{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40128499", "kind": "science-record", "revision": 4, "content_hash": "sha256:4707034ca04ee578a118325cdf46f3cee13e72bcacb69758516802491789ca6b", "created_at": "2026-11-01T20:30:19Z", "updated_at": "2026-11-01T22:56:16Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of CCNB1 as a biomarker for cellular senescence in hepatocellular carcinoma: a bioinformatics and experimental validation study.", "doi": "10.1007/s12672-025-02182-2", "pmid": "40128499", "authors": ["Zhilan Zhang", "Jie Zhou", "Ruiru Huang", "Xingxing Zhuang", "Shoudong Ni"], "journal": "Discover oncology", "year": 2025, "abstract": "BACKGROUND: Hepatocellular carcinoma (HCC), originating in the liver and often asymptomatic in early stages, frequently metastasises and recures post-surgery. Currently, reliable diagnostic biomarkers and therapeutic targets for HCC are lacking. This study investigates the influence of cellular senescence on HCC, employing bioinformatics analysis and in vitro experiments to identify potential biomarkers.\nMETHODS: We integrated data from GEO microarrays (GSE14520, GSE45267 and GSE64041) to analyse differentially expressed genes (DEGs) using the R package limma. WGCNA identified gene modules highly correlated to HCC. Then, ageing-highly related differentially expressed genes (AgHDEGs) were identified. Correlation analysis, GO and KEGG functional enrichment analysis, and gene co-expression network analysis further elucidated the functions of AgHDEGs. The STRING database identified hub AgHDEGs with CCNB1 subsequently evaluated for diagnostic value using ROC curve analysis. Additionally, we explored the correlation between CCNB1 and immune cells and assessed its biological functions via GSEA. Ultimately, the conclusions from bioinformatics analysis were confirmed via in vitro experiments, complemented by molecular docking simulations of gene-drug interactions.\nRESULTS: Eight AgHDEGs (KPNA2, CCT3, CCNB1, RACGAP1, CDKN3, FEN1, MT1X and FOXM1) were identified. PPI network analysis highlighted CCNB1 as hub AgHDEGs with ROC analysis confirming its strong diagnostic potential. Analysis of immune infiltration revealed a significant correlation between CCNB1 and M0 macrophages. Subsequent studies showed CCNB1's critical role in regulating the cell cycle. Validation experiments illustrated an upregulation of CCNB1 expression in HCC, while inhibiting CCNB1 may reduce HepG2 cell proliferation by promoting cellular senescence. Moreover, molecular docking indicated CCNB1 as a potential therapeutic target.\nCONCLUSION: Our study underscores CCNB1's potential impact on HCC senescence and progression, suggesting its candidacy as a biomarker for HCC.", "claims": [{"id": "claim-method", "statement": "Using the limma package (version 3.40.6), differential analysis was performed, identifying DEGs based on criteria of |log2FC|≥ 1 and P < 0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40128499", "locator": "sections[5] \"Identification of differentially expressed genes (DEGs)\" paragraph 2", "quote": "Using the limma package (version 3.40.6), differential analysis was performed, identifying DEGs based on criteria of |log2FC|≥ 1 and P < 0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:40128499", "locator": "sections[33] \"Data availability\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Our study underscores CCNB1’s potential impact on HCC senescence and progression, suggesting its candidacy as a biomarker for HCC.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:40128499", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Our study underscores CCNB1’s potential impact on HCC senescence and progression, suggesting its candidacy as a biomarker for HCC."