Physiological Basis of Noise-Induced Hearing Loss in a Tympanal Ear
Bibliographic record
Abstract
Acoustic overexposure, such as listening to loud music too often, results in noise-induced hearing loss. The pathologies of this prevalent sensory disorder begin within the ear at synapses of the primary auditory receptors, their postsynaptic partners and their supporting cells. The extent of noise-induced damage, however, is determined by overstimulation of primary auditory receptors, upstream of where the pathologies manifest. A systematic characterization of the electrophysiological function of the upstream primary auditory receptors is warranted to understand how noise exposure impacts on downstream targets, where the pathologies of hearing loss begin. Here, we used the experimentally-accessible locust ear (male, Schistocerca gregaria) to characterize a decrease in the auditory receptor's ability to respond to sound after noise exposure. Surprisingly, after noise exposure, the electrophysiological properties of the auditory receptors remain unchanged, despite a decrease in the ability to transduce sound. This auditory deficit stems from changes in a specialized receptor lymph that bathes the auditory receptors, revealing striking parallels with the mammalian auditory system. SIGNIFICANCE STATEMENT Noise exposure is the largest preventable cause of hearing loss. It is the auditory receptors that bear the initial brunt of excessive acoustic stimulation, because they must convert excessive sound-induced movements into electrical signals, but remain functional afterward. Here we use the accessible ear of an invertebrate to, for the first time in any animal, characterize changes in auditory receptors after noise overexposure. We find that their decreased ability to transduce sound into electrical signals is, most probably, due to changes in supporting (scolopale) cells that maintain the ionic composition of the ear. An emerging doctrine in hearing research is that vertebrate primary auditory receptors are surprisingly robust, something that we show rings true for invertebrate ears too.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".