Adipose mitochondrial metabolism controls body growth by modulating cytokine and insulin signaling
Bibliographic record
Abstract
Summary Animals need to adapt their growth to fluctuations in nutrient availability to ensure proper development and survival. These adaptations often rely on specific nutrient-sensing tissues and their control of whole-body physiology through inter-organ communication. While the signaling mechanisms that underlie this communication are well studied, the contributions of metabolic alterations in the nutrient-sensing tissues are less clear. Here, we show how reprogramming of adipose mitochondrial metabolism controls whole-body growth in Drosophila larvae. We find that dietary nutrients alter fat body mitochondrial morphology to lower their bioenergetic activity, which we see can rewire fat body glucose metabolism. Strikingly, we find that genetic reduction of mitochondrial bioenergetics just in the fat body is sufficient to accelerate body growth and development. These growth effects are caused by inhibition of the fat-derived adipokine, TNFα/Eiger, which leads to enhanced systemic insulin signaling, the main hormonal stimulator of body growth. Our work reveals how reprogramming of mitochondrial metabolism in one nutrient-sensing tissue is able to couple whole body growth to nutrient availability.
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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 | 0.001 |
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".