{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38650009", "kind": "science-record", "revision": 4, "content_hash": "sha256:b03fca373a7b3246516fdb1bdd58be6bc0f020f73358939b3c58b2957ea8fc46", "created_at": "2026-11-01T19:20:37Z", "updated_at": "2026-11-01T22:54:11Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of osteoporosis ferroptosis-related markers and potential therapeutic compounds based on bioinformatics methods and molecular docking technology.", "doi": "10.1186/s12920-024-01872-0", "pmid": "38650009", "authors": ["Shi-Wei Long", "Shi-Hong Li", "Jian Li", "Yang He", "Bo Tan", "Hao-Han Jing", "Wei Zheng", "Juan Wu"], "journal": "BMC medical genomics", "year": 2024, "abstract": "RESEARCH BACKGROUND AND PURPOSE: Osteoporosis (OP) is one of the most common bone diseases worldwide, characterized by low bone mineral density and susceptibility to pathological fractures, especially in postmenopausal women and elderly men. Ferroptosis is one of the newly discovered forms of cell death regulated by genes in recent years. Many studies have shown that ferroptosis is closely related to many diseases. However, there are few studies on ferroptosis in osteoporosis, and the mechanism of ferroptosis in osteoporosis is still unclear. This study aims to identify biomarkers related to osteoporosis ferroptosis from the GEO (Gene Expression Omnibus) database through bioinformatics technology, and to mine potential therapeutic small molecule compounds through molecular docking technology, trying to provide a basis for the diagnosis and treatment of osteoporosis in the future.\nMATERIALS AND METHODS: We downloaded the ferroptosis-related gene set from the FerrDb database ( http://www.zhounan.org/ferrdb/index.html ), downloaded the data sets GSE56815 and GSE7429 from the GEO database, and used the R software \"limma\" package to screen differentially expressed genes (DEGs) from GSE56815, and intersected with the ferroptosis gene set to obtain ferroptosis-related DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by the R software \"clusterProfiler\" package. The random forest model was further screened to obtain essential ferroptosis genes. R software \"corrplot\" package was used for correlation analysis of essential ferroptosis genes, and the Wilcox test was used for significance analysis. The lncRNA-miRNA-mRNA-TF regulatory network was constructed using Cytoscape software. The least absolute shrinkage and selection operator (LASSO) was used to construct a disease diagnosis model, and a Receiver operating characteristic (ROC) curve was drawn to evaluate the diagnostic performance, and then GSE7429 was used to verify the reliability of the diagnosis model. Molecular docking technology was used to screen potential small molecule compounds from the Drugbank database. Finally, a rat osteoporosis model was constructed, and peripheral blood mononuclear cells were extracted for qRT-PCR detection to verify the mRNA expression levels of crucial ferroptosis genes.\nRESULT: Six DEGs related to ferroptosis were initially screened out. GO function and KEGG pathway enrichment analysis showed that ferroptosis-related DEGs were mainly enriched in signaling pathways such as maintenance of iron ion homeostasis, copper ion binding function, and ferroptosis. The random forest model identified five key ferroptosis genes, including CP, FLT3, HAMP, HMOX1, and SLC2A3. Gene correlation analysis found a relatively low correlation between these five key ferroptosis genes. The lncRNA-miRNA-mRNA-TF regulatory network shows that BAZ1B and STAT3 may also be potential molecules. The ROC curve of the disease diagnosis model shows that the model has a good diagnostic performance. Molecular docking technology screened out three small molecule compounds, including NADH, Midostaurin, and Nintedanib small molecule compounds. qRT-PCR detection confirmed the differential expression of CP, FLT3, HAMP, HMOX1 and SLC2A3 between OP and normal control group.\nCONCLUSION: This study identified five key ferroptosis genes (CP, FLT3, HAMP, HMOX1, and SLC2A3), they were most likely related to OP ferroptosis. In addition, we found that the small molecule compounds of NADH, Midostaurin, and Nintedanib had good docking scores with these five key ferroptosis genes. These findings may provide new clues for the early diagnosis and treatment of osteoporosis in the future.", "claims": [{"id": "claim-method", "statement": "We used the “limma” package in R software to perform differential genetic analysis on the processed data, and the screening threshold was set to an adjusted p-value < 0.05 and |log2FC| >0.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38650009", "locator": "sections[4] \"Identification of differentially expressed genes related to ferroptosis\" paragraph 2", "quote": "We used the “limma” package in R software to perform differential genetic analysis on the processed data, and the screening threshold was set to an adjusted p-value < 0.05 and |log2FC| >0."}], "state": "complete"}, {"id": "claim-data-access", "statement": "This study downloaded the GSE56815 dataset from the GEO database as a training set and the GSE7429 dataset from the website as a validation set for model diagnostic efficacy. Among them, GSE56815 contains blood samples of 40 women with high BMD (bone mineral density) and 40 samples of women with low BMD, while GSE7429 contains blood samples of 10 women with high BMD and ten blood samples of women with low BMD.