Itaconate-Related Gene Signatures as Prognostic Markers in Colon Cancer: Insights From Transcriptomic and Spatial Analysis.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41523911", "kind": "science-record", "revision": 1, "content_hash": "sha256:da5911c7db43a1ab0316a293d981fe72bacc9cb7652498f8d413a99eccf6d931", "created_at": "2026-11-01T10:25:54Z", "updated_at": "2026-11-01T10:25:54Z", "generator": {"name": "corpus-assay-engine", "converter": "sep_to_sci_v1", "source_package_schema": "urn:bntrg:sep:1.0.0"}, "paper": {"state": "partial", "title": "Itaconate-Related Gene Signatures as Prognostic Markers in Colon Cancer: Insights From Transcriptomic and Spatial Analysis.", "doi": "10.1155/humu/7928082", "pmid": "41523911", "authors": null, "journal": "Human mutation", "year": 2026, "abstract": null, "claims": [{"id": "claim-1", "statement": "the headline numerical result the paper states for its main finding", "kind": "qualitative", "state": "blocked", "target": {"value": null, "unit": null, "tolerance": null, "source": null}, "evidence": []}], "gaps": ["abstract", "authors"]}, "experiment": {"state": "partial", "objective": "the headline numerical result the paper states for its main finding", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate and its interval from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The number a replication must land on, and the sentence it came from.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:41523911"], "outputs": ["the published estimate, its unit and its interval"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data behind the published result", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:not_downloaded", "description": "The published result cannot be recomputed without the data the paper analysed.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the source data with its provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the analysis programme", "kind": "analysis", "state": "blocked", "blocked_on": "no owned computational capability is bound to this experiment", "description": "Re-run the paper's analysis on the source data and produce the registered result. | SEP input not carried into the asset list: materials:the source data behind the published result in pmid:41523911", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the registered result"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:41523911' does not resolve to a declared asset"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:41523911", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/humu/7928082", "sha256": "sha256:06f4b51dc4b71760f8a37018023331aace1391b3d2ee7fc866b579dec8b6d6d4", "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1155/humu/7928082", "version": null, "note": "Source read by the package builder: full_text.", "structure": {"access_state": "full_text"}}], "gaps": ["asset:source:pmid:41523911 not verified"]}, "analysis": {"state": "absent", "methods": [], "targets": [], "gaps": ["method", "targets"]}, "capability": {"state": "absent", "requirements": [], "gaps": ["capability"]}, "readiness": {"state": "partial", "tier": null, "blocking_axis": null, "blocked_on": null, "axes": {}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:41523911"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:41523911"]}, "gaps": ["corpus_record_absent"]}, "review": {"state": "partial", "machine_critique": {"status": "blocked", "providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "full-text-reading-v1", "prompt_hash": "30aefe6cfc2007a598e84b81324d8936387c253787e99a88080e0685951a5a83", "source_hash": "06f4b51dc4b71760f8a37018023331aace1391b3d2ee7fc866b579dec8b6d6d4", "raw_response_sha256": "sha256:c628e848082a0b6bb630fac041fade6c58c8d248aa3f0f57cb817d5dddfb0dd8", "raw_response_chars": 4075}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "12408c44cf5686c7ebdb4b5048344d838db2f93e1fe3a7dee5662e92ee0809c4", "source_hash": "06f4b51dc4b71760f8a37018023331aace1391b3d2ee7fc866b579dec8b6d6d4", "raw_response_sha256": "sha256:0847aac922bf764ac078ea36b467faa725b422c0e84cf89f4b439469129d17ef", "raw_response_chars": 50787}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "db102302a9e9d179fc8c2d05923ab98db2051e4b8105a967dede4f995db24957", "source_hash": "06f4b51dc4b71760f8a37018023331aace1391b3d2ee7fc866b579dec8b6d6d4", "raw_response": "{\"parent_value\":0.7,\"unit\":\"C-index\",\"evidence\":\"The optimal prognostic prediction model (Enet [alpha = 0.2]) was constructed and validated, which showed good prognostic predictive value in both the training and validation sets (average C‐index > 0.7) and was superior to previous conventional clinical features and 22 prognostic models developed by researchers in the past 4 years.\",\"target_result\":\"The optimal prognostic prediction model achieved an average C-index greater than 0.7 in the training and validation sets.