Improved Performance of a Fully Gutted Adenovirus Vector Containing Two Full-Length Dystrophin cDNAs Regulated by a Strong Promoter
Bibliographic record
Abstract
Dystrophin gene transfer using gutted or helper-dependent adenoviruses (HDAd), which have most of their genes deleted, is a promising approach to treat Duchenne muscular dystrophy. In an attempt to boost the amount of dystrophin produced after gene transfer, we have constructed a fully deleted HDAd (HDCBDys2x) containing two human dystrophin cDNAs controlled by the powerful hybrid cytomegalovirus enhancer/beta-actin promoter. We demonstrated high dystrophin expression after infection of muscle cultures with HDCBDys2x. Similarly, high (mean=583) and moderate (mean=124) numbers of muscle fibers were transduced in anterior tibialis muscle after intramuscular injection of HDCBDys2x in neonate and adult dystrophindeficient (mdx) mice 10 days postinjection. In fact, in the neonatally injected mdx mice, the transferred dystrophin was five times more abundant than in normal human muscle. However, the high early transduction level was transient in both animal groups, and we observed a humoral response against the human dystrophin. In contrast, we demonstrated sustained dystrophin expression in immunodeficient mouse muscles. Dystrophin expression of HDCBDys2x could be further increased in the presence of an E1/E3-deleted (first-generation) adenovirus, thus demonstrating that the latter vector synthesizes trans-acting enhancing factors. We have achieved abundant dystrophin expression with our new, improved HDAd. It is anticipated that high longterm transgene expression will be possible by employing weaker immunogenic transgenes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".