{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39512836", "kind": "science-record", "revision": 3, "content_hash": "sha256:bc7d2ce56f713b65c5a00fd8efe3fec884f1cf4a0e779549f7eadebaf7dbc950", "created_at": "2026-11-01T20:29:46Z", "updated_at": "2026-11-01T22:13:04Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Construction of the miRNA/Pyroptosis-Related Molecular Regulatory Axis in Abdominal Aortic Aneurysm: Evidence From Transcriptome Data Combined With Multiple Machine Learning Approaches Followed by Experiment Validation.", "doi": "10.1155/2024/1429510", "pmid": "39512836", "authors": ["Yongchao Su", "Chuangang Lu", "Shuchen Chen"], "journal": "Journal of immunology research", "year": 2024, "abstract": "Background: Abdominal aortic aneurysm (AAA) represents a permanent and localized widening of the abdominal aorta, posing a potentially lethal risk of aortic rupture. Several recent studies have highlighted the role of pyroptosis, a pro-inflammatory programed cell death, as critical molecular regulators in AAA occurrence, progression, and rupture. However, the potential effects of pyroptosis in AAA and its upstream microRNA (miRNA) have not been comprehensively clarified. Methods: Through a search of the gene expression omnibus (GEO) database, the expression profiles of mRNAs (GSE7084, GSE57691, and GSE98278) and miRNAs (GSE62179) and corresponding clinical features were downloaded, respectively. Expression profiles of 15 AAA and 10 normal vascular samples were consecutively collected for in vitro experimentation and subsequent analysis. Various machine learning techniques were employed to identify hub pyroptosis-related genes (PRGs), leading to the development of a predictive model termed the PRG classifier. Quantitative real-time-polymerase chain reaction (qRT-PCR), western blot (WB), and enzyme-linked immunosorbent assay (ELISA) were used to confirm the expression of the hub PRGs. The diagnostic and predictive capabilities of the model were comprehensively evaluated in GEO and hospital cohorts. Then, the crucial immune cell infiltration and molecular pathways implicated in the initiation and rupture of AAA and their association with pyroptosis were explored. Lastly, a miRNA/hub pyroptosis-related molecular regulatory axis was constructed using the TargetScan dataset, which was further explored through loss-of-function assays. Results: Differential analysis, enrichment score analysis, and principal component analysis (PCA) revealed that pyroptosis-related molecules were significantly involved in the occurrence of AAA. Utilizing multiple machine learning algorithms, eight key PRGs (cysteinyl aspartate specific proteinase [CASP]1, infiltrating lymphocyte [IL]1B, IL18, IL6, NOD-, LRR- and pyrin domain-containing protein [NLRP]1, NLRP2, NLRP3, and tumor necrosis factor [TNF]) were integrated to establish a PRG classifier. Demonstrating robust diagnostic capabilities (area under curve [AUC] > 0.90), the PRG classifier provided clinical insights across two GEO datasets and effectively differentiated small AAA from large AAA, elective stable AAA (eAAA), and ruptured AAA (rAAA), respectively. qRT-PCR, WB, and ELISA verified the mRNA and protein expression of the hub PRGs. Notably, in hospital cohorts, a substantial positive link was unveiled between the PRG classifier and AAA risk factors (hypertension history, diastolic pressure, triglyceride levels, and aneurysm diameter). Furthermore, immune cell infiltration and functional enrichment analysis revealed significant associations of the PRG classifier/PRGs with M2 macrophage infiltration, activated dendritic cells, and enrichment scores of the cytosolic deoxyribonucleic acid (DNA) sensing pathway and tryptophan metabolism, potentially mediating AAA onset and rupture. Finally, based on 90 differentially expressed miRNAs (DEmiRNAs) and eight hub PRGs through TargetScan dataset, a hsa-miR-331-3p/TNF regulatory axis was constructed, wherein upregulation of hsa-miR-331-3p expression significantly reduced TNF and CASP1 protein levels. Conclusion: A predictive model (PRG classifier) incorporating eight PRGs through multiple machine learning algorithms was developed and validated. This model may stand as a potent tool for diagnosing AAA and assessing disease severity. The identification of the cytosolic DNA sensing pathway and the hsa-miR-331-3p/TNF interaction axis may represent crucial targets for AAA treatment, offering deeper insights into its potential pathogenesis.", "claims": [{"id": "claim-method", "statement": "Receiver operating characteristic (ROC) analysis was executed to examine the diagnostic capability of the PRG classifier with AAA as the endpoint in the GSE7084 and GSE57691 datasets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39512836", "locator": "sections[6] \"2.4. 