Alzheimer's disease: β‐amyloid plaque formation in human brain
Bibliographic record
Abstract
Although the precise cause of Alzheimer's disease is not known, the β-amyloid peptide chains of 40-42 amino acids are suspected to contribute to the disease. The β-amyloid precursor protein is found on many types of cell membranes, and the action of secretases (β and γ) on this precursor protein normally releases the β-amyloids at a high rate into the plasma and the cerebrospinal fluid. However, the concentrations of the β-amyloids in the plasma and the spinal fluid vary considerably between laboratories. The β-amyloids adsorb in the nanomolar concentration range to receptors on neuronal and glial cells. The β-amyloids are internalized, become folded in the β-folded or β-pleated shape, and then stack on each other to form long fibrils and aggregates known as plaques. The β-amyloids likely act as monomers, dimers, or multimers on cell membranes to interfere with neurotransmission and memory before the plaques build up. Treatment strategies include inhibitors of β- and γ-secretase, as well as drugs and physiological compounds to prevent aggregation of the amyloids. Several immune approaches and a cholesterol-lowering strategy are also being tested to remove the β-amyloids.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".