{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41053280", "kind": "science-record", "revision": 4, "content_hash": "sha256:6cf4b05c92d19912a6bfa72b6c2c3f4df763074e92509150d7153ae57c3b91ca", "created_at": "2026-11-01T20:31:06Z", "updated_at": "2026-11-01T22:57:15Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Transcriptome analysis combined with single-cell analysis identified that APOC1 influences cholesterol transport by macrophages in ccRCC.", "doi": "10.1038/s41598-025-18392-1", "pmid": "41053280", "authors": ["Fengran Guo", "Ziyang Ma", "Hu Wang", "Zhenwei Han"], "journal": "Scientific reports", "year": 2025, "abstract": "Renal cell carcinoma (RCC) is one of the most prevalent categories of cancer worldwide, accounting for approximately 2% of cancer diagnoses and cancer deaths worldwide. various immunotherapeutic strategies have emerged as key approaches to managing advanced RCC. Bioinformatics methodologies were employed to analyze the TCGA-KIRC RNA sequencing dataset, GSE105261, GSE168845, and single-cell dataset GSE121636. Various techniques, including PCR, Western blotting, migration assays, scratch wound assays, flow cytometry, and immunofluorescence staining, were utilized to elucidate the functional characteristics of the tumor. In this study, we obtained transcriptome RNA sequencing data from the Cancer Genome Atlas (TCGA) database. Using the ESTIMATE algorithm, 249 immune-related genes were identified. Additionally, single-cell RNA sequencing data were integrated to determine the immune-related genes that affect the prognosis of clear cell renal cell carcinoma (ccRCC). Eventually, a total of 42 immune-related genes (IMDGs) were identified. Subsequently, in vitro experiments confirmed that APOC1 is highly expressed in ccRCC and significantly affects the migration and proliferation of ccRCC cells. Furthermore, our findings indicate that APOC1 plays a critical role in modulating cholesterol transport within macrophages and significantly contributes to the polarization of macrophages toward the M2 phenotype.", "claims": [{"id": "claim-method", "statement": "A total of 501 tumor samples were selected from 538 clear cell renal cell carcinoma (ccRCC) cases, with Kaplan–Meier method employed to generate survival curves. The log-rank test was applied to assess statistical significance, with a p-value threshold set at 0.05. 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The ggpubr package was loaded to perform correlation analysis between various scores and clinical pathological features, with statistical significance evaluated using the Wilcoxon rank sum test."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used in the current study are openly available in TCGA (https://portal.gdc.cancer.gov/) database, UCSC Xena data portal (https://xenabrowser.net/), GEO (https://www.ncbi.nlm.nih.gov/geo/) database. All date and materials are available from the corresponding authors upon request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41053280", "locator": "sections[38] \"notes\" paragraph 1", "quote": "The datasets used in the current study are openly available in TCGA (https://portal.gdc.cancer.gov/) database, UCSC Xena data portal (https://xenabrowser.net/), GEO (https://www.ncbi.nlm.nih.gov/geo/) database. All date and materials are available from the corresponding authors upon request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "APOC1 is highly expressed in ccRCC and promotes ccRCC cell migration and invasion while promoting M2 macrophage polarization through cholesterol transport.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41053280", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Subsequently, in vitro experiments confirmed that APOC1 is highly expressed in ccRCC and significantly affects the migration and proliferation of ccRCC cells."}, {"asset": "source:pmid:41053280", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Furthermore, our findings indicate that APOC1 plays a critical role in modulating cholesterol transport within macrophages and significantly contributes to the polarization of macrophages toward the M2 phenotype."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "APOC1 is highly expressed in ccRCC and promotes ccRCC cell migration and invasion while promoting M2 macrophage polarization through cholesterol transport.", "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:41053280"], "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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In this study, we obtained transcriptome RNA sequencing data from the Cancer Genome A", "their microenvironments25. By measuring the transcriptome at the single-cell level, scRNA-seq can more", "traditional methodologies26. The single-cell transcriptome dataset GSE121636 was retrieved from the GEO"], "order_basis": "paper_text_order:0", "id": "assay:1"}, {"role": "data_generation", "definition_id": "western_blot", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["SE121636. Various techniques, including PCR, Western blotting, migration assays, scratch wound assays, flo"], "order_basis": "paper_text_order:540", "id": "assay:2"}, {"role": "data_generation", "definition_id": "flow_cytometry", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["ing, migration assays, scratch wound assays, flow cytometry, and immunofluorescence staining, were utili"], "order_basis": "paper_text_order:598", "id": "assay:3"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["s, scratch wound assays, flow cytometry, and immunofluorescence staining, were utilized to elucidate the fun"], "order_basis": "paper_text_order:618", "id": "assay:4"}, {"role": "data_generation", "definition_id": "scrna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "unsupported", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["related genes were identified. Additionally, single-cell RNA sequencing data were integrated to determine the immune", "hment analysis on these genes. Additionally, single-cell RNA sequencing data were integrated to determine the immune", "ontrols and ccRCC samples The advancement of single-cell RNA sequencing (scRNA-seq) has facilitated a comprehensive", "rehensive immune profile was generated using single-cell RNA-seq data derived from 25,000 immune cells isolat"], "order_basis": "paper_text_order:912", "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": 1.0, "evidence": ["A total of 501 tumor samples were selected from 538 clear cell renal cell carcinoma (ccRCC) cases, with Kaplan–Meier method employed to generate survival curves. 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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}}}