A mechanism linking lipid metabolism and longevity
Bibliographic record
Abstract
We use the yeast Saccharomyces cerevisiae as a model to study the mechanisms linking lipid metabolism and longevity. Yeast aging can be slowed down by calorie restriction (CR), a low‐calorie diet that extends life span and delays age‐related disorders in a wide spectrum of organisms. We assessed the effect of CR and numerous mutations extending yeast life span on the spatiotemporal dynamics of the proteomes and lipidomes of organelles involved in lipid metabolism. These organelles include the endoplasmic reticulum (ER), peroxisomes and lipid bodies. Our findings imply that a calorie‐rich diet suppresses peroxisomal oxidation of free fatty acids (FFA) that originate from neutral lipids synthesized in the ER and deposited within lipid bodies. The resulting accumulation of FFA initiates several negative feedback loops regulating the metabolism of neutral lipids, ultimately leading to the accumulation of diacylglycerol (DAG). The buildup of FFA promotes necrotic cell death, whereas the accumulation of DAG hampers a stress response‐related signal transduction network. Implementing our knowledge, we identified five groups of novel anti‐aging small molecules that greatly extend yeast longevity by remodelling lipid metabolism in the ER, peroxisomes and lipid bodies and by promoting "mitohormesis" through the activation of a distinct set of stress response‐related processes in mitochondria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".