Mutation Types and Aging Differently Affect Revertant Fiber Expansion in Dystrophic Mdx and Mdx52 Mice
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD), one of the most common and lethal genetic disorders, and the mdx mouse myopathies are caused by a lack of dystrophin protein. These dystrophic muscles contain sporadic clusters of dystrophin-expressing revertant fibers (RFs), as detected by immunohistochemistry. RFs are known to arise from muscle precursor cells with spontaneous exon skipping (alternative splicing) and clonally expand in size with increasing age through the process of muscle degeneration/regeneration. The expansion of revertant clusters is thought to represent the cumulative history of muscle regeneration and proliferation of such precursor cells. However, the precise mechanisms by which RFs arise and expand are poorly understood. Here, to test the effects of mutation types and aging on RF expansion and muscle regeneration, we examined the number of RFs in mdx mice (containing a nonsense mutation in exon 23) and mdx52 mice (containing deletion mutation of exon 52) with the same C57BL/6 background at 2, 6, 12, and 18months of age. Mdx mice displayed a significantly higher number of RFs compared to mdx52 mice in all age groups, suggesting that revertant fiber expansion largely depends on the type of mutation and/or location in the gene. A significant increase in the expression and clustering levels of RFs was found beginning at 6months of age in mdx mice compared with mdx52 mice. In contrast to the significant expansion of RFs with increasing age, the number of centrally nucleated fibers and embryonic myosin heavy chain-positive fibers (indicative of cumulative and current muscle regeneration, respectively) decreased with age in both mouse strains. These results suggest that mutation types and aging differently affect revertant fiber expansion in mdx and mdx52 mice.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".