Nociceptin Induces Hypophagia in the Perifornical and Lateral Hypothalamic Area
Bibliographic record
Abstract
Nociceptin/orphanin FQ (N/OFQ) is known to induce food intake when administered into the lateral ventricle or certain brain areas. This is somewhat contradictory to its reward-suppressing role, as food is a strong rewarding stimulus. This discrepancy may be due to the functional diversity of N/OFQ's target brain areas. N/OFQ has been shown to inhibit orexin and melanin-concentrating hormone (MCH) neurons, both of which are appetite-inducing cells. As the expression of these neurons is largely confined to the lateral hypothalamus/perifornical area (LH/PFA), we hypothesized that N/OFQ inhibits food intake by acting in this area. To test this hypothesis, we examined the effect of local N/OFQ infusion within the LH/PFA on food intake in the rat and found that N/OFQ decreased sugar pellet as well as chow intake. This effect was not seen when the injection site was outside of the LH/PFA, suggesting a site-specific effect. Next, to determine a possible cellular mechanism of N/OFQ action on food intake, whole cell patch clamp recordings were performed on rat orexin neurons. As previously reported in mice, N/OFQ induced a strong and long lasting hyperpolarization. Pharmacological study indicated that N/OFQ directly inhibited orexin neurons by activating ATP-sensitive potassium (KATP) channels. This effect was partially but significantly attenuated by the inhibitors of PI3K, PKC and PKA, suggesting that the N/OFQ signaling is mediated by these protein kinases. In summary, our results demonstrate a KATP channel-dependent N/OFQ signaling and that N/OFQ is a site-specific anorexic peptide.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".