The adiponectin analogue ALY688-SR attenuates diaphragm fibrosis, atrophy and mitochondrial stress in a mouse model of Duchenne muscular dystrophy
Bibliographic record
Abstract
Abstract Fibrosis is associated with respiratory and limb muscle atrophy in Duchenne muscular dystrophy (DMD). Current standard of care partially delays the progression of this myopathy but there remains an unmet need to develop additional therapies. Adiponectin receptor agonism has emerged as a possible therapeutic target to lower inflammation and improve metabolism in mdx mouse models of DMD but the degree to which fibrosis and atrophy are prevented remain unknown. Here, we demonstrate that the recently developed slow-release peptidomimetic adiponectin analogue ALY688-SR prevents fibrosis and fibre type-specific atrophy in diaphragm of D2. mdx mice treated from days 7-28 of age. ALY688-SR also lowered IL-6mRNA but increased IL-6 and TGF-β protein contents in diaphragm, suggesting dynamic inflammatory remodeling. ALY688-SR alleviated mitochondrial redox stress by decreasing complex I-stimulated H 2 O 2 emission. Treatment also lowered in vitro diaphragm force production in diaphragm suggesting a complex relationship between adiponectin receptor activity, muscle remodeling and force generating properties during the very early stages of disease progression in D2. mdx mice. In tibialis anterior, the modest fibrosis at this young age was not altered by treatment, and atrophy was not apparent at this young age. These results demonstrate that short-term treatment of ALY688-SR partially prevents fibrosis and atrophy in the more disease-apparent diaphragm of young D2. mdx mice in relation to lower mitochondrial redox stress. These results provide a foundation for the exploration of slow-release adiponectin-based therapies to prevent fibrosis and atrophy in Duchenne muscular dystrophy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".