Fibroblast Growth Factor Signaling Regulates Neurogenesis at Multiple Stages in the Embryonic Olfactory Epithelium
Bibliographic record
Abstract
Lifelong neurogenesis in the mouse olfactory epithelium (OE) is regulated by the response of stem/progenitor cells to local signals, but embryonic and adult OE progenitors appear to be quite different--with potentially different mechanisms of regulation. A recently identified progenitor unique to embryonic OE--the nestin+ radial glial-like progenitor--precedes some Mash1+ progenitors in the olfactory receptor neuron (ORN) lineage, which then gives rise to immediate neuronal precursors and immature ORNs. Neurogenic drive at each stage is governed largely by exogenous factors. Fibroblast growth factor 2 (FGF2) is believed to increase cell proliferation in both presumptive OE stem cells and immediate neuronal precursors in explants, but whether FGF2 directly acts on different target progenitors or stages in the embryonic OE is not known. Here we show that fibroblast growth factor receptor (FGFR)1 and FGFR2 are found in a variety of embryonic olfactory cells, including olfactory ensheathing cells and their precursors, and neuronal nestin+ and Mash1+ progenitors. Combining gain and loss of function for FGF2 activity in a novel in vitro clonal progenitor assay, we reveal that different colony phenotypes are formed by presumably different OE progenitors. FGF2 is essential for the survival and expansion of colony-forming cells of the OE, and also enhances the proliferation of embryonic Mash1+ progenitors, leading to long-lived enhancement of neurogenesis. Our data suggest that distinct OE progenitors yield different in vitro phenotypes with different potentials, that colony-forming activity is profoundly altered by laminin and collagen, that multiple ORNs can be produced from single colony-forming progenitors, and demonstrate a broader progenitor range of FGF action in the embryonic OE than previously demonstrated.
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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) | 0.001 | 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) | 0.000 | 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".