Glucose modulates <i>Drosophila</i> longevity and immunity independent of the microbiota
Bibliographic record
Abstract
The acquisition of nutrients is essential for maintenance of metabolic processes in all organisms. Nutritional imbalance contributes to myriad metabolic disorders that include malnutrition, diabetes and even cancer. Recently, the importance of macronutrient ratio of food has emerged as a critical factor to determine health outcomes. Here we show that individual modifications to a completely defined diet markedly impact multiple aspects of organism wellbeing in Drosophila melanogaster. Through a longitudinal survey of several diets we demonstrate that increased levels of dietary glucose significantly improve longevity and immunity in adult Drosophila. Our metagenomic studies show that relative macronutrient levels not only influence the host, but also have a profound impact on microbiota composition. However, we found that elevated dietary glucose extended the lifespan of adult flies even when raised in a germ-free environment. Furthermore, when challenged with a chronic enteric infection, flies fed a diet with added glucose had increased survival times even in the absence of an intact microbiota. Thus, in contrast to known links between the microbiota and animal health, our findings uncover a novel microbiota-independent response to diet that impacts host wellbeing. As dietary responses are highly conserved in animals, we believe our results offer a general understanding of the association between glucose metabolism and animal health.
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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".