<scp>BACE</scp>2 degradation mediated by the macroautophagy–lysosome pathway
Bibliographic record
Abstract
Neuritic plaque is the pathological hallmark in Alzheimer's disease (AD). Amyloid-β protein (Aβ), the central component of neuritic plaques, is generated from amyloid-β precursor protein (APP) by β-site APP cleaving enzyme 1 (BACE1) and γ-secretase. β-site APP cleaving enzyme 2 (BACE2), a homolog of BACE1, functions differently from BACE1 in APP processing. BACE1 is the β-secretase essential for Aβ production, and BACE2, a θ-secretase, cleaves APP within the Aβ domain, preventing Aβ production. Elucidation of the mechanism underlying BACE2 degradation is important for defining its biological features and its potential role in Alzheimer's disease drug development. In this report we first showed that the half-life of BACE2 is approximately 20 h. Lysosomal inhibition increased BACE2 protein levels whereas proteasomal inhibition had no effect on BACE2 protein expression. Furthermore, we identified that macroautophagy mediated BACE2 degradation. Finally, we showed that lysosomal inhibition increased BACE2 cleavage of APP. Taken together, our in vitro study showed that BACE2 is degraded through the macrophagy-lysosome pathway and that lysosomal inhibition affects BACE2 processing of APP. Modulation of BACE2 degradation via the lysosomal pathway could be a new target for AD drug development.
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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) | 0.002 | 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".