Transfer of the Full-Length Dystrophin-Coding Sequence into Muscle Cells by a Dual High-Capacity Hybrid Viral Vector with Site-Specific Integration Ability
Bibliographic record
Abstract
Duchenne muscular dystrophy (DMD) is caused by mutations in the DMD gene, making it a potential target for gene therapy. There is, however, a scarcity of vectors that can accommodate the 14-kb DMD cDNA and permanently genetically correct muscle tissue in vivo or proliferating myogenic progenitors in vitro for use in autologous transplantation. Here, a dual high-capacity adenovirus-adeno-associated virus (hcAd/AAV) vector with two full-length human dystrophin-coding sequences flanked by AAV integration-enhancing elements is presented. These vectors are generated from input linear monomeric DNA molecules consisting of the Ad origin of replication and packaging signal followed by the recently identified AAV DNA integration efficiency element (p5IEE), the transgene(s) of interest, and the AAV inverted terminal repeat (ITR). After infection of producer cells with a helper Ad vector, the Ad DNA replication machinery, in concert with the AAV ITR-dependent dimerization, leads to the assembly of vector genomes with a tail-to-tail configuration that are efficiently amplified and packaged into Ad capsids. These dual hcAd/AAV hybrid vectors were used to express the dystrophin-coding sequence in rat cardiomyocytes in vitro and to restore dystrophin synthesis in the muscle tissues of mdx mice in vivo. Introduction into human cells of chimeric genomes, which contain a structure reminiscent of AAV proviral DNA, resulted in AAV Rep-dependent targeted DNA integration into the AAVS1 locus on chromosome 19. Dual hcAd/AAV hybrid vectors may thus be particularly useful to develop safe treatment modalities for diseases such as DMD that rely on efficient transfer and stable expression of large genes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".