Arf6 controls beta-amyloid production by regulating macropinocytosis of the Amyloid Precursor Protein to lysosomes
Bibliographic record
Abstract
Alzheimer's disease (AD) is characterized by the deposition of Beta-Amyloid (Aβ) peptides in the brain. Aβ peptides are generated by cleavage of the Amyloid Precursor Protein (APP) by the β - and γ - secretase enzymes. Although this process is tightly linked to the internalization of cell surface APP, the compartments responsible are not well defined. We have found that APP can be rapidly internalized from the cell surface to lysosomes, bypassing early and late endosomes. Here we show by confocal microscopy and electron microscopy that this pathway is mediated by macropinocytosis. APP internalization is enhanced by antibody binding/crosslinking of APP suggesting that APP may function as a receptor. Furthermore, a dominant negative mutant of Arf6 blocks direct transport of APP to lysosomes, but does not affect classical endocytosis to endosomes. Arf6 expression increases through the hippocampus with the development of Alzheimer's disease, being expressed mostly in the CA1 and CA2 regions in normal individuals but spreading through the CA3 and CA4 regions in individuals with pathologically diagnosed AD. Disruption of lysosomal transport of APP reduces both Aβ40 and Aβ42 production by more than 30 %. Our findings suggest that the lysosome is an important site for Aβ production and that altering APP trafficking represents a viable strategy to reduce Aβ production.
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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 | 0.001 |
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".