\",\"number_stated\":true}", "reading": {"parent_value": 0.7, "unit": "C-index", "evidence": "The optimal prognostic prediction model (Enet [alpha = 0.2]) was constructed and validated, which showed good prognostic predictive value in both the training and validation sets (average C‐index > 0.7) and was superior to previous conventional clinical features and 22 prognostic models developed by researchers in the past 4 years.", "target_result": "The optimal prognostic prediction model achieved an average C-index greater than 0.7 in the training and validation sets.", "number_stated": true, "source_locator": "chars 957-1290 of source sha256 06f4b51dc4b71760f8a37018023331aace1391b3d2ee7fc866b579dec8b6d6d4"}, "recorded_at": "2026-10-31T15:16:44.637753+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "03043bb822ec6b80fa3c96cd397fac2c628ac3c8e5fd8232837a5e4a0e4f8bc9", "source_hash": "06f4b51dc4b71760f8a37018023331aace1391b3d2ee7fc866b579dec8b6d6d4", "raw_response": "<think>We need answer JSON object. Need interpret \"single numerical result that replication registered target has to reproduce. Headline number only: value paper itself states for registered target, main finding.\" Source likely abstract headline numerical result: average C-index &gt; 0.7? Need identify exact headline numerical result. Could be \"10 prognosis-related genes\", \"average C-index &gt; 0.7\". Registered target vague \"the headline numerical result the paper states for its main finding\". Need infer intended target perhaps \"average C-index &gt; 0.7\" because model performance headline result. Need report number, unit paper prints. They require parent_value number, unit string. What is number? 0.7, unit perhaps \"C-index\" or maybe \"&gt; 0.7\" unit? Exact evidence contiguous quote containing number, whole clause attribution. Need target_result perhaps describe.\n\nLet's parse task wording. \"Read supplied paper text and find the single numerical result that a replication of the registered target has to reproduce. Report the headline number only: the value the paper itself states for the registered target, not a value you calculated, converted, averaged or reconstructed. The unit must be the unit the paper prints.\" This likely benchmark asks extract one key number associated with registered target. Here registered target generic headline numerical result. Paper abstract reports many numbers: 448 patients, 7 models, 1473 cases, 10 genes, alpha .2, average C-index &gt; .7, 22 models, 4 years. Main finding's headline performance number likely C-index &gt; 0.7. \"unit must be unit paper prints\" likely unit might \"C-index\" but C-index dimensionless. Could say \"C-index &gt; 0.7\". parent_value 0.7, unit \"C-index\". Evidence exact contiguous quote perhaps \"The optimal prognostic prediction model (Enet [alpha = 0.2]) was constructed and validated, which showed good prognostic predictive value in both the training and validation sets (average C‐index &gt; 0.7) and was superior to previous conventional clinical features and 22 prognostic models developed by researchers in the past 4 years.\" This is whole sentence/clause and attribution. They ask \"headline number only.\" Evidence can quote whole clause. target_result maybe \"average C-index &gt; 0.7\". Need JSON valid, unicode hyphen exact? Use C‐index with U+2010? Source uses nonbreaking hyphen perhaps \"C‐index\" U+2010. Evidence exact. Unit \"C-index\" maybe paper prints \"C‐index\". Since exact unit printed, use \"C‐index\". Parent_value must number 0.7. target_result perhaps \"average C‐index > 0.7\". number_stated true.\n\nBut let's carefully consider possibility intended numerical result is \"10 prognosis-related genes\" or sample size. The registered target says \"the headline numerical result the paper states for its main finding\" rather than naming metric. Maybe task designed to identify headline abstract finding. Could be one number: 10 genes? Let's examine title and abstract: study comprehensively analyzes expression/biology/prognosis; through screening, 10 genes selected; optimal model, average C-index > 0.7. \"Headline numerical result\" generally result metric is C-index > .7. They ask \"unit must be the unit the paper prints,\" suggesting performance measure with unit perhaps C-index. Need only one numerical result. Could be \"average C-index > 0.7\" certainly replication target.\n\nCould parent_value need 0.7 despite >. Since JSON number no comparator. target_result preserves >. unit maybe \"C-index\". Evidence exact quotation. We can quote sentence. Exact contiguous from source. Ensure no inadvertent changes. Source: \"The optimal prognostic prediction model (Enet [alpha = 0.2]) was constructed and validated, which showed good prognostic predictive value in both the training and validation sets (average C‐index > 0.7) and was superior to previous conventional clinical features and 22 prognostic models developed by researchers in the past 4 years.\" We could evidence only clause \"(average C‐index > 0.7)\" but attribution to model requires surrounding clause. Instructions: \"When that is how the text links them, quote the whole clause so a reader can check the attribution for themselves.\" So whole sentence is safest. \"Evidence must be exact, contiguous quotation.