Identification of novel biomarkers in septic cardiomyopathy via integrated bioinformatics analysis and experimental validation.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35957694", "kind": "science-record", "revision": 5, "content_hash": "sha256:1fc9391ea0710ae15a15d9529043df96e19e4d03152b3174df91c045350f6551", "created_at": "2026-11-01T18:15:03Z", "updated_at": "2026-11-01T22:49:45Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of novel biomarkers in septic cardiomyopathy via integrated bioinformatics analysis and experimental validation.", "doi": "10.3389/fgene.2022.929293", "pmid": "35957694", "authors": ["Feng Lu", "Feng Hu", "Baiquan Qiu", "Hongpeng Zou", "Jianjun Xu"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Purpose: Septic cardiomyopathy (SCM) is an important world public health problem with high morbidity and mortality. It is necessary to identify SCM biomarkers at the genetic level to identify new therapeutic targets and strategies. Method: DEGs in SCM were identified by comprehensive bioinformatics analysis of microarray datasets (GSE53007 and GSE79962) downloaded from the GEO database. Subsequently, bioinformatics analysis was used to conduct an in-depth exploration of DEGs, including GO and KEGG pathway enrichment analysis, PPI network construction, and key gene identification. The top ten Hub genes were identified, and then the SCM model was constructed by treating HL-1 cells and AC16 cells with LPS, and these top ten Hub genes were examined using qPCR. Result: STAT3, SOCS3, CCL2, IL1R2, JUNB, S100A9, OSMR, ZFP36, and HAMP were significantly elevated in the established SCM cells model. Conclusion: After bioinformatics analysis and experimental verification, it was demonstrated that STAT3, SOCS3, CCL2, IL1R2, JUNB, S100A9, OSMR, ZFP36, and HAMP might play important roles in SCM.", "claims": [{"id": "claim-method", "statement": "After data preprocessing, DEGs were analyzed using the limma package of R software (version 4.2.1).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35957694", "locator": "sections[4] \"Identification of differentially expressed genes\" paragraph 2", "quote": "After data preprocessing, DEGs were analyzed using the limma package of R software (version 4.2.1)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/Supplementary Materials; further inquiries can be directed to the corresponding author.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35957694", "locator": "sections[18] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/Supplementary Materials; further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Nine hub genes were significantly elevated in the LPS-treated HL-1 and AC16 cell septic cardiomyopathy models: STAT3, SOCS3, CCL2, IL1R2, JUNB, S100A9, OSMR, ZFP36, and HAMP.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35957694", "locator": "sections[14] \"Quantitative real-time PCR of differentially expressed genes\" paragraph 2", "quote": "Nine hub genes were significantly elevated in the LPS-treated HL-1 cell SCM model, including STAT3, SOCS3, CCL2, IL1R2, JUNB, S100A9, OSMR, ZFP36, and HAMP (Figure 5A). The same results were obtained in the SCM model constructed by LPS-treated AC16 cells (Figure 5B)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Nine hub genes were significantly elevated in the LPS-treated HL-1 and AC16 cell septic cardiomyopathy models: STAT3, SOCS3, CCL2, IL1R2, JUNB, S100A9, OSMR, ZFP36, and HAMP.", "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:35957694"], "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": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. 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