gene expression profiling of PBMCs in patients with AMI and COVID-19 provide us with a unique view regarding underlying pathophysiology correlation between the two vital diseases.

Indexed as

AMIbioinformaticsDEGsdifferentially expressed genespathophysiologySARS-CoV-2

Identifiers

PMID35282650
PMCPMC8904943
OpenAlexW4214809278

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.