Membrane cholesterol content plays a key role in the neurotoxicity of β‐amyloid: implications for Alzheimer’s disease
Bibliographic record
Abstract
Beta amyloid (βA) plays a central role in the pathogenesis of the most common and devastating neurodegenerative disorder, Alzheimer's disease (AD). The mechanisms of βA neurotoxicity remain controversial, but include dysregulation of calcium homeostasis and oxidative stress. A large body of data suggest that cholesterol plays a significant role in AD. In mixed cultures containing hippocampal neurons and astrocytes, we have shown that neurotoxic βA peptides (1-42 and 25-35) cause sporadic cytosolic calcium ([Ca(2+) ](c) ) signals in astrocytes but not in neurons, initiating a cascade that ends in neuronal death. We now show, using the cholesterol-sensitive fluorescent probe, Filipin, that membrane cholesterol is significantly higher in astrocytes than in neurons and mediates the selective response of astrocytes to βA. Thus, lowering [cholesterol] using mevastatin, methyl-β-cyclodextrin or filipin prevented the βA-induced [Ca(2+) ](c) signals, while increased membrane [cholesterol] increased βA-induced [Ca(2+) ](c) signals in both neurons and astrocytes. Addition of βA to lipid bilayers caused the appearance of a conductance that was significantly higher in membranes containing cholesterol. Increasing membrane [cholesterol] significantly increased βA-induced neuronal and astrocytic death. We conclude that a high membrane [cholesterol] promotes βA incorporation into membranes and increased [Ca(2+) ](c) leading to cell death.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".