Brain Expression of Presenilins in Sporadic and Early-onset, Familial Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: Mutations in the presenilin proteins cause early-onset, familial Alzheimer's disease (FAD). MATERIALS AND METHODS: We characterized the cellular localization and endoproteolysis of presenilin 2 (PS2) and presenilin 1 (PS1) in brains from 25 individuals with presenilin-mutations causing FAD, as well as neurologically normal individuals and individuals with sporadic Alzheimer's disease (AD). RESULTS: Amino-terminal antibodies to both presenilins predominantly decorated large neurons. Regional differences between the broad distributions of the two presenilins were greatest in the cerebellum, where most Purkinje cells showed high levels of only PS2 immunoreactivity. PS2 endoproteolysis in brain yielded multiple amino-terminal fragments similar in size to the PS1 amino-terminal fragments detected in brain. In addition, two different PS2 amino-terminal antibodies also detected a prominent 42 kDa band that may represent a novel PS2 form in human brain. Similar to PS1 findings, neither amino-terminal nor antiloop PS2 antibodies revealed substantial full-length PS2 in brain. Immunocytochemical examination of brains from individuals with the N141I PS2 mutation or eight different PS1 mutations, spanning the molecule from the second transmembrane domain to the large cytoplasmic loop domain, revealed immunodecoration of no senile plaques and only neurofibrillary tangles in the M139I PS1 mutation stained with PS1 antibodies. CONCLUSIONS: Overall presenilin expression and the relative abundance of full-length and amino-terminal fragments in presenilin FAD cases were similar to control cases and sporadic AD cases. Thus, accumulation of full-length protein or other gross mismetabolism of neither PS2 nor PS1 is a consequence of the FAD mutations examined.
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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 | 0.001 | 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) | 0.001 | 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".