Dopamine receptors –<scp>IUPHAR R</scp>eview 13
Bibliographic record
Abstract
The variety of physiological functions controlled by dopamine in the brain and periphery is mediated by the D1, D2, D3, D4 and D5 dopamine GPCRs. Drugs acting on dopamine receptors are significant tools for the management of several neuropsychiatric disorders including schizophrenia, bipolar disorder, depression and Parkinson's disease. Recent investigations of dopamine receptor signalling have shown that dopamine receptors, apart from their canonical action on cAMP-mediated signalling, can regulate a myriad of cellular responses to fine-tune the expression of dopamine-associated behaviours and functions. Such signalling mechanisms may involve alternate G protein coupling or non-G protein mechanisms involving ion channels, receptor tyrosine kinases or proteins such as β-arrestins that are classically involved in GPCR desensitization. Another level of complexity is the growing appreciation of the physiological roles played by dopamine receptor heteromers. Applications of new in vivo techniques have significantly furthered the understanding of the physiological functions played by dopamine receptors. Here we provide an update of the current knowledge regarding the complex biology, signalling, physiology and pharmacology of dopamine receptors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.087 | 0.114 |
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".