Chronic activation of the D2 dopamine autoreceptor inhibits synaptogenesis in mesencephalic dopaminergic neurons <i>in vitro</i>
Bibliographic record
Abstract
Chronic blockade or activation of dopamine receptors is critical for the pharmacological treatment of diseases like schizophrenia, Parkinson's or attention deficit and hyperactivity disorder. However, the long-term impact of such treatments on dopamine neurons is unclear. Chronic blockade of the dopamine D2 receptor in vivo triggers an increase in the axonal arborization of dopamine neurons [European Journal of Neuroscience, 2002, 16, 787-794]. However, the specific involvement of presynaptic (autoreceptors) vs. postsynaptic D2 receptors as well as the molecular mechanisms involved have not been determined. Here, we examined the role of D2 autoreceptors in regulating the ability of mouse dopamine neurons to establish axon terminals. Chronic activation of this receptor with quinpirole, a specific agonist, decreased the number of axon terminals established by isolated dopamine neurons. This effect was accompanied by a decrease in dopamine release and was mediated through inhibition of protein kinase A. The decrease in axon terminal number induced by D2 receptor activation was also occluded when the mammalian Target of Rapamycin pathway of mRNA translation was blocked. Our results suggest that chronic activation of the D2 autoreceptor inhibits synaptogenesis by mesencephalic dopamine neurons through translational regulation of the synthesis of proteins required for synapse formation. This study provides a better understanding of the impact of long-term pharmacological interventions acting through the D2 receptor.
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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".