Revealing Potential Spinal Cord Injury Biomarkers and Immune Cell Infiltration Characteristics in Mice.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35706450", "kind": "science-record", "revision": 5, "content_hash": "sha256:506f7c73cb565740aa9f7da250a4ef0cce2dcfc136a3eafcb1ad08871f380f3a", "created_at": "2026-11-01T18:14:40Z", "updated_at": "2026-11-01T22:49:18Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Revealing Potential Spinal Cord Injury Biomarkers and Immune Cell Infiltration Characteristics in Mice.", "doi": "10.3389/fgene.2022.883810", "pmid": "35706450", "authors": ["Liang Cao", "Qing Li"], "journal": "Frontiers in genetics", "year": 2022, "abstract": "Spinal cord injury (SCI) is a disabling condition with significant morbidity and mortality. Currently, no effective SCI treatment exists. This study aimed to identify potential biomarkers and characterize the properties of immune cell infiltration during this pathological event. To eliminate batch effects, we concurrently analyzed two mouse SCI datasets (GSE5296, GSE47681) from the GEO database. First, we identified differentially expressed genes (DEGs) using linear models for microarray data (LIMMA) and performed functional enrichment studies on those DEGs. Next, we employed bioinformatics and machine-learning methods to identify and define the characteristic genes of SCI. Finally, we validated them using immunofluorescence and qRT-PCR. Additionally, this study assessed the inflammatory status of SCI by identifying cell types using CIBERSORT. Furthermore, we investigated the link between key markers and infiltrating immune cells. In total, we identified 561 robust DEGs. We identified Rab20 and Klf6 as SCI-specific biomarkers and demonstrated their significance using qRT-PCR in the mouse model. According to the examination of immune cell infiltration, M0, M1, and M2 macrophages, along with naive CD8, dendritic cell-activated, and CD4 Follicular T cells may have a role in the progression of SCI. Therefore, Rab20 and Klf6 could be accessible targets for diagnosing and treating SCI. Moreover, as previously stated, immune cell infiltration may significantly impact the development and progression of SCI.", "claims": [{"id": "claim-method", "statement": "Finally, we screened the DEGs using the LIMMA package with a p-value < 0.05 and |log2 Fold change (FC)| > 1", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35706450", "locator": "sections[4] \"Data Normalization and Differentially Expressed Genes Screening\" paragraph 2", "quote": "Finally, we screened the DEGs using the LIMMA package with a p-value < 0.05 and |log2 Fold change (FC)| > 1"}], "state": "complete"}, {"id": "claim-data-access", "statement": "The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35706450", "locator": "sections[16] \"Data Availability Statement\" paragraph 2", "quote": "The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The integrated analysis of two mouse SCI datasets identified 561 differentially expressed genes, including 536 up-regulated and 25 down-regulated genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35706450", "locator": "sections[11] \"Identification of Differentially Expressed Genes\" paragraph 2", "quote": "We found a total of 561 DEGs—536 up-regulated genes and 25 downregulated genes."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The integrated analysis of two mouse SCI datasets identified 561 differentially expressed genes, including 536 up-regulated and 25 down-regulated genes.", "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:35706450"], "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. 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According to the examination of immune cell", "emonstrated their significance using qRT-PCR in the mouse model. According to the examination of immun", "batch effects, we concurrently analyzed two mouse SCI datasets (GSE5296, GSE47681) from the GE"], "order_basis": "paper_text_order:50", "id": "assay:1"}, {"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["pressed genes (DEGs) using linear models for microarray data (LIMMA) and performed functional enrich"], "order_basis": "paper_text_order:541", "id": "assay:2"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["nes of SCI. Finally, we validated them using immunofluorescence and qRT-PCR. 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