Effects of Patulin Stress on the Physiology, Fermentation Performance, and Aroma Profile of <i>Saccharomyces cerevisiae</i> During Fermentation
Bibliographic record
Abstract
Patulin (PAT) is a mycotoxin commonly found in apples and their derived products, posing a significant threat to human health. Saccharomyces cerevisiae CICC 31084 exhibited excellent ability in removing PAT during fermentation. However, limited studies have addressed the physiological and fermentation-related responses of S. cerevisiae under PAT stress. This study investigated the effect of different concentrations of PAT on S. cerevisiae in simulated apple juice. The results revealed that the PAT removal process affected the growth and metabolism of S. cerevisiae. PAT stress increased the thickness and altered the structure of yeast cell walls while upregulating the expression of genes associated with cell wall biosynthesis. Furthermore, oxidative stress induced by PAT triggered elevated glutathione levels, catalase activity, and ATPase activity, suggesting a robust adaptive response. A total of 1 µg/mL PAT accelerated the changes of fermentation parameters, whereas 10 µg/mL impaired yeast performance. GC-MS analysis revealed that PAT influenced the content of key aroma compounds in the simulated juices. PAT concentration was positively correlated with the production of octanoic acid and ethyl octanoate and negatively correlated with the formation of phenylethyl alcohol, hexanoic acid, and esters. The results could provide a theoretical basis for the application of PAT detoxification by S. cerevisiae in cider, and the identified aroma compounds could serve as potential markers for PAT contamination.
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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".