Antinociceptive effects of novel melatonin receptor agonists in mouse models of abdominal pain
Bibliographic record
Abstract
AIM: To characterize the antinociceptive action of the novel melatonin receptor (MT) agonists, Neu-P11 and Neu-P12 in animal models of visceral pain. METHODS: Visceral pain was induced by intracolonic (ic) application of mustard oil or capsaicin solution or by intraperitoneal (ip) administration of acetic acid. Neu-P11, Neu-P12, or melatonin were given ip or orally and their effects on pain-induced behavioral responses were evaluated. To identify the receptors involved, the non-selective MT1/MT2 receptor antagonist luzindole, the MT2 receptor antagonist 4-P-PDOT, or the μ-opioid receptor antagonist naloxone were injected ip or intracerebroventricularly (icv) prior to the induction of pain. RESULTS: Orally and ip administered melatonin, Neu-P11, and Neu-P12 reduced pain responses in a dose-dependent manner. Neu-P12 was more effective and displayed longer duration of action compared to melatonin. The antinociceptive effects of Neu-P11 or Neu-P12 were antagonized by ip or icv. administered naloxone. Intracerebroventricularly, but not ip administration of luzindole or 4-P-PDOT blocked the antinociceptive actions of Neu-P11 or Neu-P12. CONCLUSION: Neu-P12 produced the most potent and long-lasting antinociceptive effect. Further development of Neu-P12 for future treatment of abdominal pain seems promising.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".