Protein turnover in pregnant pigs when feeding limiting amounts of amino acids
Bibliographic record
Abstract
Experiments to determine the amino acid (AA) requirements of pigs for threonine, lysine, tryptophan and isoleucine in early and late pregnancy were evaluated to determine which factors caused changes in protein turnover during pregnancy in pigs when the test AA intake was below requirements. In all experiments, each of 6 to 7 sows received 6 diets with graded levels of test AA in both early and late gestation. Protein turnover was determined based on the 13C enrichment in expired CO2 and plasma free phenylalanine (Phe) after oral L[1–13C]Phe dosing using a stochastic model. The observations (max n=188) were evaluated using mixed models (SAS). The final models were correlated to the data with r2 = 0.82 (protein synthesis, S) to r2 = 0.92 (Phe oxidation, Ox, g/d). Increasing AA intake decreased Ox (P=0.001) and increased Phe retention (RPhe, P=0.001) but did not affect S, breakdown (B) or Phe flux. Increasing BW and gestational age decreased Phe flux and Ox, S and B (P<0.02) and increased RPhe (P=0.001). In parity 3, values for Phe kinetics were greatest (P < 0.05), except for RPhe, which decreased linearly (P = 0.001) with sow age. Increasing litter size increased B (P=0.001) but did not affect other Phe kinetic parameters. Phe kinetics in pregnant pigs given limiting AA intakes were more affected by physical attributes, i.e. sow age (parity), BW, weight gain and gestational age than dietary attributes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".