The effect of sanitary status degradation and dietary tryptophan content on growth rate and tryptophan metabolism in weaning pigs1
Bibliographic record
Abstract
Health degradation modifies Trp metabolism through induction of Trp catabolism. This could limit the amount of Trp available for growth. The aims of the present experiment were to investigate the effects of a low grade inflammation and dietary Trp on growth and Trp metabolism. Eighty weaned pigs were assigned to 4 experimental treatments according to a 2 x 2 factorial arrangement: 2 sanitary statuses x 2 dietary Trp contents. The Trp content was deficient (low-Trp: 2.4 and 1.9 g of Trp/kg of the phase I and phase II diets, respectively) or adequate (high-Trp: 2.9 and 2.4 g of Trp/kg of the phase I and phase II diets, respectively). A low grade inflammatory response was induced by housing pigs in unsanitary environment, whereas control pigs were housed in good sanitary conditions. Pigs were not fed ad libitum to avoid feed refusals. Growth performance was calculated 3, 5, and 7 wk after weaning. Blood was sampled 12, 33, and 47 d after weaning for the determination of plasma concentrations of Trp and related metabolites, kynurenine and pyridoxal-5-phosphate. The interaction between sanitary status and dietary Trp was not statistically significant in all measured criteria. Pigs kept in poor sanitary conditions grew slower (P < 0.001) during the entire experimental period and had greater plasma concentrations of haptoglobin (P < 0.001) than pigs housed in good sanitary conditions. Pigs housed in poor sanitary conditions had also decreased Trp plasma concentrations (P < 0.001), but plasma kynurenine concentrations were not affected. Our results indicated that a moderate inflammatory response was obtained by degrading the sanitary quality of environment. Additionally, poor sanitary conditions modified Trp metabolism, indicating that the amount of Trp available for growth and other metabolic functions might be reduced.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".