Identification of a New Presenilin-dependent ζ-Cleavage Site within the Transmembrane Domain of Amyloid Precursor Protein
Bibliographic record
Abstract
Gamma-secretase cleavage of beta-amyloid precursor protein (APP) is crucial in the pathogenesis of Alzheimer disease, because it is the decisive step in the formation of the C terminus of beta-amyloid protein (Abeta). To better understand the molecular events involved in gamma-secretase cleavage of APP, in this study we report the identification of a new intracellular long Abeta species containing residues 1-46 (Abeta46), which led to the identification of a novel zeta-cleavage site between the known gamma- and epsilon-cleavage sites within the transmembrane domain of APP. Our data clearly demonstrate that the new zeta-cleavage is a presenilin-dependent event. It is also noted that the new zeta-cleavage site at Abeta46 is the APP717 mutation site. Furthermore, we show that the new zeta-cleavage is inhibited by gamma-secretase inhibitors known as transition state analogs but less affected by inhibitors known as non-transition state gamma-secretase inhibitors. Thus, the identification of Abeta46 establishes a system to determine the specificity or the preference of the known gamma-secretase inhibitors by examining their effects on the formation or turnover of Abeta46.
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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 | 0.001 |
| 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".