Circular RNA circAHSA1 serves as a stable serum biomarker for the diagnosis and progression of gastric cancer.

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"Negative", "79", "41", "38"], ["Depth of infiltration", "Muscular layer and below", "87", "66", "21", "<0.001"], ["", "submucosa and above", "40", "31", "9"], ["Ki67", "Positive", "85", "42", "43", "0.251"], ["", "Negative", "42", "20", "22"], ["CK", "Positive", "66", "34", "32", "0.148"], ["", "Negative", "61", "27", "34"]], "row_count": 23, "column_count": 6, "numeric_cells": 82, "header_rows": 1, "locator": "section[18]/table-wrap[1]#tbl0002"}}, {"id": "asset:table:pmid:41330006:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:59f19f521d99b0462a1dbc22cfe0fa3124bffb49842e4cecb0b4f4e40166fce9", "bytes": 907, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[19]/table-wrap[1]#tbl0003", "version": null, "note": "Diagnostic performance of circAHSA1, CEA, CA199, and CA724 in differentiating GC patients from healthy donors.", "structure": {"pmcid": 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["circAHSA1+CEA+CA199+CA724", "0.356", "0.866", "0.739", "0.805", "0.78", "0.838", "< 0.001"]], "row_count": 9, "column_count": 8, "numeric_cells": 60, "header_rows": 1, "locator": "section[19]/table-wrap[1]#tbl0003"}}, {"id": "asset:table:pmid:41330006:4", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:98012e0b59cf86bcc3322a8ee14c9932756a469f62610ab571afe371cb211573", "bytes": 907, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[19]/table-wrap[2]#tbl0004", "version": null, "note": "Diagnostic performance of circAHSA1, CEA, CA199, and CA724 in differentiating GC patients from gastritis patients.", "structure": {"pmcid": "PMC12719094", "section_index": 19, "section_title": "circAHSA1 as a novel serum biomarker for differentiating GC from controls and gastritis patients", "row_count": 9, "column_count": 8}, "table": {"label": "Table 4", "caption": "Diagnostic performance of circAHSA1, CEA, CA199, and CA724 in differentiating GC patients from gastritis patients.", "rows": [["Model", "Cutoff", "SEN", "SPE", "ACCU", "PPV", "NPV", "P (vs circAHSA1)"], ["circAHSA1", "2.042", "0.669", "0.804", "0.729", "0.81", "0.661", "–"], ["CEA", "1.820", "0.819", "0.588", "0.716", "0.712", "0.723", "0.040"], ["CA199", "8.455", "0.543", "0.304", "0.437", "0.493", "0.348", "< 0.001"], ["CA724", "16.920", "0.213", "1", "0.563", "1", "0.505", "< 0.001"], ["circAHSA1+CEA", "0.484", "0.717", "0.716", "0.716", "0.758", "0.67", "0.355"], ["circAHSA1+CA199", "0.460", "0.772", "0.706", "0.742", "0.766", "0.713", "0.456"], ["circAHSA1+CA724", "0.494", "0.717", "0.765", "0.738", "0.791", "0.684", "0.239"], ["circAHSA1+CEA+CA199+CA724", "0.458", "0.764", "0.725", "0.747", "0.776", "0.712", "0.228"]], "row_count": 9, "column_count": 8, "numeric_cells": 60, "header_rows": 1, "locator": "section[19]/table-wrap[2]#tbl0004"}}], "gaps": ["asset:source:pmid:41330006 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:41330006", "asset:table:pmid:41330006:1", "asset:table:pmid:41330006:2", "asset:table:pmid:41330006:3", "asset:table:pmid:41330006:4"], "steps": ["read_published_estimate"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": ["xml"], "capabilities": [], "data_gaps": ["source:pmid:41330006"]}, "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": "25b3b5009f12f9c0fb2f1ab4b9400001ad314662a491ef95981ac16edbf4c3c1", "source_hash": "c324bb09f17c2875efaf9eae71acfc90d758220e4200b35d9cf4507971d34efa", "raw_response_sha256": "sha256:f6b557b49c0d9983ad4e5b58ff2a38d8c454a89c82500961781f50d58d026c9d", "raw_response_chars": 3582}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "full-text-reading-v1", "prompt_hash": "ac6f1f056e4309dd618252e0e2a8c100ce8972210af92811f64d119772201f85", "source_hash": "c324bb09f17c2875efaf9eae71acfc90d758220e4200b35d9cf4507971d34efa", "raw_response_sha256": "sha256:afcb540f73d84b884fdc5e1554667fd10903c5bb21a9e750eb007dffe50d8564", "raw_response_chars": 28483}], "target_providers": [{"provider": "minimax", "model": "MiniMax-M3.1-Flash", "prompt_version": "replication-target-v2", "prompt_hash": "5745042dce66ba1167efd703dfa7a7aa8b285fe6f05ee7e2b981d04b2c2065d0", "source_hash": "c324bb09f17c2875efaf9eae71acfc90d758220e4200b35d9cf4507971d34efa", "raw_response": "{\"parent_value\":0.787,\"unit\":\"AUC\",\"evidence\":\"Serum circAHSA1 effectively discriminated GC from healthy controls (AUC = 0.787) and gastritis patients (AUC = 0.752), outperforming conventional markers, with statistical superiority confirmed by DeLong analysis.\",\"target_result\":\"Serum circAHSA1 discriminated gastric cancer from healthy controls with an AUC of 0.787.