{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40275351", "kind": "science-record", "revision": 4, "content_hash": "sha256:d625c6f753b2d50be9f86cb71162997a9d4e880db47449705f38d37578d23d4c", "created_at": "2026-11-01T20:30:25Z", "updated_at": "2026-11-01T22:56:24Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Revealing shared molecular and mechanistic signatures between intracranial aneurysms and abdominal aortic aneurysms: a comprehensive genomic analysis.", "doi": "10.1186/s13023-025-03689-1", "pmid": "40275351", "authors": ["Xiao Liu", "Zhenjun Li", "Hongzhen Xu", "Wangqing He", "Lei Wu", "Bin Ji", "Nuerzhati Nuermaimaiti", "Guangnan Ao", "Yuhang Feng", "Xuying He"], "journal": "Orphanet journal of rare diseases", "year": 2025, "abstract": "Intracranial aneurysms (IAs) and abdominal aortic aneurysms (AAAs) are both vascular diseases that are closely linked. However, the pathogenesis underlying the co-occurrence of IAs and AAAs remains poorly understood. This study aims to identify key biomarkers that shed light on the molecular mechanisms connecting these two diseases using bioinformatics analysis. Gene expression profiles (GSE122897, GSE237229) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) common to both IAs and AAAs were identified and subjected to functional enrichment analysis. The Cytoscape cytoHubba plugin was used to identify hub genes, and their predictive ability was evaluated using the receiver operating characteristic (ROC) curve. Additionally, immune infiltration analyses and single-gene gene set enrichment analysis (GSEA) were conducted for the hub genes. A total of 46 DEGs were identified, including 40 upregulated genes and 6 downregulated genes. The common DEGs were found to be involved in extracellular matrix structural constituents, collagen fibril organization, and regulation of basic cellular processes. ITGA11 was identified as a key gene implicated in the comorbidity of IAs and AAAs, with its upregulation strongly associated with plasma cells. Furthermore, in both IAs and AAAs, glycosaminoglycan biosynthesis of extracellular matrix components and immune-related diseases were significantly linked to the high expression of ITGA11. Our findings suggest that the comorbidity of IAs and AAAs may be driven by shared inflammatory and immune response mechanisms, with ITGA11 emerging as a potential biomarker for this co-occurrence.", "claims": [{"id": "claim-method", "statement": "To further evaluate the hub crosstalk gene as a common potential indicator for IAs and AAAs, receiver operating characteristic (ROC) analyses were performed using the datasets GSE122897 and GSE237229, with GSE75436 and GSE57691 serving as validation datasets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40275351", "locator": "sections[8] \"ROC analysis\" paragraph 2", "quote": "To further evaluate the hub crosstalk gene as a common potential indicator for IAs and AAAs, receiver operating characteristic (ROC) analyses were performed using the datasets GSE122897 and GSE237229, with GSE75436 and GSE57691 serving as validation datasets."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The GEO dataset used in this study is publicly available at (https://www.ncbi.nlm.nih.gov/geo/).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40275351", "locator": "sections[24] \"notes\" paragraph 1", "quote": "The GEO dataset used in this study is publicly available at (https://www.ncbi.nlm.nih.gov/geo/)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Receiver operating characteristic analysis identified ITGA11 as the strongest diagnostic marker for both intracranial aneurysms and abdominal aortic aneurysms, with AUC values of 0.872 and 0.948, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40275351", "locator": "sections[14] \"Diagnostic effect evaluation\" paragraph 2", "quote": "The results of the ROC curve analysis revealed that ITGA11 had the highest predictive power for both diseases, with AUC values of 0.872 and 0.948."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Receiver operating characteristic analysis identified ITGA11 as the strongest diagnostic marker for both intracranial aneurysms and abdominal aortic aneurysms, with AUC values of 0.872 and 0.948, 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:40275351"], "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:GSE122897"], "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:GSE122897"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40275351", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s13023-025-03689-1", "sha256": 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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}}}