Implication of prostaglandin receptors in the accumulation of osteoprotegerin in human osteoblast cultures.
Bibliographic record
Abstract
OBJECTIVE: Prostaglandins are important mediators in bone metabolism and in pathologies such as rheumatoid arthritis and osteoarthritis. We investigated the roles of cyclooxygenases (COX) and prostaglandin receptors in the accumulation of osteoprotegerin (OPG) in the supernatants of human osteoblasts in culture. METHODS: Three different cellular models were used, the human osteosarcoma cell lines MG-63 and Saos-2, and primary cultures of human osteoblasts. OPG concentrations were determined by ELISA. RESULTS: RT-PCR analysis showed that, like primary human osteoblasts, MG-63 cells express DP, EP4, FP, IP, and TP receptors, whereas the Saos-2 cells lack IP. Concentration of OPG was highest in MG-63 cell supernatants (36 +/- 12.5 ng/ml), followed by human osteoblasts (12.77 +/- 2.2 ng/ml) and Saos-2 (3.6 +/- 0.76 ng/ml). COX inhibitors did not alter these values. Prostaglandin E2 and BW 245C (a synthetic DP receptor agonist) decreased OPG in the supernatants of human osteoblasts but not in immortalized cell lines. These effects were concentration-dependent and were inhibited by EP4 and DP receptor antagonists. Fluprostenol, an FP receptor agonist, increased the accumulation of OPG in MG-63 but not in primary human osteoblasts or Saos-2. CONCLUSION: Our results show that activation of EP4 or DP receptors decreased the accumulation of OPG in supernatants of osteoblasts in culture, and suggest that these receptors could be interesting pharmacological targets in bone diseases. They also demonstrate important differences between primary osteoblasts and immortalized cell lines, both in the distribution and in the effects mediated by prostaglandin receptors.
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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) | 0.002 | 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".