A Novel Dopamine Receptor Signaling Unit in Brain: Heterooligomers of D1 And D2 Dopamine Receptors
Bibliographic record
Abstract
The ability of G protein coupled receptors to heterooligomerize and create novel signaling complexes has demonstrated the tremendous potential of these receptors to access diverse signaling cascades, as well as to modulate the nature of the transduced signal. In the dopamine receptor field, the existence of a D1-like receptor in brain that activated phosphatidylinositol turnover has been shown, but definition of the molecular entity remained elusive. We discovered that the D1 and D2 receptors form a heterooligomer, which on activation of both receptors, coupled to Gq to activate phospholipase C and generate intracellular calcium release. The activation of Gq by the D1-D2 heterooligomer has been shown to occur in cells expressing both receptors, as well as in striatum, distinct from Gs/olf or Gi/o activation by the D1 and D2 receptor homooligomers, respectively. The activation of the D1-D2 receptor heterooligomer in brain led to a calcium signal-mediated increase in phosphorylation of calmodulin kinase lla. The calcium signal rapidly desensitized and the receptors cointernalized after occupancy of either the D1 or D2 binding pocket. Thus, the D1-D2 heterooligomer directly links the action of dopamine to rapid calcium signaling and likely has important effects on dopamine-mediated synaptic plasticity and its functional correlates in brain.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".