Osteogenic Differentiation of Human Mesenchymal Stem Cells Cultured with Dexamethasone, Vitamin D3, Basic Fibroblast Growth Factor, and Bone Morphogenetic Protein-2
Bibliographic record
Abstract
PURPOSE: Human mesenchymal stem cells (hMSCs) are pursued for cell-based therapies of bone defects. Successful use of hMSCs will require them to be osteogenically differentiated before transplantation. This study was intended to determine the optimal combination(s) of supplements needed for inducing osteogenesis in hMSCs. METHODS: The hMSCs were cultured with combinations of β-glycerophosphate, dexamethasone (Dex), vitamin D3 (Vit-D3), basic fibroblast growth factor (bFGF), and bone morphogenetic protein-2 (BMP-2) to assess cell growth and osteogenesis. Osteogenic responses of the supplements were evaluated by alkaline phosphatase (ALP) activity, mineralization, and gene expression of ALP, Runx2, bone sialoprotein, and osteonectin. Adipogenesis was characterized based on Oil Red O staining, gene expression of peroxisome proliferator-activated receptor γ2, and adipocyte protein-2. RESULTS: Dex was found to be essential for mineralization of hMSCs. Cultures treated with Dex (100 nM), Vit-D3 (10/50 nM), and BMP-2 (500 ng/mL) demonstrated maximal calcification and up-regulation of ALP and bone sialoprotein expression. However, adipogenesis was up-regulated in parallel with osteogenesis in these cultures, as evident by the presence of lipid droplets and significant up-regulation of peroxisome proliferator-activated receptor γ2 and adipocyte protein-2 expression. An optimal condition was obtained at Dex (10 nM) and BMP-2 (500 ng/mL) for mineralization without increasing adipogenesis-related markers. The bFGF mitigated osteogenesis and enhanced adipogenesis. Vit-D3 appears essential for calcification only in the presence of bFGF. CONCLUSION: Treatment of hMSCs with appropriate supplements at optimal doses results in robust osteogenic differentiation with minimal adipogenesis. These findings could be used in the cultivation of hMSCs for cell-based strategies for bone regeneration.
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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) | 0.001 | 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".