Sch9S6K controls DNA repair and DNA damage response efficiency in aging cells
Bibliographic record
Abstract
Survival from UV-induced DNA lesions relies on nucleotide excision repair (NER) and the Mec1 ATR DNA damage response (DDR). We study DDR and NER in aging cells and find that old cells struggle to repair DNA and activate Mec1 ATR . We employ pharmacological and genetic approaches to rescue DDR and NER during aging. Conditions activating Snf1 AMPK rescue DDR functionality, but not NER, while inhibition of the TORC1-Sch9 S6K axis restores NER and enhances DDR by tuning PP2A activity, specifically in aging cells. Age-related repair deficiency depends on Snf1 AMPK -mediated phosphorylation of Sch9 S6K on Ser160 and Ser163. PP2A activity in old cells is detrimental for DDR and influences NER by modulating Snf1 AMPK and Sch9 S6K . Hence, the DDR and repair pathways in aging cells are influenced by the metabolic tuning of opposing AMPK and TORC1 networks and by PP2A activity. Specific Sch9 S6K phospho-isoforms control DDR and NER efficiency, specifically during aging.
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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".