Melanocortin-1 receptor gene variants affect pain and μ-opioid analgesia in mice and humans
Bibliographic record
Abstract
BACKGROUND: A recent genetic study in mice and humans revealed the modulatory effect of MC1R (melanocortin-1 receptor) gene variants on kappa-opioid receptor mediated analgesia. It is unclear whether this gene affects basal pain sensitivity or the efficacy of analgesics acting at the more clinically relevant mu-opioid receptor. OBJECTIVE: To characterise sensitivity to pain and mu-opioid analgesia in mice and humans with non-functional melanocortin-1 receptors. METHODS: Comparisons of spontaneous mutant C57BL/6-Mc1r(e/e) mice to C57BL/6 wildtype mice, followed by a gene dosage study of pain and morphine-6-glucuronide (M6G) analgesia in humans with MC1R variants. RESULTS: C57BL/6-Mc1r(e/e) mutant mice and human redheads--both with non-functional MC1Rs--display reduced sensitivity to noxious stimuli and increased analgesic responsiveness to the mu-opioid selective morphine metabolite, M6G. In both species the differential analgesia is likely due to pharmacodynamic factors, as plasma levels of M6G are similar across genotype. CONCLUSIONS: Genotype at MC1R similarly affects pain sensitivity and M6G analgesia in mice and humans. These findings confirm the utility of cross species translational strategies in pharmacogenetics.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".