Evidence map›Paper›PMID 36420258›Full record

ArticleFrontiers in immunology2022

Bioinformatics and systems biology approaches to identify molecular targeting mechanism influenced by COVID-19 on heart failure.

Kezhen Yang, Jipeng Liu, Yu Gong, Yinyin Li, Qingguo Liu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 39% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

5 authors at 1 institution in 1 country.

Kezhen YangSchool of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China.
Jipeng LiuSchool of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China.
Yu GongSchool of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China.
Yinyin LiSchool of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China.
Qingguo LiuSchool of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese Medicine, Beijing, China.
Beijing University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has emerged as a contemporary hazard to people. It has been known that COVID-19 can both induce heart failure (HF) and raise the risk of patient mortality. However, the mechanism underlying the association between COVID-19 and HF remains unclear. The common molecular pathways between COVID-19 and HF were identified using bioinformatic and systems biology techniques. Transcriptome analysis was performed to identify differentially expressed genes (DEGs). To identify gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways, common DEGs were used for enrichment analysis. The results showed that COVID-19 and HF have several common immune mechanisms, including differentiation of T helper (Th) 1, Th 2, Th 17 cells; activation of lymphocytes; and binding of major histocompatibility complex class I and II protein complexes. Furthermore, a protein-protein interaction network was constructed to identify hub genes, and immune cell infiltration analysis was performed. Six hub genes (

Indexed as

COVID-19Heart FailureComputational BiologyHumansMolecular Targeted TherapySARS-CoV-2Systems Biologybioinformatics analysisCOVID-19heart failureimmunologysystems biology approaches

Identifiers

PMID36420258
PMCPMC9678344
OpenAlexW4308477176

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.