Evidence map›Paper›PMID 35812190›Full record

ArticleTranslational andrology and urology2022

Bioinformatics analysis of the potential regulatory mechanisms of renal fibrosis and the screening and identification of factors related to human renal fibrosis.

Cixiao Wang, Shaobo Wu, Jiang Li, Yuexian Ma, Youqun Huang, Na Fang

Open access · diamondAbstract read
In one paragraph

Article in Translational andrology and urology, 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
0.3field-weighted citation impact, top 42% 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, 3 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

6 authors at 2 institutions in 1 country.

Cixiao Wang *Department of Nephrology-2, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Shaobo Wu *Department of Nephrology-1, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Jiang Li *Department of General Practice, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Yuexian MaDepartment of Nephrology-2, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Youqun HuangDepartment of Nephrology-2, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Na FangDepartment of Endocrine, Institute of Traditional Chinese Medicine of Sichuan Academy of Chinese Medicine Sciences, Chengdu, China.
Chengdu University of Traditional Chinese Medicine · CNSichuan Academy of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This paper aimed to identify the key genes and potential mechanisms of renal fibrosis, and provide methods of evaluation and new ideas for the early diagnosis and treatment of renal fibrosis. Methods: The GSE102515 dataset was searched from the Gene Expression Omnibus (GEO) database was searched, the differential genes were screened out, and the down-regulated and up-regulated genes were identified. Enrichment analysis of differential genes in the development of renal fibrosis was carried out using the DAVID database, differential genes were analyzed using the STRING database, and Cytoscape software was used for visual processing. Results: Eighteen up-regulated genes and ten down-regulated genes were screened. Differential genes are mainly involved in the integrin-mediated signaling pathway and mitotic sister chromatid binding, etc. We found that the molecular functions (MFs) of the differential genes are phospholipid binding and regulatory region DNA binding, etc. Moreover, the cellular components (CCs) of the differential genes are mainly related to low-density lipoprotein (LDL) particles and nuclei. Screening revealed that Conclusions: In this study, the differential genes in the occurrence of renal fibrosis were screened out via dataset analysis. It was found that

Indexed as

Bioinformatics analysischronic kidney disease (CKD)diagnosis and treatmentrenal fibrosis

Identifiers

PMID35812190
PMCPMC9262747
OpenAlexW4283590187

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.