Screening and identification of biomarkers associated with the immune infiltration of intracerebral hemorrhage.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35318719", "kind": "science-record", "revision": 2, "content_hash": "sha256:de4680ec389b3236c5598bfbe20675fceef8032df6e081bb1de077d57b25ed7e", "created_at": "2026-11-01T18:14:07Z", "updated_at": "2026-11-01T18:58:32Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Screening and identification of biomarkers associated with the immune infiltration of intracerebral hemorrhage.", "doi": "10.1002/jcla.24361", "pmid": "35318719", "authors": ["Hao Guo", "Yanjun Zhang", "Zhanfei Hu", "Li Wang", "Hongyin Du"], "journal": "Journal of clinical laboratory analysis", "year": 2022, "abstract": "BACKGROUND: Recent studies showed that inflammation and immunity might play essential roles in the progression of intracerebral hemorrhage (ICH). However, the underlying mechanisms for changes at the cellular and molecular levels after ICH remain unclear.\nMETHODS: We downloaded the microarray dataset of ICH from the Gene Expression Omnibus (GEO) database. The differential expression gene analysis was obtained by weighted gene co-expression network analysis (WGCNA). We got the hub genes and performed the biological functions and signaling pathways of these genes by Metascape. GSVA algorithm was used to evaluate the potential physical function of time-varying ICH samples. We used single-sample gene set enrichment analysis (ssGSEA) to assess the immune signatures infiltration and analyzed the correlation between hub genes and immune signatures.\nRESULTS: The data sets of all 22 ICH samples in GSE125512 were examined by the WGCNA R package. We finally screened five hub genes (GAPDH, PF4, SELP, APP, and PPBP) in the royal blue module. Metascape analysis displayed the biological processes related to inflammation and immunology. Cell adhesion molecule binding, myeloid leukocyte activation, CXCR chemokine receptor binding, and regulation of cytokine production were the most enriched pathophysiological process. The immune signatures infiltration analyses showed that ICH patients' early and late samples had different activity and abundance of immune-related cells and types.\nCONCLUSIONS: GAPDH, PF4, SELP, APP, and PPBP are identified as potential biomarkers for predicting the progression of ICH. This study may help us better understand the immunologic mechanism and shed new light on the promising approaches of immunotherapy for ICH patients.", "claims": [{"id": "claim-data-access", "statement": "The data sets analyzed in this manuscript are publicly available. The data set is available on the Gene Expression Omnibus (GEO) database, and the accession number is GSE125512.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35318719", "locator": "sections[24] \"DATA AVAILABILITY STATEMENT\" paragraph 2", "quote": "The data sets analyzed in this manuscript are publicly available. The data set is available on the Gene Expression Omnibus (GEO) database, and the accession number is GSE125512."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We finally screened five hub genes (GAPDH, PF4, SELP, APP, and PPBP) in the royal blue module.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35318719", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We finally screened five hub genes (GAPDH, PF4, SELP, APP, and PPBP) in the royal blue module."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "We finally screened five hub genes (GAPDH, PF4, SELP, APP, and PPBP) in the royal blue module.", "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:35318719"], "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:GSE125512"], "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:GSE125512"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35318719", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1002/jcla.24361", "sha256": "sha256:21d287d4ae6fc0aebdbf7c3d200b450f81054724ae6d27ddf13c087cf499dfdf", "bytes": 38059, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1002/jcla.24361", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9102626", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE125512", "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=GSE125512", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE125512", "version": null, "note": "The data sets analyzed in this manuscript are publicly available. The data set is available on the Gene Expression Omnibus (GEO) database, and the accession number is GSE125512.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data sets analyzed in this manuscript are publicly available. The data set is available on the Gene Expression Omnibus (GEO) database, and the accession number is GSE125512.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM3576253", "GSM3576254", "GSM3576255", "GSM3576256", "GSM3576257", "GSM3576258", "GSM3576259", "GSM3576260", "GSM3576261", "GSM3576262", "GSM3576263", "GSM3576264", "GSM3576265", "GSM3576266", "GSM3576267", "GSM3576268", "GSM3576269", "GSM3576270", "GSM3576271", "GSM3576272", "GSM3576273", "GSM3576274"], "sample_count": 22, "group_sizes": null, "group_sizes_basis": null, "platform": "15433", "taxon": "Homo sapiens", "title": "Intracerebral Hemorrhage Induces Inflammatory Gene Expression in Peripheral Blood: Global Transcriptional Profiling in ICH Patients", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE125512 not downloaded", "asset:data:geo:GSE125512 licence not read"]}, "analysis": {"state": "absent", "methods": [], "targets": [], "gaps": ["method", "operations"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "blocked", "tier": "R4", "blocking_axis": "method", "blocked_on": "method:not_determinable", "axes": {"method": {"tier": "R4", "expressible": false, "required_operations": [], "missing_operations": [], "basis": "The reader quoted the method the paper names (not named), but the corpus's method extractor could not map it onto a DSL operation, so the method is published but not expressible."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. 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