Acute 5-HT7 receptor activation increases NMDA-evoked currents and differentially alters NMDA receptor subunit phosphorylation and trafficking in hippocampal neurons
Bibliographic record
Abstract
BACKGROUND: N-methyl-D-aspartate (NMDA) receptors are regulated by several G protein-coupled receptors (GPCRs) as well as receptor tyrosine kinases. Serotonin (5-HT) type 7 receptors are expressed throughout the brain including the thalamus and hippocampus. Long-term (2-24 h) activation of 5-HT7 receptors promotes the expression of neuroprotective growth factor receptors, including the platelet-derived growth factor (PDGF) β receptors which can protect neurons against NMDA-induced neurotoxicity. RESULTS: In contrast to long-term activation of 5-HT7 receptors, acute (5 min) treatment of isolated hippocampal neurons with the 5-HT7 receptor agonist 5-carboxamidotryptamine (5-CT) enhances NMDA-evoked peak currents and this increase in peak currents is blocked by the 5-HT7 receptor antagonist, SB 269970. In hippocampal slices, acute 5-HT7 receptor activation increases NR1 NMDA receptor subunit phosphorylation and differentially alters the phosphorylation state of the NR2B and NR2A subunits. NMDA receptor subunit cell surface expression is also differentially altered by 5-HT7 receptor agonists: NR2B cell surface expression is decreased whereas NR1 and NR2A surface expression are not significantly altered. CONCLUSIONS: In contrast to the negative regulatory effects of long-term activation of 5-HT7 receptors on NMDA receptor signaling, acute activation of 5-HT7 receptors promotes NMDA receptor activity. These findings highlight the potential for temporally differential regulation of NMDA receptors by the 5-HT7 receptor.
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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".