Nuclear receptor retinoid-related orphan receptor α1 modulates the metabolic activity of human osteoblasts
Bibliographic record
Abstract
Nuclear receptor retinoid-related orphan receptor alpha (RORα1) is a member of ROR-family receptors. It is broadly expressed in various tissues and organs during embryonic development. However, so far, little is known about its function in bone. Here, we have elucidated the expression and function of RORα1 in human MG-63 osteoblast-like cells. Reverse transcriptase-polymerase chain reaction and immunocytochemical analysis revealed that human MG-63 osteoblasts expressed and produced RORα1. Other cell lines, such as THP-1 monocytes expressed also RORα1. RORα1 over-expression increased alkaline phosphatase, osteocalcin, cell mineralization, and collagen type I mRNA and protein expression, while RORα1 RNA silencing inhibited these responses. In addition, RORα1 over-expression suppressed the tumor necrosis factor-alpha (TNFα)-induced production of cyclooxygenase-2, prostaglandin E(2) , and metalloproteinase-9. Examination of the signaling pathways disclosed that RORα1 was able to block TNFα-evoked nuclear factor-kappaB activation. In conclusion, this study demonstrates that RORα1 is involved in human osteoblast metabolism by stimulating osteoblast marker expression and inhibiting inflammatory responses. The results may encourage further exploration of RORα1 as a potential target for the treatment of bone disorders related to inflammation.
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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".