Evidence map›Paper›PMID 35322335›Full record

ArticleFunctional & integrative genomics2022

Identification of the TF-miRNA-mRNA co-regulatory networks involved in sepsis.

Xiaoqian Luo, Weina Lu, Jianfeng Zhao, Jun Hu, Enjiang Chen, Shi Fu, Qinghui Fu

Abstract read
PubMed Publisher
In one paragraph

Article in Functional & integrative genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 48% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. miR-130a-3p Exacerbates Sepsis-Induced Cardiac Dysfunction by Promoting Inflammation and Targeting PDK4.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis
    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

7 authors at 2 institutions in 1 country.

Xiaoqian LuoThe Department of SICU, The Second Affiliated Hospital of Zhejiang University School of Medicine, Jiefang street 88th, Hangzhou, 310009, Zhejiang Province, China.
Weina LuThe Department of SICU, The Second Affiliated Hospital of Zhejiang University School of Medicine, Jiefang street 88th, Hangzhou, 310009, Zhejiang Province, China.
Jianfeng ZhaoThe Department of SICU, The First Affiliated Hospital, Zhejiang University School of Medicine, Qingchun street 79th, Hangzhou, 310003, Zhejiang Province, China.
Jun HuThe Department of SICU, The Second Affiliated Hospital of Zhejiang University School of Medicine, Jiefang street 88th, Hangzhou, 310009, Zhejiang Province, China.
Enjiang ChenThe Department of SICU, The Second Affiliated Hospital of Zhejiang University School of Medicine, Jiefang street 88th, Hangzhou, 310009, Zhejiang Province, China.
Shi FuThe Department of SICU, The First Affiliated Hospital, Zhejiang University School of Medicine, Qingchun street 79th, Hangzhou, 310003, Zhejiang Province, China.
Qinghui FuThe Department of SICU, The First Affiliated Hospital, Zhejiang University School of Medicine, Qingchun street 79th, Hangzhou, 310003, Zhejiang Province, China. 2513107@zju.edu.cn.ORCID http://orcid.org/0000-0001-6380-7803
Second Affiliated Hospital of Zhejiang University · CNFirst Affiliated Hospital Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sepsis is a life-threatening medical condition caused by a dysregulated host response to infection. Recent studies have found that the expression of miRNAs is associated with the pathogenesis of sepsis and septic shock. Our study aimed to reveal which miRNAs may be involved in the dysregulated immune response in sepsis and how these miRNAs interact with transcription factors (TFs) using a computational approach with in vitro validation studies. To determine the network of TFs, miRNAs, and target genes involved in sepsis, GEO datasets GSE94717 and GSE131761 were used to identify differentially expressed miRNAs and DEGs. TargetScan and miRWalk databases were used to predict biological targets that overlap with the identified DEGs of differentially expressed miRNAs. The TransmiR database was used to predict the differential miRNA TFs that overlap with the identified DEGs. The TF-miRNA-mRNA network was constructed and visualized. Finally, qRT-PCR was used to verify the expression of TFs and miRNA in HUVECs. Between the healthy and sepsis groups, there were 146 upregulated and 98 downregulated DEGs in the GSE131761 dataset, and there were 1 upregulated and 183 downregulated DEMs in the GSE94717 dataset. A regulatory network of the TF-miRna target genes was established. According to the experimental results, RUNX3 was found to be downregulated while MAPK14 was upregulated, which corroborates the result of the computational expression analysis. In a HUVECs model, miR-19b-1-5p and miR-5009-5p were found to be significantly downregulated. Other TFs and miRNAs did not correlate with our bioinformatics expression analysis. We constructed a TF-miRNA-target gene regulatory network and identified potential treatment targets RUNX3, MAPK14, miR-19b-1-5p, and miR-5009-5p. This information provides an initial basis for understanding the complex sepsis regulatory mechanisms.

Indexed as

MicroRNAsMitogen-Activated Protein Kinase 14SepsisTranscription FactorsComputational BiologyGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansRNA, MessengerMicroRNAsMitogen-Activated Protein Kinase 14RNA, MessengerTranscription FactorsmiRNASepsisTranscription factors

Identifiers

PMID35322335
OpenAlexW4220942418

What OpenQuestion holds

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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.