Metformin rescues muscle function in BAG3 myofibrillar myopathy models
Bibliographic record
Abstract
Abstract Dominant de novo mutations in the co-chaperone BAG3 cause a severe form of myofibrillar myopathy, exhibiting progressive muscle weakness, muscle structural failure, and protein aggregation. To identify therapies we generated two zebrafish models, one conditionally expressing BAG3 P209L and one with a nonsense mutation in bag3 . Whilst transgenic BAG3 P209L expressing fish display protein aggregation, modelling the early phase of the disease, bag3 −/− fish demonstrate impaired autophagic activity, exercise dependent fibre disintegration, and reduced swimming activity, consistent with later stages. We confirmed the presence of impaired autophagy in patient samples and screened autophagy promoting compounds for their effectiveness at removing protein aggregates, identifying nine including Metformin. Further evaluation demonstrated Metformin is not only able to remove the protein aggregates in zebrafish and human myoblasts but is also able to rescue the fibre disintegration and swimming deficit observed in the bag3 −/− fish. Therefore, repurposing Metformin provides a promising therapy for BAG3 myopathy.
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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 | 0.001 | 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) | 0.002 | 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".