Prolonged dystrophin expression and functional correction of mdx mouse muscle following gene transfer with a helper-dependent (gutted) adenovirus-encoding murine dystrophin
Bibliographic record
Abstract
Dystrophin gene transfer using helper-dependent adenoviruses (HDAd), which are deleted of all viral genes, is a promising option to treat muscles in Duchenne muscular dystrophy. We investigated the benefits of this approach by injecting the tibialis anterior (TA) muscle of neonatal and juvenile (4-6-week-old) dystrophin-deficient (mdx) mice with a fully deleted HDAd (HDCBDysM). This vector encoded two full-length murine dystrophin cDNAs regulated by the powerful cytomegalovirus enhancer/beta-actin promoter. At 10 days post-injection of neonatal muscles, 712 fibers (42% of the total number of TA fibers) were dystrophin-positive (dys+), a value that did not decrease for 6 months (the study duration). In treated juveniles, maximal transduction occurred at 30 days post-injection (414 dys+ fibers, 24% of the total number of TA fibers), but decreased by 51% after 6 months. All studied aspects of the pathology were improved in neonatally treated muscles: the percentage of dys+ fibers with centrally localized myonuclei remained low, localization of the dystrophin associated protein complex was restored at the plasma membrane, muscle hypertrophy was reduced, and maximal force-generating capacity and resistance to contraction-induced injuries were increased. The same pathological aspects were improved in the treated juveniles, except for reduction of muscle hypertrophy and maximal force-generating capacity. We demonstrated a strong humoral response against murine dystrophin in both animal groups, but mild inflammatory response occurred only in the treated juveniles. HDCBDysM is thus one of the most promising and efficient vectors for treating DMD by gene therapy.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".