\",\"number_stated\":true}", "reading": {"parent_value": 0.787, "unit": "AUC", "evidence": "Serum circAHSA1 effectively discriminated GC from healthy controls (AUC = 0.787) and gastritis patients (AUC = 0.752), outperforming conventional markers, with statistical superiority confirmed by DeLong analysis.", "target_result": "Serum circAHSA1 discriminated gastric cancer from healthy controls with an AUC of 0.787.", "number_stated": true, "source_locator": "chars 1374-1587 of source sha256 c324bb09f17c2875efaf9eae71acfc90d758220e4200b35d9cf4507971d34efa"}, "recorded_at": "2026-10-31T15:15:10.201182+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "02332c74fa29f62066712be9b40c670a9a1078a1c1a983eee908ea59596540eb", "source_hash": "c324bb09f17c2875efaf9eae71acfc90d758220e4200b35d9cf4507971d34efa", "raw_response": "<think>We need answer JSON only. Need identify single numerical result replication registered target headline main finding. Paper source. Need determine likely headline number: combined detection AUC=0.871? \"headline numerical result paper states for registered target\" Registered target vague: headline numerical result for main finding. Main finding title circAHSA1 stable serum biomarker diagnosis/progression. Results include AUC healthy 0.787, gastritis 0.752, combined 0.871. Which single headline number? Need infer likely \"combined detection further improved diagnostic accuracy (AUC = 0.871)\" as headline numerical result. They ask singular numerical result registered target perhaps benchmark task where identify parent_value from paper. Need report headline number only, printed unit. AUC dimensionless, unit maybe \"AUC\" or empty? They explicitly unit must be unit paper prints. Since AUC is metric, could unit be \"AUC\". parent_value 0.871. Evidence exact contiguous quote containing number. \"Combined detection further improved diagnostic accuracy (AUC = 0.871).\" Exact sentence. target_result perhaps concise \"AUC = 0.871\". number_stated true. Need ensure evidence quote perhaps whole clause. JSON valid. Could headline instead AUC 0.787 for serum circAHSA1 discriminating GC from healthy controls. Main finding perhaps circAHSA1 diagnostic performance, and combined panel further improved. Registered target phrasing broad. They likely expect one number likely 0.871 because that's combined model's headline. Let's deeply inspect wording.\n\nPrompt: \"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.\" REGISTERED TARGET: \"the headline numerical result the paper states for its main finding\". They want extract headline numerical result. Source has abstract-like intro and Results. Main finding: circAHSA1 significantly upregulated, serum detects; distinguishes; combination improves; silencing etc. Single headline numerical result perhaps \"Combined detection further improved diagnostic accuracy (AUC = 0.871).\" Since highest and explicit summary. Need not quote abstract because no number there. Evidence exact contiguous quote.\n\nWhat should unit string be? AUC has no physical unit. They might expect unit \"\" and parent_value 0.871. Schema says unit string; \"The unit must be the unit the paper prints.\" Paper prints \"AUC\", arguably unit as metric label. Usually these tasks output {\"parent_value\":..., \"unit\":\"...\", \"evidence\":\"...\", ...}. For AUC, unit could \"AUC\" because metric. But \"unit\" often expect e.g. \"%\", \"mg/L\", etc. Here no unit printed, so empty string likely. Yet target_result states AUC = 0.871. Need interpret \"Report headline number only: value... unit must be unit paper prints.\" They insist number only perhaps parent_value, unit. For dimensionless AUC, unit likely \"AUC\". Could output unit: \"AUC\" as paper prints it. Evidence sentence.\n\nLet's ensure target_result maybe \"Combined detection further improved diagnostic accuracy (AUC = 0.871).\" Or target_result \"AUC = 0.871 for combined detection\". Evidence exact. Number stated true. \"headline number only\" likely target_result should only say \"AUC = 0.871\". Fine.\n\nNeed no markdown, valid JSON. Use escaped unicode? Regular okay. Exact quote can omit period? Exact contiguous quotation. Quote exact entire sentence, including punctuation. Ensure source: \"Combined detection further improved diagnostic accuracy (AUC = 0.871).\" yes.\n\nPotential concern main finding may be AUC=0.787 (circAHSA1 alone). Let's analyze wording hierarchy. Abstract (source intro) says:\n- circAHSA1 significantly upregulated...\n- Serum circAHSA1 distinguishes...\n- Combined ... improves...\n- silencing...\n- correlates...\nNo numerical numbers in abstract. Results:\n\"Serum circAHSA1 effectively discriminated GC from healthy controls (AUC = 0.787) and gastritis patients (AUC = 0.752), outperforming conventional markers, with statistical superiority confirmed by DeLong analysis. Combined detection further improved diagnostic accuracy (AUC = 0.871).