Dried Yeast: Impact of Dehydration and Rehydration on Brewing Yeast DNA Integrity
Bibliographic record
Abstract
As a consequence of fluidized bed drying, yeast cells may be exposed to a series of physiological stresses, of which the most evident is water loss. Desiccation can lead to cell wall crenellation, cytoplasmic crowding, loss of DNA supercoiling, membrane disruption, phase transitions, and ultimately cell death. Although the dehydrated phenotype has been well characterized, the sequence of events that causes damage to the cell has not been widely reported. Here we investigate the impact of dehydration and rehydration on the stability of the brewing yeast genome, including both the chromosomal and mitochondrial DNA (mtDNA). Analysis of rehydrated and control yeast populations for chromosome length polymorphisms (karyotyping), DNA sequence changes (PCR analysis of interdelta sequences), gross mitochondrial damage (presence of respiratory deficient mutants), and mitochondrial sequence changes (mtDNA RFLP [restriction fragment length polymorphisms]) indicated that the genetic constitution of dried yeast is not affected by the drying process. Active dried yeast (ADY) populations also demonstrated an enhanced tolerance to mutagen challenge (targeted at mtDNA), suggesting that the susceptibility of mtDNA to change is not associated with fluidized bed drying. These results demonstrate that the genetic stability of ADY is comparable to control populations.
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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".