Acute, next‐generation <scp>AMPK</scp> activation initiates a disease‐resistant gene expression program in dystrophic skeletal muscle
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is a life-limiting neuromuscular disorder characterized by muscle weakness and wasting. Previous proof-of-concept studies demonstrate that the dystrophic phenotype can be mitigated with the pharmacological stimulation of AMP-activated protein kinase (AMPK). However, first-generation AMPK activators have failed to translate from bench to bedside due to either their lack of potency or toxic, off-target effects. The identification of safe and efficacious molecules that stimulate AMPK in dystrophic muscle is of particular importance as it may broaden the therapeutic landscape for DMD patients regardless of their specific dystrophin mutation. Here, we demonstrate that a single dose of the next generation, orally-bioactive AMPK agonist MK-8722 (MK) to mdx mice evoked skeletal muscle AMPK and extensive downstream stimulation within 12 h post-treatment. Specifically, MK elicited a gene expression profile indicative of a more disease-resistant slow, oxidative phenotype including increased peroxisome proliferator-activated receptor ɣ coactivator-1⍺ activity and utrophin levels. In addition, we observed augmented autophagy signaling downstream of AMPK, as well as elevations in critical autophagic genes such as Map1lc3 and Sqstm1 subsequent to the myonuclear accumulation of the master regulator of the autophagy gene program, transcription factor EB. Lastly, we show that pharmacological AMPK stimulation normalizes the expression of myogenic regulatory factors and amends activated muscle stem cell content in mdx muscle. Our results indicate that AMPK activation via MK enhances disease-mitigating mechanisms in dystrophic muscle and prefaces further investigation on the chronic effects of novel small molecule AMPK agonists.
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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".