CYR61 Regulates BMP-2-dependent Osteoblast Differentiation through the αvβ3 Integrin/Integrin-linked Kinase/ERK Pathway
Bibliographic record
Abstract
Osteoporosis is one of the most common bone pathologies. A number of novel molecules have been reported to increase bone formation including cysteine-rich protein 61 (CYR61), a ligand of integrin receptor, but mechanisms remain unclear. It is known that bone morphogenetic proteins (BMPs), especially BMP-2, are crucial regulators of osteogenesis. However, the interaction between CYR61 and BMP-2 is unclear. We found that CYR61 significantly increases proliferation and osteoblastic differentiation in MC3T3-E1 osteoblasts and primary cultured osteoblasts. CYR61 enhances mRNA and protein expression of BMP-2 in a time- and dose-dependent manner. Moreover, CYR61-mediated proliferation and osteoblastic differentiation are significantly decreased by knockdown of BMP-2 expression or inhibition of BMP-2 activity. In this study we found integrin α(v)β(3) is critical for CYR61-mediated BMP-2 expression and osteoblastic differentiation. We also found that integrin-linked kinase, which is downstream of the α(v)β(3) receptor, is involved in CYR61-induced BMP-2 expression and subsequent osteoblastic differentiation through an ERK-dependent pathway. Taken together, our results show that CYR61 up-regulates BMP-2 mRNA and protein expression, resulting in enhanced cell proliferation and osteoblastic differentiation through activation of the α(v)β(3) integrin/integrin-linked kinase/ERK signaling pathway.
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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".