RNAi-mediated knockdown of dystrophin expression in adult mice does not lead to overt muscular dystrophy pathology
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is a fatal muscle wasting disorder caused by mutations in the dystrophin gene. DMD has a complex and as yet incompletely defined molecular pathophysiology. The peak of the pathology attributed to dystrophin deficiency happens between 3 and 8 weeks of age in mdx mice, the animal model of DMD. Accordingly, we hypothesized that the pathology observed with dystrophin deficiency may be developmentally regulated. Initially, we demonstrated that profound small interfering RNA-mediated dystrophin knockdown could be achieved in mouse primary muscle cultures. The use of adeno-associated virus vectors to express short-hairpin RNAs targeting dystrophin in skeletal muscle in vivo yielded a potent and specific dystrophin knockdown, but only after approximately 5 months, indicating the very long half-life of dystrophin. Interestingly, and in contrast to what is observed in congenital dystrophin deficiency, long-term ( approximately 1 year) dystrophin knockdown in adult mice did not result, per se, in overt dystrophic pathology or upregulation of utrophin. This supports our hypothesis and suggests new pathophysiology of the disease. Furthermore, taking into account the rather long half-life of dystrophin, and the notion that the development of pathology is age-dependent, it indicates that a single gene therapy approach before the onset of pathology might convey a long-term cure for DMD.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".