Implication of Circulating Extracellular Vesicles-Bound Amyloid-β42 Oligomers in the Progression of Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: The perplex interrelation between circulating extracellular vesicles (cEVs) and amyloid-β (Aβ) deposits in the context of Alzheimer's disease (AD) is poorly understood. OBJECTIVE: This study aims to 1) analyze the possible cross-linkage of the neurotoxic amyloid-β oligomers (oAβ) to the human cEVs, 2) identify cEVs corona proteins associated with oAβ binding, and 3) analyze the distribution and expression of targeted cEVs proteins in preclinical participants converted to AD 5 years later (Pre-AD). METHODS: cEVs were isolated from 15 Pre-AD participants and 15 healthy controls selected from the Canadian Study of Health and Aging. Biochemical, clinical, lipid, and inflammatory profiles were measured. oAβ and cEVs interaction was determined by nanoparticle tracking analysis and proteinase K digestion. cEVs bound proteins were determined by ELISA. RESULTS: oAβ were trapped by cEVs and were topologically bound to their external surface. We identified surface-exposed proteins functionally able to conjugate oAβ including apolipoprotein J (apoJ), apoE and RAGE, with apoJ being 30- to 130-fold higher than RAGE and apoE, respectively. The expression of cEVs apoJ was significantly lower in Pre-AD up to 5 years before AD onset. CONCLUSION: Our findings suggest that cEVs might participate in oAβ clearance and that early dysregulation of cEVs could increase the risk of conversion to AD.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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".