Identification of Dopamine D1–D3 Receptor Heteromers
Bibliographic record
Abstract
The function of dopamine D(3) receptors present in the striatum has remained elusive. In the present study evidence is provided for the existence of dopamine D(1)-D(3) receptor heteromers and for an intramembrane D(1)-D(3) receptor cross-talk in living cells and in the striatum. The formation of D(1)-D(3) receptor heteromers was demonstrated by fluorescence resonance energy transfer and bioluminescence resonance energy transfer techniques in transfected mammalian cells. In membrane preparations from these cells, a synergistic D(1)-D(3) intramembrane receptor-receptor interaction was observed, by which D(3) receptor stimulation enhances D(1) receptor agonist affinity, indicating that the D(1)-D(3) intramembrane receptor-receptor interaction is a biochemical characteristic of the D(1)-D(3) receptor heteromer. The same biochemical characteristic was also observed in membrane preparations from brain striatum, demonstrating the striatal co-localization and heteromerization of D(1) and D(3) receptors. According to the synergistic D(1)-D(3) intramembrane receptor-receptor interaction, experiments in reserpinized mice showed that D(3) receptor stimulation potentiates D(1) receptor-mediated behavioral effects by a different mechanism than D(2) receptor stimulation. The present study shows that a main functional significance of the D(3) receptor is to obtain a stronger dopaminergic response in the striatal neurons that co-express the two receptors.
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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) | 0.002 | 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".