p27Kip1 independently promotes neuronal differentiation and migration in the cerebral cortex
Bibliographic record
Abstract
The generation of glutamatergic neurons by stem and progenitor cells is a complex process involving the tight coordination of multiple cellular activities, including cell cycle exit, initiation of neuronal differentiation and cell migration. The mechanisms that integrate these different events into a coherent program are not well understood. Here we show that the cyclin-dependent kinase inhibitor p27Kip1 plays an important role in neurogenesis in the mouse cerebral cortex, by promoting the differentiation and radial migration of cortical projection neurons. Importantly, p27Kip1 promotes neuronal differentiation and neuronal migration via two distinct mechanisms, which are themselves independent of the cell cycle regulatory function of p27Kip1. p27Kip1 inactivation by gene targeting or RNA interference results in neuronal differentiation and radial migration defects, demonstrating that p27Kip1 regulates cell migration in vivo. The differentiation defect, but not the migration defect, is rescued by overexpression of the proneural gene Neurogenin 2. p27Kip1 acts by stabilizing Neurogenin 2 protein, an activity carried by the N-terminal half of the protein. The migration defect resulting from p27Kp1 inactivation is rescued by blocking RhoA signalling, an activity that resides in the c-terminal half of p27Kip1. Thus, p27Kip1 plays a key role in cortical development, acting as a modular protein that independently regulates and couples multiple cellular pathways contributing to neurogenesis.
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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 | 0.003 | 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) | 0.000 | 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".