FGF dependent regulation of Zfhx1b gene expression promotes the formation of definitive neural stem cells in the mouse anterior neurectoderm
Bibliographic record
Abstract
BACKGROUND: Mouse definitive neural stem cells (NSCs) are derived from a population of LIF-responsive primitive neural stem cells (pNSCs) within the neurectoderm, yet details on the early signaling and transcriptional mechanisms that control this lineage transition are lacking. Here we tested whether FGF and Wnt signaling pathways can regulate Zfhx1b expression to control early neural stem cell development. RESULTS: By microinjecting FGF8b into the pro-amniotic cavity ex vivo at 7.0 days post-coitum (dpc) and culturing whole embryos, we demonstrate that neurectoderm-specific gene expression (for example, Sox2, Nestin, Zfhx1b) is increased, whereas Wnt3a represses neurectoderm gene expression. To determine whether FGF signaling also mediates the lineage transition from a pNSC to a NSC, 7.0-dpc embryos were microinjected with either FGF8b or inhibitors of the FGF receptor-MAP kinase signaling pathway ex vivo, cultured as whole embryos to approximately 8.5 dpc and assayed for clonal NSC colony formation. We show that pre-activation of FGF signaling in the anterior neurectoderm causes an increase in the number of colony forming NSCs derived later from the anterior neural plate, whereas inhibition of FGF signaling significantly reduces the number of NSC colonies. Interestingly, inhibition of FGF signaling causes the persistence of LIF-responsive pNSCs within the anterior neural plate and over-expression of Zfhx1b in these cells is sufficient to rescue the transition from a LIF-responsive pNSC to an FGF-responsive NSC. CONCLUSION: Our data suggest that definitive NSC fate specification in the mouse neurectoderm is facilitated by FGF activation of Zfhx1b.
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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 | 0.001 |
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".