SIRT1/FOXO3a axis plays an important role in the prevention of mandibular bone loss induced by 1,25(OH)<sub>2</sub>D deficiency
Bibliographic record
Abstract
It has been reported that 1,25 dihydroxyvitamin D [1,25(OH)2D] deficiency leads to the loss of mandibular bone, however the mechanism is unclear.We investigated whether the Sirt1/FOXO3a signaling pathway is involved in this process.Using a 1,25(OH)2D deficiency model induced by genetic deletion in mice of 25-hydroxyvitamin D-1α hydroxylase [1α(OH)ase -/-mice].We first documented a sharp reduction of expression levels of Sirt1 in the 1α(OH)ase -/-mice in vivo.Next, we demonstrated dose-dependent upregulation of Sirt1 by treatment with exogenous 1,25(OH)2D3 in vitro.We then identified a functional VDR binding site in the Sirt1 promoter.By crossing Prx1-Sirt1 transgenic mice with 1α(OH)ase -/-mice we demonstrated that the overexpression of Sirt1 in mesenchymal stem cells (MSCs) greatly improved the 1α(OH)ase -/-mandibular bone loss phenotype by increasing osteoblastic bone formation and reducing osteoclastic bone resorption.In mechanistic studies, we showed, in 1α(OH)ase -/- mice, decreases of Sirt1 and FoxO3a, an increase in oxidative stress as reflected by a reduction of the antioxidant enzymes peroxiredoxin1 (Prdx1), SOD1 and SOD2 expression, and an increase of markers for osteocyte senescence and senescence associated secretory phenotypes (SASP), including β-galactosidase (β-gal), p16, p53 and p21.The targeted overexpression of Sirt1 in the 1α(OH)ase -/-mice restored the expression levels of these molecules.Finally, we demonstrated that a Sirt1 agonist can upregulate FOXO3a activity by increasing deacetylation and nuclear translocation.Overall, results from this study support the concept that targeted increases in Sirt1/FOXO3a signaling levels can greatly improve the bone loss caused by 1,25(OH)2D deficiency.
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".