Temporally tuned neuronal differentiation supports the functional remodeling of a neuronal network in <i>Drosophila</i>
Bibliographic record
Abstract
During insect metamorphosis, neuronal networks undergo extensive remodeling by restructuring their connectivity and recruiting newborn neurons from postembryonic lineages. The neuronal network that directs the essential behavior, ecdysis, generates a distinct behavioral sequence at each developmental transition. Larval ecdysis replaces the cuticle between larval stages, and pupal ecdysis externalizes and expands the head and appendages to their adult position. However, the network changes that support these differences are unknown. Crustacean cardioactive peptide (CCAP) neurons and the peptide hormones they secrete are critical for ecdysis; their targeted ablation alters larval ecdysis progression and results in a failure of pupal ecdysis. In this study, we demonstrate that the CCAP neuron network is remodeled immediately before pupal ecdysis by the emergence of 12 late CCAP neurons. All 12 are CCAP efferents that exit the central nervous system. Importantly, these late CCAP neurons were found to be entirely sufficient for wild-type pupal ecdysis, even after targeted ablation of all other 42 CCAP neurons. Our evidence indicates that late CCAP neurons are derived from early, likely embryonic, lineages. However, they do not differentiate to express their peptide hormone battery, nor do they project an axon via lateral nerve trunks until pupariation, both of which are believed to be critical for the function of CCAP efferent neurons in ecdysis. Further analysis implicated ecdysone signaling via ecdysone receptors A/B1 and the nuclear receptor ftz-f1 as the differentiation trigger. These results demonstrate the utility of temporally tuned neuronal differentiation as a hard-wired developmental mechanism to remodel a neuronal network to generate a scheduled change in behavior.
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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".