Dopamine D4 Receptor Activation Inhibits Presynaptically Glutamatergic Neurotransmission in the Rat Supraoptic Nucleus
Bibliographic record
Abstract
Oxytocin and vasopressin release from magnocellular neurons of the supraoptic nucleus is under the control of glutamate-dependent excitation. The supraoptic nucleus also receives a generalized dopaminergic input from hypothalamic sources. To determine if dopamine can influence this excitatory drive onto the magnocellular neurons, we used whole-cell patch clamp to record the effect of dopamine on evoked and miniature excitatory postsynaptic currents in rat hypothalamic slices. Dopamine exposure (30 microM to 1 mM) induced a large and reversible reduction in the amplitude of evoked excitatory postsynaptic current in nearly all magnocellular cells tested. D4 receptors appeared to mediate dopamine's activity, based on inhibition of the response with 50 microM clozapine, but not by SCH 23390 or sulpiride, and mimicry of dopamine's action with the D4 specific agonist, PD 168077. Analysis of paired-pulse experiments and miniature postsynaptic currents indicated that dopamine's action involved a presynaptic mechanism, since the frequency of miniature postsynaptic currents was reduced with dopamine exposure without any change in current kinetics or amplitude, while the paired-pulse ratio increased. We therefore have demonstrated for the first time a role for dopamine D4 receptors in the supraoptic nucleus in the presynaptic inhibition of glutamatergic neurotransmission onto magnocellular neurons.
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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".