Serotype-dependent packaging of large genes in adeno-associated viral vectors results in effective gene delivery in mice
Bibliographic record
Abstract
Vectors derived from adeno-associated virus (AAV) are promising for human gene therapy, including treatment for retinal blindness. One major limitation of AAVs as vectors is that AAV cargo capacity has been considered to be restricted to 4.7 kb. Here we demonstrate that vectors with an AAV5 capsid (i.e., rAAV2/5) incorporated up to 8.9 kb of genome more efficiently than 6 other serotypes tested, independent of the efficiency of the rAAV2/5 production process. Efficient packaging of the large murine Abca4 and human MYO7A and CEP290 genes, which are mutated in common blinding diseases, was obtained, suggesting that this packaging efficiency is independent of the specific sequence packaged. Expression of proteins of the appropriate size and function was observed following transduction with rAAV2/5 carrying large genes. Intraocular administration of rAAV2/5 encoding ABCA4 resulted in protein localization to rod outer segments and significant and stable morphological and functional improvement of the retina in Abca4(-/-) mice. This use of rAAV2/5 may be a promising therapeutic strategy for recessive Stargardt disease, the most common form of inherited macular degeneration. The possibility of packaging large genes in AAV greatly expands the therapeutic potential of this vector system.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".