In vitro bioassessment of the immunomodulatory activity of Saccharomyces cerevisiae components using bovine macrophages and Mycobacterium avium ssp. paratuberculosis
Bibliographic record
Abstract
The yeast Saccharomyces cerevisiae and its components are used for the prevention and treatment of enteric disease in different species; therefore, they may also be useful for preventing Johne's disease, a chronic inflammatory bowel disease of ruminants caused by Mycobacterium avium ssp. paratuberculosis (MAP). The objective of this study was to identify potential immunomodulatory S. cerevisiae components using a bovine macrophage cell line (BOMAC). The BOMAC phagocytic activity, reactive oxygen species production, and immune-related gene (IL6, IL10, IL12p40, IL13, IL23), transforming growth factor β, ARG1, CASP1, and inducible nitric oxide synthase expression were investigated when BOMAC were cocultured with cell wall components from 4 different strains (A, B, C, and D) and 2 forms of dead yeast from strain A. The BOMAC phagocytosis of mCherry-labeled MAP was concentration-dependently attenuated when BOMAC were cocultured with yeast components for 6 h. Each yeast derivative also induced a concentration-dependent increase in BOMAC reactive oxygen species production after a 6-h exposure. In addition, BOMAC mRNA expression of the immune-related genes was investigated after 6 and 24 h of exposure to yeast components. All yeast components were found to regulate the immunomodulatory genes of BOMAC; however, the response varied among components and over time. The in vitro bioassessment studies reported here suggest that dead yeast and its cell wall components may be useful for modulating macrophage function before or during MAP infection.
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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) | 0.000 | 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 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".