Growth Hormone Secretagogue Receptor Dimers: A New Pharmacological Target
Bibliographic record
Abstract
The growth hormone secretagogue receptor (GHSR1a), the target of the ghrelin peptide, is widely distributed throughout the brain, and, while studies have often reported very low or absent levels of central ghrelin, it is now known that GHSR1a, even in the absence of a natural ligand, has physiological roles. Not only do these roles originate from the receptor's constitutive activity, but recent data indicate that GHSR1a dimerizes with a wide array of other receptors. These include the dopamine 1 receptor (D1R), the dopamine 2 receptor (D2R), the melanocortin-3 receptor (MC3R), the serotonin 2C receptor (5-HT2C), and possibly the cannabinoid type 1 receptor (CB1). Within these dimers, signaling of the protomers involved are modified through facilitation, inhibition, and even modification of signaling pathways resulting in physiological consequences not seen in the absence of these dimers. While in some cases the ghrelin peptide is not required for these modifications to occur, in others, the presence is necessary for these changes to take effect. These heterodimers demonstrate the broad array of roles and complexity of the ghrelin system. By better understanding how these dimers work, it is hoped that improved treatments for a variety of disorders, including Parkinson's disease, schizophrenia, addiction, obesity, diabetes, and more, can be devised. In this review, we examine the current state of knowledge surrounding GHSR heterodimers, and how we can apply this knowledge to various pharmacological treatments.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 0.002 |
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".