Clarin-2 gene supplementation durably preserves hearing in a model of progressive hearing loss
Bibliographic record
Abstract
Hearing loss is a major health concern affecting millions of people worldwide with currently limited treatment options. In clarin-2-deficient Clrn2 −/− mice, used here as a model of progressive hearing loss, we report synaptic auditory abnormalities in addition to the previously demonstrated defects of hair bundle structure and mechanoelectrical transduction. We sought an in-depth evaluation of viral-mediated gene delivery as a therapy for these hearing-impaired mice. Supplementation with either the murine Clrn2 or human CLRN2 genes preserved normal hearing in treated Clrn2 −/− mice. Conversely, mutated forms of CLRN2 , identified in patients with post-lingual moderate to severe hearing loss, failed to prevent hearing loss. The ectopic expression of clarin-2 successfully prevented the loss of stereocilia, maintained normal mechanoelectrical transduction, preserved inner hair cell synaptic function, and ensured near-normal hearing thresholds over time. Maximal hearing preservation was observed when Clrn2 was delivered prior to the loss of transducing stereocilia. Our findings demonstrate that gene therapy is effective for the treatment of post-lingual hearing impairment and age-related deafness associated with CLRN2 patient mutations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".