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pmid:40076525

MGST1 Protects Pancreatic Ductal Cells from Inflammatory Damage in Acute Pancreatitis by Inhibiting Ferroptosis: Bioinformatics Analysis with Experimental Validation.

International journal of molecular sciences · 2025 doi:10.3390/ijms26051899

Paper

partial

Experiment

partial

Data

partial

Analysis

absent

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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MGST1 Protects Pancreatic Ductal Cells from Inflammatory Damage in Acute Pancreatitis by Inhibiting Ferroptosis: Bioinformatics Analysis with Experimental Validation.
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10.3390/ijms26051899
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40076525
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null
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International journal of molecular sciences
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2025
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the headline numerical result the paper states for its main finding
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4.1. Data Source and Analysis of Differential Expression Genes (DEGs)
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{"parent_value":0.889,"unit":"AUC","evidence":"Additionally, the combined model of the three hub genes yielded an overall area under curve (AUC) value of 0.889 (Figure 4J), suggesting the potential diagnostic value of these genes for acute pancreatitis.","target_result":"The combined diagnostic model of the three hub genes yielded an overall AUC of 0.889.","number_stated":true}
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Additionally, the combined model of the three hub genes yielded an overall area under curve (AUC) value of 0.889 (Figure 4J), suggesting the potential diagnostic value of these genes for acute pancreatitis.
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The combined diagnostic model of the three hub genes yielded an overall AUC of 0.889.
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<think>We need answer JSON only. Need interpret registered target "headline numerical result the paper states for its main finding". Need identify single numerical result replication target. Paper abstract: 22 driver genes, 3 hub genes, AUC 0.889. Headline numerical result likely AUC = 0.889 for diagnosis model. Need exact contiguous quote containing number and attribution. Unit paper prints? AUC dimensionless, perhaps unit empty string. parent_value number 0.889. Evidence exact clause perhaps "The disease diagnosis model constructed utilizing these three genes demonstrated high sensitivity and specificity (AUC = 0.889)." This explicitly links model and number. Or "Additionally, the combined model of the three hub genes yielded an overall area under curve (AUC) value of 0.889 (Figure 4J), suggesting..." Exact quote. They ask headline number only, value paper itself states for registered target. Registered target vague, likely target result is numerical headline main finding. Which one? Need infer benchmark intent. Could be 0.889. Need ensure "unit must be unit paper prints". AUC no unit. JSON unit "". Evidence exact contiguous quotation no ellipsis. target_result concise "AUC = 0.889" perhaps. number_stated true. Need only JSON object, valid. parent_value 0.889. Evidence quote exact. Maybe quote abstract sentence. Need no markdown.</think> {"parent_value":0.889,"unit":"","evidence":"The disease diagnosis model constructed utilizing these three genes demonstrated high sensitivity and specificity (AUC = 0.889).","target_result":"AUC = 0.889","number_stated":true}
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The combined model based on the three hub genes AQP3, TRIB2, and MGST1 achieved an AUC of 0.889 for diagnosing acute pancreatitis.
minimax_alt
AUC = 0.889 for the combined AQP3, TRIB2, and MGST1 acute pancreatitis diagnosis model.
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animal models
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receiver operating characteristic (ROC) curve analysis
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nomogram diagnostic model
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calibration curve analysis
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gene set enrichment analysis (GSEA)
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[13]
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Support vector machine (SVM) with hyperparameter optimization by 10-fold cross-validation
