Investigating the AC079305/DUSP1 Axis as Oxidative Stress-Related Signatures and Immune Infiltration Characteristics in Ischemic Stroke.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35746962", "kind": "science-record", "revision": 5, "content_hash": "sha256:4054777727d0e71d32b77555083e906e1c83b4a0aca737308a67901c1bba74cc", "created_at": "2026-11-01T18:14:46Z", "updated_at": "2026-11-01T22:49:23Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Investigating the AC079305/DUSP1 Axis as Oxidative Stress-Related Signatures and Immune Infiltration Characteristics in Ischemic Stroke.", "doi": "10.1155/2022/8432352", "pmid": "35746962", "authors": ["Jiaxin Fan", "Shuai Cao", "Mengying Chen", "Qingling Yao", "Xiaodong Zhang", "Shuang Du", "Huiyang Qu", "Yuxuan Cheng", "Shuyin Ma", "Meijuan Zhang", "Yizhou Huang", "Nan Zhang", "Kaili Shi", "Shuqin Zhan"], "journal": "Oxidative medicine and cellular longevity", "year": 2022, "abstract": "Background: Oxidative stress (OS) and immune inflammation play complex intersections in the pathophysiology of ischemic stroke (IS). However, a competing endogenous RNA- (ceRNA-) based mechanism linked to the intersections in IS has not been explored. We aimed to identify potential OS-related signatures and analyze immune infiltration characteristics in IS.\nMethods: Three datasets (GSE22255, GSE110993, and GSE140275) from the GEO database were extracted. Differentially expressed long noncoding RNAs, microRNAs, and messenger RNAs (DElncRNAs, DEmiRNAs, and DEmRNAs) between IS patients and controls were identified. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were explored. Moreover, a triple ceRNA network was constructed to reveal transcriptional regulation mechanisms. A comprehensive strategy among least absolute shrinkage and selection operator (LASSO) regression, DEmRNAs, uprelated DEmRNAs, and OS-related genes was adopted to select the best signature. Then, we evaluated and verified the discriminant ability of the signature via receiver operating characteristic (ROC) analysis. Immune infiltration characteristics were explored via the CIBERSORT algorithm. Moreover, the best signature was verified via qPCR and western blot methods in rat brain tissues and PC12 cells.\nResults: 11 DEmRNAs were identified totally. Enrichment analysis showed that the DEmRNAs were primarily concentrated in MAPK-associated biological processes and immune or inflammation-involved pathways. DUSP1 was identified as the best signature with an area under the ROC curve of 73.5% (95%CI = 57.02-89.98, sensitivity = 95%, and specificity = 60%) in GSE22255 and 100.0% (95%CI = 100.00-100.00, sensitivity = 100%, and specificity = 100%) in GSE140275. Importantly, we also identified the AC079305/DUSP1 axis in the ceRNA network. Immune infiltration showed that resting mast cells infiltrate less in IS patients compared with controls. And DUSP1 was negatively correlated with resting mast cells (r = -0.703, P < 0.01), whereas it was positively correlated with neutrophils (r = 0.339, P < 0.05). Both in vivo and in vitro models confirmed the upregulated expression of DUSP1 and the downregulated expression of miR-429.\nConclusion: This study identified the ceRNA-based AC079305/DUSP1 axis as a promising OS-related signature for IS. Immune infiltrating cells, especially mast cells, may exert a pivotal role in IS progression. Pharmacological agents targeting signatures, their receptors, or mast cells may shed a novel light on therapeutic targets for IS.", "claims": [{"id": "claim-method", "statement": "After normalization and log2 conversion of raw data, we used the Linear Model for Microarray Data (LIMMA) method [15] in the R′ Bioconductor package for difference analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35746962", "locator": "sections[4] \"2.2. Data Preprocessing and Identification of DEmRNAs, DEmiRNAs, and DElncRNA\" paragraph 2", "quote": "After normalization and log2 conversion of raw data, we used the Linear Model for Microarray Data (LIMMA) method [15] in the R′ Bioconductor package for difference analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets generated and/or analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/) (GEO profiles: GSE22255, GSE110993, and GSE140275) and GeneCards website (https://www.genecards.org). And they are also available from the corresponding author, upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35746962", "locator": "sections[29] \"Data Availability\" paragraph 2", "quote": "The datasets generated and/or analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/) (GEO profiles: GSE22255, GSE110993, and GSE140275) and GeneCards website (https://www.genecards.org). And they are also available from the corresponding author, upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "DUSP1 was identified as the best signature with an area under the ROC curve of 73.5% (95%CI = 57.02-89.98, sensitivity = 95%, and specificity = 60%) in GSE22255 and 100.0% (95%CI = 100.00-100.00, sensitivity = 100%, and specificity = 100%) in GSE140275.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35746962", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "DUSP1 was identified as the best signature with an area under the ROC curve of 73.5% (95%CI = 57.02-89.98, sensitivity = 95%, and specificity = 60%) in GSE22255 and 100.0% (95%CI = 100.00-100.00, sensitivity = 100%, and specificity = 100%) in GSE140275."