Differential Effects of Endocannabinoids on Amyloid-Beta Aggregation and Toxicity
Bibliographic record
Abstract
The regulation and metabolism of the endocannabinoid system has received extensive attention for their potential neuroprotective effect in neurodegenerative diseases such as Alzheimer's disease (AD), which is characterized by amyloid β (Aβ) -induced cell toxicity, inflammation, and oxidative stress. Using in vitro techniques and two cell lines, the mouse hippocampus-derived HT22 cells and Chinese hamster ovary (CHO) cells expressing human cannabinoid receptor type 1 (CB1), we investigated the ability of endocannabinoids to inhibit Aβ aggregation and protect cells against Aβ toxicity. The present study provides evidence that endocannabinoids N-arachidonoyl ethanol amide (AEA), noladin and O-arachidonoyl ethanolamine (OAE) inhibit Aβ42 aggregation. They were able to provide protection against Aβ42 induced cytotoxicity via receptor-mediated and non-receptor-mediated mechanisms in CB1-CHO and HT22 cells, respectively. The aggregation kinetic experiments demonstrate the anti-Aβ aggregation activity of some endocannabinoids (AEA, noladin). These data demonstrate the potential role and application of endocannabinoids in AD pathology and treatment.
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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".