A Novel Cell-based β-secretase Enzymatic Assay for Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: Deposition of the amyloid β protein (Aβ) into neuritic plaques is the neuropathological hallmark of Alzheimer's Disease (AD). Aβ is generated through the cleavage of the Amyloid Precursor Protein (APP) by β-secretase and γ-secretase. Currently, the evaluation of APP cleavage by β-secretase in experimental settings has largely depended on models that do not replicate the physiological conditions of this process. OBJECTIVE: To establish a novel live cell-based β-secretase enzymatic assay utilizing a novel chimeric protein that incorporates the natural sequence of APP and more closely replicates its cleavage by β-secretase under physiological conditions. METHODS: We have developed a chimeric protein construct, ASGβ, incorporating the β-site cleavage sequence of APP targeted by β-secretase and its intracellular trafficking signal into a Phosphatase-eGFP secreted reporter system. Upon cleavage by β-secretase, ASGβ releases a phosphatase-containing portion that can be measured in the culture medium, and an intracellular fraction that can be detected through Western Blot. Subsequently, we have generated a cell line stably expressing ASGβ that can be utilized to assay β-secretase in real time. RESULTS: ASGβ is specifically targeted by β-secretase, being cleaved exclusively at the site responsible for the generation of Aβ. Dosage response to β-secretase inhibitors shows that β-secretase activity can be positively correlated to phosphatase activity in culture media. CONCLUSION: Our findings suggest this system could be a high-throughput tool to screen compounds that aim to modulate β-secretase activity and Aβ production under physiological conditions, as well as evaluating factors that regulate this cleavage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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; both teacher heads agree on what is shown here.
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".