Evidence map›Paper›PMID 35221717›Full record

ArticleInternational journal of general medicine2022

Identifying of miRNA-mRNA Regulatory Networks Associated with Acute Kidney Injury by Weighted Gene Co-Expression Network Analysis.

Jie Xu, Yunfei Xu

Open access · goldAbstract read
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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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 37% 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 4 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Jie XuDepartment of Urology, Pudong New Area People's Hospital, Shanghai, 201299, People's Republic of China.
Yunfei XuDepartment of Urology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai, 200072, People's Republic of China.
Shanghai Tenth People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute kidney injury (AKI) is a clinical emergency characterized by a dramatic decline in renal function and the accumulation of metabolic waste products in the body, with a high morbidity and mortality rate. The pathogenesis of AKI remains unclear and there are no effective treatment options.

methodsWe aimed to identify critical genes involved in the pathogenesis of AKI and construct a miRNA-mRNA regulatory network using gene expression data downloaded from Gene Expression Omnibus (GSE85957) for 38 kidneys of AKI and 19 control rats and cisplatin treated kidneys of 3 AKI and 3 control rats. Data in GSE85957 were processed using weighted gene co-expression network analysis (WGCNA), and biological function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to analyze the functions associated with critical genes.

resultsTwenty-eight modules in the GSE85957 dataset were identified by WGCNA, of which 103 genes in the orange module and 30 genes in the black module were closely associated with AKI and dose. Biological function analysis of genes in the orange and black modules revealed that skeletal muscle cell differentiation, tissue development and organ development were involved in the pathological changes of AKI. Combining with our experimentally processed AKI rat kidney data, eight genes (Atf3, Egr1, Egr2, Fos, Fosb, Gdf15, Serpine1 and Nr1d1) were identified as potential biomarkers of AKI, and miRNA-mRNA regulatory networks were constructed based on the above eight critical genes. Further tissue validation revealed that Egr1 and Fos were highly expressed in AKI.

conclusionOur study identified potential biomarkers of AKI and constructed an associated miRNA-mRNA regulatory network, which may provide new insights into the molecular pathogenesis of AKI.

Indexed as

acute kidney injurycritical genesmiRNA–mRNA regulatory networksWGCNA analysis

Identifiers

PMID35221717
PMCPMC8865863
OpenAlexW4213177940

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