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38650009", "locator": "sections[3] \"Data collection and organization\" paragraph 2", "quote": "This study downloaded the GSE56815 dataset from the GEO database as a training set and the GSE7429 dataset from the website as a validation set for model diagnostic efficacy. Among them, GSE56815 contains blood samples of 40 women with high BMD (bone mineral density) and 40 samples of women with low BMD, while GSE7429 contains blood samples of 10 women with high BMD and ten blood samples of women with low BMD."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Using limma on the GSE56815 dataset, the analysis screened 400 differentially expressed genes and identified six ferroptosis-related differentially expressed genes.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38650009", "locator": "sections[16] \"Identification of differentially expressed genes related to ferroptosis\" paragraph 2", "quote": "Through differential expression analysis, a total of 400 DEGs were screened from the dataset GSE56815, including 118 up-regulated genes and 282 down-regulated genes (Fig. 1A and B)."}, {"asset": "source:pmid:38650009", "locator": "sections[16] \"Identification of differentially expressed genes related to ferroptosis\" paragraph 2", "quote": "The obtained 376 ferroptosis-related genes were intersected with 400 DGEs to obtain six ferroptosis-related DEGs, as shown in the Venn diagram and heat map of ferroptosis-related DEGs (Fig. 1C and D)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Using limma on the GSE56815 dataset, the analysis screened 400 differentially expressed genes and identified six ferroptosis-related differentially expressed genes.", "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:38650009"], "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:GSE56815"], "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:GSE56815"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38650009", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12920-024-01872-0", "sha256": "sha256:52cbdb2fc8546accb2400b514a086996aa8b4c9c6bbd61429b98b7d56b677f89", "bytes": 40335, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12920-024-01872-0", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11036634", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE56815", "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=GSE56815", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE56815", "version": null, "note": "This study downloaded the GSE56815 dataset from the GEO database as a training set and the GSE7429 dataset from the website as a validation set for model diagnostic efficacy. 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE56815", "GSE7429"], "resolved_accessions": ["GSE56815", "GSE7429"], "statements": ["This study downloaded the GSE56815 dataset from the GEO database as a training set and the GSE7429 dataset from the website as a validation set for model diagnostic efficacy. Among them, GSE56815 contains blood samples of 40 women with high BMD (bone mineral density) and 40 samples of women with low BMD, while GSE7429 contains blood samples of 10 women with high BMD and ten blood samples of women with low BMD."], "basis": "The paper names GSE56815, GSE7429 in GEO (Gene Expression Omnibus) 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:38650009", "data:geo:GSE56815"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE56815"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:16:22Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 5, "usage": {"prompt_tokens": 11128, "completion_tokens": 2174, "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:38650009", "type": "paper", "label": "pmid:38650009"}, {"id": "source:pmid:38650009", "type": "manuscript", "label": "PMID 38650009 full text"}, {"id": "data:geo:GSE56815", "type": "dataset", "label": "GEO GSE56815"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:38650009", "type": "paper", "label": "pmid:38650009"}, {"id": "source:pmid:38650009", "type": "manuscript", "label": "PMID 38650009 full text"}, {"id": "data:geo:GSE56815", "type": "dataset", "label": "GEO GSE56815"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-38650009", "type": "extraction", "used": ["source:pmid:38650009"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE56815", "type": "accession_resolution", "used": ["data:geo:GSE56815"], "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:38650009", "parent_hash": "sha256:d603119652e2b2a264d4c388117f70352ed7f05d16fc11a39ea597289a166aef", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE56815 licence not read", "asset:data:geo:GSE56815 not downloaded", "asset:data:geo:GSE7429 licence not read", "asset:data:geo:GSE7429 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["ounds from the Drugbank database. Finally, a rat osteoporosis model was constructed, and peri", "fter Micro-CT scanning of the proximal femur in rats. It can be seen from the coronal layer-by-la", "r Micro-CT scanning of the proximal femur in rats. 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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}}}