}, {"asset": "source:pmid:35746962", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "This study identified the ceRNA-based AC079305/DUSP1 axis as a promising OS-related signature for IS."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "DUSP1 was identified as the best signature with an area under the ROC curve of 73.5% (95%CI = 57.02-89.98, sensitivity = 95%, and specificity = 60%) in GSE22255 and 100.0% (95%CI = 100.00-100.00, sensitivity = 100%, and specificity = 100%) in GSE140275.", "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:35746962"], "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:GSE110993"], "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:GSE110993"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:35746962", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2022/8432352", "sha256": "sha256:d6804c8e0bfaef150f2c03e40495368f7f1c8d56dd8c7d81357e1b7a6ebec4e7", "bytes": 40345, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/2022/8432352", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9213160", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE110993", "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=GSE110993", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE110993", "version": null, "note": "The datasets generated and/or analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/) (GEO profiles: GSE22255, GSE110993, and GSE140275) and GeneCards website (https://www.genecards.org). And they are also available from the corresponding author, upon reasonable request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets generated and/or analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/) (GEO profiles: GSE22255, GSE110993, and GSE140275) and GeneCards website (https://www.genecards.org). And they are also available from the corresponding author, upon reasonable request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM3019808", "GSM3019809", "GSM3019810", "GSM3019811", "GSM3019812", "GSM3019813", "GSM3019814", "GSM3019815", "GSM3019816", "GSM3019817", "GSM3019818", "GSM3019819", "GSM3019820", "GSM3019821", "GSM3019822", "GSM3019823", "GSM3019824", "GSM3019825", "GSM3019826", "GSM3019827", "GSM3019828", "GSM3019829", "GSM3019830", "GSM3019831", "GSM3019832", "GSM3019833", "GSM3019834", "GSM3019835", "GSM3019836", "GSM3019837", "GSM3019838", "GSM3019839", "GSM3019840", "GSM3019841", "GSM3019842", "GSM3019843", "GSM3019844", "GSM3019845", "GSM3019846", "GSM3019847"], "sample_count": 40, "group_sizes": null, "group_sizes_basis": null, "platform": "15456", "taxon": "Homo sapiens", "title": "RNA-seq identifies circulating miR-125a-5p, miR-125b-5p and miR-143-3p as potential biomarkers for acute ischemic stroke", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE140275", "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=GSE140275", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE140275", "version": null, "note": "The datasets generated and/or analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/) (GEO profiles: GSE22255, GSE110993, and GSE140275) and GeneCards website (https://www.genecards.org). And they are also available from the corresponding author, upon reasonable request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets generated and/or analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/) (GEO profiles: GSE22255, GSE110993, and GSE140275) and GeneCards website (https://www.genecards.org). And they are also available from the corresponding author, upon reasonable request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM4158685", "GSM4158686", "GSM4158687", "GSM4158688", "GSM4158689", "GSM4158690"], "sample_count": 6, "group_sizes": null, "group_sizes_basis": null, "platform": "16791", "taxon": "Homo sapiens", "title": "Expression profile and potential functions of circulating long noncoding RNAs in acute ischemic stroke in the Southern Chinese Han population", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE22255", "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=GSE22255", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE22255", "version": null, "note": "The datasets generated and/or analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/) (GEO profiles: GSE22255, GSE110993, and GSE140275) and GeneCards website (https://www.genecards.org). And they are also available from the corresponding author, upon reasonable request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets generated and/or analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/) (GEO profiles: GSE22255, GSE110993, and GSE140275) and GeneCards website (https://www.genecards.org). And they are also available from the corresponding author, upon reasonable request.