Dissociated phenotypes in presenilin transgenic mice define functionally distinct γ-secretases
Bibliographic record
Abstract
Gamma-secretase depends on presence of presenilins (PS), Nct, Aph-1, and PEN-2 within a core complex. This endoproteolytic activity cleaves within transmembrane domains of amyloid-beta precursor protein (APP) and Notch, and familial Alzheimer's disease (FAD) mutations in PS1 or PS2 genes shift APP cleavage from production of amyloid-beta (Abeta) 40 peptide to greater production of Abeta42. Although studies in PS1/PS2-deficient embryonic cells define overlapping activities for these proteins, in vivo complementation of PS1-deficient animals described here reveals an unexpected spectrum of activities dictated by PS1 and PS2 alleles. Unlike PS1 transgenes, wild-type PS2 transgenes expressed in the mouse CNS support little Abeta40 or Abeta42 production, and FAD PS2 alleles support robust production of only Abeta42. Although wild-type PS2 transgenes failed to rescue Notch-associated skeletal defects in PS1 hypomorphs, a "gained" competence in this regard was apparent for FAD alleles of PS2. The range of discrete and divergent processing activities in mice reconstituted with different PS genes and alleles argues against gamma-secretase being a single enzyme with intrinsically relaxed substrate and cleavage site specificities. Instead, our studies define functionally distinct gamma-secretase variants. We speculate that extrinsic components, in combination with core complexes, may tailor functional variants of this enzyme to their preferred substrates.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".