Intracellular pH homeostasis during cell-cycle progression and growth state transition in<i>Schizosaccharomyces pombe</i>
Bibliographic record
Abstract
Accurate measurement of intracellular pH in unperturbed cells is fraught with difficulty. Nevertheless, using a variety of methods, intracellular pH oscillations have been reported to play a regulatory role in the control of the cell cycle in several eukaryotic systems. Here, we examine pH homeostasis in Schizosaccharomyces pombe using a non-perturbing ratiometric pH sensitive GFP reporter. This method allows for accurate intracellular pH measurements in living, entirely undisturbed, logarithmically growing cells. In addition, the use of a flow cell allows internal pH to be monitored in real time during nutritional, or growth state transition. We can find no evidence for cell-cycle-related changes in intracellular pH. By contrast, all data are consistent with a very tight homeostatic regulation of intracellular pH near 7.3 at all points in the cell cycle. Interestingly, pH set point changes are associated with growth state. Spores, as well as vegetative cells starved of either nitrogen, or a carbon source, show a marked reduction in their internal pH compared with logarithmically growing vegetative cells. However, in both cases, homeostatic regulation is maintained.
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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 | 0.001 | 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".