Developmental Decrease in NMDA Receptor Desensitization Associated with Shift to Synapse and Interaction with Postsynaptic Density-95
Bibliographic record
Abstract
NMDA receptors (NMDARs) play a crucial role in neuronal development, synaptic plasticity, and excitotoxicity; therefore, regulation of NMDAR function is important in both physiological and pathological conditions. Previous studies indicate that the NMDAR-mediated synaptic current decay rate increases during development because of a switch in receptor subunit composition, contributing to developmental changes in plasticity. To test whether NMDAR desensitization also changes during development, we recorded whole-cell NMDA-evoked currents in cultured rat hippocampal neurons. We found that glycine-independent desensitization of NMDARs decreases during development. This decrease was not dependent on a switch in subunit composition or differential receptor sensitivity to agonist-, Ca2+-, or Zn2+-induced increase in desensitization. Instead, several lines of evidence indicated that the developmental decrease in desensitization was tightly correlated with synaptic localization of the receptor, suggesting that association of NMDARs with proteins selectively expressed at synapses in mature neurons might account for developmental alterations in desensitization. Accordingly, we tested the role of interactions between PSD-95 (postsynaptic density-95) and NMDARs in regulating receptor desensitization. Overexpression of PSD-95 reduced NMDAR desensitization in immature neurons, whereas agents that interfere with synaptic targeting of PSD-95, or induce movement of NMDARs away from synapses and uncouple the receptor from PSD-95, increased NMDAR desensitization in mature neurons. We conclude that synaptic localization and association with PSD-95 increases stability of hippocampal neuronal NMDAR responses to sustained agonist exposure. Our results elucidate an additional mechanism for differentially regulating NMDAR function in neurons of different developmental stages or the response of subpopulations of NMDARs in a single neuron.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".