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Further inquiries can be directed to the corresponding author."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Demonstrating robust diagnostic capabilities (area under curve [AUC] > 0.90), the PRG classifier provided clinical insights across two GEO datasets and effectively differentiated small AAA from large AAA, elective stable AAA (eAAA), and ruptured AAA (rAAA), respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39512836", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Demonstrating robust diagnostic capabilities (area under curve [AUC] > 0.90), the PRG classifier provided clinical insights across two GEO datasets and effectively differentiated small AAA from large AAA, elective stable AAA (eAAA), and ruptured AAA (rAAA), respectively."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "Demonstrating robust diagnostic capabilities (area under curve [AUC] > 0.90), the PRG classifier provided clinical insights across two GEO datasets and effectively differentiated small AAA from large AAA, elective stable AAA (eAAA), and ruptured AAA (rAAA), respectively.", "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:39512836"], "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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Cell Culture and Treatment The mouse smooth muscle cell (SMC) line MOVAS was sour"], "order_basis": "paper_text_order:6423", "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": 0.8, "evidence": ["Wilcoxon"], "order_basis": "consumes_earlier_output", "id": "assay:6"}]},"meta":{"api_version":"v1","automation_ladder_snapshot":"ba34b49490d9bfaf","automation_ladder_caveats":["Method extraction is rule-based and has no hand-judged accuracy sample. Evidence bands order textual support; method agreement intervals are null (n=0), never probabilities. Work-type validation does not validate methods.","Operation coverage describes only explicitly named methods. It does not prove a complete protocol, compatible parameters, successful compilation or re-execution. Unrecognised or ambiguous methods require review.","Data reachability is a textual accession or public-data statement. No dataset was downloaded or checked for access, completeness or licence.","Capabilities are planning states seeded from the dated equipment register. No bench ownership, completed quote or partner booking is inferred. Procurement counts are dependencies, not guaranteed replications or financial returns.","Tier and blocker counts are deterministic assessments of this corpus, not measured agreement. R3 is reserved for procurement; unresolved methods and data require human work (R4). The most restrictive axis wins, with capability, method, data as tie-breaks. Resolving one blocker can leave another at the same tier."],"engine":"corpus_engine","engine_provider":"rule_based_v1+lex99e1195c7d6f","run_id":"run-20261023T122449232913","source":"esearch","source_detail":"PubMed mirror biomed_pubmed (read-only)","run_status":"complete","imported_at":"2026-11-03T20:16:52+00:00","generated_at":"2026-11-04T03:47:11+00:00","total_papers":5529,"total_assays_tracked":29,"automatable_assay_families":6,"validated":true,"caveat_count":9,"blocking_caveats":5,"caveats":[{"code":"low_evidence_dominates","basis":["4,152 of 5,529 classifications (75.1%) matched no cue evidence and sit at the 0.05 floor.","34 of 230 data_only calls (14.8%) are in that group."],"claim":"Work type and confidence bands","gloss":"Most records were classified from their title and framing alone, with assay-cue coverage at zero.","detail":"Most classifications in this run rest on no matched evidence at all. At the evidence floor the work type comes from title framing and a fixed prior, not from anything in the paper, so the published work-type split should be read as a rough triage signal rather than a measured distribution. The impact is bounded but not removed: since 2026-10-23 the engine excludes floor-confidence