The changes in growth performance and lipid metabolism of pigs with yellow fat induced by high dietary fish oil
Bibliographic record
Abstract
The aim of this study was to investigate the alteration in growth performance and lipid metabolism during the development of yellow fat in pigs. A total of 30 pigs (9.23 ± 0.21 kg) were assigned to three treatments: (1) low fish oil (LFO), basal diet + 2% fresh fish oil; (2) high fish oil (HFO), basal diet + 8% fresh fish oil; and (3) oxidized fish oil (OFO), basal diet + 8% OFO (peroxide value = 250 meqO2 kg−1). Pigs fed HFO and OFO diets showed yellow staining of fat and decreased growth performance, including average daily gain, average daily feed intake, and final body weight (P < 0.01). The oxidized lipid markers malondialdehyde, yellowness b* of backfat, perirenal fat, and abdominal fat were markedly increased in the pigs fed with HFO and OFO (P < 0.05). Furthermore, following HFO feeding, pigs showed significant decreases in n-6 polyunsaturated fatty acid, n-6/n-3 polyunsaturated fatty acid ratio and mRNA expression levels of CCAAT-/enhancer-binding protein alpha, fatty acid synthase, lipoprotein lipase, and hormone-sensitive lipase in backfat (P < 0.01). Overall, pigs with yellow-fat trait showed decreased growth performance and altered lipid metabolism by the high fish oil feeding.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".