GIRK channel-mediated inhibition of melanin-concentrating hormone neurons by nociceptin/orphanin FQ
Bibliographic record
Abstract
Targeting the melanin-concentrating hormone (MCH) system has been suggested as a potential treatment for obesity, anxiety disorders, as well as addiction. Despite the therapeutic potential of MCH agonists and antagonists, the endogenous factors regulating MCH activity, in particular those implicated in anxiety and reward, are ill-defined. The present study investigated the cellular effects of nociceptin/orphanin FQ (N/OFQ), an endogenous opioid with anxiolytic and antireward properties, on MCH neurons. We found that N/OFQ induced a concentration-dependent reversible outward current in MCH neurons (EC(50) = 50.7 nM), an effect that was blocked by the competitive antagonist of the nociceptin opioid peptide (NOP) receptor UFP-101. N/OFQ-induced outward currents persisted in TTX, reversed near the potassium equilibrium potential, and displayed inward rectification, suggesting direct postsynaptic potassium channel activation. Tertiapin-Q completely abolished the N/OFQ effect, whereas glibenclamide did not, implicating protein G-dependent inwardly rectifying potassium (GIRK) and not ATP-sensitive potassium (K(ATP)) channels as the effector ion channel. The N/OFQ-induced outward current desensitized during repeated applications and occluded the inhibitory effect of dynorphin, suggesting that dynorphin and N/OFQ activate the same pathway. N/OFQ also reversibly inhibited voltage-gated calcium currents in MCH neurons. In conclusion, our study indicates N/OFQ as a robust endogenous regulator of MCH neurons, which may play a role in anxiety and drug addiction.
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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 | 0.001 |
| 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".