Evidence map›Paper›PMID 37772261›Full record

ArticleOpen life sciences2023

Bioinformatics analysis to identify potential biomarkers for the pulmonary artery hypertension associated with the basement membrane.

Qian Li, Hu Zhang

Open access · goldAbstract read
In one paragraph

Article in Open life sciences, 2023. 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
0.5field-weighted citation impact, top 28% 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, 2 citations in OpenAlex.

  1. 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

2 authors at 1 institution in 1 country.

Qian LiDepartment of Cardiac Surgery, The First Affiliated Hospital of Kunming Medical University, Kunming 650000, China.
Hu ZhangDepartment of Cardiology, The First Affiliated Hospital of Kunming Medical University, Kunming 650000, China.
First Affiliated Hospital of Kunming Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pulmonary arterial hypertension (PAH) is a rapidly progressing cardiopulmonary disease. It is characterized by increased pulmonary artery pressure and vascular resistance. The most notable histopathological characteristic is vascular remodeling. The changes in the basement membrane (BM) are believed to be related to vascular remodeling. It is crucial to identify potential biomarkers associated with the BM in PAH, to guide its treatment. The microarray datasets GSE117261 and GSE113439 were downloaded from the Gene Expression Omnibus. Two data sets were examined to identify genes associated with the BM by analyzing gene expression changes. Next, we analyzed the relevant genes in the Kyoto Encyclopedia of Genes and Genomes using Gene Ontology and Disease Ontology annotationand conducted pathway enrichment analysis. We conducted a protein-protein interaction network analysis on the genes related to BMs and used the cell cytoHubba plug-in to identify the hub genes. Furthermore, we conducted an immune infiltration analysis and implemented a histogram model. Finally, we predicted and analyzed potential therapeutic drugs for PAH and set up a miRNA network of genetic markers. Six candidate genes related to BMs, namely Integrin Subunit Alpha V, Integrin Subunit Alpha 4, ITGA2, ITGA9, Thrombospondin 1, and Collagen Type IV Alpha 3 Chain, were identified as potential modulators of the immune process in PAH. Furthermore, ginsenoside Rh1 was found to significantly impact drug targeting based on its interactions with the six BM-related genes identified earlier. A novel biomarker related to the BM, which plays a crucial role in the development of PAH, has been identified.

Indexed as

basement membranebioinformatics analysisceRNA networkimmune infiltration analysispulmonary arterial hypertension

Identifiers

PMID37772261
PMCPMC10523280
OpenAlexW4387068180

What OpenQuestion holds

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LicenceCC BY
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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.