Skin-resident dendritic cells mediate postoperative pain via CCR4 on sensory neurons
Bibliographic record
Abstract
myeloid cells in the pathogenesis of postoperative pain. We now show that the chemokines CCL17 and CCL22, with their cognate receptor CCR4, are key mediators of this response. Both chemokines are up-regulated early after tissue injury by skin-resident dendritic and Langerhans cells to act on peripheral sensory neurons that express CCR4. CCL22, and to a lesser extent CCL17, elicit acute mechanical and thermal hypersensitivity when administered subcutaneously; this response abrogated by pharmacological blockade or genetic silencing of CCR4. Electrophysiological assessment of dissociated sensory neurons from naïve and postoperative mice showed that CCL22 was able to directly activate neurons and enhance their excitability after injury. These responses were blocked using C 021 and small interfering RNA (siRNA)-targeting CCR4. Finally, our data show that acute postoperative pain is significantly reduced in mice lacking CCR4, wild-type animals treated with CCR4 antagonist/siRNA, as well as transgenic mice depleted of dendritic cells. Together, these results suggest an essential role for the peripheral CCL17/22:CCR4 axis in the genesis of inflammatory pain via direct communication between skin-resident dendritic cells and sensory neurons, opening therapeutic avenues for its control.
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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) | 0.002 | 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".