Protein kinase C enhances glycine‐insensitive desensitization of NMDA receptors independently of previously identified protein kinase C sites
Bibliographic record
Abstract
Protein kinase C (PKC) phosphorylates the NR1 and NR2A subunits of NMDARs at consensus sites located within their intracellular C-terminal tails. However, the functional consequences of these biochemical events are not well understood. In HEK293 cells expressing NR1/NR2A, activation of endogenous PKC by 4beta-phorbol 12-myristate 13-acetate (PMA) increased NMDAR desensitization as evidenced by a reduced steady-state current without any change in peak. The effects of PMA on NMDAR-mediated responses were prevented by specific PKC inhibitors and were not mimicked by an inactive enantiomer of PMA. The effects of PMA were preserved despite mutagenesis of the major PKC sites on the NR1 subunit (S889A, S890A, S896A and S897A) or removal of the entire NR1 C-terminal tail (NR1(stop838)). When co-expressing NR1(stop838)/NR2A the effects of PMA could only be observed with agonist concentrations sufficient to induce glycine-insensitive desensitization. Moreover, the effects of PMA were observed in receptors composed of NR1/NR2A and NR1/NR2B, but not NR1/NR2C, a subunit combination in which desensitization is absent. The NR2 subunit dependence suggested that the actions of PMA might require specific PKC sites previously identified within NR2A. However, a C-terminal truncated form of NR2A (NR2A(stop905)) remained responsive to PMA. We conclude that activation of PKC increases NMDAR glycine-insensitive desensitization independently of previously identified sites located within the NR1 C-terminus and distal segment of the NR2A C-terminus.
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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 | 0.001 |
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".