Bibliographic record
Abstract
In this article, we support the case that the neurotoxic agent in Alzheimer's disease is a soluble aggregated form of the amyloid beta peptide (Abeta), probably complexed with divalent copper. The structure and chemical properties of the monomeric peptide and its Cu(ii) complex are discussed, as well as what little is known about the oligomeric species. Abeta oligomers are neurotoxic by a variety of mechanisms. They adhere to plasma and intracellular membranes and cause lesions by a combination of radical-initiated lipid peroxidation and formation of ion-permeable pores. In endothelial cells this damage leads to loss of integrity of the blood-brain barrier and loss of blood flow to the brain. At synapses, the oligomers close neuronal insulin receptors, mirroring the effects of Type II diabetes. In intracellular membranes, the most damaging effect is loss of calcium homeostasis. The oligomers also bind to a variety of substances, mostly with deleterious effects. Binding to cholesterol is accompanied by its oxidation to products that are themselves neurotoxic. Possibly most damaging is the binding to tau, and to several kinases, that results in the hyperphosphorylation of the tau and abrogation of its microtubule-supporting role in maintaining axon structure, leading to diseased synapses and ultimately the death of neurons. Several strategies are presented and discussed for the development of compounds that prevent the oligomerization of Abeta into the neurotoxic species.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".