Glycine-induced NMDA receptor internalization provides neuroprotection and preserves vasculature following ischemic stroke
Bibliographic record
Abstract
Abstract Ischemic stroke is the second leading cause of death worldwide. Compelling evidence demonstrates that following an ischemic event, neuronal death is triggered by uncontrolled glutamate release leading to overactivation of glutamate sensitive N-methyl-D-aspartate receptor (NMDAR). For gating, NMDARs require not only the binding of glutamate, but also the binding of glycine or a glycine-like compound as a co-agonist. Glycine fulfills several roles in biology including protein synthesis, inhibitory transmission via glycine receptor activation and excitatory transmission through NMDARs. Low glycine doses enhance NMDAR function while high doses trigger glycine-induced NMDAR internalization (GINI) in vitro. The physiological relevance of GINI has been questioned given that the high-affinity glycine transporter type 1 (GlyT1), located on astrocytes and neurons, maintains synaptic glycine concentrations far below the level that would saturate the glycine binding site (GBS). Here, we report that following an ischemic event, in vivo, GINI also occurs and provides neuroprotection. Mice pre-treated with a GlyT1 antagonist (GlyT1-A), which increases glycine synaptic levels, exhibited smaller stroke volume, reduced cell death, and minimized behavioural deficits following stroke induction by either photothrombosis or endothelin-1. Therefore, increasing glycine levels in the synaptic cleft will enhance GBS occupancy and will reach the set point to trigger GINI. However, we report that GINI is triggered during ischemic stroke, in vivo, only in the presence of GlyT1-As. Moreover, we show evidence that in ischemic conditions, GlyT1-As preserve the vasculature in the peri-infarct area. Therefore, the clinical efficacy of GlyT1-As should be tested for the treatment of ischemic stroke.
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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) | 0.001 | 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".