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Our study underscores CCNB1’s potential impact on HCC senescence and progression, suggesting its candidacy as a biomarker for HCC.", "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:40128499"], "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:GSE14520"], "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:GSE14520"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40128499", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1007/s12672-025-02182-2", "sha256": "sha256:82b8cf94ff4e51de4ac3f93efb34b1b3d78979009af43364ceaf8085ec7550ab", "bytes": 46646, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1007/s12672-025-02182-2", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11933616", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE14520", "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=GSE14520", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE14520", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM362947", "GSM362948", "GSM362949", "GSM362950", "GSM362951", "GSM362952", "GSM362953", "GSM362954", "GSM362955", "GSM362956", "GSM362957", "GSM362958", "GSM362959", "GSM362960", "GSM362961", "GSM362962", "GSM362963", "GSM362964", "GSM362965", "GSM362966", "GSM362967", "GSM362968", "GSM362969", "GSM362970", "GSM362971", "GSM362972", "GSM362973", "GSM362974", "GSM362975", "GSM362976", "GSM362977", "GSM362978", "GSM362979", "GSM362980", "GSM362981", "GSM362982", "GSM362983", "GSM362984", "GSM362985", "GSM362986", "GSM362987", "GSM362988", "GSM362989", "GSM362990", "GSM362991", "GSM362992", "GSM362993", "GSM362994", "GSM362995", "GSM362996", "GSM362997", "GSM362998", "GSM362999", "GSM363000", "GSM363001", "GSM363002", "GSM363003", "GSM363004", "GSM363005", "GSM363006", "GSM363007", "GSM363008", "GSM363009", "GSM363010", "GSM363011", "GSM363012", "GSM363013", "GSM363014", "GSM363015", "GSM363016", "GSM363017", "GSM363018", "GSM363019", "GSM363020", "GSM363021", "GSM363022", "GSM363023", "GSM363024", "GSM363025", "GSM363026", "GSM363027", "GSM363028", "GSM363029", "GSM363030", "GSM363031", "GSM363032", "GSM363033", "GSM363034", "GSM363035", "GSM363036", "GSM363037", "GSM363038", "GSM363039", "GSM363040", "GSM363041", "GSM363042", "GSM363043", "GSM363044", "GSM363045", "GSM363046", "GSM363047", "GSM363048", "GSM363049", "GSM363050", "GSM363051", "GSM363052", "GSM363053", "GSM363054", "GSM363055", "GSM363056", "GSM363057", "GSM363058", "GSM363059", "GSM363060", "GSM363061", "GSM363062", "GSM363063", "GSM363064", "GSM363065", "GSM363066", "GSM363067", "GSM363068", "GSM363069", "GSM363070", "GSM363071", "GSM363072", "GSM363073", "GSM363074", "GSM363075", "GSM363076", "GSM363077", "GSM363078", "GSM363079", "GSM363080", "GSM363081", "GSM363082", "GSM363083", "GSM363084", "GSM363085", "GSM363086", "GSM363087", "GSM363088", "GSM363089", "GSM363090", "GSM363091", "GSM363092", "GSM363093", "GSM363094", "GSM363095", "GSM363096", "GSM363097", "GSM363098", "GSM363099", "GSM363100", "GSM363101", "GSM363102", "GSM363103", "GSM363104", "GSM363105", "GSM363106", "GSM363107", "GSM363108", "GSM363109", "GSM363110", "GSM363111", "GSM363112", "GSM363113", "GSM363114", "GSM363115", "GSM363116", "GSM363117", "GSM363118", "GSM363119", "GSM363120", "GSM363121", "GSM363122", "GSM363123", "GSM363124", "GSM363125", "GSM363126", "GSM363127", "GSM363128", "GSM363129", "GSM363130", "GSM363131", "GSM363132", "GSM363133", "GSM363134", "GSM363135", "GSM363136", "GSM363137", "GSM363138", "GSM363139", "GSM363140", "GSM363141", "GSM363142", "GSM363143", "GSM363144", "GSM363145", "GSM363146", "GSM363147", "GSM363148", "GSM363149", "GSM363150", "GSM363151", "GSM363152", "GSM363153", "GSM363154", "GSM363155", "GSM363156", "GSM363157", "GSM363158", "GSM363159", "GSM363160", "GSM363161", "GSM363162", "GSM363163", "GSM363164", "GSM363165", "GSM363166", "GSM363167", "GSM363168", "GSM363169", "GSM363170", "GSM363171", "GSM363172", "GSM363173", "GSM363174", "GSM363175", "GSM363176", "GSM363177", "GSM363178", "GSM363179", "GSM363180", "GSM363181", "GSM363182", "GSM363183", "GSM363184", "GSM363185", "GSM363186", "GSM363187", "GSM363188", "GSM363189", "GSM363190", "GSM363191", "GSM363192