Cellular Membrane Composition Defines Aβ-Lipid Interactions
Bibliographic record
Abstract
Alzheimer's disease pathology has demonstrated amyloid plaque formation associated with plasma membranes and the presence of intracellular amyloid-beta (A beta) accumulation in specific vesicular compartments. This suggests that lipid composition in different compartments may play a role in A beta aggregation. To test this hypothesis, we have isolated cellular membranes from human brain to evaluate A beta 40/42-lipid interactions. Plasma, endosomal, lysosomal, and Golgi membranes were isolated using sucrose gradients. Electron microscopy demonstrated that A beta fibrillogenesis is accelerated in the presence of plasma and endosomal and lysosomal membranes with plasma membranes inducing an enhanced surface organization. Alternatively, interaction of A beta with Golgi membranes fails to progress to fibril formation, suggesting that A beta-Golgi head group interaction stabilizes A beta. Fluorescence spectroscopy using the environment-sensitive probes 1,6-diphenyl-1,3,5-hexatriene, laurdan, N-epsilon-dansyl-L-lysine, and merocyanine 540 demonstrated variations in the inherent lipid properties at the level of the fatty acyl chains, glycerol backbone, and head groups, respectively. Addition of A beta 40/42 to the plasma and endosomal and lysosomal membranes decreases the fluidity not only of the fatty acyl chains but also the head group space, consistent with A beta insertion into the bilayer. In contrast, the Golgi bilayer fluidity is increased by A beta 40/42 binding which appears to result from lipid head group interactions and the production of interfacial packing defects.
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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".