records from the shortlist entirely and publishes them separately as held out, so the recommendation is unaffected even though the census is.","status":"unverified","severity":"high"},{"code":"runtime_is_modelled","basis":["Runtime is summed from published per-assay hour figures. Timing awaits the first executed replication.","4,407 of 5,529 records (79.7%) model to 0.00 hours because no assay was matched, which the ranking then reads as \"cheapest\".","0 of 10 shortlisted records carry a 0.00-hour estimate."],"claim":"Estimated replication runtime","gloss":"The hour figures are estimates built from assay mentions; timing awaits the first executed replication.","detail":"The hour figures are a cost model derived from the bench steps implied by each matched assay family. The first executed replication will supply measured timing. Records without an assay match currently receive a zero-hour model value.","status":"unverified","severity":"high"},{"code":"signal_score_without_citations","basis":["5,529 of 5,529 records (100.0%) have no citation count from the source metadata."],"claim":"Signal score","gloss":"The signal score uses publication-type weight because the mirror supplied zero citation counts.","detail":"The source supplied no citation counts for any record in this run, so the signal score is publication-type weight only. The citation term of the ranking is inert here, and the shortlist is ordered by publication type alone.","status":"unverified","severity":"high"},{"code":"abstract_absent","basis":["1,667 of 5,529 records (30.2%) carry no abstract at all."],"claim":"Evidence base for classification","gloss":"Some records contain a title and publication type only, defining the available classification evidence.","detail":"Where the mirror contains a title and publication types only, those fields define the classifier evidence. A methods section is required for fuller automated and human review.","status":"unverified","severity":"medium"},{"code":"classifier_agreement_measured","basis":["Published two-way decision agreement 77.7% (310 of 399 decidable records) from a stratified hand-check of 438 real records.","Three-way diagnostic agreement 73.9% (288 of 390 decidable records).","data_only agreement 75.2% (100 of 133 decidable).","48 record(s) could not be decided from title and abstract and were excluded from the denominator.","56 analysis-only records were published under another work type, so the data_only share is not an upper bound."],"claim":"Published automatable decision","gloss":"This figure has been checked against a human reading the same papers, so we know how often it is right.","detail":"The published automatable / not-automatable distribution comes from a rule-based classifier that was hand-checked against a fixed ground-truth definition. The agreement rates below are measured, not estimated. The three-way work type remains a diagnostic and is reported separately.","status":"measured","severity":"high"},{"code":"llm_comparison_not_measured","basis":["rule_based_v1+lex99e1195c7d6f produced 5,529 of 5,529 classifications.","Measured on 438 labelled records; these are RULE-BASED figures, not model results."],"claim":"Rule-based versus LLM agreement","gloss":"Every number here is the rule engine’s own. Model comparison begins when a working API credential is connected and measured.","detail":"The published two-way decision agreed with a human reading on 310 of 399 decidable records (77.7%). The diagnostic three-way label agreed on 288 of 390 decidable records (73.9%). Every percentage in this run belongs to the rule engine. Model comparison begins when a working API credential is connected and measured.","status":"not_measured","severity":"high"},{"code":"confidence_is_a_band","basis":["low band: 135 of 210 hand-judged records were correct, 64.3% [57.6, 70.5] (95% CI).","medium band: 80 of 104 hand-judged records were correct, 76.9% [68.0, 84.0] (95% CI).","high band: 73 of 76 hand-judged records were correct, 96.0% [89.0, 98.7] (95% CI).","A fitted calibrated probability was built, measured and withdrawn: it overstated held-out accuracy and reorders nothing."],"claim":"Confidence band and evidence score","gloss":"The confidence band carries a measured accuracy interval; 0.85 represents relative rank strength.","detail":"Confidence on this run is a BAND plus its measured accuracy interval. The number stored