Tripartite signalling by NMDA receptors
Bibliographic record
Abstract
Abstract N -methyl- d -aspartate receptors (NMDARs) are excitatory glutamatergic receptors that are fundamental for many neuronal processes, including synaptic plasticity. NMDARs are comprised of four subunits derived from heterogeneous subunit families, yielding a complex diversity in NMDAR form and function. The quadruply-liganded state of binding of two glutamate and two glycine molecules to the receptor drives channel gating, allowing for monovalent cation flux, Ca 2+ entry and the initiation of Ca 2+ -dependent signalling. In addition to this ionotropic function, non-ionotropic signalling can be initiated through the exclusive binding of glycine or of glutamate to the NMDAR. This binding may trigger a transmembrane conformational change of the receptor, inducing intracellular protein-protein signalling between the cytoplasmic domain and secondary messengers. In this review, we outline signalling cascades that can be activated by NMDARs and propose that the receptor transduces signalling through three parallel streams: (i) signalling via both glycine and glutamate binding, (ii) signalling via glycine binding, and (iii) signalling via glutamate binding. This variety in signal transduction mechanisms and downstream signalling cascades complements the widespread prevalence and rich diversity of NMDAR activity throughout the central nervous system and in disease pathology.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".