Machine learning-based prediction model for lung ischemia-reperfusion injury: insights from disulfidptosis-related genes.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40538538", "kind": "science-record", "revision": 4, "content_hash": "sha256:b752f5b7606a1cb40b2a89795967cc092ffba153cca48a6f72d77804f234c060", "created_at": "2026-11-01T20:30:38Z", "updated_at": "2026-11-01T22:56:40Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Machine learning-based prediction model for lung ischemia-reperfusion injury: insights from disulfidptosis-related genes.", "doi": "10.3389/fphar.2025.1545111", "pmid": "40538538", "authors": ["Yanpeng Zhang", "Jingyang Sun", "Yihan Lin", "Rongxuan Jiang", "Niuniu Dong", "Huanhuan Dong", "Peng Li", "Jinteng Feng", "Zijiang Zhu", "Guangjian Zhang"], "journal": "Frontiers in pharmacology", "year": 2025, "abstract": "Objective: This study aims to explore potential ischemia-reperfusion injury (IRI) predictive biomarkers related to disulfidptosis following lung transplantation.\nMethods: The study utilized datasets from the GEO database, specifically GSE145989 and GSE127003, which include samples of lung cold ischemia and reperfusion following transplantation. Differential expressed analysis and functional enrichment analysis were conducted to identify key genes associated with lung transplant IRI. Multiple machine learning algorithms (Generalized Linear Model, Support Vector Machine, and Random Forest) were applied for joint screening, leading to the construction of a predictive model. The CIBERSORT method was used to assess the infiltration levels of immune cells in lung tissue samples post-transplant. Finally, cell line and animal experiments were carried out to validate the effectiveness and applicability of the model.\nResults: A total of 14,592 hub differential-expressed genes were identified, showing significant changes in cold ischemia and reperfusion samples. Using the three machine learning algorithms for joint analysis, a predictive model composed of SLC7A11 and LRPPRC was constructed. This model demonstrated excellent predictive efficacy across multiple datasets, with area under the curve (AUC) values of 0.742 and 0.938, respectively. Additionally, significant differences in neutrophils and macrophages were observed in lung transplant cold ischemia and reperfusion samples. Based on the differential genes associated with disulfidptosis and utilizing the CMap database, we identified two potential drugs targeting IRI: olanzapine and vortioxetine. Ultimately, cell line and animal experiments validated the predictive model's reliability and potential clinical value, revealing that disulfidptosis presents in IRI, and high SLC7A11 expression promotes IRI, while low LRPPRC expression contributes to its occurrence.\nConclusion: SLC7A11 and LRPPRC can serve as predictive biomarkers for IRI following lung transplantation.", "claims": [{"id": "claim-method", "statement": "We utilized the “limma” package and “Wilcoxon test” to compare 1-h and 2-h reperfusion samples in the lung transplantation (LTx) cohort against cold ischemia samples, identifying differentially expressed disulfidptosis-related genes (DEDRGs) through their intersection with known disulfidptosis genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40538538", "locator": "sections[5] \"Identification of DEDRGs\" paragraph 2", "quote": "We utilized the “limma” package and “Wilcoxon test” to compare 1-h and 2-h reperfusion samples in the lung transplantation (LTx) cohort against cold ischemia samples, identifying differentially expressed disulfidptosis-related genes (DEDRGs) through their intersection with known disulfidptosis genes."}], "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:40538538", "locator": "sections[25] \"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": "A predictive model composed of SLC7A11 and LRPPRC demonstrated excellent predictive efficacy, with AUC values of 0.742 in the training cohort and 0.938 in the validation cohort.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40538538", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "This model demonstrated excellent predictive efficacy across multiple datasets, with area under the curve (AUC) values of 0.742 and 0.938, respectively."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "A predictive model composed of SLC7A11 and LRPPRC demonstrated excellent predictive efficacy, with AUC values of 0.742 in the training cohort and 0.938 in the validation cohort.", "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:40538538"], "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:GSE127003"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:group_comparison_wilcoxon", "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:GSE127003"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:group_comparison_wilcoxon"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40538538", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": 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The mice were housed in a standard environment at 24°C wit", "nstitutional ethics committee. Specifically, mice were anesthetized with an intraperitoneal injecti", ". Tracheal intubation was performed, and the mice were ventilated with specific parameters: a tidal", ". Experimental validation In our constructed mouse model of lung IRI, we observed that the expression"], "order_basis": "paper_text_order:2276", "id": "assay:1"}, {"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": ["ng et al., 2024). Cell culture study BEAS-2B cell line was cultured in Dulbecco’s Modified Eagle Medium (DMEM) s", "4). Cell culture study BEAS-2B cell line was cultured in Dulbecco’s Modified Eagle Medium (DMEM) supp"], "order_basis": "paper_text_order:3544", "id": "assay:2"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ut of SLC7A11 and LRPPRC, BEAS-2B cells were transfected with sgSLC7A11 and sgLRPPRC constructs, 72 h", "(E) Knockout of LRPPRC and SLC7A11 in stably transfected cell lines was verified. (F) CCK-8 assay sho"], "order_basis": "paper_text_order:3873", "id": "assay:3"}, {"role": "data_generation", "definition_id": "western_blot", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": [". Surviving knockout clones were screened by immunoblotting using the corresponding antibodies. Experime", "ion of the role of SLC7A11 and LRPPRC. (A,B) Immunoblot analysis and quantification of SLC7A11 and L", "sues from normal and IRI mouse models. (C,D) Immunoblot analysis and quantification of SLC7A11 and L", "lls. (I) The use of reducing and nonreducing immunoblot analysis in lung tissue from mouse models wi"], "order_basis": "paper_text_order:4068", "id": "assay:4"}, {"role": "data_generation", "definition_id": "apoptosis_assay", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["l lines for SLC7A11 and LRPPRC and performed CCK8 assays to assess cell viability (Figure 7E).", "bly transfected cell lines was verified. (F) CCK-8 assay showing cell viability in normal contr"], "order_basis": "paper_text_order:4895", "id": "assay:5"}, {"role": "analysis", "definition_id": "group_comparison", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["We utilized the “limma” package and “Wilcoxon test” to compare 1-h and 2-h reperfusion samples in the lung transplantation (LTx) cohort against cold ischemia samples, identifying differentially expressed disulfidptosis-related genes (DEDRGs) through their intersection with known disulfidptosis genes."], "order_basis": "consumes_earlier_output", "id": "assay:6"}]}