Promoting basal levels of autophagy in the nervous system enhances longevity and oxidant resistance in adult Drosophila
Bibliographic record
Abstract
Autophagy is involved with the turnover of intracellular components and the management of stress responses. Genetic studies in mice have shown that suppression of neuronal autophagy can lead to the accumulation of protein aggregates and neurodegeneration. However, no study has shown that increasing autophagic gene expression can be beneficial to an aging nervous system. Here we demonstrate that expression of several autophagy genes is reduced in Drosophila neural tissues as a normal part of aging. The age-dependent suppression of autophagy occurs concomitantly with the accumulation of insoluble ubiquitinated proteins (IUP), a marker of neuronal aging and degeneration. Mutations in the Atg8a gene (autophagy-related 8a) result in reduced lifespan, IUP accumulation and increased sensitivity to oxidative stress. In contrast, enhanced Atg8a expression in older fly brains extends the average adult lifespan by 56% and promotes resistance to oxidative stress and the accumulation of ubiquitinated and oxidized proteins. These data indicate that genetic or age-dependent suppression of autophagy is closely associated with the buildup of cellular damage in neurons and a reduced lifespan, while maintaining the expression of a rate-limiting autophagy gene prevents the age-dependent accumulation of damage in neurons and promotes longevity.
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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".