\" We can quote exactly. target_result could be \"average C‐index > 0.7\". Is target_result supposed plain text. Unit perhaps \"C‐index\" (dimensionless). Maybe unit empty because C-index is unitless? Yet schema says unit string. They demand \"unit must be the unit the paper prints.\" If paper prints C-index as metric, call it unit. Could use \"C‐index\". Parent_value 0.7.\n\nNeed no markdown, just JSON. Ensure JSON valid Unicode.</think>\n\n{\"parent_value\":0.7,\"unit\":\"C‐index\",\"evidence\":\"The optimal prognostic prediction model (Enet [alpha = 0.2]) was constructed and validated, which showed good prognostic predictive value in both the training and validation sets (average C‐index > 0.7) and was superior to previous conventional clinical features and 22 prognostic models developed by researchers in the past 4 years.\",\"target_result\":\"average C‐index > 0.7\",\"number_stated\":true}", "reading": {"parent_value": 0.7, "unit": "C‐index", "evidence": "The optimal prognostic prediction model (Enet [alpha = 0.2]) was constructed and validated, which showed good prognostic predictive value in both the training and validation sets (average C‐index > 0.7) and was superior to previous conventional clinical features and 22 prognostic models developed by researchers in the past 4 years.", "target_result": "average C‐index > 0.7", "number_stated": true, "source_locator": "chars 957-1290 of source sha256 06f4b51dc4b71760f8a37018023331aace1391b3d2ee7fc866b579dec8b6d6d4"}, "recorded_at": "2026-10-31T15:16:50.916931+00:00"}], "agreement": false, "disagreements": {"target_result": {"minimax": "The Enet (alpha = 0.2) prognostic model achieved an average C-index > 0.7 in the training and validation sets.", "minimax_alt": "The Enet [alpha = 0.2] prognostic prediction model achieved an average C‐index > 0.7 in the training and validation sets, comprising 448 TCGA training patients and 1473 GEO validation cases.", "decisive": false}, "work_type": {"minimax": "analysis_only_for_target", "minimax_alt": "analysis_plus_physical_validation", "decisive": true}, "physical_methods": {"minimax": [], "minimax_alt": ["Tissue microarray (TMA)"], "decisive": false}, "analysis_methods": {"minimax": ["Enet (elastic net) prognostic prediction model with alpha = 0.2", "C-index evaluation", "Univariate and multivariate survival analysis", "Gene Set Enrichment Analysis (GSEA)", "CIBERSORT", "TIMER", "MCPcounter", "ESTIMATE"], "minimax_alt": ["Enet [alpha = 0.2]", "Seurat package (v4.3.0)", "AUCell package (v1.16.0)", "Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses", "CARD algorithm (v0.1.0)", "Gene Set Enrichment Analysis (GSEA, v4.3.2)", "CIBERSORT (v1.06)", "TIMER (v2.0)", "MCPcounter (v1.2.0)", "ESTIMATE (v1.0.13)", "maftools package (v2.14.0)", "CellChat package (v1.5.0)"], "decisive": false}, "statistical_method": {"minimax": "Enet (alpha = 0.2)", "minimax_alt": "Enet [alpha = 0.2]", "decisive": true}, "unit": {"minimax": "C-index", "minimax_alt": "C‐index", "decisive": true}}, "agreement_basis": {"policy": "decisive_fields", "decisive_fields": ["work_type", "number_stated", "parent_value", "unit"]}, "blinded": true}, "human_critique": {"status": "not_run", "reviewer": null, "signed_at": null, "conflict_checked": false, "commentary": null}, "stages": [{"key": "target_materials", "status": "pending", "reason": null, "evidence": null}, {"key": "independent_readings", "status": "blocked", "reason": "The independent readings are incomplete or disagree; the source evidence must resolve the difference.", "evidence": {"provider_errors": []}}, {"key": "source_resolution", "status": "pending", "reason": null, "evidence": null}, {"key": "protocol_reconstruction", "status": "pending", "reason": null, "evidence": null}, {"key": "control_execution", "status": "pending", "reason": null, "evidence": null}, {"key": "control_comparison", "status": "pending", "reason": null, "evidence": null}, {"key": "publication", "status": "pending", "reason": null, "evidence": null}], "gaps": ["review.human_critique", "review.machine_critique.blocked"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:4c9a8a1940e0fa378100213d3db83ed91923300d2dfe5e7e1b0a5ce764e5753d", "type": "sep_package", "label": "SEP v1 package for pmid:41523911"}], "activities": [{"id": "activity:conversion:pmid:41523911", "type": "conversion", "used": ["package:4c9a8a1940e0fa378100213d3db83ed91923300d2dfe5e7e1b0a5ce764e5753d"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:minimax", "type": "model", "label": "minimax"}, {"id": "agent:minimax_alt", "type": "model", "label": "minimax_alt"}, {"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}], "source_run_id": "run-20261023T122449232913", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "e8738768-4fe4-49c6-a9d8-7eb3852a5e46", "parent_hash": "4c9a8a1940e0fa378100213d3db83ed91923300d2dfe5e7e1b0a5ce764e5753d", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:41523911 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.blocked", "step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:41523911' does not resolve to a declared asset", "targets"]}