It Takes Two to Tango: Investigating the Relationship between Ghrelin and Endocannabinoids within the Ventral Tegmental Area with Regards to Feeding
Bibliographic record
Abstract
Ghrelin is a hormone that targets the brain to increase food intake and energy balance.Recent evidence suggests that ghrelin increases appetite in part by acting on growth hormone secretagogue receptors (GHSR) in the ventral tegmental area (VTA), a brain region associated with reward seeking behaviors.The ability of ghrelin to induce appetite is reminiscent of the appetite inducing effects of endogenous cannabinoids (CBs).Interestingly, ghrelin's ability to stimulate feeding within the hypothalamus is dependent on a functional CB system within this region.In the present thesis we hypothesized that ghrelin and CB systems work in tandem within the VTA to stimulate feeding.Here we showed that ghrelin significantly increased food intake (p < .05)when directly microinjected into the VTA of rats.Furthermore, we demonstrated that this corresponding increase in food intake depended on a functional endocannabinoid system as peripheral pre-treatment with a selective CB-1 receptor (CB-1R) antagonist (i.e.rimonabant) completely attenuated this increase in food intake to control rat levels.Furthermore, we also demonstrated via reverse transcription quantitative polymerase chain reaction (RT-qPCR) experiments that CB-1R mRNA expression is significantly lower in the VTA but enhanced in the prefrontal cortex (PFC) of GHSR knock-out (GHSR KO) relative to wildtype (WT) rats (p < .05).Together, these data provide evidence that ghrelin targets the VTA to increase food intake through a mechanism that requires a functional endocannabinoid system.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".