The Amyloid-β42 Proxy, Amyloid-β25-35, Induces Normal Human Cerebral Astrocytes to Produce Amyloid-β42
Bibliographic record
Abstract
Astrocytes in amyloid-β (Aβ)₄₂-accumulating human brains afflicted with Alzheimer's disease (AD) upregulate vascular endothelial growth factor (VEGF)-A synthesis and also become loaded with Aβ₄₂. We have already shown that Aβ(25-35) (surrogate of Aβ₄₂)-induced VEGF-A production in 'normoxic' cultures of early passage normal human cerebral astrocytes (NAHAs) is mediated by the stabilization of VEGF gene-stimulating hypoxia-inducible factor (HIF)-1α and nuclear translocation of HIF-1α•HIF-1β complexes. We have now found that treating these NAHAs with Aβ(25-35) also stimulates them to make Aβ₄₂ (appearing in immunoblots as several bands with M(r)'s from 8 kDa upwards), whose levels peak at 48 h (2.8-fold versus 0 h, p < 0.001) and then start falling slowly. This rise of Aβ₄₂ peptide production coincides with a transiently increased flow of HIF-1α (therefore HIF-1α•HIF-1β complexes; at 24 h, 1.5-fold versus 0 h, p < 0.001) into the nucleus and transient surges first of β-secretase (BACE-1/β-S) mRNA expression (1.2-fold versus 0 h, p = 0.013) and activity peaking at 24-h (1.4-fold versus 0 h, p = 0.001), and then of γ-secretase (γ-S) activity cresting at 48 h (1.6-fold versus 0 h, p < 0.001) that cleave the Aβ₄₂ peptides from amyloid-β protein precursor. Since the genes encoding components of these two secretases have the same HIF-1α•HIF-1β-responsive elements in their promoters as the VEGF gene, these observations suggest that the Aβ₄₂ released from neurons in the AD brain can recruit associated astrocytes via HIF-1α•HIF-1β signaling into the pool of Aβ₄₂-producing cells. In other words, Aβ₄₂ begets Aβ₄₂ in NAHAs.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".