alongside each record is a monotone evidence score that orders records; 0.85 represents relative rank strength. A fitted probability was withdrawn after it overstated held-out accuracy. Threshold on the band.","status":"measured","severity":"medium"},{"code":"three_way_split_is_diagnostic","basis":["The corpus is published at the two-way decision: automatable or not-automatable. The three-way split (data_only / physical / mixed) is published as a diagnostic with its measured reliability attached, not as a claim, because the rule engine's `mixed` call cannot be defended.","The engine called 22 record(s) mixed; 10 matched the human judgement (45.5%, 95% CI 26.9-65.3).","The engine's `mixed` call is right on 10/22 hand-judged records (45.5%, 95% CI 26.9%-65.3%); a constant `physical` guess scores 36.4%.","The engine's `mixed` call does not reliably beat a constant `physical` guess on the hand-judged records it labels mixed.","The sign of that difference flips between two independent samples, so the three-way refinement is not demonstrably informative.","The mixed stratum contributes a disproportionate share of errors relative to its size.","At title-only depth the physical/mixed split collapses: a title says that work was done, not whether it was also analysed."],"claim":"The published decision is two-way","gloss":"The three-way split is shown for diagnosis only. The published split is two ways.","detail":"Count and filter the corpus on automatable versus not-automatable. The data_only / physical / mixed split remains an internal engine diagnostic because the mixed call has lower measured reliability.","status":"measured","severity":"medium"},{"code":"automatable_flag_unproven","basis":["6 of 29 assay families are marked automatable now: meta_analysis, machine_learning, survival_analysis, pca, molecular_docking, differential_expression.","The flag is a rule over assay family and work type; validation begins with the first executed replication.","It inherits the 75.2% data_only agreement rate, because the flag requires the record to be analysis-only."],"claim":"Automatable now","gloss":"This flag marks assay families the rules classify as data-only. The first executed replication will validate it.","detail":"This flag marks families the rules consider replicable from data alone. Its validity depends on the analysis-only classification and will be measured through an executed replication.","status":"unverified","severity":"medium"}],"confidence_policy":"band_with_measured_interval","confidence_contract":{"policy":"band_with_measured_interval","summary":"Confidence is reported as a BAND with a measured accuracy interval. The raw evidence score supplies monotone ordering. A fitted point estimate was withdrawn after it overstated held-out accuracy.","evidence_score":"A monotone evidence score in [0,1] built from cue mass, axis separation and text coverage. Use it to order records. Interpret 0.85 as relative rank strength.","confidence_band":"low | medium | high. Consumers threshold on this value.","band_accuracy":"Wilson 95% interval on the measured agreement of the hand-judged records in this band.","calibrated_confidence":"WITHDRAWN. Reintroduction requires held-out evidence demonstrating reliable estimates across every bin."},"band_accuracy":{"low":{"n":210,"low":0.576,"band":"low","high":0.7046,"agree":135,"accuracy":0.6429},"high":{"n":76,"low":0.8903,"band":"high","high":0.9865,"agree":73,"accuracy":0.9605},"medium":{"n":104,"low":0.6795,"band":"medium","high":0.8397,"agree":80,"accuracy":0.7692}},"provider":"rule_based_v1+lex99e1195c7d6f","lexicon_id":"99e1195c7d6f","contract_published_at":"2026-10-23T12:25:29.022232+00:00","confidence_is_band":true,"confidence_is_probability":false,"decision_taxonomy":"two_way","decidable_fraction_two_way":0.8854,"decidable_fraction_two_way_low":0.8565,"decidable_fraction_two_way_high":0.9143,"decidable_fraction_three_way":0.8586,"decidable_fraction_three_way_low":0.8287,"decidable_fraction_three_way_high":0.8884,"decidable_population":5529,"validation_sample_size":438,"three_way_cost_fraction":0.0268,"three_way_cost_records":148,"decision_counts":{"automatable":230,"not_automatable":5299},"decision_split":{"automatable":{"count":230,"share":0.04159884246699222},"not_automatable":{"count":5299,"share":0.9584011575330078}},"diagnostic_work_type_counts":{"mixed":24,"physical":5275,"data_only":230}}}