Expression Characteristics and Prognostic Value of KLRG2 in Endometrial Cancer: A Comprehensive Analysis Based on Multi-Omics Data.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:40722666", "kind": "science-record", "revision": 1, "content_hash": "sha256:57f35ba7d5b9a2a5facc5ae20bcf112edc4042f9d2c25270c94cbc33ed13ff2f", "created_at": "2026-11-01T10:25:52Z", "updated_at": "2026-11-01T10:25:52Z", "generator": {"name": "corpus-assay-engine", "converter": "sep_to_sci_v1", "source_package_schema": "urn:bntrg:sep:1.0.0"}, "paper": {"state": "partial", "title": "Expression Characteristics and Prognostic Value of KLRG2 in Endometrial Cancer: A Comprehensive Analysis Based on Multi-Omics Data.", "doi": "10.3390/biomedicines13071592", "pmid": "40722666", "authors": null, "journal": "Biomedicines", "year": 2025, "abstract": null, "claims": [{"id": "claim-1", "statement": "the headline numerical result the paper states for its main finding", "kind": "quantitative", "state": "complete", "target": {"value": 3.08, "unit": "hazard ratio", "tolerance": null, "source": "chars 1208-1308 of source sha256 bf25043efcea70a8d90c51fb7acd28283a3c684710dd508a4885c068704ada54"}, "evidence": [{"asset": "source:pmid:40722666", "locator": "chars 1208-1308 of source sha256 bf25043efcea70a8d90c51fb7acd28283a3c684710dd508a4885c068704ada54", "quote": "High KLRG2 expression independently predicted worse overall survival (HR = 3.08, 95% CI = 1.92–4.96)"}]}], "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:40722666"], "outputs": ["the published estimate, its unit and its interval"], "instruments": [], "reagents": []}, {"id": 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"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:40722666' does not resolve to a declared asset"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:40722666", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3390/biomedicines13071592", "sha256": "sha256:bf25043efcea70a8d90c51fb7acd28283a3c684710dd508a4885c068704ada54", "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3390/biomedicines13071592", "version": null, "note": "Source read by the package builder: full_text.", "structure": {"access_state": "full_text"}}], "gaps": ["asset:source:pmid:40722666 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:40722666"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:40722666"]}, "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": "722d50752be0a285188af5584def54616da4e074100afde3673134d965d74c85", "source_hash": "bf25043efcea70a8d90c51fb7acd28283a3c684710dd508a4885c068704ada54", "raw_response_sha256": "sha256:c164eb6da37ff402de0a80d6496aa873c4e898a52983c051a5f2eeaeb6e9ab17", "raw_response_chars": 5650}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "613d8ea079b7723ba7f4a0762cdb64c27a8992960d586e7f72e7ba84e705964b", "source_hash": "bf25043efcea70a8d90c51fb7acd28283a3c684710dd508a4885c068704ada54", "raw_response_sha256": "sha256:52ac21753f656332f366a4d340fb20e7448c9b357c846351bd877b63e0be0f05", "raw_response_chars": 74006}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "d78206785e58cd68f1f2d433ff5f5ff2ca7da3e73ed2aa50be6f5cdc1201e78a", "source_hash": "bf25043efcea70a8d90c51fb7acd28283a3c684710dd508a4885c068704ada54", "raw_response": "{\"parent_value\":3.08,\"unit\":\"HR\",\"evidence\":\"High KLRG2 expression independently predicted worse overall survival (HR = 3.08, 95% CI = 1.92–4.96)\",\"target_result\":\"High KLRG2 expression independently predicted worse overall survival (HR = 3.08, 95% CI = 1.92–4.96).\",\"number_stated\":true}", "reading": {"parent_value": 3.08, "unit": "HR", "evidence": "High KLRG2 expression independently predicted worse overall survival (HR = 3.08, 95% CI = 1.92–4.96)", "target_result": "High KLRG2 expression independently predicted worse overall survival (HR = 3.08, 95% CI = 1.92–4.96).", "number_stated": true, "source_locator": "chars 1208-1308 of source sha256 bf25043efcea70a8d90c51fb7acd28283a3c684710dd508a4885c068704ada54"}, "recorded_at": "2026-10-31T15:23:24.872716+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "996f5f0b1a119e119dcfe59aa9b48260e2d783171af26959b739b7e825cf0be7", "source_hash": "bf25043efcea70a8d90c51fb7acd28283a3c684710dd508a4885c068704ada54", "raw_response": "<think>We need