A live yeast supplementation to gestating ewes improves bioactive molecule composition in colostrum with no impact on its bacterial composition and beneficially affects immune status of the offspring
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Bibliographic record
Abstract
Abstract Colostrum quality is of paramount importance in the management of optimal ruminant growth and infectious disease prevention in early life. Live yeast supplementation effect during the last month of gestation was evaluated on ewes’ colostrum composition. Two groups of ewes ( n = 14) carrying twin lambs were constituted and twins were separated into groups (mothered or artificially fed) 12 h after birth. Nutrient, oligosaccharides (OS), IgG and lactoferrin concentrations were measured over 72 h after lambing, and bacterial community was described in colostrum collected at parturition (T0). Immune passive transfer was evaluated through IgG measurement in lamb serum. In both groups, colostral nutrient, OS concentrations and IgG concentrations in colostrum and lamb serum decreased over time ( P < 0⋅01), except for lactose, which slightly increased ( P < 0⋅001), and lactoferrin, which remained stable. Bacterial population was stable over time with high relative abundances of Aerococcaceae, Corynebacteriaceae, Moraxellaceae and Staphylococcaceae in T0 colostrum. No effect of supplementation was observed in nutrient and lactoferrin concentrations. In supplemented ewes, the level of colostral IgG was higher at T0 and a higher level of serum IgG was observed in lambs born from supplemented mothers and artificially fed, while no effect of supplementation was observed in the mothered lamb groups. Using a metabolomic approach, we showed that supplementation affected OS composition with significantly higher levels of colostral Neu-5Gc compounds up to 5 h after birth. No effect of supplementation was observed on bacterial composition. Our data suggest that live yeast supplementation offsets the negative impact of early separation and incomplete colostrum feeding in neonate lambs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it