Gene Transfer with AAV9-PHP.B Rescues Hearing in a Mouse Model of Usher Syndrome 3A and Transduces Hair Cells in a Non-human Primate
Bibliographic record
Abstract
Hereditary hearing loss often results from mutation of genes expressed by cochlear hair cells. Gene addition using AAV vectors has shown some efficacy in mouse models, but clinical application requires two additional advances. First, new AAV capsids must mediate efficient transgene expression in both inner and outer hair cells of the cochlea. Second, to have the best chance of clinical translation, these new vectors must also transduce hair cells in non-human primates. Here, we show that an AAV9 capsid variant, PHP.B, produces efficient transgene expression of a GFP reporter in both inner and outer hair cells of neonatal mice. We show also that AAV9-PHP.B mediates almost complete transduction of inner and outer HCs in a non-human primate. In a mouse model of Usher syndrome type 3A deafness (gene CLRN1 ), we use AAV9-PHP.B encoding Clrn1 to partially rescue hearing. Thus, we have identified a vector with promise for clinical treatment of hereditary hearing disorders, and we demonstrate, for the first time, viral transduction of the inner ear of a primate with an AAV vector.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".