Neural stem cells are increased after loss of β-catenin, but neural progenitors undergo cell death
Bibliographic record
Abstract
Neurons and glia in the central nervous system originate from neural stem and progenitor cells that reside in the ventricular zones. Here we examine the role of β-catenin in neural stem cell (NSC) regulation in mouse embryos lacking β-catenin specifically in the brain germinal zone. An in vitro clonal neurosphere assay was performed in order to ascertain the status of the NSC population. Intact neurospheres did not form from β-catenin-null cells due to a loss of cell adhesion and the number of expanded cells was reduced. Rescue of β-catenin expression restored adhesion and revealed that the number of NSCs increased in the knockout population. Using a clonal colony-forming assay, which confines precursor cells within a solid collagen matrix, we show that the number of NSCs in the hippocampus is unchanged although the β-catenin knockout striatum actually contains a larger proportion of NSCs. However, these colonies were smaller than those of control cells, due to increased apoptosis in the progenitor population. Furthermore, β-catenin knockout NSCs also retained multipotentiality as shown by their ability to clonally differentiate into neurons and glia. The effects on neural precursor cells were not due to loss of downstream T-cell factor signaling, as this pathway is not active in vivo in regions of the embryonic brain where NSCs and progenitor cells reside, nor is it active in vitro in NSC colonies. These data reveal that β-catenin is not required for the maintenance or differentiation of NSCs, but is required for the adhesion and survival of neural 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".