Involvement of the opioid system in the orexigenic and hedonic effects of melanin-concentrating hormone
Bibliographic record
Abstract
Melanin-concentrating hormone (MCH) exerts an orexigenic effect that resembles that of opioids, suggesting that the MCH and opioid systems could interact in controlling the food intake behavior. Three series of experiments were conducted in male Wistar rats: 1) to test the ability of the κ-, μ-, and δ-opioid receptor antagonists binaltorphimine (nor-BNI-κ), β-funaltrexamine (β-FNA-μ), and naltrindole (NTI-δ), respectively, to block the stimulating effects of MCH on food intake; 2) to verify the ability of MCH to induce a positive hedonic response to a sweet stimulus when injected into the nucleus accumbens shell (NAcSh) or right lateral ventricle (LV) of the brain; and 3) to assess the ability of nor-BNI, β-FNA, and NTI to block the effects of MCH on the hedonic response to a sweet stimulus. Nor-BNI, NTI (0, 10 and 40 nmol), and β-FNA (0, 10 and 50 nmol) were administered into the LV prior to injecting MCH (2.0 nmol). To assess the hedonic response, rats were implanted with an intraoral cannula allowing for the infusion of a sweet solution into the oral cavity. Food intake was assessed in sated rats during the first 3 h following the MCH or vehicle (i.e., artificial cerebrospinal fluid) injection. The hedonic response to a sweet stimulus was assessed by examining facial mimics, following the intraoral administration of a sucrose solution. Blockade of each of the three opioid receptors by selective antagonists prevented MCH-induced feeding. Furthermore, MCH-injections into the NAcSh and right LV resulted in enhanced hedonic responses. Finally, antagonism of the three opioid receptors blunted the LV-injected, MCH-induced, facial-liking expressions in response to an intraoral sweet stimulus. Overall, the present study provides evidence to link the MCH and opioid systems in the food intake behavior.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".