The Snail Transcription Factor Regulates the Numbers of Neural Precursor Cells and Newborn Neurons throughout Mammalian Life
Bibliographic record
Abstract
The Snail transcription factor regulates diverse aspects of stem cell biology in organisms ranging from Drosophila to mammals. Here we have asked whether it regulates the biology of neural precursor cells (NPCs) in the forebrain of postnatal and adult mice, taking advantage of a mouse containing a floxed Snail allele (Snailfl/fl mice). We show that when Snail is inducibly ablated in the embryonic cortex, this has long-term consequences for cortical organization. In particular, when Snailfl/fl mice are crossed to Nestin-cre mice that express Cre recombinase in embryonic neural precursors, this causes inducible ablation of Snail expression throughout the postnatal cortex. This loss of Snail causes a decrease in proliferation of neonatal cortical neural precursors and mislocalization and misspecification of cortical neurons. Moreover, these precursor phenotypes persist into adulthood. Adult neural precursor cell proliferation is decreased in the forebrain subventricular zone and in the hippocampal dentate gyrus, and this is coincident with a decrease in the number of adult-born olfactory and hippocampal neurons. Thus, Snail is a key regulator of the numbers of neural precursors and newborn neurons throughout life.
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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".