Influence of Medium Buffering Capacity on Inhibition of<i>Saccharomyces cerevisiae</i>Growth by Acetic and Lactic Acids
Bibliographic record
Abstract
Acetic acid (167 mM) and lactic acid (548 mM) completely inhibited growth of Saccharomyces cerevisiae both in minimal medium and in media which contained supplements, such as yeast extract, corn steep powder, or a mixture of amino acids. However, the yeast grew when the pH of the medium containing acetic acid or lactic acid was adjusted to 4.5, even though the medium still contained the undissociated form of either acid at a concentration of 102 mM. The results indicated that the buffer pair formed when the pH was adjusted to 4.5 stabilized the pH of the medium by sequestering protons and by lessening the negative impact of the pH drop on yeast growth, and it also decreased the difference between the extracellular and intracellular pH values (Delta(pH)), the driving force for the intracellular accumulation of acid. Increasing the undissociated acetic acid concentration at pH 4.5 to 163 mM by raising the concentration of the total acid to 267 mM did not increase inhibition. It is suggested that this may be the direct result of decreased acidification of the cytosol because of the intracellular buffering by the buffer pair formed from the acid already accumulated. At a concentration of 102 mM undissociated acetic acid, the yeast grew to higher cell density at pH 3.0 than at pH 4.5, suggesting that it is the total concentration of acetic acid (104 mM at pH 3.0 and 167 mM at pH 4.5) that determines the extent of growth inhibition, not the concentration of undissociated acid alone.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".