", "GSM363193", "GSM363194", "GSM363195", "GSM363196", "GSM363197", "GSM363198", "GSM363199", "GSM363200", "GSM363201", "GSM363202", "GSM363203", "GSM363204", "GSM363205", "GSM363206", "GSM363207", "GSM363208", "GSM363209", "GSM363210", "GSM363211", "GSM363212", "GSM363213", "GSM363214", "GSM363215", "GSM363216", "GSM363217", "GSM363218", "GSM363219", "GSM363220", "GSM363221", "GSM363222", "GSM363223", "GSM363224", "GSM363225", "GSM363226", "GSM363227", "GSM363228", "GSM363229", "GSM363230", "GSM363231", "GSM363232", "GSM363233", "GSM363234", "GSM363235", "GSM363236", "GSM363237", "GSM363238", "GSM363239", "GSM363240", "GSM363241", "GSM363242", "GSM363243", "GSM363244", "GSM363245", "GSM363246", "GSM363247", "GSM363248", "GSM363249", "GSM363250", "GSM363251", "GSM363252", "GSM363253", "GSM363254", "GSM363255", "GSM363256", "GSM363257", "GSM363258", "GSM363259", "GSM363260", "GSM363261", "GSM363262", "GSM363263", "GSM363264", "GSM363265", "GSM363266", "GSM363267", "GSM363268", "GSM363269", "GSM363270", "GSM363271", "GSM363272", "GSM363273", "GSM363274", "GSM363275", "GSM363276", "GSM363277", "GSM363278", "GSM363279", "GSM363280", "GSM363281", "GSM363282", "GSM363283", "GSM363284", "GSM363285", "GSM363286", "GSM363287", "GSM363288", "GSM363289", "GSM363290", "GSM363291", "GSM363292", "GSM363293", "GSM363294", "GSM363295", "GSM363296", "GSM363297", "GSM363298", "GSM363299", "GSM363300", "GSM363301", "GSM363302", "GSM363303", "GSM363304", "GSM363305", "GSM363306", "GSM363307", "GSM363308", "GSM363309", "GSM363310", "GSM363311", "GSM363312", "GSM363313", "GSM363314", "GSM363315", "GSM363316", "GSM363317", "GSM363318", "GSM363319", "GSM363320", "GSM363321", "GSM363322", "GSM363323", "GSM363324", "GSM363325", "GSM363326", "GSM363327", "GSM363328", "GSM363329", "GSM363330", "GSM363331", "GSM363332", "GSM363333", "GSM363334", "GSM363335", "GSM363336", "GSM363337", "GSM363338", "GSM363339", "GSM363340", "GSM363341", "GSM363342", "GSM363343", "GSM363344", "GSM363345", "GSM363346", "GSM363347", "GSM363348", "GSM363349", "GSM363350", "GSM363351", "GSM363352", "GSM363353", "GSM363354", "GSM363355", "GSM363356", "GSM363357", "GSM363358", "GSM363359", "GSM363360", "GSM363361", "GSM363362", "GSM363363", "GSM363364", "GSM363365", "GSM363366", "GSM363367", "GSM363368", "GSM363369", "GSM363370", "GSM363371", "GSM363372", "GSM363373", "GSM363374", "GSM363375", "GSM363376", "GSM363378", "GSM363380", "GSM363381", "GSM363382", "GSM363384", "GSM363386", "GSM363388", "GSM363391", "GSM363393", "GSM363397", "GSM363400", "GSM363402", "GSM363404", "GSM363407", "GSM363417", "GSM363420", "GSM363421", "GSM363422", "GSM363423", "GSM363424", "GSM363425", "GSM363426", "GSM363427", "GSM363428", "GSM363429", "GSM363430", "GSM363431", "GSM363432", "GSM363433", "GSM363434", "GSM363435", "GSM363436", "GSM363437", "GSM363438", "GSM363439", "GSM363440", "GSM363441", "GSM363442", "GSM363443", "GSM363444", "GSM363445", "GSM363446", "GSM363447", "GSM363448", "GSM363449", "GSM363450", "GSM363451", "GSM712532", "GSM712533", "GSM712534", "GSM712535", "GSM712536", "GSM712537", "GSM712538", "GSM712539", "GSM712540", "GSM712541", "GSM712542"], "sample_count": 488, "group_sizes": null, "group_sizes_basis": null, "platform": "3921;571", "taxon": "Homo sapiens", "title": "Gene expression data of human hepatocellular carcinoma (HCC)", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE45267", "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=GSE45267", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE45267", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM1100370", "GSM1100371", "GSM1100372", "GSM1100373", "GSM1100374", "GSM1100375", "GSM1100376", "GSM1100377", "GSM1100378", "GSM1100379", "GSM1100380", "GSM1100381", "GSM1100382", "GSM1100383", "GSM1100384", "GSM1100385", "GSM1100386", "GSM1100387", "GSM1100388", "GSM1100389", "GSM1100390", "GSM1100391", "GSM1100392", "GSM1100393", "GSM1100394", "GSM1100395", "GSM1100396", "GSM1100397", "GSM1100398", "GSM1100399", "GSM1100400", "GSM1100401", "GSM1100402", "GSM1100403", "GSM1100404", "GSM1100405", "GSM1100406", "GSM1100407", "GSM1100408", "GSM1100409", "GSM1100410", "GSM1100411", "GSM1100412", "GSM1100413", "GSM1100414", "GSM1100415", "GSM1100416", "GSM1100417", "GSM1100418", "GSM1100419", "GSM1100420", "GSM1100421", "GSM1100422", "GSM1100423", "GSM1100424", "GSM1100425", "GSM1100426", "GSM1100427", "GSM1100428", "GSM1100429", "GSM1100430", "GSM1100431", "GSM1100432", "GSM1100433", "GSM1100434", "GSM1100435", "GSM1100436", "GSM1100437", "GSM1100438", "GSM1100439", "GSM1100440", "GSM1100441", "GSM1100442", "GSM1100443", "GSM1100444", "GSM1100445", "GSM1100446", "GSM1100447", "GSM1100448", "GSM1100449", "GSM1100450", "GSM1100451", "GSM1100452", "GSM1100453", "GSM1100454", "GSM1100455", "GSM1100456"], "sample_count": 87, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Gene expression profiles of human hepatocellular carcinoma (training set 1)", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE64041", "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=GSE64041", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE64041", "version": null, "note": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM2052455", "GSM2052456", "GSM2052457", "GSM2052458", "GSM2052459", "GSM2052460", "GSM2052461", "GSM2052462", "GSM2052463", "GSM2052464", "GSM2052465", "GSM2052466", "GSM2052467", "GSM2052468", "GSM2052469", "GSM2052470", "GSM2052471", "GSM2052472", "GSM2052473", "GSM2052474", "GSM2052475", "GSM2052476", "GSM2052477", "GSM2052478", "GSM2052479", "GSM2052480", "GSM2052481", "GSM2052482", "GSM2052483", "GSM2052484", "GSM2052485", "GSM2052486", "GSM2052487", "GSM2052488", "GSM2052489", "GSM2052490", "GSM2052491", "GSM2052492", "GSM2052493", "GSM2052494", "GSM2052495", "GSM2052496", "GSM2052497", "GSM2052498", "GSM2052499", "GSM2052500", "GSM2052501", "GSM2052502", "GSM2052503", "GSM2052504", "GSM2052505", "GSM2052506", "GSM2052507", "GSM2052508", "GSM2052509", "GSM2052510", "GSM2052511", "GSM2052512", "GSM2052513", "GSM2052514", "GSM2052515", "GSM2052516", "GSM2052517", "GSM2052518", "GSM2052519", "GSM2052520", "GSM2052521", "GSM2052522", "GSM2052523", "GSM2052524", "GSM2052525", "GSM2052526", "GSM2052527", "GSM2052528", "GSM2052529", "GSM2052530", "GSM2052531", "GSM2052532", "GSM2052533", "GSM2052534", "GSM2052535", "GSM2052536", "GSM2052537", "GSM2052538", "GSM2052539", "GSM2052540", "GSM2052541", "GSM2052542", "GSM2052543", "GSM2052544", "GSM2052545", "GSM2052546", "GSM2052547", "GSM2052548", "GSM2052549", "GSM2052550", "GSM2052551", "GSM2052552", "GSM2052553", "GSM2052554", "GSM2052555", "GSM2052556", "GSM2052557", "GSM2052558", "GSM2052559", "GSM2052560", "GSM2052561", "GSM2052562", "GSM2052563", "GSM2052564", "GSM2052565", "GSM2052566", "GSM2052567", "GSM2052568", "GSM2052569", "GSM2052570", "GSM2052571", "GSM2052572", "GSM2052573", "GSM2052574", "GSM2052575", "GSM2052576", "GSM2052577", "GSM2052578", "GSM2052579"], "sample_count": 125, "group_sizes": null, "group_sizes_basis": null, "platform": "6244", "taxon": "Homo sapiens", "title": "Gene expression profiling in paired human hepatocellular carcinoma and liver parenchyma biopsies and normal liver biopsies.", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE14520 not downloaded", "asset:data:geo:GSE14520 licence not read", "asset:data:geo:GSE45267 not downloaded", "asset:data:geo:GSE45267 licence not read", "asset:data:geo:GSE64041 not downloaded", "asset:data:geo:GSE64041 licence not read"]}, "analysis": {"state": "partial", "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": "Using the limma package (version 3.40.6), differential analysis was performed, identifying DEGs based on criteria of |log2FC|≥ 1 and P < 0.05."