Analysis of beta-amyloid aggregation and amyloid precursor protein dimerization
Bibliographic record
Abstract
Alzheimer's Disease (AD) is a neuropathological disorder characterized by the progressive deposition of insoluble amyloid plaques and vascular deposits consisting primarily of 4.5 kDa amyloid beta peptides (Abeta). There is increasing evidence that the deposition of Abeta fibrils in the brain, an invariable feature of AD, and/or prefibrillar aggregates likely cause neurodegeneration in AD. While Abeta fibrils were a previous research focus, recent experiments implicate prefibrillar aggregates as the toxic species. The identification and characterization of prefibrillar aggregates is of great importance to understanding AD and the development of therapeutic strategies. Biophysical and spectroscopic techniques were used to examine the effects of electrostatic interactions on Abeta oligomerization. Experimental work demonstrated that, while salt bridges likely provide stability to preformed Abeta aggregates, these interactions are not essential for the early stages of aggregation. Abeta oligomerization is driven by the formation of pH-independent interactions and is impeded by electrostatic repulsion at pH values away from the isoelectric point. Diffuse plaques, containing only the 42-residue form of Abeta, are unstructured and non-toxic; they appear before toxic senile plaques containing both 40 and 42-residue forms. Through incubation, Abeta40 and Abeta42 were shown to co-incorporate into unstructured aggregates early during fibrillogenesis later leading to tightly packed aggregates with secondary structure. Previously, the stage at which the Abeta variants co-incorporated during the fibrillogenic process was unknown. After observing that the amyloid precursor protein transmembrane (APP-TM) domain contains two known dimerization motifs (GXXXG/A), oligomerization of the APP-TM domain was examined. A model system was developed to investigate the effects of familial AD mutations on the dimerization propensity of APP-TM domains. This work culminated in the first experimentally supported mechanism to explain how genetic mutations within the APP gene lead to the observed phenotype and predisposition to AD. Further experimentation led to the discovery of non-denaturing detergents that stabilize suspected on-pathway spherical Abeta aggregates. These detergent-stabilized Abeta oligomers share many of the structural features and biological activities of both membrane bound Abeta and spherical oligomers of Abeta formed in solution. Thus, these stabilizing detergents may prove useful in high-resolution structural analysis of spherical oligomers.
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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 | 0.001 |
| 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".