Changes in carcass traits, meat quality, muscle fiber characteristics, and liver function of finishing pigs fed high level of fish oil
Bibliographic record
Abstract
The study was aimed to investigate the changes in carcass traits, meat quality, muscle fiber characteristics, and liver function in pigs fed with high levels of fresh fish oil and oxidized fish oil. About 30 piglets were randomly assigned to receive basal diet plus 2% fish oil (LFO), basal diet plus 8% fish oil (HFO), or basal diet plus 8% oxidized fish oil (OFO) for 120 d. Pigs of the HFO and OFO group showed reduced carcass weight, dressing percentage, loin eye area, and increased yellowness of the longissimus dorsi muscle compared with LFO group (P < 0.05). Dietary HFO and OFO suppressed the relative expression levels of myosin heavy chain (MyHC) isoform (I and II a), glutathione peroxidase 4, and NAD(P)H: quinone oxidoreductase-1 and mitochondrial biogenesis in longissimus dorsi muscle (P < 0.05). Dietary HFO or OFO increased the serum aspartates aminotransferase, alanine aminotransferase, total bilirubin, direct bilirubin, oxidized low-density lipoprotein, liver index, and concentration of malondialdehyde (MDA) in liver (P < 0.05). In conclusion, high levels of fresh fish oil and oxidized fish oil have adverse effects on carcass traits, muscle fiber characteristics, and liver function, which may be partly due to the mitochondrial dysfunction and impaired antioxidative capacity.
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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 | 0.001 |
| 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".