}}, {"id": "method-2", "family": "group_comparison", "specific": "anova", "label": "Group comparison", "dsl_operations": ["group_summary", "welch_t", "bootstrap_mean_difference", "group_comparison_anova"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "ANOVA"}}, {"id": "method-3", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "KM"}}, {"id": "method-4", "family": "correlation_analysis", "specific": "pearson", "label": "Correlation analysis", "dsl_operations": ["pearson_r"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["paired_numeric_columns"], "evidence": {"score": 0.8, "band": "high", "quote": "Pearson correlation"}}, {"id": "method-5", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "PPI"}}, {"id": "method-6", "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-7", "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": ["method.reader_differs_from_extractor"]}, "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": ["GSE14520", "GSE45267", "GSE64041"], "resolved_accessions": ["GSE14520", "GSE45267", "GSE64041"], "statements": ["The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material."], "basis": "The paper names GSE14520, GSE45267, GSE64041 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:40128499", "data:geo:GSE14520"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE14520"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:49:02Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 12964, "completion_tokens": 1318, "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:40128499", "type": "paper", "label": "pmid:40128499"}, {"id": "source:pmid:40128499", "type": "manuscript", "label": "PMID 40128499 full text"}, {"id": "data:geo:GSE14520", "type": "dataset", "label": "GEO GSE14520"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:40128499", "type": "paper", "label": "pmid:40128499"}, {"id": "source:pmid:40128499", "type": "manuscript", "label": "PMID 40128499 full text"}, {"id": "data:geo:GSE14520", "type": "dataset", "label": "GEO GSE14520"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-40128499", "type": "extraction", "used": ["source:pmid:40128499"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE14520", "type": "accession_resolution", "used": ["data:geo:GSE14520"], "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:40128499", "parent_hash": "sha256:df1accb834772554af016ae5301e541b7d6504925886f649323063d738b49e8c", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE14520 licence not read", "asset:data:geo:GSE14520 not downloaded", "asset:data:geo:GSE45267 licence not read", "asset:data:geo:GSE45267 not downloaded", "asset:data:geo:GSE64041 licence not read", "asset:data:geo:GSE64041 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"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": ["on in HCC, while inhibiting CCNB1 may reduce HepG2 cell proliferation by promoting cellular sen", "immune cells. Cell culture and transfection HepG2 cells obtained from Procell Life Science & T", "r negative control Si-non-CCNB1 (Si-NC) into HepG2 cells. Transfection efficiency was assessed"], "order_basis": "paper_text_order:1882", "id": "assay:1"}, {"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": ["d 22 types of immune cells. Cell culture and transfection HepG2 cells obtained from Procell Life Scien", "enePharma, Shanghai, China) was utilised for transfection of si-RNA targeting CCNB1 (Si-CCNB1) or nega", "ntrol Si-non-CCNB1 (Si-NC) into HepG2 cells. Transfection efficiency was assessed by qPCR after 48 h."], "order_basis": "paper_text_order:3631", "id": "assay:2"}, {"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": ["lls. Transfection efficiency was assessed by qPCR after 48 h. Statistical analysis Data were a"], "order_basis": "paper_text_order:4165", "id": "assay:3"}, {"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": ["Using the limma package (version 3.40.6), differential analysis was performed, identifying DEGs based on criteria of |log2FC|≥ 1 and P < 0.05."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]},"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":"2026-11-04T00:33:13+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}}}