answer JSON only. Need identify single numerical result headline for registered target main finding. Paper abstract: high KLRG2 independently predicted worse OS HR=3.08 and PFI HR=1.98. Which single numerical result headline? Need discern perhaps target is \"headline numerical result paper states for its main finding\" and likely one prominent number. They ask unit must paper prints. Could be HR = 3.08 (unit maybe \"HR\" or perhaps unitless?). Need report headline number only. We need exact contiguous quote containing number and attribution clause. Likely parent_value 3.08, unit \"HR\", evidence exact quote: \"High KLRG2 expression independently predicted worse overall survival (HR = 3.08, 95% CI = 1.92–4.96)\" target_result maybe \"HR = 3.08\". But question says report headline number only: value paper itself states for registered target, not calculated etc. The schema includes target_result perhaps describe. Unit must be unit paper prints. Could say unit \"HR\" because printed. But perhaps unit is \"hazard ratio (HR)\"? They say unit must be unit paper prints, so likely \"HR\". Evidence exact contiguous quotation. Maybe target result should be \"HR = 3.08\". number_stated true.\n\nYet ambiguity: Main finding could be overexpression p &lt;0.001, or HR. The \"single numerical result\" a replication target has to reproduce perhaps likely paper has a specific target inferred from \"registered target: headline numerical result ... main finding.\" We need extract main headline numerical result. Abstract first results: KLRG2 significantly overexpressed p&lt;.001; high expression predicted OS HR=3.08 and PFI HR=1.98. Which one is headline? The primary survival result likely HR 3.08. Need select one number. Could unit perhaps \"hazard ratio\". They demand headline number only, likely don't include CI in parent value but evidence can include exact clause. The target_result can likely be \"3.08\". We should not report extra numeric details outside evidence? JSON evidence necessarily includes quote with CI, which has other numbers. They say headline number only, evidence exact quotation containing number. Exact full clause likely includes CI. That's okay, parent_value only headline.\n\nNeed ensure quote exact contiguous. \"High KLRG2 expression independently predicted worse overall survival (HR = 3.08, 95% CI = 1.92–4.96) and progression-free interval (HR = 1.98, 95% CI = 1.37–2.87).\" Since attribution attached by target names and if number tied target quote whole clause. Could quote only first clause ending at \")\"—is that contiguous and attribution checkable. Yes. They said do not shorten it perhaps means evidence quote must be exact contiguous quotation, don't truncate? \"The evidence must be an exact, contiguous quotation from SOURCE TEXT that contains the number; do not shorten it, do not add an ellipsis and do not paraphrase it.\" Ambiguity \"do not shorten it\" perhaps quote entire relevant clause rather than just \"(HR = 3.08)\"? Better quote full sentence including both OS and PFI? They say attribution may be carried by text wording; when linked, quote whole clause so reader can check. We could quote sentence through progression-free interval, which includes extra number. But \"headline number only\" refers reported number not evidence. Exact full sentence safest. Yet perhaps \"do not shorten it\" says don't shorten quotation, but source itself no designated quote. Usually extract evidence as exact quote. Full sentence ideal.\n\nUnit: paper prints \"HR\", so use \"HR\". target_result perhaps \"HR = 3.08\". Could mention no other prose. JSON valid with Unicode. Let's formulate:\n\n{\n \"parent_value\": 3.08,\n \"unit\":\"HR\",\n \"evidence\":\"High KLRG2 expression independently predicted worse overall survival (HR = 3.08, 95% CI = 1.92–4.96) and progression-free interval (HR = 1.98, 95% CI = 1.37–2.87).\",\n \"target_result\":\"HR = 3.08\",\n \"number_stated\":true\n}\n\nIs HR a unit? They might expect \"hazard ratio\" as unit. User says unit paper prints. It prints \"HR =\". Unit perhaps \"HR\". In extraction tasks, parent_value likely numeric, unit exact. Could be unit \"HR\". Good.