Opposing Roles of Synaptic and Extrasynaptic NMDA Receptor Signaling in Cocultured Striatal and Cortical Neurons
Bibliographic record
Abstract
The NMDAR plays a unique and vital role in subcellular signaling. Calcium influx initiates signaling cascades important for both synaptic plasticity and survival; however, overactivation of the receptor leads to toxicity and cell death. This dichotomy is partially explained by the subcellular location of the receptor. NMDARs located at the synapse stimulate cell survival pathways, while extrasynaptic receptors signal for cell death. Thus far, this interplay between synaptic and extrasynaptic NMDARs has been studied exclusively in cortical (CTX) and hippocampal neurons. It was unknown whether other cell types, such as GABAergic medium-sized spiny projection neurons of the striatum (MSNs), which bear the brunt of neurodegeneration in Huntington's disease, follow the same pattern. Here we report synaptic versus extrasynaptic NMDAR signaling in striatal MSNs and resultant activation of cAMP response element binding protein (CREB), in rat primary corticostriatal cocultures. Similarly to CTX, we found in striatal MSNs that synaptic NMDARs activate CREB, whereas extrasynaptic NMDARs dominantly oppose CREB activation. However, MSNs are much less susceptible to NMDA-mediated toxicity than CTX cells and show differences in subcellular GluN2B distribution. Blocking NMDARs with memantine (30 μm) or GluN2B-containing receptors with ifenprodil (3 μm) prevents CREB shutoff effectively in CTX and MSNs, and also rescues both neuronal types from NMDA-mediated toxicity. This work may provide cell and NMDAR subtype-specific targets for treatment of diseases with putative NMDAR involvement, including neurodegenerative disorders and ischemia.
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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 | 0.001 | 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".