Evidence map›Paper›PMID 37745040›Full record

ArticleExperimental and therapeutic medicine2023

Integrated bioinformatics analysis and experimental validation reveals hub genes of rheumatoid arthritis.

Kun Luo, Yumei Zhong, Yanding Guo, Jingwei Nie, Yimei Xu, Haiyan Zhou

Abstract read
In one paragraph

Article in Experimental and therapeutic medicine, 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
–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

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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.

  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

6 authors.

Kun LuoAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, P.R. China.
Yumei ZhongDepartment of Painology, Chengdu Integrated TCM & Western Medicine Hospital/Chengdu First People's Hospital, Chengdu, Sichuan 610095, P.R. China.
Yanding GuoAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, P.R. China.
Jingwei NieAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, P.R. China.
Yimei XuAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, P.R. China.
Haiyan ZhouAcupuncture and Tuina School, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rheumatoid arthritis (RA) is an autoimmune disease characterized by systemic inflammation, especially synovitis, leading to joint damage. It is important to explore potential biomarkers and therapeutic targets to improve the clinical treatment of RA. However, the potential underlying mechanisms of action of available treatments for RA have not yet been fully elucidated. The present study investigated the potential biomarkers of RA and identified specific targets for therapeutic intervention. A comprehensive analysis was performed using mRNA files downloaded from the Gene Expression Omnibus. Differences in gene expression were analyzed and compared between the normal and RA groups. In addition, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on differentially expressed genes (DEGs). A protein-protein interaction network, Molecular Complex Detection and cytoHubba network were evaluated to identify hub genes. Finally, using an experimental RA rat model induced by Freund's complete adjuvant (FCA), the expression of potential biomarkers or target genes in RA were verified through reverse transcription-quantitative PCR. The results of the mRNA dataset processing revealed 195 DEGs in patients with RA when compared with the healthy controls. Moreover, 10 hub genes were identified in patients with RA and four candidate mRNAs were identified, as follows: Discs large homolog-associated protein 5 (

Indexed as

autoimmune diseasebioinformaticsbiomarkersgene expression omnibusrheumatoid arthritis

Identifiers

PMID37745040
PMCPMC10515114

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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.