Disruption of the autism-related gene Pak1 causes stereocilia disorganization, hair cell loss, and deafness in mice
Bibliographic record
Abstract
Several clinical studies have reported that hearing loss is correlated with autism in children. However, little is known about the underlying mechanism between hearing loss and autism. p21-activated kinases (PAKs) are a family of serine/threonine kinases that can be activated by multiple signaling molecules, particularly the Rho family of small GTPases. Previous studies have shown that Pak1 mutations are associated with autism. In the present study, we take advantage of Pak1 knockout (Pak1−/−) mice to investigate the role of PAK1 in hearing function. We find that PAK1 is highly expressed in the postnatal mouse cochlea and that PAK1 deficiency leads to hair cell (HC) apoptosis and severe hearing loss. Further investigation indicates that PAK1 deficiency downregulates the phosphorylation of cofilin and ezrin-radixin-moesin and the expression of βII-spectrin, which further decreases the HC synapse density in the basal turn of cochlea and disorganized the HC stereocilia in all three turns of cochlea in Pak1−/− mice. Overall, our work demonstrates that the autism-related gene Pak1 plays a crucial role in hearing function. As the first candidate gene linking autism and hearing loss, Pak1 may serve as a potential target for the clinical diagnosis of autism-related hearing loss.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".