Effects of amino acid intake level in pregnant pigs on plasma metabolome (643.3)
Bibliographic record
Abstract
The objective of this study was to determine commonalities and differences in the metabolome in non‐pregnant pigs and in early (EG), late (LG) and entire pregnancy during the study of amino acid (AA) requirements. Each pig was fed 6 levels of test AA at maintenance and in both EG and LG. The metabolome of 331 plasma samples from 19 sows in their 2nd to 4th parity was analyzed by nuclear magnetic resonance, gas chromatography‐mass spectroscopy (MS) and direct injection MS. Data were evaluated using partial least square‐discriminant analysis (PLS‐DA) in www.metaboanalyst.ca . Across AA tested, AA limitation affected (P<0.05) the metabolome at maintenance and in EG but not in LG. The AA level, across AA tested, was only significant in EG (P=0.01). For AA level, only urea was an important feature in maintenance, EG and LG. There were no common metabolites for AA limitation. The AA tested (Thr, Ile, Lys, Trp) affected (P<0.001) the metabolome at maintenance and in the entire pregnancy, EG and LG. Within AA tested, no significant results were found for Ile and Trp because of fewer observations (<40). The stage of pregnancy affected (P<0.05) the metabolome when studying Thr or Lys. In EG and LG, threonine and aminoadipate were the only common features for Thr and Lys, respectively. For Lys, AA limitation affected (P=0.036) the metabolome in EG but not in LG. For Thr, AA level affected (P=0.029) the metabolome in LG but not in EG. In this study, PLS‐DA could not identify common key metabolites for different AA and status of pregnancy. Metabolomics to determine key metabolites for the effect of AA intake needs to be applied within AA tested and within stage of pregnancy in pigs. Grant Funding Source : Alberta Livestock and Meat Agency
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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) | 0.000 | 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 | 0.000 |
| 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".