Increased prion protein processing and expression of metabotropic glutamate receptor 1 in a mouse model of Alzheimer's disease
Bibliographic record
Abstract
Prion protein (PrP(C) ), a glycosylphosphatidylinositol-anchored protein corrupted in prion diseases, has been shown recently to interact with group I metabotropic glutamate receptors (mGluRs). Moreover, both PrP(C) and mGluRs were proposed to function as putative receptors for β-amyloid in Alzheimer's disease. PrP(C) can be processed in neurons via α or β-cleavage to produce PrP(C) fragments that are neuroprotective or toxic, respectively. We found PrP(C) α-cleavage to be 2-3 times higher in the cortex of APPswe/PS1dE9 mice, a mouse model of Alzheimer's disease. A similar age-dependent increase was observed for PrP(C) β-cleavage. Moreover, we observed considerable age-dependent increase in cortical expression of mGluR1, but not mGluR5. Exposure of cortical neuronal cultures to β-amyloid oligomers upregulated mGluR1 and PrP(C) α-cleavage, while activation of group I mGluRs increased PrP(C) shedding from the membrane, likely due to increased levels of a disintegrin and metalloprotease10, a key disintegrin for PrP(C) shedding. Interestingly, a similar increase in a disintegrin and metalloprotease10 was detected in the cortex of 9-month-old APPswe/PS1dE9 animals. Our experiments reveal novel and complex processing of PrP(C) in connection with mGluR overexpression that seems to be triggered by β-amyloid peptides. Prion protein (PrP(C) ) and metabotropic glutamate receptors (mGluR) are implicated in Alzheimer's disease (AD). We found age-dependent increase in PrP(C) processing, ADAM10 and mGluR1 levels in AD mouse model. These changes could be reproduced in cultured cortical neurons treated with Aβ peptide. Our findings suggest that increased levels of Aβ can trigger compensatory responses that may affect neuronal toxicity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".