Dopamine D2 Antagonist-Induced Striatal Nur77 Expression Requires Activation of mGlu5 Receptors by Cortical Afferents
Bibliographic record
Abstract
Dopamine D(2) receptor antagonists modulate gene transcription in the striatum. However, the molecular mechanism underlying this effect remains elusive. Here we used the expression of Nur77, a transcription factor of the orphan nuclear receptor family, as readout to explore the role of dopamine, glutamate, and adenosine receptors in the effect of a dopamine D(2) antagonist in the striatum. First, we investigated D(2) antagonist-induced Nur77 mRNA in D(2L) receptor knockout mice. Surprisingly, deletion of the D(2L) receptor isoform did not reduce eticlopride-induced upregulation of Nur77 mRNA levels in the striatum. Next, we tested if an ibotenic acid-induced cortical lesion could block the effect of eticlopride on Nur77 expression. Cortical lesions strongly reduced eticlopride-induced striatal upregulation of Nur77 mRNA. Then, we investigated if glutamatergic neurotransmission could modulate eticlopride-induced Nur77 expression. A combination of a metabotropic glutamate type 5 (mGlu5) and adenosine A(2A) receptor antagonists abolished eticlopride-induced upregulation of Nur77 mRNA levels in the striatum. Direct modulation of Nur77 expression by striatal glutamate and adenosine receptors was confirmed using corticostriatal organotypic cultures. Taken together, these results indicate that blockade of postsynaptic D(2) receptors is not sufficient to trigger striatal transcriptional activity and that interaction with corticostriatal presynaptic D(2) receptors and subsequent activation of postsynaptic glutamate and adenosine receptors in the striatum is required. Thus, these results uncover an unappreciated role of presynaptic D(2) heteroreceptors and support a prominent role of glutamate in the effect of D(2) antagonists.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".