Unkempt Is Negatively Regulated by mTOR and Uncouples Neuronal Differentiation from Growth Control
Bibliographic record
Abstract
Neuronal differentiation is exquisitely controlled both spatially and temporally during nervous system development. Defects in the spatiotemporal control of neurogenesis cause incorrect formation of neural networks and lead to neurological disorders such as epilepsy and autism. The mTOR kinase integrates signals from mitogens, nutrients and energy levels to regulate growth, autophagy and metabolism. We previously identified the insulin receptor (InR)/mTOR pathway as a critical regulator of the timing of neuronal differentiation in the Drosophila melanogaster eye. Subsequently, this pathway has been shown to play a conserved role in regulating neurogenesis in vertebrates. However, the factors that mediate the neurogenic role of this pathway are completely unknown. To identify downstream effectors of the InR/mTOR pathway we screened transcriptional targets of mTOR for neuronal differentiation phenotypes in photoreceptor neurons. We identified the conserved gene unkempt (unk), which encodes a zinc finger/RING domain containing protein, as a negative regulator of the timing of photoreceptor differentiation. Loss of unk phenocopies InR/mTOR pathway activation and unk acts downstream of this pathway to regulate neurogenesis. In contrast to InR/mTOR signalling, unk does not regulate growth. unk therefore uncouples the role of the InR/mTOR pathway in neurogenesis from its role in growth control. We also identified the gene headcase (hdc) as a second downstream regulator of the InR/mTOR pathway controlling the timing of neurogenesis. Unk forms a complex with Hdc, and Hdc expression is regulated by unk and InR/mTOR signalling. Co-overexpression of unk and hdc completely suppresses the precocious neuronal differentiation phenotype caused by loss of Tsc1. Thus, Unk and Hdc are the first neurogenic components of the InR/mTOR pathway to be identified. Finally, we show that Unkempt-like is expressed in the developing mouse retina and in neural stem/progenitor cells, suggesting that the role of Unk in neurogenesis may be conserved in mammals.
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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) | 0.001 | 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 | 0.001 |
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".