The β-Secretase BACE1 in Alzheimer’s Disease
Bibliographic record
Abstract
, which aggregates into bioactive conformational species and likely initiates toxicity in Alzheimer's disease (AD). BACE1 concentrations and rates of activity are increased in AD brains and body fluids, thereby supporting the hypothesis that BACE1 plays a critical role in AD pathophysiology. Therefore, BACE1 is a prime drug target for slowing down Aβ production in early AD. Besides the amyloidogenic pathway, BACE1 has other substrates that may be important for synaptic plasticity and synaptic homeostasis. Indeed, germline and adult conditional BACE1 knockout mice display complex neurological phenotypes. Despite BACE1 inhibitor clinical trials conducted so far being discontinued for futility or safety reasons, BACE1 remains a well-validated therapeutic target for AD. A safe and efficacious compound with high substrate selectivity as well as a more accurate dose regimen, patient population, and disease stage may yet be found. Further research should focus on the role of Aβ and BACE1 in physiological processes and key pathophysiological mechanisms of AD. The functions of BACE1 and the homologue BACE2, as well as the biology of Aβ in neurons and glia, deserve further investigation. Cellular and molecular studies of BACE1 and BACE2 knockout mice coupled with biomarker-based human research will help elucidate the biological functions of these important enzymes and identify their substrates and downstream effects. Such studies will have critical implications for BACE1 inhibition as a therapeutic approach for AD.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".