Towards amino acid recommendations for specific physiological and patho-physiological states in pigs
Bibliographic record
Abstract
The objective of this review is to provide an overview of the implication of amino acids (AA) in important physiological functions. This is done in the context of pig production where the competition for AA utilisation is exacerbated by constraints to maximise productive responses and the necessity to reduce dietary protein input for environmental, economic and sanitary issues. Therefore, there is an opportunity to refine the nutritional recommendations by exploring the physiological roles of AA. For example, methionine and cysteine, either in selenised or sulfur forms, are directly involved in the regulation of the glutathione antioxidative system. In sows, glutathione antioxidative system may contribute to improving ovulation conditions through control of oxidative pressure. Supplementation of sow diets with l-arginine, a precursor of NO and polyamines, may stimulate placental growth, promoting conceptus survival, growth and tissue development. The beneficial effect of arginine supplementation has been also suggested to improve lactation performance. Feed intake is usually the first response that is impacted by an inadequate AA supply. Valine and tryptophan imbalances may act as signals for decreasing feed intake. AA are also important nutrients for maintaining the animal's defence systems. Threonine, one of the main constituents of mucin protein, is important for gut development during the postnatal period. It may exert a protective effect that reduces the impact of weaning on gut morphology and associated disturbances. Finally, tryptophan is involved in the regulation of the defence system through its action as a precursor of antioxidants and its effect on the inflammatory response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".