In Vitro Osteogenic Response of Rat Bone Marrow Cells to bFGF and BMP-2 Treatments
Bibliographic record
Abstract
Basic fibroblast growth factor (bFGF) and bone morphogenetic protein-2 (BMP-2) are actively pursued for stimulation of bone formation. To assess their promise for systemic therapy of osteoporosis, we ascertained the effects of bFGF and BMP-2 on bone marrow cells in vitro. Bone marrow cells were obtained from young (8 weeks) and adult (32 weeks) rats by femoral aspiration and were exposed to osteogenic medium (ie, basal medium with 10 mM beta-glycerolphosphate and 100 nM dexamethasone) containing the growth factors. The cell viability in osteogenic medium was reduced after 3 weeks but not if the concentration of beta-glycerolphosphate/dexamethasone was reduced to 3 mM/30 nM. Unlike BMP-2, bFGF at 2-50 ng/mL was capable of enhancing long-term cell viability. Continuous treatment of bone marrow cells for 3 weeks resulted in dose-dependent stimulation of mineralization by BMP-2, but not by bFGF, whose activity was optimal at 2-10 ng/mL. To explore the effect of short-term exposure, bone marrow cells were treated with growth factors for 1 week and subsequent mineralization was investigated. BMP-2 exposure increased the extent of mineralization, but bFGF was not effective after the short exposure. We concluded bFGF was more potent (ie, required lower concentration) for stimulating osteogenic parameters, but BMP-2 effects were lasting on the bone marrow cells.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".