The Mouse Dystrophin Muscle Promoter/Enhancer Drives Expression of Mini-dystrophin in Transgenic mdx Mice and Rescues the Dystrophy in These Mice
Bibliographic record
Abstract
Successful gene therapy for Duchenne muscular dystrophy (DMD) requires the restoration of dystrophin protein in skeletal muscles. To achieve this goal, appropriate regulatory elements that impart tissue-specific transgene expression need to be identified. Currently, most muscle-directed gene therapy studies utilize the muscle creatine kinase promoter. We have previously described a muscle enhancer element (mDME-1) derived from the mouse dystrophin gene that increases transcription from the mouse dystrophin muscle promoter. Here, we explore the use of this native mouse dystrophin muscle promoter/enhancer to drive expression of a human dystrophin minigene in transgenic mice. We show that the dystrophin promoter can provide tissue-specific transgene expression and that the mini-dystrophin protein is expressed at the sarcolemma of skeletal muscles from mdx mice, where it restores the dystrophin-associated glycoprotein complex. The level of transgene expression obtained is sufficient to protect mdx muscles from the morphological and physiological symptoms of muscular dystrophy, as well as from exercise-induced damage. Therefore, the dystrophin muscle promoter/enhancer sequence represents an alternative for use in gene therapy vectors for the treatment of 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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".