Evidence map›Paper›PMID 36103997›Full record

ArticleJournal of burn care & research : official publication of the American Burn Association2024

Identification of Key Genes Related to Skin Burns Based on Bioinformatics Analysis.

Boheng Zhu, Gaofei Zhang, Wuquan Li, Wende Cao, Jinglin Zhang, Hong Wang

Open access · hybridAbstract read
In one paragraph

Article in Journal of burn care & research : official publication of the American Burn Association, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 53% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 1 institution in 1 country.

Boheng ZhuDepartment of Burns, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Gaofei ZhangDepartment of Burns, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Wuquan LiDepartment of Burns, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Wende CaoDepartment of Burns, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Jinglin ZhangDepartment of Burns, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Hong WangDepartment of Burns, The Second Affiliated Hospital of Kunming Medical University, Kunming, China.
Kunming Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To further understand the regulatory network and molecular mechanisms of gene expression after skin burns, we performed bioinformatics analysis of gene expression profiles of skin burn samples and identified key genes associated with skin burns. The GSE8056 and GSE139028 datasets were downloaded from the Gene Expression Omnibus database for analysis and validation. The limma package was used to screen for differentially expressed genes (DEGs). Gene ontology and pathway enrichment analyses (KEGG) were then performed. Subsequently, LASSO regression analysis was performed on DEGs and a regulatory network map of skin burn-related genes was constructed. Finally, the infiltration of immune cells was calculated and coexpression network maps of immune-related key genes and skin regeneration genes were constructed. Analysis of the GSE8056 dataset showed that 432 genes were upregulated and 351 genes were downregulated. The DEGs were mainly focused on immune response and skin regeneration. Meanwhile, these two groups of pivotal genes were significantly associated with abnormal infiltration of nine immune cells. GSE139028 validation revealed that three hub genes associated with skin burn immunity were differentially expressed, except for S100A8, while only the DPT gene was differentially expressed among the seven hub genes associated with skin regeneration. In short, the effect of skin burn on patients is to regulate the expression of immune-related genes UPP1, MMP1, MMP3, and skin regeneration-related gene DPT, which may be the key target for the treatment of skin burn.

Indexed as

BurnsComputational BiologyGene Expression ProfilingGene Regulatory NetworksHumansTranscriptome

Identifiers

PMID36103997
PMCPMC11379151
OpenAlexW4295793803

What Socratic holds

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LicenceCC BY
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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 Socratic graph.