272 The Effect of Increasing Standardized Ileal Digestible Methionine Intake on Whole-Body Nitrogen Retention and Plasma Amino Acids, Homocysteine, and Glutathione of Gilts in Late Gestation
Bibliographic record
Abstract
Abstract Gestating gilts (n = 70; 166 ± 13 kg initial body weight at d 31 of gestation) were used to determine the dietary standardized ileal digestible (SID) Methionine (Met) content required to optimize whole-body nitrogen (N) retention versus the appearance of biomolecules derived via Met metabolism. On d 102 of gestation, gilts were randomly assigned to one of seven dietary treatments that provided between 50 and 150% of estimated SID Met requirements for late gestation gilts (0.10 to 0.30% SID Met). All other indispensable amino acids were supplied at least 20% above estimated requirements (NRC, 2012). A N balance (total urine collection and fecal grab sampling) was conducted for each gilt between days 109 and 112 of gestation, blood samples were collected on day 109 after a 24-h fasting period for analyses of plasma amino acids, homocysteine (Hcys), and reduced glutathione (GSH). Contrast statements were used to determine linear and quadratic effects of dietary SID Met levels. Linear and quadratic broken-line and polynomial quadratic models were used to determine the optimum level of SID Met for whole-body N retention and plasma concentrations of Hcys and GSH. Whole-body N retention increased with increasing dietary Met (linear and quadratic; P < 0.001; Table 1). Plasma concentrations of Hcys increased with increasing dietary Met (linear; P < 0.05). Glutathione tended to decrease and then increase at dietary SID Met greater than 0.20% (quadratic; P = 0.061; Table 2). Plasma glutamine increased with increasing dietary SID Met (linear; P < 0.01). Histidine increased then decreased at dietary SID Met greater than 0.20% (quadratic; P < 0.05), other amino acids were not influenced by dietary treatment. Linear and quadratic broken-line models described a lower breaking point for whole-body N retention, plasma Hcys, and plasma GSH compared with the quadratic polynomial model (0.154% and 0.155% vs. 0.226%, 0.185% and 0.188% vs. 0.328%, and 0.114% and 0.124% vs. 0.224% SID Met, respectively). The Bayesian information criterion (BIC) indicated that the quadratic polynomial model best fit the data versus the linear and quadratic broken-line models for plasma GSH (BIC 317.9 vs. 320.3 and 322.6, respectively; Graphic 1). However, the fits were similar among models for whole-body N retention (BIC 385.2 vs. 384.6 and 386.9, respectively; Graphic 2) and Hcys (BIC 465.5 vs. 465.6 and 467.9, respectively; Graphic 3). Based on the best fit (quadratic polynomial) model 0.226% SID Met is required to optimize whole-body N retention for late gestation gilts which is greater than that recommended by the NRC (2012; 0.20% SID Met). It appears that gilts have further capacity for Met transmethylation since the plasma Hcys breakpoint occurred at a greater dietary SID Met level than for whole-body N retention, though the impact on transsulfuration and remethylation pathways cannot be discounted. Therefore, greater feeding levels of SID Met might be required to maximize both protein and non-protein utilization of Met.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".