Ultrastructural changes of<i>Saccharomyces cerevisiae</i>in response to ethanol stress
Bibliographic record
Abstract
In the fermentative process using Saccharomyces cerevisiae to produce bioethanol, the performance of cells is often compromised by the accumulation of ethanol. However, the mechanism of how S. cerevisiae responds against ethanol stress remains elusive. In the current study, S. cerevisiae cells were cultured in YPD (yeast extract - peptone - dextrose) medium containing various concentrations of ethanol (0%, 2.5%, 5%, 7.5%, 10%, and 15% (v/v)). Compared with the control group without ethanol, the mean cell volume of S. cerevisiae decreased significantly in the presence of 7.5% and 10% ethanol after incubation for 16 h (P < 0.05), and in the presence of 15% ethanol at all 3 sampling time points (1, 8, and 16 h) (P < 0.05). The exposure of S. cerevisiae cells to ethanol also led to an increase in malonyldialdehyde content (P < 0.05) and a decrease in sulfhydryl group content (P < 0.05). Moreover, the observations through transmission electron microscopy enabled us to relate ultrastructural changes elicited by ethanol with the cellular stress physiology. Under ethanol stress, the integrity of the cell membrane was compromised. The swelling or distortion of mitochondria together with the occurrence of a single and large vacuole was correlated with the addition of ethanol. These results suggested that the cell membrane is one of the targets of ethanol, and the degeneration of mitochondria promoted the accumulation of intracellular reactive oxygen species.
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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".