Identification of Key Genes Associated with Changes in the Host Response to Severe Burn Shock: A Bioinformatics Analysis with Data from the Gene Expression Omnibus (GEO) Database.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33293847", "kind": "science-record", "revision": 9, "content_hash": "sha256:3cf38cf40338b83ad6f78edffdee0b607a83344edb6d8e1d8ca5cab69b0205c8", "created_at": "2026-11-01T15:41:18Z", "updated_at": "2026-11-01T22:45:46Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of Key Genes Associated with Changes in the Host Response to Severe Burn Shock: A Bioinformatics Analysis with Data from the Gene Expression Omnibus (GEO) Database.", "doi": "10.2147/JIR.S282722", "pmid": "33293847", "authors": ["Xiao Fang", "Shu-Fang Duan", "Yu-Zhou Gong", "Fei Wang", "Xu-Lin Chen"], "journal": "Journal of inflammation research", "year": 2020, "abstract": "BACKGROUND: Patients with severe burns continue to display a high mortality rate during the initial shock period. The precise molecular mechanism underlying the change in host response during severe burn shock remains unknown. This study aimed to identify key genes leading to the change in host response during burn shock.\nMETHODS: The GSE77791 dataset, which was utilized in a previous study that compared hydrocortisone administration to placebo (NaCl 0.9%) in the inflammatory reaction of severe burn shock, was downloaded from the Gene Expression Omnibus (GEO) database and analyzed to identify the differentially expressed genes (DEGs). Functional enrichment analyses of Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were performed. The protein-protein interaction (PPI) network of DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and then visualized in Cytoscape. In addition, important modules in this network were selected using the Molecular Complex Detection (MCODE) algorithm, and hub genes were identified in cytoHubba, a Cytoscape plugin.\nRESULTS: A total of 1059 DEGs (508 downregulated genes and 551 upregulated genes) were identified from the dataset. The DEGs enriched in GO terms and KEGG pathways were related to immune response. The PPI network contained 439 nodes and 2430 protein pairs. Finally, important modules and hub genes were identified using the different Cytoscape plugins. The key genes in burn shock were identified as arginase 1 (ARG1), cytoskeleton-associated protein (CKAP4), complement C3a receptor (C3AR1), neutrophil elastase (ELANE), gamma-glutamyl hydrolase (GGH), orosomucoid (ORM1), and quiescin sulfhydryl (QSOX1).\nCONCLUSION: The DEGs, functional terms and pathways, and hub genes identified in the present study can help shed light on the molecular mechanism underlying the changes in host response during burn shock and provide potential targets for early detection and treatment of burn shock.", "claims": [{"id": "claim-method", "statement": "The data were normalized, and DEGs were subsequently identified using the linear models for microarray data (LIMMA) package in R software (version 3.6.1).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33293847", "locator": "sections[4] \"Data Preprocessing: Identification of DEGs\" paragraph 2", "quote": "The data were normalized, and DEGs were subsequently identified using the linear models for microarray data (LIMMA) package in R software (version 3.6.1)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:33293847"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE77791"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE77791"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33293847", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/JIR.S282722", "sha256": "sha256:357d6656cbe15351e5b342de6f22ea9a83adcd925821288201350d8c3c4ff331", "bytes": 42875, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.2147/JIR.S282722", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7718973", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE77791", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE77791", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE77791", "version": null, "note": "“We acquired the microarray expression profiles of severe burn shock patients from the National Center for Biotechnology Information GEO database (http://www.ncbi.nlm.nih.gov/geo), which contains high-throughput gene expression data, chips, and microarrays, under the accession number GSE77791.” “The GSE77791 dataset, based on GPL570 (a platform for Affymetrix Human Genome U133 Plus 2.0 Array), contains 117 samples, including 30 samples collected from patients with burn shock prior to any treatment and 13 samples collected from healthy volunteers that served as controls.”", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "“We acquired the microarray expression profiles of severe burn shock patients from the National Center for Biotechnology Information GEO database (http://www.ncbi.nlm.nih.gov/geo), which contains high-throughput gene expression data, chips, and microarrays, under the accession number GSE77791.” “The GSE77791 dataset, based on GPL570 (a platform for Affymetrix Human Genome U133 Plus 2.0 Array), contains 117 samples, including 30 samples collected from 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