Clearance of defective muscle stem cells by senolytics restores myogenesis in myotonic dystrophy type 1
Bibliographic record
Abstract
Muscle stem cells, the engine of muscle repair, are affected in myotonic dystrophy type 1 (DM1); however, the underlying molecular mechanism and the impact on the disease severity are still elusive. Here, we show using patients' samples that muscle stem cells/myoblasts exhibit signs of cellular senescence in vitro and in situ. Single cell RNAseq uncovers a subset of senescent myoblasts expressing high levels of genes related to the senescence-associated secretory phenotype (SASP). We show that the levels of interleukin-6, a prominent SASP cytokine, in the serum of DM1 patients correlate with muscle weakness and functional capacity limitations. Drug screening revealed that the senolytic BCL-XL inhibitor (A1155463) can specifically remove senescent DM1 myoblasts by inducing their apoptosis. Clearance of senescent cells reduced the expression of SASP, which rescued the proliferation and differentiation capacity of DM1 myoblasts in vitro and enhanced their engraftment following transplantation in vivo. Altogether, this study identifies the pathogenic mechanism associated with muscle stem cell defects in DM1 and opens a therapeutic avenue that targets these defective cells to restore myogenesis.
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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) | 0.001 | 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) | 0.001 | 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".