Proteasome Activity in the Plasma as a Novel Biomarker in Mild Cognitive Impairment with Chronic Tinnitus
Bibliographic record
Abstract
BACKGROUND: Although the existence of proteasomes in human blood, termed circulating proteasomes (c-proteasomes), has been reported previously, their origin and pathophysiological functions remain largely unknown. OBJECTIVE: Given that c-proteasome activity was significantly reduced in Alzheimer's disease model mice and relatively high frequency of mild cognitive impairment (MCI) is accompanied by chronic tinnitus in aged patients, we examined whether c-proteasome activity in human plasma was associated with cognitive function in patients with chronic tinnitus. METHODS: c-Proteasome activity in the plasma of tinnitus patients (N = 55) was measured with fluorogenic reporter substrate, suc-LLVY-AMC. To assess MCI, the Montreal Cognitive Assessment was conducted with a cut-off score of 22/23. All patients underwent audiological and psychoacoustic analyses. Levels of c-proteasomes, Aβ42, and Aβ40 were measured using ELISA, and their association with c-proteasome activity was evaluated. RESULTS: The activity of circulating proteasomes was significantly lower in patients with chronic tinnitus and MCI (p = 0.042), whereas activities of other plasma enzymes showed little correlation. In addition, c-proteasome activity was negatively associated with the level of plasma Aβ and was directly dependent on its own concentration in the plasma of patients with chronic tinnitus. CONCLUSION: Our current work provides a new perspective for understanding the potential relationship between circulating proteasomes in the plasma and cognitive dysfunction, suggesting a novel, non-invasive biomarker in the context of MCI diagnosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".