Coupling of dopamine receptor subtypes to multiple and diverse G proteins
Bibliographic record
Abstract
The family of five dopamine receptors subtypes activate cellular effector systems through G proteins. Historically, dopamine receptors were thought to only stimulate or inhibit adenylyl cyclase, by coupling to either G(s)alpha or G(i)alpha, respectively. Recent studies in transfected cells, reviewed here, have shown that multiple and highly diverse signaling pathways are activated by specific dopamine receptor subtypes. This multiplicity of signaling responses occurs through selective coupling to distinct G proteins and each of the receptors can interact with more than one G protein. Although some of the multiple coupling of dopamine receptors to different G proteins occurs from within the same family of G proteins, these receptors can also couple to G proteins belonging to different families. Such multiple interactions between receptors and G proteins elicits functionally distinct physiological effects which acts to enhance and subsequently suppress the original receptor response, and to activate apparently distinct signaling pathways. In the brain, where coexpression of functionally distinct receptors in heterogeneous cells further adds to the complexity of dopamine signaling, minor alterations in receptor/G protein coupling states during either development or in adults, may underlie the imbalanced signaling seen in dopaminergic-linked diseases such as schizophrenia, Parkinson's disease and attention deficit hyperactivity disorder.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".