Presynaptic G Protein‐Coupled Receptors Differentially Modulate Spontaneous Glutamate Release in the Supraoptic Nucleus
Bibliographic record
Abstract
Spontaneous glutamate release in the supraoptic nucleus is modulated by a number of inhibitory G protein coupled receptors (GPCR), including GABAB , adenosine A1 and group III metabotropic glutamate receptors (mGluR). It remains unclear whether they have distinct roles or are redundant mechanisms that protect from hyperexcitation. To address this question, we facilitated spontaneous glutamate release using nifedipine or forskolin, which act in a protein kinase A (PKA)-independent and -dependent manner, respectively, and tested the effects of inhibitory GPCR agonists. We found that a GABAB receptor (GABAB R) agonist specifically inhibited forskolin-induced miniature excitatory postsynaptic currents (mEPSC), in contrast to an adenosine A1 receptor (A1R) agonist, which specifically inhibited nifedipine-induced mEPSCs. This suggests that GABAB Rs and A1 Rs modulate independent mechanisms activated by forskolin and nifedipine, respectively. However, the inhibitory effects of GABAB R and A1 R agonists on basal mEPSCs occluded each other, suggesting that these receptors also have an overlapping role. Group III mGluRs appear to have a greater control over glutamate release because agonists to these receptors inhibited both nifedipine- and forskolin-induced mEPSCs. mEPSCs induced by norepinephrine had the same characteristics as those induced by forskolin [i.e. PKA-dependence and sensitivity to GABAB R and group III mGluR agonists, but not an A1 R agonist]. In summary, the present study highlights the differential effects of GABAB R, A1 R and mGluR agonists on glutamate release stimulated by different secretagogues, including the endogenous neuromodulator norepinephrine. These results suggest that the roles of these inhibitory GPCRs are not completely redundant, and also indicate the physiological implications of having different excitatory and inhibitory GPCRs on the same synapse.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".