D2 Receptors Inhibit the Secretory Process Downstream From Calcium Influx in Dopaminergic Neurons: Implication of K<sup>+</sup> Channels
Bibliographic record
Abstract
Dopaminergic (DAergic) neurons possess D2-like somatodendritic and terminal autoreceptors that modulate cellular excitability and dopamine (DA) release. The cellular and molecular processes underlying the rapid presynaptic inhibition of DA release by D2 receptors remain unclear. Using a culture system in which isolated DAergic neurons establish self-innervating synapses ("autapses") that release both DA and glutamate, we studied the mechanism by which presynaptic D2 receptors inhibit glutamate-mediated excitatory postsynaptic currents (EPSCs). Action-potential evoked EPSCs were reversibly inhibited by quinpirole, a selective D2 receptor agonist. This inhibition was slightly reduced by the inward rectifier K(+) channel blocker barium, largely prevented by the voltage-dependent K(+) channel blocker 4-aminopyridine, and completely blocked by their combined application. The lack of a residual inhibition of EPSCs under these conditions argues against the implication of a direct inhibition of presynaptic Ca(2+) channels. To evaluate the possibility of a direct inhibition of the secretory process, spontaneous miniature EPSCs were evoked by the Ca(2+) ionophore ionomycin. Ionomycin-evoked release was insensitive to cadmium and dramatically reduced by quinpirole, providing evidence for a direct inhibition of quantal release at a step downstream to Ca(2+) influx through voltage-dependent Ca(2+) channels. Surprisingly, this effect of quinpirole on ionomycin-evoked release was blocked by 4-aminopyridine. These results suggest that D2 receptor activation decreases neurotransmitter release from DAergic neurons through a presynaptic mechanism in which K(+) channels directly inhibit the secretory process.
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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".