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Receiver operating characteristic (ROC) curve analysis using the pROC package
[5]
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Need interpret registered target \"headline numerical result the paper states for its main finding\". Need identify single numerical result replication target. Paper abstract: 22 driver genes, 3 hub genes, AUC 0.889. Headline numerical result likely AUC = 0.889 for diagnosis model. Need exact contiguous quote containing number and attribution. Unit paper prints? AUC dimensionless, perhaps unit empty string. parent_value number 0.889. Evidence exact clause perhaps \"The disease diagnosis model constructed utilizing these three genes demonstrated high sensitivity and specificity (AUC = 0.889).\" This explicitly links model and number. Or \"Additionally, the combined model of the three hub genes yielded an overall area under curve (AUC) value of 0.889 (Figure 4J), suggesting...\" Exact quote. They ask headline number only, value paper itself states for registered target. Registered target vague, likely target result is numerical headline main finding. Which one? Need infer benchmark intent. Could be 0.889. Need ensure \"unit must be unit paper prints\". AUC no unit. JSON unit \"\". Evidence exact contiguous quotation no ellipsis. target_result concise \"AUC = 0.889\" perhaps. number_stated true.\n\nNeed only JSON object, valid. parent_value 0.889. Evidence quote exact. Maybe quote abstract sentence. Need no markdown.</think>\n\n{\"parent_value\":0.889,\"unit\":\"\",\"evidence\":\"The disease diagnosis model constructed utilizing these three genes demonstrated high sensitivity and specificity (AUC = 0.889).\",\"target_result\":\"AUC = 0.889\",\"number_stated\":true}", "reading": {"parent_value": 0.889, "unit": "", "evidence": "The disease diagnosis model constructed utilizing these three genes demonstrated high sensitivity and specificity (AUC = 0.889).", "target_result": "AUC = 0.889", "number_stated": true, "source_locator": "chars 1211-1339 of source sha256 28c1c8f431afee4da668b10cfef4de2113907719e9e5a2bb8a069992b6ab5a5d"}, "recorded_at": "2026-10-31T15:34:32.173592+00:00"}], "agreement": false, "disagreements": {"target_result": {"minimax": "The combined model based on the three hub genes AQP3, TRIB2, and MGST1 achieved an AUC of 0.889 for diagnosing acute pancreatitis.", "minimax_alt": "AUC = 0.889 for the combined AQP3, TRIB2, and MGST1 acute pancreatitis diagnosis model.", "decisive": false}, "physical_methods": {"minimax": ["clinical sample validation", "animal models", "in vitro experiments"], "minimax_alt": ["Clinical samples", "Animal models", "In vitro experiments"], "decisive": false}, "analysis_methods": {"minimax": ["principal component analysis (PCA)", "differential expression analysis using the limma package", "gene ontology (GO) enrichment analysis", "KEGG pathway analysis", "least absolute shrinkage and selection operator (LASSO) regression", "support vector machine (SVM)", "10-fold cross-validation", "receiver operating characteristic (ROC) curve analysis", "nomogram diagnostic model", "calibration curve analysis", "gene set enrichment analysis (GSEA)", "CIBERSORT", "Spearman correlation analysis", "single-cell RNA sequencing analysis", "t-distributed stochastic neighbor embedding (t-SNE)", "t-test or ANOVA"], "minimax_alt": ["Severity-associated differential expression analysis using the limma package", "Intersection of differentially expressed genes with the ferroptosis gene set", "Least absolute shrinkage and selection operator (LASSO) regression with 10-fold cross-validation", "Support vector machine (SVM) with hyperparameter optimization by 10-fold cross-validation", "Receiver operating characteristic (ROC) curve analysis using the pROC package", "Nomogram diagnostic-model construction using the rms package"], "decisive": false}, "unit": {"minimax": "AUC", "minimax_alt": "", "decisive": true}}, "agreement_basis": {"policy": "decisive_fields", "decisive_fields": ["work_type", "number_stated", "parent_value", "unit"]}, "blinded": true}, "human_critique": {"status": "not_run", "reviewer": null, "signed_at": null, "conflict_checked": false, "commentary": null}, "stages": [{"key": "target_materials", "status": "pending", "reason": null, "evidence": null}, {"key": "independent_readings", "status": "blocked", "reason": "The independent readings are incomplete or disagree; 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