Role of beta-arrestin 2 downstream of dopamine receptors in the basal ganglia
Bibliographic record
Abstract
Multifunctional scaffolding protein beta-arrestins (βArr) and the G protein-receptor kinases are involved in the desensitization of several G protein-coupled receptors (GPCR). However, arrestins can also contribute to GPCR signaling independently from G proteins. In this review, we focus on the role of βArr in the regulation of dopamine receptor functions in the striatum. First, we present in vivo evidence supporting a role for these proteins in the regulation of dopamine receptor desensitization. Second, we provide an overview of the roles of βArr2 in the regulation of extracellular-signal-regulated kinases/MAP kinases and Akt/GSK3 signaling pathways downstream of the D1 and D2 dopamine receptors. Thereafter, we examine the possible involvement of βArr-mediated signaling in the action of dopaminergic drugs used for the treatment of mental disorders. Finally, we focus on different potential cellular proteins regulated by βArr-mediated signaling which could contribute to the regulation of behavioral responses to dopamine. Overall, the identification of a cell signaling function for βArr downstream of dopamine receptors underscores the intricate complexity of the intertwined mechanisms regulating and mediating cell signaling in the basal ganglia. Understanding these mechanisms may lead to a better comprehension of the several roles played by these structures in the regulation of mood and to the development of new psychoactive drugs having better therapeutic efficacy.
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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 | 0.001 | 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".