Growth performance and expression of genes encoding enzymes involved in methionine and cysteine metabolism in piglets fed increasing sulphur amino acid to lysine ratio during enterotoxigenic <i>Escherichia coli</i> challenge
Bibliographic record
Abstract
A study was conducted to examine the effect of standardised ileal digestible (SID) sulphur amino acids/lysine ratio (SAA/Lys) on performance and expression of methionine adenosyltransferase 1 and 2 alpha (MAT1α and MAT2α), and cystathionine gamma-lyase (CTH) in piglets challenged with an enterotoxigenic Escherichia coli (ETEC). Thirty five [Duroc × (Yorkshire × Landrace)] piglets (6.9 ± 0.5 kg) were randomly assigned to five dietary treatments. The diets were antibiotic free with SID SAA/Lys of 48%, 54%, 60%, 66%, and 72%. Pigs were orally challenged with 6 and 15 mL of ciprofloxacin-resistant ETEC K88+ on days 7 and 10. Blood samples were collected before (BC) and 6, 24, and 48 h after challenge (AC). Body weight gain and feed intake were collected on days 0, 6, and 12 to determine average daily gain (ADG). Gain to feed ratio (G/F) was calculated by dividing ADG by average daily feed intake (ADFI). On day 13, all pigs were euthanized to collect liver and ileal samples to analyse gene expression using real-time polymerase chain reaction. Pigs fed the diet containing SAA/Lys of 66% had the highest ADG, ADFI, and G/F BC. However, ADG, ADFI, and G/F were similar across all ratios AC. Serum tumor necrosis factor alpha concentration at 6 h AC was higher (P < 0.05) than BC and was improved with increasing SAA/Lys. Increasing SAA/Lys quadratically increased (P < 0.01) CTH and MAT1α expression. Ileal expression of CTH and MAT2α were quadratically increased (P < 0.05) with increasing SAA/Lys. In conclusion, SAA/Lys of 60% is suggested to be optimum for piglets to tolerate ETEC pathogenic challenge.
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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) | 0.001 | 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 | 0.001 | 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".