Hypoxia delays steroid-induced developmental maturation in <i>Drosophila</i> by suppressing EGF signaling
Bibliographic record
Abstract
Summary Animals often grow and develop in unpredictable environments where factors like food availability, temperature, and oxygen levels can fluctuate dramatically. To ensure proper sexual maturation into adulthood, juvenile animals need to adapt their growth and developmental rates to these fluctuating environmental conditions. Failure to do so can result in impaired maturation and incorrect body size. Here we describe a mechanism by which Drosophila larvae adapt their development in low oxygen (hypoxia). During normal development, larvae grow and increase in mass until they reach critical weight (CW), after which point a neuroendocrine circuit triggers the production of the steroid hormone ecdysone from the prothoracic gland (PG), which promotes maturation to the pupal stage. However, when raised in hypoxia (5% oxygen), larvae slow their growth and delay their maturation to the pupal stage. We find that, although hypoxia delays the attainment of CW, the maturation delay occurs mainly because of hypoxia acting late in development to suppress ecdysone production. This suppression operates through a distinct mechanism from nutrient deprivation, occurs independently of HIF-1 alpha and does not involve modulation of PTTH, the main neuropeptide that initiates ecdysone production in the PG. Instead, we find that hypoxia lowers the expression of the EGF ligand, spitz, and that the delay in maturation occurs due to reduced EGFR/ERK signaling in the PG. Our study sheds light on how animals can adjust their development rate in response to changing oxygen levels in their environment. Given that hypoxia is a feature of both normal physiology and many diseases, our findings have important implications for understanding how low oxygen levels may impact animal development in both normal and pathological situations.
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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".