The Effect of Aβ<sub>1-42</sub> Oligomers on APP Processing and Aβ<sub>1-40</sub> Generation in Cultured U-373 Astrocytes
Bibliographic record
Abstract
BACKGROUND: Amyloid-β (Aβ) peptides are a family of proteins that are considered to be a principal aspect of Alzheimer's disease (AD), the most common cause of senile dementia affecting elderly individuals. These peptides result from the proteolytic processing of amyloid precursor protein (APP) by sequential cleavage mediated via β- and x03B3;-secretases. Evidence suggests that an overproduction and/or a lack of degradation may increase brain Aβ levels which, in turn, contribute to neuronal loss and development of AD. OBJECTIVES: In this study, we seek to determine what effect Aβ has on APP processing in cultured astrocytes. METHODS: Using the human astrocytoma cell line U-373, we investigated the effects induced by oligomeric Aβ1-42 treatment on the cellular levels/expression of APP and its products, C-terminal fragments αCTF and βCTF, and Aβ1-40. In conjunction with these experiments, we examined the relative levels and activity of β- and x03B3;-secretases in Aβ-treated astrocytes. RESULTS: We report here that Aβ1-42 treatment of astrocytes increased the expression of APP and its cleaved products including Aβ1-40 in a time-dependent manner. CONCLUSIONS: These results suggest that activated astrocytes can contribute to the development of AD by enhancing levels and processing of APP leading to an increased production/secretion of Aβ-related peptides.
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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".