Regulation of osteoprotegerin production by androgens and anti-androgens in human osteoblastic lineage cells
Bibliographic record
Abstract
BACKGROUND: Estrogens and androgens have anti-resorptive effects on bone, although recent evidence indicates that, even in men, estrogen is the dominant sex steroid regulating bone resorption. The receptor activator of NF-kappaB ligand is essential for osteoclastic bone resorption, and its effects are blocked by the decoy receptor, osteoprotegerin (OPG). While estrogen has been shown to induce osteoblastic OPG production, the effects of androgens on OPG production have not been defined. METHODS: In this study, we assessed the regulation of OPG by androgens in hFOB/AR-6, an immortalized fetal osteoblastic cell line stably transfected with the human androgen receptor (AR), and MSC cells, primary human pluripotent marrow stromal cells capable of differentiating towards mature osteoblasts. RESULTS AND CONCLUSIONS: 5Alpha-dihydrotestosterone (DHT) dose-dependently decreased OPG mRNA levels and protein concentrations in hFOB/AR-6 cells by up to 50 and 60% respectively (P<0.001). Inhibition of OPG mRNA levels and protein production by 5alpha-DHT was completely abrogated by the AR antagonist, hydroxyflutamide (OHF), indicating that these effects are directly mediated by the AR. Of note, OHF alone increased OPG mRNA levels and protein secretion by 2- to 3-fold. Moreover, 5alpha-DHT and testosterone also decreased OPG protein secretion by 40-46% in the untransformed MSC cells, while OHF stimulated it. In conclusion, we demonstrate that androgens specifically inhibit OPG mRNA levels and protein secretion by osteoblastic 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 | 0.000 | 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".