Interaction of human and mouse Aβ peptides
Bibliographic record
Abstract
Transgenic mice over-expressing mutant human amyloid precursor protein have become an important tool for research on Alzheimer's disease (AD) and, in particular, for therapeutic screening. Many models have reported formation of amyloid plaques with age as is detected in AD. However, the plaques generated in transgenic mice are more soluble than human plaques. Differences in solubility may occur for a number of reasons; one proposal is the presence of murine Abeta peptides within the CNS milieu. Here, we report the interaction of human and murine Abeta peptides, Abeta40 and Abeta42, utilizing a fluorescence assay to monitor formation of mixed pre-fibrillar aggregates, electron microscopy to examine morphological characteristics and detergent solubility to monitor stability. Our results demonstrate that interspecies Abeta aggregates and fibres are readily formed and are more stable than homogenous human fibres. Furthermore, these results suggest that the presence of endogenous murine Abeta in human APP transgenic mice does not account for the increased solubility of plaques.
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) | 0.000 | 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) | 0.002 | 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".