<i>Zfhx1b</i> Induces a Definitive Neural Stem Cell Fate in Mouse Embryonic Stem Cells
Bibliographic record
Abstract
Inducing a stable and predictable program of neural cell fate in pluripotent cells in vitro is an important goal for utilizing these cells for modeling human disease mechanisms. However, the extent to which in vitro neural specification recapitulates in vivo neural specification remains to be fully established. We previously demonstrated that in the mouse embryo, activation of fibroblast growth factor (FGF) signalling promotes definitive neural stem cell (NSC) development through the upregulation of the transcription factor Zfhx1b. Here, we asked whether Zfhx1b is similarly required during neural lineage development of embryonic stem (ES) cells. Zfhx1b gene expression is rapidly upregulated in mouse ES cells cultured in a permissive neural-inducing environment, compared to ES cells in a standard pluripotency maintenance environment, and is potentiated by FGF signalling. However, overexpression of Zfhx1b in ES cells in maintenance conditions, containing serum and leukemia inhibitory factor (LIF), is sufficient to induce Sox1 expression, a marker found in neural precursors and to promote definitive NSC colony formation. Knockdown of Zfhx1b in ES cells using siRNA did not affect the initial transition of ES cells to a neural cell fate, but did diminish the ability of these neural cells to develop further into definitive NSCs. Thus, our findings using ES cells are congruent with evidence from mouse embryos and support a model, whereby intercellular FGF signaling induces Zfhx1b, which promotes the development of definitive NSCs subsequent to an initial neural specification event that is independent of this pathway.
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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) | 0.004 | 0.002 |
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".