Fibroblast Growth Factor (FGF) 18 Signals through FGF Receptor 3 to Promote Chondrogenesis
Bibliographic record
Abstract
Signaling by fibroblast growth factor (FGF) 18 and FGF receptor 3 (FGFR3) have been shown to regulate proliferation, differentiation, and matrix production of articular and growth plate chondrocytes in vivo and in vitro. Notably, the congenital absence of either FGF18 or FGFR3 resulted in similar expansion of the growth plates of fetal mice and the addition of FGF18 to human articular chondrocytes in culture enhanced proliferation and matrix production. Based on these and other experiments it has been proposed that FGF18 signals through FGFR3 to promote cartilage production by chondrocytes. Its role in chondrogenesis remains to be defined. In the current work we used the limb buds of FGFR3(+/+) and FGFR3(-/-) embryonic mice as a source of mesenchymal cells to determine how FGF18 signaling affects chondrogenesis. Confocal laser-scanning microscopy demonstrated impaired cartilage nodule formation in the FGFR3(-/-) cultures. Potential contributing factors to the phenotype were identified as impaired mitogenic response to FGF18, decreased production of type II collagen and proteoglycan in response to FGF18 stimulation, impaired interactions with the extracellular matrix resulting from altered integrin receptor expression, and altered expression of FGFR1 and FGFR2. The data identified FGF18 as a selective ligand for FGFR3 in limb bud mesenchymal cells, which suppressed proliferation and promoted their differentiation and production of cartilage matrix. This work, thus, identifies FGF18 and FGFR3 as potential molecular targets for intervention in tissue engineering aimed at cartilage repair and regeneration of damaged cartilage.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".