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM554014", "GSM554015", "GSM554016", "GSM554017", "GSM554018", "GSM554019", "GSM554020", "GSM554021", "GSM554022", "GSM554023", "GSM554024", "GSM554025", "GSM554026", "GSM554027", "GSM554028", "GSM554029", "GSM554030", "GSM554031", "GSM554032", "GSM554033", "GSM554034", "GSM554035", "GSM554036", "GSM554037", "GSM554038", "GSM554039", "GSM554040", "GSM554041", "GSM554042", "GSM554043", "GSM554044", "GSM554045", "GSM554046", "GSM554047", "GSM554048", "GSM554049", "GSM554050", "GSM554051", "GSM554052", "GSM554053"], "sample_count": 40, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Blood genomic expression profile for ischemic stroke (IS)", "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:GSE110993 not downloaded", "asset:data:geo:GSE110993 licence not read", "asset:data:geo:GSE140275 not downloaded", "asset:data:geo:GSE140275 licence not read", "asset:data:geo:GSE22255 not downloaded", "asset:data:geo:GSE22255 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "differential_expression", "specific": "limma_voom", "label": "Differential expression analysis", "dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["count_matrix_with_condition"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "After normalization and log2 conversion of raw data, we used the Linear Model for Microarray Data (LIMMA) method [15] in the R′ Bioconductor package for difference analysis."}}, {"id": "method-2", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "pathway enrichment"}}, {"id": "method-3", "family": "diagnostic_evaluation", "specific": "roc", "label": "Diagnostic test evaluation", "dsl_operations": ["confusion_counts", "roc_curve", "sensitivity_specificity", "solve_confusion_matrix", "classification_metrics", "published_precision_envelope"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["reference_standard_and_test"], "evidence": {"score": 0.7, "band": "medium", "quote": "ROC curve"}}], "targets": [], "gaps": []}, "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": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE22255", "GSE110993", "GSE140275"], "resolved_accessions": ["GSE22255", "GSE110993", "GSE140275"], "statements": ["The datasets generated and/or analyzed during the current study are available in the GEO database (https://www.ncbi.nlm.nih.gov/) (GEO profiles: GSE22255, GSE110993, and GSE140275) and GeneCards website (https://www.genecards.org). And they are also available from the corresponding author, upon reasonable request."], "basis": "The paper names GSE22255, GSE110993, GSE140275 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:35746962", "data:geo:GSE110993"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE110993"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:52:07Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 12037, "completion_tokens": 1946, "cached_tokens": 264}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:35746962", "type": "paper", "label": "pmid:35746962"}, {"id": "source:pmid:35746962", "type": "manuscript", "label": "PMID 35746962 full text"}, {"id": "data:geo:GSE110993", "type": "dataset", "label": "GEO GSE110993"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:35746962", "type": "paper", "label": "pmid:35746962"}, {"id": "source:pmid:35746962", "type": "manuscript", "label": "PMID 35746962 full text"}, {"id": "data:geo:GSE110993", "type": "dataset", "label": "GEO GSE110993"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-35746962", "type": "extraction", "used": ["source:pmid:35746962"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE110993", "type": "accession_resolution", "used": ["data:geo:GSE110993"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:35746962", "parent_hash": "sha256:0ec74d0d76ff8e96ec602a7e3e1afa1899332ca2b3b5db8705fdeb45bc4ea924", "fork_of": null, "generation": 4}, "gaps": ["asset:data:geo:GSE110993 licence not read", "asset:data:geo:GSE110993 not downloaded", "asset:data:geo:GSE140275 licence not read", "asset:data:geo:GSE140275 not downloaded", "asset:data:geo:GSE22255 licence not read", "asset:data:geo:GSE22255 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "qpcr", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["oreover, the best signature was verified via qPCR and western blot methods in rat brain tissue"], "order_basis": "paper_text_order:1358", "id": "assay:1"}, {"role": "data_generation", "definition_id": "western_blot", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["the best signature was verified via qPCR and western blot methods in rat brain tissues and PC12 cells."], "order_basis": "paper_text_order:1367", "id": "assay:2"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["with neutrophils (r = 0.339, P < 0.05). Both in vivo and in vitro models confirmed the upregulate", "erified via qPCR and western blot methods in rat brain tissues and PC12 cells. Results: 11 DE", "value < 0.05. 2.9. Animals and Cerebral I/R In Vivo Model Male SD rats (240-270 g) were purchase", "n occlusion of middle cerebral artery (MCAO) in vivo model according to the previously reported m"], "order_basis": "paper_text_order:1391", "id": "assay:3"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["estern blot methods in rat brain tissues and PC12 cells. Results: 11 DEmRNAs were identified t", "Chinese Academy of Sciences. PC12 cells were cultured in DMEM medium supplemented with 10% fetal bovi", "2.10. Cell Culture and OGD/R In Vitro Model PC12 cells, a rat pheochromocytoma cell line, wer", "ogical Science, Chinese Academy of Sciences. PC12 cells were cultured in DMEM medium supplemen"], "order_basis": "paper_text_order:1413", "id": "assay:4"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["After normalization and log2 conversion of raw data, we used the Linear Model for Microarray Data (LIMMA) method [15] in the R′ Bioconductor package for difference analysis."], "order_basis": "consumes_earlier_output", "id": "assay:5"}]}