Characterization of molecular mechanisms underlying the neurogenic effect of the bHLH protein Hes6
Bibliographic record
Abstract
Hes1 is a mammalian basic helix-loop-helix (bHLH) transcriptional repressor that inhibits neuronal differentiation and acts together with the corepressor Gro/TLE. Hes1 interacts with Gro/TLE through its WRPW motif and recruits Gro/TLE to specific DNA sites. In contrast, a related Hes family member, Hes6, promotes neuronal differentiation. Little is known about the molecular mechanisms underlying the neurogenic effect of Hes6. To address this question, a structure/function analysis was performed to identify domains of Hes6 important for its biological activity during the differentiation of cortical neurons. It is shown here that the nuclear translocation of Hes6 is required to promote cortical neurogenesis. However, Hes6 neurogenic activity does not appear to be DNA-binding dependent, suggesting that it is mediated by protein-protein interaction mechanisms. Moreover, a conserved potential PEST sequence present at the C-terminus of Hes6, which may regulate protein turnover, is also important for the neurogenic activity of Hes6. It is also shown that the nuclear translocation-incompetent form of Hes6 and, to a lesser extent, the PEST sequence-defective form have a reduced ability to promote a proteolytic degradation of Hes1. This correlation suggests that Hes6 may regulate cortical neurogenesis by a protein-protein interaction mechanism in which Hes6 interacts with Hes1 and promotes a proteolytic degradation of the latter.
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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".