Administration of a Soluble Activin Type IIB Receptor Promotes the Transplantation of Human Myoblasts in Dystrophic Mice
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is a recessive disease caused by a dystrophin gene mutation. Myoblast transplantation permits the introduction of the dystrophin gene into dystrophic muscle fibers. However, this strategy has so far produced limited results. Modulation of transforming growth factor-β (TGF-β) superfamily signaling promotes skeletal muscle differentiation and growth and myogenic regeneration. We investigated the possibility that the combination of TGF-β superfamily signaling inhibition with myoblast transplantation might be an effective therapeutic approach in dystrophin-deficient patients. In vitro, blocking myostatin and other ligands with a soluble form of the extracellular domain of the activin IIB receptor (ActRIIB/Fc) upregulated the expression of myogenic differentiation factors and increased human myoblast fusion. In vivo, systemic inhibition of activin IIB receptor signaling by delivery of ActRIIB/Fc increased the success of the myoblast transplantation. This effect was further increased by forcing the mice to swim weekly to induce cycles of muscle degeneration and regeneration. Treatment of dystrophic mice with ActRIIB/Fc led to increased body weight, increased skeletal muscle mass, and improved myoblast transplantation. Thus, ActRIIB/Fc represents an effective therapeutic strategy for muscular dystrophies, and its effects are enhanced when combined with muscle exercise.
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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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".