Role of Bovine Bone Morphogenetic Proteins in Bone Matrix Protein and Osteoblast-Related Gene Expression During Rat Bone Marrow Stromal Cell Differentiation
Bibliographic record
Abstract
Bone morphogenetic proteins (BMPs) are known to promote osteogenesis, and clinical trials are currently underway evaluating the ability of certain BMPs to promote bone graft and fracture healing. To observe the mechanism of osteoinductive and bone formation, 100 microg of bovine BMP was tested during osteogenic differentiation of rat bone marrow stromal cells (MSCs) and C2C12 line culture for 14 and 28 days. We examined alkaline phosphatase (ALP) by assay, immunohistochemical studies for bone matrix proteins, and mRNA expression of bone matrix proteins and osteoblast-related analysis by reverse-transcription polymerase chain reaction. ALP activity in MSC cultures was elevated by bovine BMP by two to fivefold (P < 0.05-0.001). DNA and protein content increased over 14 days. BMP significantly increased the mRNA expression of type I collagen, ALP, osterix, osteocalcin, osteopontin, vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF)-A, and parathyroid hormone receptor time dependently during the osteoblastic differentiation. There was no markedly enhanced mRNA expression of bone sialoprotein (BSP) and glyceraldehyde-3-phosphate dehydrogenase compared with that of control. Immunohistochemical results also showed BMP increased immunoreactive positivity of type I collagen, osteocalcin, osteonectin, osteopontin, and BSP during the C2C12 differentiation. These data indicated that BMP enhances our ability to stimulate the differentiation of osteoblast-like cells and increases osteoinductivity, bone matrix protein formation and mineralization, angiogenesis, and chondrogenesis during osteoblast progenitor cell differentiation in vitro and that the role of chondrogenic is weak.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".