Protective mutation A673T as a potential gene therapy for most forms of APP Familial Alzheimer’s Disease
Bibliographic record
Abstract
Abstract The accumulation of plaque in the brain leads to the onset and development of Alzheimer’s disease. The Amyloid precursor protein (APP) is usually cut by α-secretase, however an abnormal cleavage profile by β-secretase (BACE1) leads to the accumulation of Aβ peptides, which forms these plaques. Numerous APP gene mutations favor plaque accumulation, causing Familial Alzheimer Disease (FAD). However, a variant of the APP gene (A673T) in Icelanders reduces BACE1 cleavage by 40 %. A library of plasmids containing APP genes with 29 FAD mutations with or without the additional A673T mutation was generated and transfected in neuroblastomas to assess the effect of this mutation on Aβ peptide production. In most cases the production of Aβ peptides was decreased by the co-dominant A673T mutation. The reduction of Aβ peptide concentrations for the London mutation (V717I) even reached the same level as A673T carriers. These results suggest that the insertion of A673T in the APP gene of genetically susceptible FAD patients may prevent the onset of, slow down, or stop the progression of the disease.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".