Defective bone mineralization and osteopenia in young adult FGFR3-/- mice
Bibliographic record
Abstract
Mutations that cause constitutive activation of fibroblast growth factor receptor 3 (FGFR3) result in skeletal disorders that are characterized by short-limbed dwarfism and premature closure of cranial sutures. In previous work, it was shown that congenital deficiency of FGFR3 led to skeletal overgrowth. Using a combination of imaging, classic histology and molecular cell biology we now show that young adult FGFR3(-/-) mice are osteopenic due to reduced cortical bone thickness and defective trabecular bone mineralization. The reduction in mineralized bone and lack of trabecular connectivity observed by micro-computed tomography were confirmed in histological and histomorphometric analyses, which revealed a significant decrease in calcein labelling of mineralizing surfaces and a significant increase in osteoid in the long bones of 4-month-old FGFR3(-/-) mice. These alterations were associated with increased staining for recognized markers of differentiated osteoblasts and increased numbers of tartrate-resistant acid phsophatase postitive osteoclasts. Primary cultures of adherent bone marrow-derived cells from FGFR3(-/-) mice expressed markers of differentiated osteoblasts but developed fewer mineralized nodules than FGFR3(+/+) cultures of the same age. Our observations reveal a role for FGFR3 in post-natal bone growth and remodelling, which identifies it as a potential therapeutic target for osteopenic disorders and those associated with defective bone mineralization.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".