Insulin-Like Peptides Regulate Feeding Preference and Metabolism in <i>Drosophila</i>
Bibliographic record
Abstract
SUMMARY Fruit flies have eight identified Drosophila insulin-like peptides (DILPs) involved in regulation of carbohydrate concentrations in hemolymph as well as accumulation of storage metabolites. In the present study, we investigated diet-dependent roles of DILPs encoded by genes dilp1–5 , and dilp7 in regulation of insect appetite, food choice, accumulation of triglycerides, glycogen, glucose, and trehalose in fruit fly body and carbohydrates in hemolymph. We found that dilp2 gene predominantly influences body glycogen level, dilp3 – trehalose level in hemolymph, while dilp5 and dilp7 affect triglyceride level. Fruit fly appetite was found to be regulated by dilp3 and dilp7 genes. Our data contribute to the understanding of Drosophila as a model for further studies of metabolic diseases and may serve as a guide for uncovering the evolution of metabolic regulatory pathways. HIGHLIGHTS Different Drosophila insulin-like peptides play distinctive roles in metabolism, physiology and appetite regulation. Lack of Dilp2 and Dilp5 abrogates glycogen accumulation on high carbohydrate diets Lack of Dilp3 leads to build-up of trehalose in haemolymph on high-carbohydrate-low-protein diets Lack of Dilp3 and Dilp7 leads to increased consumption of protein on low-carbohydrate-high-protein diets GRAPHICAL ABSTRACT
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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) | 0.002 | 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".