Electrotransfer of the Full-Length Dog Dystrophin into Mouse and Dystrophic Dog Muscles
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is an X-linked genetic disease characterized by the absence of dystrophin (427 kDa). An approach to eventually restore this protein in patients with DMD is to introduce into their muscles a plasmid encoding dystrophin cDNA. Because the phenotype of the dystrophic dog is closer to the human phenotype than is the mdx mouse phenotype, we have studied the electrotransfer of a plasmid carrying the full-length dog dystrophin (FLDYS(dog)) in dystrophic dog muscle. To achieve this nonviral delivery, the FLDYS(dog) cDNA was cloned in two plasmids containing either a cytomegalovirus or a muscle creatine kinase promoter. In both cases, our results showed that the electrotransfer of these large plasmids (∼17 kb) into mouse muscle allowed FLDYS(dog) expression in the treated muscle. The electrotransfer of pCMV.FLDYS(dog) in a dystrophic dog muscle also led to the expression of dystrophin. In conclusion, introduction of the full-length dog dystrophin cDNA by electrotransfer into dystrophic dog muscle is a potential approach to restore dystrophin in patients with DMD. However, the electrotransfer procedure should be improved before applying it to humans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".