Comparative Proteome Analysis of Porcine Longissimus dorsi on the Basis of pH24 of Post-mortem Muscle
Bibliographic record
Abstract
To identify proteins contributing to meat quality, a comparative shotgun proteomic profiling of Berkshire longissimus dorsi muscles was conducted in high pH group (HpHG) and low pH group (LpHG) based on 24 hour post-mortem pH. Triplicate liquid chromatography–tandem mass spectrometry analysis identified a total of 208 and 204 proteins in the HpHG and LpHG, respectively. A total of 128 proteins were classified on the basis of molecular function, cellular components, and biological process by gene ontology analysis, of which 13 and 21 proteins were exclusively found in the HpHG and LpHG, respectively. A total of 15 proteins, of which 6 proteins belonged to the LpHG and 2 to the HpHG, were assigned to the Sus scrofa genomic database. The dominant expressions of Igc, Prep, Ldhb, and Aco2 were identified in the LpHG by shotgun proteomic analysis, and confirmed by reverse transcriptase–mediated polymerase chain reaction analysis. These protein markers are suitable for determining meat quality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".