Regulation of Neurogenesis and Epidermal Growth Factor Receptor Signaling by the Insulin Receptor/Target of Rapamycin Pathway in Drosophila
Bibliographic record
Abstract
Determining how growth and differentiation are coordinated is key to understanding normal development, as well as disease states such as cancer, where that control is lost. We have previously shown that growth and neuronal differentiation are coordinated by the insulin receptor/target of rapamycin (TOR) kinase (InR/TOR) pathway. Here we show that the control of growth and differentiation diverge downstream of TOR. TOR regulates growth by controlling the activity of S6 kinase (S6K) and eIF4E. Loss of s6k delays differentiation, and is epistatic to the loss of tsc2, indicating that S6K acts downstream or in parallel to TOR in differentiation as in growth. However, loss of eIF4E inhibits growth but does not affect the timing of differentiation. We also show, for the first time in Drosophila, that there is crosstalk between the InR/TOR pathway and epidermal growth factor receptor (EGFR) signaling. InR/TOR signaling regulates the expression of several EGFR pathway components including pointedP2 (pntP2). In addition, reduction of EGFR signaling levels phenocopies inhibition of the InR/TOR pathway in the regulation of differentiation. Together these data suggest that InR/TOR signaling regulates the timing of differentiation through modulation of EGFR target genes in developing photoreceptors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".