Convergence of PKC-Dependent Kinase Signal Cascades on NMDA Receptors
Bibliographic record
Abstract
Synaptic plasticity, or long-term potentiation (LTP), of excitatory synapses in the hippocampus contributes to learning and the establishment of spatial memories. In the CA1 region, induction of LTP enhances the function of postsynaptic alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionate receptors (AMPARs) because of the Ca2+-calmodulin kinase II (CaMKII)-dependent phosphorylation of this subtype of glutamate receptor. Entry of Ca2+, via N-methyl-D-aspartate receptors (NMDARs), during strong synaptic stimulation provides the stimulus to trigger phosphorylation of AMPARs. However, this induction also requires activation of a protein kinase C (PKC)-dependent tyrosine kinase signal cascade and a concomitant upregulation of NMDARs. This review focuses upon NMDARs as potential targets of PKC and/or of the PKC-dependent tyrosine kinase cascade. PKC, acting via the CAKbeta/Src tyrosine kinase cascade, enhances NMDAR activation and may increase the number of receptors expressed in synapses. In contrast, direct phosphorylation of NMDARs by PKC increases the sensitivity of NMDA channel inactivation to intracellular Ca2+. In CAI neurons, PKC provides a point of convergence of control of NMDARs and synaptic plasticity for a wide variety of G-protein coupled and growth factor receptors.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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".