451 Late-Breaking: Saccharomyces cerevisiae boulardii stimulates immunoglobulin A production in the gut of neonate dairy calves
Bibliographic record
Abstract
Abstract Calves are born with a naïve immune system at birth and undergo rapid changes in terms of immunity. This study focused on evaluating the effect of S. boulardii CNCMI-1079 (SCB) supplementation from birth on immunoglobulin A (IgA) production in the gut of neonate dairy calves. Holstein bull calves (n = 20) were delivered naturally and immediately removed from the dam, and housed in individual straw-bedded pens with a random assignment to a treated group (supplementation with SCB: 10 × 109 CFU/d in each morning meal) or a control group (no supplementation). All the calves received two first meals of a standardized colostrum at 2 h and 12 h after birth followed by two meals per day of milk replacer (7.5% of birth BW; 260 g/kg CP; 160 g/kg crude fat, at 150g/L). Calves were euthanized at 7 d of age and samples from jejunum, ileum and colon were collected. The concentration of IgA and the gene expressions of polymeric Ig receptor (pIgR) and a receptor of plasma B cells (CD79α) were compared between the two groups and among the locations. The expression of CD79α was up-regulated in the ileum compared to jejunum and colon tissues (P < 0.01), whereas pIgR down-regulated in the ileum compared to jejunum and colon (P < 0.01). The supplementation of SCB increased the IgA concentration in the ileum and colon of treated calves compared to the control calves (respectively 1.98 ± 0.09 vs 1.18 ± 0.15 mg/g DM of ileum content, and 1.45 ± 0.14 vs 0.59 ± 0.06 mg/g DM of colon content, P < 0.001). The results suggest that one of the mechanisms by which SCB exerts an immunoprotective effect in the gut is by stimulation of IgA’s secretion which may play a major role in mucosal protection in neonatal calves.
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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".