{"data":{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41114291", "kind": "science-record", "revision": 3, "content_hash": "sha256:f12843f7005217a61ade6ba254621768cc5b1b0f6b1cb8e23cc2fa7a947495a9", "created_at": "2026-11-01T20:31:10Z", "updated_at": "2026-11-01T22:14:51Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "SWATH-MS proteomics data on differentially abundant proteins between normal and dark-cutting beef.", "doi": "10.1016/j.dib.2025.112099", "pmid": "41114291", "authors": ["Laura González-Blanco", "Mamen Oliván", "Yolanda Diñeiro", "Susana B Bravo", "Verónica Sierra", "Mohammed Gagaoua"], "journal": "Data in brief", "year": 2025, "abstract": "Dark, firm, and dry (DFD) beef, also known as dark-cutting beef, lead to economic losses, food waste, and potential consumer rejection due to its very dark color at the point of sale. This condition is associated with a high ultimate pH, a limited blooming capacity, a redder cooked color that appears undercooked, and increased spoilage rates. Although several pre-slaughter factors have been linked to high ultimate pH, the mechanisms underlying DFD beef remain complex, multifactorial and not yet fully understood [1]. Proteomic approaches on post-mortem muscles have increasingly been employed to unravel the molecular mechanisms and biological pathways underlying this quality defect and to identify candidate protein biomarkers for its early prediction or better characterization using explanatory models. In this study, SWATH-MS proteomics, a data-independent acquisition strategy, was applied for the first time for an in-depth characterization and quantification of post-mortem muscle proteomes. The analysis was conducted using the most extensive dataset available to date on this quality defect conditions, which included 26 DFD beef samples (pH24 ≥ 6.2) and 26 CONTROL samples (5.4 ≤ pH24 ≤ 5.6). Muscle samples from the Longissimus thoracis et lumborum of Asturiana de los Valles yearling bulls were collected at 24 h post-mortem to investigate protein expression differences associated with DFD beef condition. A total of 735 proteins were quantified, among which 35 exhibited a significant difference in their abundances between the DFD condition and CONTROL samples, suggesting their potential as putative biomarkers for DFD beef. The data provided in this article can facilitate further research into beef quality defects and are available for reuse and/or reprocess and/or integration to support the development of early prediction tools for DFD beef. These data could further contribute to previous integrative studies [1], in the frame of integromics. Those approaches aimed combining multiple public proteomics datasets and DFD proteomics studies in a unique repository with the ultimate objective of refining the selection of dark-cutting beef biomarkers and deepen our understanding on the underlying biological mechanisms, hence revealing novel patterns inaccessible from individual datasets [1]. A more detailed analysis of this dataset is available in the study published by González-Blanco et al. [2]. The mass spectrometry (MS) proteomics data generated using a sequential window acquisition of all theoretical mass spectra (SWATH-MS) have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository [3] with the dataset identifier PXD059876.", "claims": [{"id": "claim-method", "statement": "Differences in protein abundance were further assessed using an unpaired, two-tailed Student’s t-test implemented in MetaboAnalyst 6.0.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41114291", "locator": "sections[4] \"Data Description\" paragraph 2", "quote": "Differences in protein abundance were further assessed using an unpaired, two-tailed Student’s t-test implemented in MetaboAnalyst 6.0."}], "state": "complete"}, {"id": "claim-data-access", "statement": "PRIDE/ProteomeXchange repositorySequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) as an emerging proteomics approach for the discovery of dark-cutting beef biomarkers (Original data).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41114291", "locator": "sections[14] \"Data Availability\" paragraph 2", "quote": "PRIDE/ProteomeXchange repositorySequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) as an emerging proteomics approach for the discovery of dark-cutting beef biomarkers (Original data)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A total of 735 proteins were quantified, among which 35 exhibited a significant difference in their abundances between the DFD condition and CONTROL samples, suggesting their potential as putative biomarkers for DFD beef.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41114291", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "A total of 735 proteins were quantified, among which 35 exhibited a significant difference in their abundances between the DFD condition and CONTROL samples, suggesting their potential as putative biomarkers for DFD beef."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "A total of 735 proteins were quantified, among which 35 exhibited a significant difference in their abundances between the DFD condition and CONTROL samples, suggesting their potential as putative biomarkers for DFD beef.", "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:41114291"], "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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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. 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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. 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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. 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