A promoterless AAV6.2FF-based lung gene editing platform for the correction of surfactant protein B deficiency
Bibliographic record
Abstract
Surfactant protein B (SP-B) deficiency is a rare genetic disease that causes fatal respiratory failure within the first year of life. Currently, the only corrective treatment is lung transplantation. Here, we co-transduced the murine lung with adeno-associated virus 6.2FF (AAV6.2FF) vectors encoding a SaCas9-guide RNA nuclease or donor template to mediate insertion of promoterless reporter genes or the (murine) Sftpb gene in frame with the endogenous surfactant protein C (SP-C) gene, without disrupting SP-C expression. Intranasal administration of 3 × 10 11 vg donor template and 1 × 10 11 vg nuclease consistently edited approximately 6% of lung epithelial cells. Frequency of gene insertion increased in a dose-dependent manner, reaching 20%–25% editing efficiency with the highest donor template and nuclease doses tested. We next evaluated whether this promoterless gene editing platform could extend survival in the conditional SP-B knockout mouse model. Administration of 1 × 10 12 vg SP-B-donor template and 5 × 10 11 vg nuclease significantly extended median survival (p = 0.0034) from 5 days in the untreated off doxycycline group to 16 days in the donor AAV and nuclease group, with one gene-edited mouse living 243 days off doxycycline. This AAV6.2FF-based gene editing platform has the potential to correct SP-B deficiency, as well as other disorders of alveolar type II cells.
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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 | 0.001 | 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".