Reduced acoustic startle response and peripheral hearing loss in the<scp>5xFAD</scp>mouse model of Alzheimer's disease
Bibliographic record
Abstract
Hearing dysfunction has been associated with Alzheimer's disease (AD) in humans, but there is little data on the auditory function of mouse models of AD. Furthermore, characterization of hearing ability in mouse models is needed to ensure that tests of cognition that use auditory stimuli are not confounded by hearing dysfunction. Therefore, we assessed acoustic startle response and pre-pulse inhibition in the double transgenic 5xFAD mouse model of AD from 3-4 to 16 months of age. The 5xFAD mice showed an age-related decline in acoustic startle as early as 3-4 months of age. We subsequently tested auditory brainstem response (ABR) thresholds at 4 and 13-14 months of age using tone bursts at frequencies of 2-32 kHz. The 5xFAD mice showed increased ABR thresholds for tone bursts between 8 and 32 kHz at 13-14 months of age. Finally, cochleae were extracted and basilar membranes were dissected to count hair cell loss across the cochlea. The 5xFAD mice showed significantly greater loss of both inner and outer hair cells at the apical and basal ends of the basilar membrane than wild-type mice at 15-16 months of age. These results indicate that the 5xFAD mouse model of AD shows age-related decreases in acoustic startle responses, which are at least partially due to age-related peripheral hearing loss. Therefore, we caution against the use of cognitive tests that rely on audition in 5xFAD mice over 3-4 months of age, without first confirming that performance is not confounded by hearing dysfunction.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".