Circulating and Extracellular Vesicles Levels of N-(1-Carboxymethyl)-L-Lysine (CML) Differentiate Early to Moderate Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: Both advanced glycation end products (AGEs) N-(1-carboxymethyl)-L-lysine (CML) and pentosidine were found in the brain from Alzheimer's disease (AD) patients and were associated with the neuropathological hallmarks of AD. In AD patients, the circulating level of both AGEs remains unknown. Moreover, their levels in peripheral extracellular vesicles (EVs) and their association with AD remain to be determined. Finally, it is not known if neuronal cells can release AGEs via EVs and propagate AGEs. OBJECTIVE: To determine the levels of circulating CML and pentosidine during the progression of AD. Moreover, their levels in circulating EVs were determined and their association with the clinical cognitive scores were analyzed. Finally, we have studied the possibility that neuronal cells eliminate and transfer these AGEs through EVs. METHODS: CML and pentosidine levels were measured in serum and in circulating EVs. Released-EVs from SK-N-SH neuronal cells were isolated and CML levels were also determined. RESULTS: The levels of CML in albumin-free serum proteins were higher in the early stage of AD while the levels of pentosidine remained unchanged. In contrast, the levels of CML in the EVs were lower in the moderate stage of AD. Interestingly, the levels of CML in serum were negatively correlated with the clinical cognitive scores MMSE and MoCA. For the first time, we were able to demonstrate that CML was present in EVs released from neuronal cells in culture. CONCLUSION: Peripheral and circulating EVs levels of CML can differentiate early to moderate AD. In the brain, neuronal CML can propagate from cells-to-cells via EVs.
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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 | 0.000 | 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".