Alzheimer's Disease‐Related Analytes Amyloid‐β and Tau in Perilymph: Correlation With Patient Age and Cognitive Score
Bibliographic record
Abstract
Abstract Objective To describe the collection methods for perilymph fluid biopsy during cochlear implantation, detect levels of amyloid β 42 and 40 (Aβ42 and Aβ40), and total tau (tTau) analytes with a high‐precision assay, to compare these levels with patient age and Montreal Cognitive Assessment (MoCA) scores, and explore potential mechanisms and relationships with otic pathology. Study Design Prospective study. Setting Tertiary referral center. Methods Perilymph was collected from 25 patients using polyimide tubing to avoid amyloid adherence to glass, and analyzed with a single‐molecule array advanced digital enzyme‐linked immunosorbent assay platform for Aβ40, Aβ42, and tTau. Cognition was assessed by MoCA. Results Perilymph volumes ranged from ∼1 to 13 µL, with analyte concentrations spanning 2.67 to 1088.26 pg/mL. All samples had detectable levels of tTau, Aβ40, and Aβ42, with a significant positive correlation between Aβ42 and Aβ40 levels. Levels of Aβ42, Aβ40, and tTau were positively correlated with age, while MoCA scores were inversely correlated with age. tTau and Aβ42/Aβ40‐ratios were significantly correlated with MoCA scores. Conclusion Alzheimer's disease‐associated peptides Aβ42, Aβ40, and tau analytes are detectable in human perilymph at levels approximately 10‐fold lower than those found in cerebrospinal fluid (CSF). These species increase with age and correlate with cognitive impairment indicators, suggesting their potential utility as biomarkers for cognitive impairment in patients undergoing cochlear implantation. Future research should investigate the origin of these analytes in the perilymph and their potential links to inner ear pathologies and hearing loss, as well as their relationships to CSF and plasma levels in individuals.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".