Dexamethasone shifts bone marrow stromal cells from osteoblasts to adipocytes by C/EBPalpha promoter methylation
Bibliographic record
Abstract
Dexamethasone (Dex)-induced osteoporosis has been described as the most severe side effect in long-term glucocorticoid therapy. The decreased bone mass and the increased marrow fat suggest that Dex possibly shifts the differentiation of bone marrow stromal cells (BMSCs) to favor adipocyte over osteoblast, but the underlying mechanisms are still unknown. In this paper, we established a Dex-induced osteoporotic mouse model, and found that BMSCs from Dex-treated mice are more likely to differentiate into adipocyte than those from control mice, even under the induction of bone morphogenetic protein-2 (BMP2). We also discovered both in vitro and in vivo that the expression level of adipocyte regulator CCAAT/enhancer-binding protein alpha (C/EBPalpha) is significantly upregulated in Dex-induced osteoporotic BMSCs during osteoblastogenesis by a mechanism that involves inhibited DNA hypermethylation of its promoter. Knockdown of C/EBPalpha in Dex-induced osteoporotic cells rescues their differentiation potential, suggesting that Dex shifts BMSC differentiation by inhibiting C/EBPalpha promoter methylation and upregulating its expression level. We further found that the Wnt/beta-catenin pathway is involved in Dex-induced osteoporosis and C/EBPalpha promoter methylation, and its activation by LiCl rescues the effect of Dex on C/EBPalpha promoter methylation and osteoblast/adipocyte balance. This study revealed the C/EBPalpha promoter methylation mechanism and evaluated the function of Wnt/beta-catenin pathway in Dex-induced osteoporosis, providing a useful therapeutic target for this type of osteoporosis.
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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 | 0.001 |
| 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".