Notch Signaling Imparts and Preserves Neural Stem Characteristics in the Adult Brain
Bibliographic record
Abstract
Although the role of Notch has been studied extensively in the developing nervous system, the embryonic lethality of Notch pathway mutants has hindered studies in the adult brain. The creation of cre/lox-mediated conditional gain- and loss-of-function mice has allowed us to investigate the role of Notch signaling in adult neural stem and progenitor cells. We have determined that Notch signaling is important for conferring stem cell characteristics upon neural precursor cells. Knocking-out Notch signaling in vivo results in neural progenitors, leaving the subependymal niche and migrating along the rostral migratory stream to the olfactory bulb, while overexpressing Notch results in retention of cells in the subependyma. Further, increased Notch signaling in progenitor cells resulted in the expression of stem cell markers in vivo as well as conferring the characteristics of self-renewal and multipotentiality upon subsequent isolation in vitro. Similar to what has been reported from the embryonic brain, the overexpression of Notch in neural precursor cells in vitro increased the numbers of neurospheres from the adult brain. Finally, overexpression of Notch1 in pure populations of progenitor cells (excluding neural stem cells) isolated by fluorescence activated cell sorting led to the formation of multipotent, self-renewing neurospheres from the non-neurosphere forming fraction. Hence, Notch overexpression confers stem cell properties upon progenitor cells and demonstrates that Notch signaling not only preserves stem cell characteristics, but that it can confer stem cell characteristics upon a subset of progenitor cells.
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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 | 0.001 | 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".