Revertant fiber studies in Duchenne muscular dystrophy
Bibliographic record
Abstract
Duchenne Muscular Dystrophy (DMD) is genetic disorder caused by mutations in the dystrophin gene. DMD patients’ progressively lose muscle function due to lack of dystrophin, a protein required for muscle stability. However, sporadic dystrophin-positive revertant fibers (RFs) are observed in dystrophic muscles of DMD patients and murine models such as mdx. RFs clonally expand with age during frequent regeneration of necrotic fibers, and are believed to arise from muscle precursor cells that undergo spontaneous exon skipping of the mutation during translation. Mdx (nonsense mutation in exon 23), a DMD mouse model, is found to have lower regenerative capacity with a DBA/2 genetic background (mdx-DBA/2) than a C57BL/6 genetic background (mdx-C57BL/6). We hypothesize that RF expansion depends on the regenerative capacity of dystrophic muscles. To test our hypothesis, we employed haematoxylin and eosin (H&E) straining and immunostaining of tibialis anterior (TA) and gastrocnemius (GC) muscles in mdx-DBA/2 mice for 2, 6, 12 and 18 months of age. We compared our results to our recently published data, which examined the RF expansion and regenerative capacity in mdx-C57BL/6 mice (Echigoya et al., 2013). We found, via H&E staining, that the number of centrally nucleated fibers (indicative of regenerating muscle fibers) in mdx-DBA/2 is lower than mdx-C57BL/6 mice in TA and GC muscles for all age groups. Our immunostaining results show that mdx-DBA mice have lower RF expansion than mdx-C57BL/6 in all age groups. Taken together, our results show that lower RF expansion is attributable to reduced regenerative capacity of muscle precursor cells.
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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 | 0.001 | 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) | 0.003 | 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".