Cell-autonomous mechanisms of chronological aging in the yeast Saccharomyces cerevisiae
Bibliographic record
Abstract
. Based on our analysis, we propose a concept of a biomolecular network underlying the chronology of cellular aging in yeast. The concept posits that such network progresses through a series of lifespan checkpoints. At each of these checkpoints, the intracellular concentrations of some key intermediates and products of certain metabolic pathways - as well as the rates of coordinated flow of such metabolites within an intricate network of intercompartmental communications - are monitored by some checkpoint-specific "master regulator" proteins. The concept envisions that a synergistic action of these master regulator proteins at certain early-life and late-life checkpoints modulates the rates and efficiencies of progression of such processes as cell metabolism, growth, proliferation, stress resistance, macromolecular homeostasis, survival and death. The concept predicts that, by modulating these vital cellular processes throughout lifespan (i.e., prior to an arrest of cell growth and division, and following such arrest), the checkpoint-specific master regulator proteins orchestrate the development and maintenance of a pro- or anti-aging cellular pattern and, thus, define longevity of chronologically aging yeast.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".