Aggregation State and Neurotoxic Properties of Alzheimer β-Amyloid Peptide
Bibliographic record
Abstract
Alzheimer's disease (AD) represents the most common form of senile dementia and represents a tremendous health problem as the world population is aging. AD is characterized by the accumulation of amyloid β-peptide (Aβ) in the brain and the loss of cholinergic neurons in the basal forebrain. Accumulation of soluble and insoluble assemblies of Aβ in the brain is a crucial event in AD pathogenesis and the presence of amyloid plaques in the brain is required for definitive identification of AD. Yet, there is no correlation between amyloid plaques and the degree of dementia. In the past two decades researchers have devoted their effort to study and explain the mechanisms involved in the pathology of this devastating disease. Studies from different areas of the natural and medical sciences have provided important information towards the elucidation of some of the pathological processes that take place in AD. An aspect of crucial importance is the aggregation state of Aβ peptide and its role in neuropathology. Here, we discuss recent studies aimed at the identification of Aβ protein aggregates, the characterization of their toxic potential and the development of therapeutic strategies that target Aβ aggregation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".