Extended longevity and survivorship during amino-acid starvation in a Drosophila <i>Sir2</i> mutant heterozygote
Bibliographic record
Abstract
The regulation of energy homeostasis is pivotal to survive periods of inadequate nutrition. A combination of intricate pathways and proteins are responsible for maximizing longevity during such conditions. The sirtuin deacetylase Sir2 is well conserved from single-celled yeast to mammals, and it controls a number of downstream targets that are active during periods of extreme stress. Overexpression of Sir2 has been established to enhance survival of a number of model organisms undergoing calorie restriction, during which insulin receptor signalling (IRS) is reduced, a condition that itself can enhance survivorship during starvation. Increased Sir2 expression and reduced IRS result in an increase in the activity of the transcription factor foxo, an advantageous activation during stress but lethal when overly active. We have found that a lowered gene dosage of Sir2, in mutant heterozygotes, can extend normal longevity and greatly augment survivorship during amino-acid starvation in Drosophila. Additionally, these mutants, in either heterozygous or homozygous form, do not appear to have any disadvantageous effects upon development or cell growth of the organism unlike IRS mutants. These results may advance the understanding of the biological response to starvation and allow for the development of a model organism to mimic the ability of individuals to tolerate nutrient deprivation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".