Fibroblast growth factor receptor‐3 null mice exhibit a delay in the development of oligodendrocytes and myelination
Bibliographic record
Abstract
Fibroblast growth factors (FGFs) comprise of a family of twenty‐three members which bind to four receptor tyrosine kinases (R1–R4). They induce a broad spectrum of biological effects in a variety of cell types, including neurons and glia in the CNS. In oligodendrocytes (OLs), FGF‐2 elicits a number of specific responses depending on their stage of development. During OL development in vitro, the expressions of FGF‐receptor mRNAs are differentially regulated. R1 mRNA increases gradually along with OL maturation, whereas R3 and R2 mRNAs peak at the OL progenitor and mature OL stages, respectively, suggesting a differential roles of these receptors in OL development. R3 is also expressed by astrocytes. To determine the roles of R3 during OL development and myelination in vivo, we have employed mice lacking functional R3 (R3‐null). During myelination (P7, P9, P13), reduced numbers of differentiated OLs and myelinated fibers are observed in the brains of R3 null mice compared to wild type mice. Moreover, up‐regulation of glial fibrillary acidic protein‐positive astrocytes is found in the cerebellum and spinal cord of R3 null mutants. However, the number of OL progenitors (PDGF‐Ra), BrdU incorporation, and cell survival (TUNEL assay) are all comparable, and R3‐null myelin in adult mice appears to be similar to that of wild type mice. In mixed primary cultures of post‐natal R3 null brain (that have few if any neurons), OLs exhibit a delay in differentiation similar to that observed in vivo. In summary, our results elucidate regulatory roles of FGF‐R3 in mouse brain, in particular with regard to its roles in the timing of OL maturation and myelin formation (MS Society, Canada, NIH NS38878‐03).
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".