Assessing a Novel Dual-Endonuclease System in Restoring CFTR Expression in Cystic Fibrosis Models
Bibliographic record
Abstract
Cystic fibrosis (CF) is caused by dysfunction or absence of the CF Transmembrane Conductance Regulator (CFTR), a chloride channel essential for normal epithelial function. While CFTR modulators have been approved to enhance protein trafficking and function, they are not effective for all patients, particularly those with non-sense mutations, highlighting the need for gene therapy approaches. Dualase® is a dual-endonuclease system designed to improve editing efficiency by targeting two specific DNA sites while minimizing off-target effects. This study aimed to evaluate the efficacy of Dualase® in correcting G542X CFTR nonsense mutation in fetal lung progenitor cells (fLPs) and G542X humanized mouse models. Results demonstrated successful delivery of Dualase® to fLPs (mean 37.80%, SD=7.78) and to lungs of humanized mice via nebulization (mean 7.71%, SD=5.69) and intratracheal administration (mean 17.79%, SD=26.96). Additionally, forskolin-stimulated assays revealed CFTR channel activity averaging 11.86%, SD=7.73. These results support the potential of Dualase® as a therapeutic strategy for CF, especially in patients with rare mutations lacking effective treatments.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".