Anti-RANKL Therapy Prevents Glucocorticoid-Induced Bone Loss and Promotes Muscle Function in a Mouse Model of Duchenne Muscular Dystrophy
Bibliographic record
Abstract
Bisphosphonates prevent bone loss in glucocorticoid (GC)-treated boys with Duchenne muscular dystrophy (DMD) and are recommended as standard of care. Targeting receptor activator of nuclear factor kappa-B ligand (RANKL) may have advantages in DMD by ameliorating dystrophic skeletal muscle function in addition to their bone anti-resorptive properties. However, the potential effects of anti-RANKL treatment upon discontinuation in GC-induced animal models of DMD are unknown and need further investigation prior to exploration in the clinical research setting. In the first study, the effects of anti-RANKL and deflazacort (DFZ) on dystrophic skeletal muscle function and bone microstructure were assessed in mdx mice treated with DFZ or anti-RANKL, or both for 8 weeks. Anti-RANKL and DFZ improved grip force performance of mdx mice but an additive effect was not noted. However, anti-RANKL but not DFZ improved ex vivo contractile properties of dystrophic muscles. This functional improvement was associated with a reduction in muscle damage and fibrosis, and inflammatory cell number. Anti-RANKL treatment, with or without DFZ, also improved trabecular bone structure of mdx mice. In a second study, intravenous zoledronate (Zol) administration (1 or 2 doses) following 2 months of discontinuation of anti-RANKL treatment was mostly required to record an improvement in bone microarchitecture and biomechanical properties in DFZ-treated mdx mice. In conclusion, the ability of anti-RANKL therapy to restore muscle function has profound implications for DMD patients as it offers the possibility of improving skeletal muscle function without the steroid-related skeletal side effects.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".