Ribbon Synapse Plasticity in the Cochleae of Guinea Pigs after Noise-Induced Silent Damage
Bibliographic record
Abstract
Noise exposure at low levels or low doses can damage hair cell afferent ribbon synapses without causing permanent threshold shifts. In contrast to reports in the mouse cochleae, initial damage to ribbon synapses in the cochleae of guinea pigs is largely repairable. In the present study, we further investigated the repair process in ribbon synapses in guinea pigs after similar noise exposure. In the control samples, a small portion of afferent synapses lacked synaptic ribbons, suggesting the co-existence of conventional no-ribbon and ribbon synapses. The loss and recovery of hair cell ribbons and post-synaptic densities (PSDs) occurred in parallel, but the recovery was not complete, resulting in a permanent loss of less than 10% synapses. During the repair process, ribbons were temporally separated from the PSDs. A plastic interaction between ribbons and postsynaptic terminals may be involved in the reestablishment of synaptic contact between ribbons and PSDs, as shown by location changes in both structures. Synapse repair was associated with a breakdown in temporal processing, as reflected by poorer responses in the compound action potential (CAP) of auditory nerves to time-stress signals. Thus, deterioration in temporal processing originated from the cochlea. This deterioration developed with the recovery in hearing threshold and ribbon synapse counts, suggesting that the repaired synapses had deficits in temporal processing.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".