Group II Metabotropic Glutamate Receptor Stimulation Triggers Production and Release of Alzheimer's Amyloid β<sub>42</sub>from Isolated Intact Nerve Terminals
Bibliographic record
Abstract
Aberrant accumulation of amyloid beta (Abeta) oligomers may underlie the cognitive failure of Alzheimer's disease (AD). All species of Abeta peptides are produced physiologically during normal brain activity. Therefore, elucidation of mechanisms that interconnect excitatory glutamatergic neurotransmission, synaptic amyloid precursor protein (APP) processing and production of its metabolite, Abeta, may reveal synapse-specific strategies for suppressing the pathological accumulation of Abeta oligomers and fibrils that characterize AD. To study synaptic APP processing, we used isolated intact nerve terminals (cortical synaptoneurosomes) from TgCRND8 mice, which express a human APP with familial AD mutations. Potassium chloride depolarization caused sustained release from synaptoneurosomes of Abeta(42) as well as Abeta(40), and appeared to coactivate alpha-, beta- and gamma-secretases, which are known to generate a family of released peptides, including Abeta(40) and Abeta(42). Stimulation of postsynaptic group I metabotropic glutamate receptor (mGluRs) with DHPG (3,5-dihydroxyphenylglycine) induced a rapid accumulation of APP C-terminal fragments (CTFs) in the synaptoneurosomes, a family of membrane-bound intermediates generated from APP metabolized by alpha- and beta-secretases. Following stimulation with the group II mGluR agonist DCG-IV, levels of APP CTFs in the synaptoneurosomes initially increased but then returned to baseline by 10 min after stimulation. This APP CTF degradation phase was accompanied by sustained accumulation of Abeta(42) in the releasate, which was blocked by the group II mGluR antagonist LY341495. These data suggest that group II mGluR may trigger synaptic activation of all three secretases and that suppression of group II mGluR signaling may be a therapeutic strategy for selectively reducing synaptic generation of Abeta(42).
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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".