Ghrelin and Dopamine: New Insights on the Peripheral Regulation of Appetite
Bibliographic record
Abstract
A review is provided of current evidence supporting the actions of the stomach-derived peptide ghrelin on ventral tegmental area (VTA) dopamine cells to increase food intake and other appetitive behaviours. Ghrelin is a 28 amino-acid peptide that was first identified as an endogenous ligand to growth hormone secretagogue receptors (GHS-R). In addition to the hypothalamus and brain stem, GHS-R message and protein are distributed throughout the brain, with high expression being detected in regions associated with goal directed behaviour. Of these, the VTA shows relatively high levels of mRNA transcript and protein. Interestingly, ghrelin infusions into the VTA increase food intake dramatically, and stimulate dopamine release from the VTA. Moreover, VTA dopamine neurones increase their activity in response to ghrelin in slice preparations, suggesting that ghrelin increases food intake by modulating the activity of dopaminergic neurones in the VTA. On the basis of these data as well as the fact that VTA dopamine cells respond to other metabolic hormones such as insulin and leptin, it is proposed that VTA dopamine cells, similar to cells in the mediobasal hypothalamus, are first-order sensory neurones that regulate appetitive behaviour in response to metabolic and nutritional signals.
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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) | 0.001 | 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 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".