Noise-Induced Dysregulation of<i>Quaking</i>RNA Binding Proteins Contributes to Auditory Nerve Demyelination and Hearing Loss
Bibliographic record
Abstract
Noise exposure causes auditory nerve (AN) degeneration and hearing deficiency, though the proximal biological consequences are not entirely understood. Most AN fibers and spiral ganglion neurons are ensheathed by myelinating glia that provide insulation and ensure rapid transmission of nerve impulses from the cochlea to the brain. Here we show that noise exposure administered to mice of either sex rapidly affects myelinating glial cells, causing molecular and cellular consequences that precede nerve degeneration. This response is characterized by demyelination, inflammation, and widespread expression changes in myelin-related genes, including the RNA splicing regulator Quaking (QKI) and numerous QKI target genes. Analysis of mice deficient in QKI revealed that QKI production in cochlear glial cells is essential for proper myelination of spiral ganglion neurons and AN fibers, and for normal hearing. Our findings implicate QKI dysregulation as a critical early component in the noise response, influencing cochlear glia function that leads to AN demyelination and, ultimately, to hearing deficiency. SIGNIFICANCE STATEMENT Auditory glia cells ensheath a majority of spiral ganglion neurons with myelin, protect auditory neurons, and allow for fast conduction of electrical impulses along the auditory nerve. Here we show that noise exposure causes glial dysfunction leading to myelin abnormality and altered expression of numerous genes in the auditory nerve, including QKI, a gene implicated in regulating myelination. Study of a conditional mouse model that specifically depleted QKI in glia showed that QKI deficiency alone was sufficient to elicit myelin-related abnormality and auditory functional declines. These results establish QKI as a key molecular target in the noise response and a causative agent in hearing loss.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".