\n\nBut let's carefully inspect possibility \"headline numerical result\" refers 223 DEGs? No, main finding in title and abstract. They may be testing extraction from paper text with a registered target deliberately generic. Need determine what \"paper itself states for registered target\" means. It asks \"find the single numerical result that a replication of the registered target has to reproduce.\" Target: headline numerical result the paper states for its main finding. The paper is likely synthetic abstract with headline HR 3.08. Could be p &lt;0.001, but less replicable? \"headline numerical result\" likely a benchmark target from source. The prominent result is HR = 3.08. Let's think if unit should be \"95% CI\" no.\n\nCould target result be \"3.08\" only and unit \"HR\"? \"Report the headline number only: the value ...\". target_result perhaps should describe result, perhaps they want \"High KLRG2 expression independently predicted worse overall survival (HR = 3.08...)\" But schema wants target_result string and evidence string separately. Usually output target_result might be e.g. \"HR = 3.08\". That's okay.\n\nNeed JSON no markdown.</think>\n\n{\"parent_value\":3.08,\"unit\":\"HR\",\"evidence\":\"High KLRG2 expression independently predicted worse overall survival (HR = 3.08, 95% CI = 1.92–4.96) and progression-free interval (HR = 1.98, 95% CI = 1.37–2.87).\",\"target_result\":\"HR = 3.08\",\"number_stated\":true}", "reading": {"parent_value": 3.08, "unit": "HR", "evidence": "High KLRG2 expression independently predicted worse overall survival (HR = 3.08, 95% CI = 1.92–4.96) and progression-free interval (HR = 1.98, 95% CI = 1.37–2.87).", "target_result": "HR = 3.08", "number_stated": true, "source_locator": "chars 1208-1371 of source sha256 bf25043efcea70a8d90c51fb7acd28283a3c684710dd508a4885c068704ada54"}, "recorded_at": "2026-10-31T15:23:39.293882+00:00"}], "agreement": false, "disagreements": {"target_result": {"minimax": "High KLRG2 expression independently predicted worse overall survival (HR = 3.08, 95% CI = 1.92–4.96) and progression-free interval (HR = 1.98, 95% CI = 1.37–2.87).", "minimax_alt": "High KLRG2 expression independently predicted worse overall survival (HR = 3.08, 95% CI = 1.92–4.96)", "decisive": false}, "physical_methods": {"minimax": ["Immunohistochemistry", "Quantitative real-time PCR (qRT-PCR)"], "minimax_alt": ["qRT-PCR validation using 14 endometrial carcinoma tissues and 14 proliferative-phase endometrial controls", "Immunohistochemistry"], "decisive": false}, "analysis_methods": {"minimax": ["Cox proportional hazards regression with multivariable adjustment", "Kaplan–Meier survival curves compared by log-rank test", "Time-dependent ROC analysis", "Univariate and multivariate logistic regression", "Shapiro–Wilk test", "Unpaired Student's t-test", "Mann–Whitney U test", "Paired t-test", "Wilcoxon signed-rank test", "Chi-square test with Yates' continuity correction", "ROC curve analysis with DeLong's variance estimation", "Inverse probability of censoring weighting", "Differential expression analysis", "Gene Ontology enrichment analysis", "KEGG pathway analysis", "Gene Set Enrichment Analysis (GSEA)", "Spearman correlation analysis"], "minimax_alt": ["Cox proportional hazards regression with multivariable adjustment", "Kaplan–Meier curves with log-rank test", "Time-dependent ROC analysis", "Proportional-hazards assessment using Schoenfeld residuals"], "decisive": false}, "statistical_method": {"minimax": "Cox proportional hazards regression with multivariable adjustment for predefined clinical covariates", "minimax_alt": "Cox proportional hazards regression with multivariable adjustment", "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:3d37c1804330551571b77dcfc373c39cebb8e69a3febb36a6c0044f2f5319bcb", "type": "sep_package", "label": "SEP v1 package for pmid:40722666"}], "activities": [{"id": "activity:conversion:pmid:40722666", "type": "conversion", "used": ["package:3d37c1804330551571b77dcfc373c39cebb8e69a3febb36a6c0044f2f5319bcb"], "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": "4a9cbb1c-d2ef-4ed0-bae2-856d59753c4b", "parent_hash": "3d37c1804330551571b77dcfc373c39cebb8e69a3febb36a6c0044f2f5319bcb", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:40722666 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:40722666' does not resolve to a declared asset", "targets"]}