Evidence map›Paper›PMID 29512785›Full record

ArticleMolecular medicine reports2018

Identification of potential genes and miRNAs associated with sepsis based on microarray analysis.

Yin Li, Fengxia Zhang, Yan Cong, Yun Zhao

Open access · hybridAbstract read
In one paragraph

Article in Molecular medicine reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.4field-weighted citation impact, top 41% 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

9 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. TheInfection and drug resistance · 2021
    Article
  8. Article
  9. Bioinformatics Analysis for Multiple Gene Expression Profiles in Sepsis.Medical science monitor : international medical journal of experimental and clinical research · 2020
    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

4 authors at 1 institution in 1 country.

Yin Li *Emergency Department, Huadong Hospital, Shanghai 200040, P.R. China.
Fengxia Zhang *Emergency Department, Huadong Hospital, Shanghai 200040, P.R. China.
Yan CongEmergency Department, Huadong Hospital, Shanghai 200040, P.R. China.
Yun ZhaoEmergency Department, Huadong Hospital, Shanghai 200040, P.R. China.
Huadong Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sepsis is a type of systemic inflammatory response syndrome caused by infection. The present study aimed to examine key genes and microRNAs (miRNAs) involved in the pathogenesis of sepsis. The GSE13205 microarray dataset, downloaded from the Gene Expression Omnibus was analyzed using bioinformatics tools, and included muscle biopsy specimens of 13 patients with sepsis and eight healthy controls. The differentially expressed genes (DEGs) in samples from patients with sepsis were identified using the Linear Models for Microarray package in R language. Using the Database for Annotation, Visualization and Integration Discovery tool, functional and pathway enrichment analyses were performed to examine the potential functions of the DEGs. The protein‑protein interaction (PPI) network was constructed with the DEGs using the Search Tool for the Retrieval of Interacting Genes, and the network topology was analyzed using CytoNCA. Subsequently, MCODE in Cytoscape was used to identify modules in the PPI network. Finally, the integrated regulatory network was constructed based on the DEGs, miRNAs and transcription factors (TFs). A total of 259 upregulated DEGs (MYC and BYSL) and 204 downregulated DEGs were identified in the patients with sepsis. NOP14, NOP2, AATF, GTPBP4, BYSL and TRMT6 were key genes in the MCODE module. In the integrated DEG‑miRNA‑TF regulatory network, hsa‑miR‑150 (target gene MYLK3) and 21 TFs, comprising 14 upregulated DEGs (including MYC) and seven downregulated DEGs, were identified. The results suggested that NOP14, NOP2, AATF, GTPBP4, BYSL, MYC, MYLK3 and miR‑150 may be involved in the pathogenesis of sepsis.

Indexed as

Gene Expression ProfilingGene Expression RegulationOligonucleotide Array Sequence AnalysisFemaleHumansMaleMicroRNAsSepsisMicroRNAsMIR150, humanarget geneintegrated regulatory networkmicroRNArotein‑protein interactionsepsis

Identifiers

PMID29512785
PMCPMC5928603
OpenAlexW2790907485

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.