Bibliographic record
Abstract
After two decades of ups and downs, gene therapy has recently achieved a milestone in treating patients with Leber's congenital amaurosis (LCA). LCA is a group of inherited blinding diseases with retinal degeneration and severe vision loss in early infancy. Mutations in several genes, including RPE65, cause the disease. Using adeno-associated virus as a vector, three independent teams of investigators have recently shown that RPE65 can be delivered to retinal pigment epithelial cells of LCA patients by subretinal injections resulting in clinical benefits without side effects. However, considering the whole field of gene therapy, there are still major obstacles to clinical applications for other diseases. These obstacles include innate and immune barriers to vector delivery, toxicity of vectors and the lack of sustained therapeutic gene expression. Therefore, new strategies are needed to overcome these hurdles for achieving safe and effective gene therapy. In this article, we shall review the major advancements over the past two decades and, using lung gene therapy as an example, discuss the current obstacles and possible solutions to provide a roadmap for future gene therapy research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".