Modulation of haloperidol-induced patterns of the transcription factor Nur77 and Nor-1 expression by serotonergic and adrenergic drugs in the mouse brain
Bibliographic record
Abstract
Different patterns of expression of the transcription factors of Nur77 and Nor-1 are induced following acute administration of typical and atypical antipsychotic drugs. The pharmacological profile of atypical antipsychotics suggests that serotonergic and/or adrenergic receptors might contribute to these reported differences. In order to test this possibility, we examined the abilities of serotonin 5-HT(1A) and 5-HT(2A/2C), and α₁- and α₂-adrenergic receptor drugs to modify the pattern of Nur77 (NR4A1) and Nor-1 (NR4A3) mRNA expression induced by haloperidol. Various groups of mice were treated with either saline, DOI, a 5-HT(2A/2C) agonist, MDL11939, a 5-HT(2A) antagonist, 8-OH-DPAT, a 5-HT(1A) agonist, prazosin, an α₁-adrenergic antagonist and idazoxan, an α₂-adrenergic antagonist, alone or in combination with haloperidol. The 5-HT(2A/2C) agonist DOI alone significantly increased Nur77 expression in the medial striatum and nucleus accumbens. DOI reduced Nor-1 expression, while MDL11939 increased the expression of this transcript in the cortex. Prazosin reduced Nur77 expression in the dorsal striatum and nucleus accumbens. Interestingly, 8-OH-DPAT and MDL11939 partially prevented haloperidol-induced Nur77 up-regulation, while MDL11939 completely abolished Nor-1 expression in the striatum. In addition, MDL11939 decreased haloperidol-induced Nur77 and Nor-1 mRNA levels in the ventral tegmental area. On the contrary, idazoxan (α₂ antagonist) consistently potentiated haloperidol-induced Nur77, but not Nor-1 mRNA levels in the striatum, whereas prazosin (α₁ antagonist) remained without effect. Taken together, these results show the ability of a 5-HT(1A) agonist or a 5-HT(2A) antagonist to reduce haloperidol-induced Nur77 and Nor-1 striatal expression, suggesting that these serotonin receptor subtypes participate in the differential pattern of gene expression induced by typical and atypical antipsychotic drugs.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".