A Toolbox for Rapid Quantitative Assessment of Chronological Lifespan and Survival in <i>Saccharomyces cerevisiae</i>
Why this work is in the frame
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Bibliographic record
Abstract
Saccharomyces cerevisiae is a well-established model organism to study the mechanisms of longevity. One of the two aging paradigms studied in yeast is termed chronological lifespan (CLS). CLS is defined by the amount of time non-dividing yeast cells can survive at stationary phase. Here, we propose new approaches that allow rapid and efficient quantification of survival rates in aging yeast cultures using either a fluorescent cell counter or microplate imaging. We have generated a software called analysr (Analytical Algorithm for Yeast Survival Rates) that allows automated and highly reproducible analysis of cell survival in aging yeast cultures using fluorescent data. To demonstrate the efficiency of our new experimental tools, we tested the previously characterized ability of caloric restriction to extend lifespan. Interestingly, we found that this process is independent of the expression of three central yeast heat shock proteins (Hsp26, Hsp42, Hsp104). Finally, our new assay is easily adaptable to other types of toxicity studies. Here, we assessed the toxicity of various concentrations of acetic acid, a known contributor of yeast chronological aging. These assays provide researchers with cost-effective, low- and high-content assays that can serve as an efficient complement to the time-consuming colony forming unit assay usually used in CLS studies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it