Itch induced by peripheral mu opioid receptors is dependent on TRPV1-expressing neurons and alleviated by channel activation
Bibliographic record
Abstract
Opioids remain the gold standard for the treatment of moderate to severe pain. However, their analgesic properties come with important side effects, including pruritus, which occurs frequently after systemic or neuraxial administration. Although part of the opioid-induced itch is mediated centrally, recent evidence shows that the opioid receptor system in the skin also modulates itch. The goal of our study was to identify the peripherally located transducer mechanisms involved in opioid-induced pruritus. Scratching behaviors in response to an intradermal injection of the mu-opioid receptor (MOR) agonist [D-Ala2, N-MePhe4, Gly-ol]-enkephalin (DAMGO) was quantified in mast cell-, PAR2- and TRPV1-deficient mice or following ablation of TRPV1+ sensory neurons. We found that mast cells-/-, PAR-2-/-, or TRPV1-/- mice still exhibit DAMGO-induced itch responses. However, we show that ablation of TRPV1+ neurons or acute TRPV1 activation by capsaicin abolishes DAMGO-induced itch. Overall, our work shows that peripheral DAMGO-induced itch is dependent on the presence of TRPV1-expressing pruriceptors, but not the TRPV1 channel itself. Activation of these fibers by capsaicin prevents the opioid-induced itch.
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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) | 0.003 | 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".