Endogenous Pituitary Adenylate Cyclase-Activating Polypeptide (PACAP) Plays a Protective Effect Against Noise-Induced Hearing Loss
Bibliographic record
Abstract
Pituitary adenylyl cyclase-activating polypeptide (PACAP) is a member of the vasoactive intestinal polypeptide (VIP)-the secretin-glucagon family of neuropeptides. They act through two classes of receptors: PACAP type 1 (PAC1) and type 2 (VPAC1 and VPAC2). Among their pleiotropic effects throughout the body, PACAP functions as neuromodulators and neuroprotectors, rescuing neurons from apoptosis, mostly through the PAC1 receptor. To explore the potential protective effect of endogenous PACAP against Noise-induced hearing loss (NIHL), we used a knockout mouse model lacking PAC1 receptor expression (PACR1−/−) and a transgenic humanized mouse model expressing the human PAC1 receptor (TgHPAC1R). Based on complementary approaches combining electrophysiological, histochemical, and molecular biological evaluations, we show PAC1R expression in spiral ganglion neurons and in cochlear apical cells of the organ of Corti. Wild-type (WT), PAC1R−/−, and TgHPAC1R mice exhibit similar auditory thresholds. For most of the frequencies tested after acute noise damage, however, PAC1R−/− mice showed a larger elevation of the auditory threshold than did their WT counterparts. By contrast, in a transgene copy number-dependent fashion, TgHPAC1R mice showed smaller noise-induced elevations of auditory thresholds compared to their WT counterparts. Together, these findings suggest that PACAP could be a candidate for endogenous protection against noise-induced 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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 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".