Overcoming the Undesirable CRISPR-Cas9 Expression in Gene Correction
Bibliographic record
Abstract
The CRISPR-Cas9 system is attractive for gene therapy, as it allows for permanent genetic correction. However, as a new technology, Cas9 gene editing in clinical applications faces major challenges, such as safe delivery and gene targeting efficiency. Cas9 is a foreign protein to recipient cells; thus, its expression may prompt the immune system to eliminate gene-edited cells. To overcome these challenges, we have engineered a novel delivery system based on the helper-dependent adenoviral (HD-Ad) vector, which is capable of delivering genes to airway basal stem cells in vivo. Using this system, we demonstrate the successful co-delivery of both CRISPR-Cas9/single-guide RNA and the LacZ reporter or CFTR gene as donor DNA to cultured cells. HD-Ad vector genome integrity is compromised following donor DNA integration, and because the CRISPR-Cas9/single-guide RNA and donor DNA are carried on the same vector, CRISPR-Cas9 expression is concurrently eliminated. Thus, we show the feasibility of site-specific gene targeting with limited Cas9 expression. In addition, we achieved stable CFTR expression and functional correction in cultured cells following successful gene integration.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".