\" If asked headline numerical result for main finding, which is headline? The headline may be combined detection AUC 0.871. Usually paper's abstract might report specific AUC perhaps source transformed? The registered target wording perhaps generated generic target, and intended numerical result extraction benchmark has one \"headline\" number. They might consider \"AUC = 0.787\" the key performance of circAHSA1 itself, while 0.871 is combination. Title biomarker circAHSA1, so main finding's headline number could be 0.787 (healthy) or 0.752 (gastritis). But \"headline numerical result the paper states for its main finding\" likely asks select strongest main result from source. Need infer expected target result singular.\n\nLet's parse user's wording carefully: \"Read the 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. 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. Attribution may be carried by the text's own wording: a number may be attached to the target by a parenthetical list, by the word 'respectively', or by words that name the target directly. When that is how the text links them, quote the whole clause so a reader can check the attribution for themselves. If the text states no number for the registered target, set number_stated to false, leave parent_value at 0, leave unit and evidence empty, and say in target_result what the text does state instead. Never invent a source.\"\n\nREGISTERED TARGET: the headline numerical result the paper states for its main finding\n\nThis is meta target, likely they expect model to pick one. \"single numerical result\" perhaps one explicitly designated headline. The source itself likely synthetic abstract and methods. Among results, multiple AUCs. Maybe \"Combined detection further improved diagnostic accuracy (AUC = 0.871)\" is clearly headline/highest. Replication main finding (diagnostic panel) needs reproduce 0.871. Main title finding serum biomarker, though combined panel includes CEA etc.\n\nCould answer 0.871. Let's examine phrase \"headline number only\" often in benchmark prompts where registered target e.g. \"the headline numerical result the paper states for its main finding.\" They expect a key metric in abstract, often AUC. Here source's Results paragraph gives 0.787, 0.752, 0.871. \"headline\" likely last and best performance. \"Combined detection further improved diagnostic accuracy (AUC = 0.871)\" can be headline result. If replication target is main finding (circAHSA1 as stable serum biomarker), perhaps AUC 0.787 in GC vs healthy and 0.752 gastritis are two related values, not single. To meet single number, select combined 0.871 because single metric. This seems intended.\n\nUnit maybe \"AUC\".</think>\n\n{\"parent_value\":0.871,\"unit\":\"AUC\",\"evidence\":\"Combined detection further improved diagnostic accuracy (AUC = 0.871).\",\"target_result\":\"AUC = 0.871\",\"number_stated\":true}", "reading": {"parent_value": 0.871, "unit": "AUC", "evidence": "Combined detection further improved diagnostic accuracy (AUC = 0.871).", "target_result": "AUC = 0.871", "number_stated": true, "source_locator": "chars 1588-1658 of source sha256 c324bb09f17c2875efaf9eae71acfc90d758220e4200b35d9cf4507971d34efa"}, "recorded_at": "2026-10-31T15:15:19.085960+00:00"}], "agreement": false, "disagreements": {"physical_methods": {"minimax": ["qRT-PCR", "ROC curve analysis", "proliferation, apoptosis, migration, and invasion assays", "nuclear–cytoplasmic fractionation"], "minimax_alt": ["qRT-PCR for circAHSA1 (hsa_circ_0032777) measurement in GC tissues, serum, and cell lines"], "decisive": false}, "analysis_methods": {"minimax": ["DeLong test", "Student’s t-test", "one-way analysis of variance (ANOVA)", "chi-square (χ²) test", "Pearson or Spearman correlation methods", "Youden index"], "minimax_alt": ["2−ΔΔCt relative-expression calculation", "Receiver operating characteristic (ROC) curve analysis with area under the curve (AUC)", "DeLong test for ROC curve and AUC comparisons", "Youden index for optimal cut-off selection"], "decisive": false}, "statistical_method": {"minimax": "DeLong test", "minimax_alt": "ROC curve analysis with AUC comparisons performed using the DeLong test", "decisive": true}, "parent_value": {"minimax": 0.787, "minimax_alt": 0.871, "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:d4575ede973a35f6585b52a4a06498b613295dd2dffc3efcd41a3ca7a03360fb", "type": "sep_package", "label": "SEP v1 package for pmid:41330006"}], "activities": [{"id": "activity:conversion:pmid:41330006", "type": "conversion", "used": ["package:d4575ede973a35f6585b52a4a06498b613295dd2dffc3efcd41a3ca7a03360fb"], "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": "pmid:41330006", "parent_hash": "sha256:e02f683c1c1bbb4497323507f22053244c818271d3654af6932fdda2e42e39c2", "fork_of": null, "generation": 2}, "gaps": ["abstract", "asset:source:pmid:41330006 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:41330006' does not resolve to a declared asset", "targets"]}