Associations of the expression levels of genes involved in <i>CFL2b</i> and <i>MyHC</i> isoform type changes in longissimus dorsi muscle of HeBao and Large White pigs (<i>Sus scrofa</i>) during postnatal growth
Bibliographic record
Abstract
This study aimed to compare the patterns of postnatal transformation of myosin heavy chain (MyHC) isoform types in the longissimus dorsi (LD) muscle between HeBao (HB) and Large White (LW) pigs, and assess the association of porcine cofilin2b (CFL2b) mRNA abundance with changes of myofiber type composition. The four MyHC isoforms (MyHC-1, -2a, -2b, and -2x) of the LD muscle were assessed for mRNA levels in 28 HB and 28 LW pigs by reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The associations of CFL2b mRNA expression and myofiber type (MyHC-1, -2a, -2b, and -2x) changes were analyzed by RT-qPCR. Although the mRNA expression patterns of MyHCs were different between the two breeds, they had similar expression levels. During postnatal growth, relative CFL2b abundance was gradually increased, with dramatic changes observed after 90 d between the two breeds (P < 0.01). Further analysis revealed significant positive correlations of CFL2b gene expression with MyHC-1/slow (HB: r = 0.871), MyHC-2b [LW: r = 0.881 (P < 0.01)], and MyHC-2x (HB: r = 0.795, LW: r = 0.814), and a significant negative correlation with MyHC-1/slow [r = −0.938 (P < 0.01)] in LW. No significant associations of CFL2b expression with MyHC-2a (HB: r = −0. 195, r = −0.697) and MyHC-2b (HB: r = 0.493) were found. Our findings suggested that HB pigs had different muscle development mechanisms in the LD muscle compared with LW, and the CFL2b expression difference could affect the levels of myofiber types which could account for meat quality differences. HB pigs possessed less glycolytic, with more oxidative metabolism and better meat quality traits compared with LW pigs at different growth stages.
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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 | 0.000 | 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".