An anti-RANKL treatment reduces muscle inflammation and dysfunction and strengthens bone in dystrophic mice
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is the most severe form of muscular dystrophy which leads to progressive muscle degeneration and inflammation. The receptor activator of nuclear factor NF-κB ligand (RANKL) and its receptor (RANK), which are expressed in bone and skeletal and cardiac muscles, form a signaling network upstream from nuclear factor-kappa B (NF-κB). We thus hypothesized that prolonged silencing RANKL/RANK signaling would significantly improve DMD. We showed that RANK and RANKL protein levels were increased in the microenvironment of myofibers of 5-month-old utrophin haploinsufficient mdx (mdx/utrn+/-) mice and that a 4 mg/kg dose of anti-RANKL antibody every 3 d for 28 days is optimal and more effective than 1 mg/kg every 3 d for improving the ex vivo maximum specific force (sP0) of dystrophic EDL muscles from mdx/utrn+/- mice. This functional improvement was associated with a reduction in muscle edema, damage, and fibrosis and a marked reduction in serum CK levels. The anti-RANKL treatment inhibited the NF-κB pathway, increased the proportion of anti-inflammatory and non-cytotoxic M2 macrophages, and reduced the number of centrally-nucleated myofibers and the frequency of small myofibers, suggesting that anti-RANKL inhibits the cycle of degeneration/regeneration in dystrophic mice. A three-point bending test showed that a 28-d anti-RANKL treatment increases the mechanical properties of bone in mdx/utrn+/- dystrophic mice. In conclusion, the anti-RANKL treatment protected against skeletal muscle dysfunctions while enhancing bone mechanical properties, filling two needs with one deed in the context of muscular dystrophy.
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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".