Aβ neurotoxicity depends on interactions between copper ions, prion protein, and <i>N</i> -methyl- <scp>d</scp> -aspartate receptors
Bibliographic record
Abstract
N-methyl-d-aspartate receptors (NMDARs) mediate critical CNS functions, whereas excessive activity contributes to neuronal damage. At physiological glycine concentrations, NMDAR currents recorded from cultured rodent hippocampal neurons exhibited strong desensitization in the continued presence of NMDA, thus protecting neurons from calcium overload. Reducing copper availability by specific chelators (bathocuproine disulfonate, cuprizone) induced nondesensitizing NMDAR currents even at physiologically low glycine concentrations. This effect was mimicked by, and was not additive with, genetic ablation of cellular prion protein (PrP(C)), a key copper-binding protein in the CNS. Acute ablation of PrP(C) by enzymatically cleaving its cell-surface GPI anchor yielded similar effects. Biochemical studies and electrophysiological measurements revealed that PrP(C) interacts with the NMDAR complex in a copper-dependent manner to allosterically reduce glycine affinity for the receptor. Synthetic human Aβ(1-42) (10 nM-5 μM) produced an identical effect that could be mitigated by addition of excess copper ions or NMDAR blockers. Taken together, Aβ(1-42), copper chelators, or PrP(C) inactivation all enhance the activity of glycine at the NMDAR, giving rise to pathologically large nondesensitizing steady-state NMDAR currents and neurotoxicity. We propose a physiological role for PrP(C), one that limits excessive NMDAR activity that might otherwise promote neuronal damage. In addition, we provide a unifying molecular mechanism whereby toxic species of Aβ(1-42) might mediate neuronal and synaptic injury, at least in part, by disrupting the normal copper-mediated, PrP(C)-dependent inhibition of excessive activity of this highly calcium-permeable glutamate receptor.
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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) | 0.000 | 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) | 0.000 | 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".