Effects of a Saccharomyces cerevisiae-Derived Postbiotic in Adult Labrador Retrievers Undergoing Exercise and Transport Stress
Bibliographic record
Abstract
Postbiotics are emerging as potential functional ingredients for companion animal diets. This study aimed to determine if a Saccharomyces cerevisiae-based postbiotic can alter cytokine and stress responses to exercise and transport stress in adult Labrador Retrievers. Dogs received 15 g ground corn germ (Control, n = 12), 7.5 g postbiotic (Low, n = 12), or 15 g postbiotic (High, n = 12), daily for 63 days. Exercise was twice weekly for 7 weeks, and a single transport per dog occurred in week 8. Fecal inflammatory biomarkers, serum chemistries, and complete blood counts were assessed at the beginning and end of the study. Serum cytokines were quantified before and 18–20 h after the first and last exercise runs. Gait analysis was assessed before and 24 h after the first and final runs. Saliva cortisol was measured before and after transportation. Treatment did not affect blood chemistries, gait, fecal biomarkers, or saliva cortisol (p ≥ 0.19). Eosinophils increased slightly in Controls (p = 0.01), though remained below 0.80 × 109 cells/L. Most cytokines were unaffected by treatment (p ≥ 0.15), but there were minor changes in circulating monocyte chemoattractant protein-1 (p = 0.01) and IL-8 over time at the initial run (p = 0.03) and IL-10 in males (p = 0.02) in the Low dose dogs. The High dose decreased Blautia (p = 0.04) slightly and tended to decrease Fusobacterium abundances (p = 0.07). The Low dose tended to increase Clostridium hiranonis (p = 0.07) slightly. The tested S. cerevisiae postbiotic produced small changes in immune function and gut microbial species in dogs.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".