Dynamic restoration of dystrophin to dystrophin-deficient myotubes
Bibliographic record
Abstract
Dystrophin domains are observed in myoblast transplantation experiments and in muscle fibers after somatic reversion in human Duchenne and mdx mouse muscular dystrophy. However, the formation and evolution of dystrophin-positive domains are not well established. Using a muscle satellite cell coculture system, we examined the dynamic restoration of dystrophin expression in dystrophin-deficient myotubes. The dystrophin-positive domains around source nuclei were clearly identified in hybrid myotubes. The occurrence of dystrophin domains was higher in myotubes differentiated from cocultures with a low concentration of normal wild-type satellite cells in relation to dystrophin-deficient satellite cells. At higher seeding ratios, the domain feature of dystrophin expression was more transitory and decreased as myotubes differentiated over time in culture. The average domain size initially increased with the addition of new nuclei by fusion early after differentiation of cocultures. However, separating dystrophin-positive domains according to their number of dystrophin-expressing contributory nuclei showed that diffusion of dystrophin contributed to domain elongation, even in early myotubes and later without fusion of additional nuclei. Diffusion occurred for all domains of one to six wild-type nuclei, and the diffusion rate was higher in domains with larger numbers of nuclei. This dynamic domain feature of dystrophin expression was also related to restoring the organization of dystrophin-associated proteins and acetylcholine receptors to hybrid myotubes. Factors regulating domain formation and diffusion therefore are important considerations in the design of strategies for both myoblast transplantation and gene therapy of 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) | 0.000 | 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 | 0.000 |
| 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".