Comparative Assessment of Different Yeast Cell Wall-Based Mycotoxin Adsorbents Using a Model- and Bioassay-Based In Vitro Approach
Bibliographic record
Abstract
Frequently reported occurrences of deoxynivalenol (DON), beauvericin (BEA), and, to a lesser extent, ochratoxin A (OTA) and citrinin (CIT) in ruminant feed or feedstuff could represent a significant concern regarding feed safety, animal health, and productivity. Inclusion of yeast cell wall-based mycotoxin adsorbents in animal feeds has been a common strategy to mitigate adverse effects of mycotoxins. In the present study, an in vitro approach combining adsorption isotherm models and bioassays was designed to assess the efficacy of yeast cell wall (YCW), yeast cell wall extract (YCWE), and a postbiotic yeast cell wall-based blend (PYCW) products at the inclusion rate of 0.5% (w/v) (ratio of adsorbent mass to buffer solution volume). The Hill’s adsorption isotherm model was found to best describe the adsorption processes of DON, BEA, and CIT. Calculated binding potential for YCW and YCWE using the Hill’s model exhibited the same ranking for mycotoxin adsorption, indicating that BEA had the highest adsorption rate, followed by DON and CIT, which was the least adsorbed. PYCW had the highest binding potential for BEA compared with YCW and YCWE. In contrast, the Freundlich isotherm model presented a good fit for OTA adsorption by all adsorbents and CIT adsorption by PYCW. Results indicated that YCW was the most efficacious for sequestering OTA, whereas YCWE was the least efficacious. PYCW showed greater efficacy at adsorbing OTA than CIT. All adsorbents exhibited high adsorption efficacy for BEA, with an overall percentage average of bound mycotoxin exceeding 60%, whereas moderate efficacies for the other mycotoxins were observed (up to 37%). Differences in adsorbent efficacy of each adsorbent significantly varied according to experimental concentrations tested for each given mycotoxin (p < 0.05). The cell viability results from the bioassay using a bovine mammary epithelial cell line (MAC-T) indicated that all tested adsorbents could potentially mitigate mycotoxin-related damage to bovine mammary epithelium. Results from our studies suggested that all tested adsorbents had the capacity to adsorb selected mycotoxins in vitro, which could support their use to mitigate their effects in vivo.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".