Protein turnover in pregnant pigs at amino acid intake in excess of requirements
Bibliographic record
Abstract
Ten experiments to determine amino acid (AA) requirements of pigs in early and late pregnancy were evaluated to determine which factors affected protein turnover when the test AA intake was above requirements. In all experiments, each of 6 to 7 sows were fed 6 diets with graded levels of test AA in both early and late gestation. Protein turnover was determined based on 13C enrichment after oral L[1–13C]phenylalanine (Phe) dosing using a stochastic model. The observations (max n=200) were evaluated using mixed models (SAS). The final models fit the data with r2 = 0.79 (protein synthesis, S) to r2 = 0.87 (Phe oxidation, Ox, g/d). Greater AA and Phe intake increased (P < 0.05) S, breakdown (B) and Phe flux. Ox and B decreased as pregnancy progressed (P < 0.02), while S, flux and Phe retention (RPhe) increased (P<0.08). Interactions (P<0.02) between AA intake, Phe intake and gestational age increased S, flux and RPhe, indicating a need for more AA towards term. Greater metabolizable energy (ME) intake increased flux (P = 0.003) but decreased B (P = 0.001) in interaction with AA intake (P < 0.02). Thus, pregnant sows can use more AA at higher ME intake. Ox was greatest (P = 0.001) in the 3rd parity but was reduced (P < 0.03) by interactions with increasing BW, ME intake and gestational age. Thus, Phe kinetics may change from adolescent to adult sows. More AA and ME than stated in requirements may be needed close to term when sows carry large litters.
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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) | 0.000 | 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".