Altered processing of amyloid precursor protein in the human neuroblastoma SH‐SY5Y by chronic hypoxia
Bibliographic record
Abstract
Alzheimer's disease (AD) is more prevalent following an ischemic or hypoxic episode, such as stroke. Indeed, brain levels of amyloid precursor protein (APP) and the cytotoxic amyloid beta peptide (Abeta) fragment are enhanced in these patients and in animal models following experimental ischaemia. We have investigated the effect of chronic hypoxia (CH; 2.5% O2, 24 h) on processing of APP in the human neuroblastoma, SH-SY5Y. We demonstrate that constitutive and muscarinic-receptor-enhanced secretion of the alpha-secretase cleaved fragment of APP, sAPPalpha, was reduced by approximately 60% in CH cells. The caspase inhibitor BOC-D(Ome)FMK did not reverse this effect of CH, and CH cells were as viable as controls, based on MTT assays. Thus, loss of sAPPalpha is not related to cell death or caspase processing of APP. Pre-incubation with antioxidants did not reverse the effect of CH, and the effect could not be mimicked by H2O2, discounting the involvement of reactive oxygen species in hypoxic loss of sAPPalpha. CH did not affect muscarinic activation of extracellular-signal regulated kinase. However, expression of ADAM 10 (widely believed to be alpha-secretase) was decreased approximately 50% following CH. Thus, CH selectively decreases processing of APP by the alpha-secretase pathway, most likely by decreasing levels of ADAM 10.
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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 | 0.000 |
| 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".