Spinal CCL2 pronociceptive action is no longer effective in CCR2 receptor antagonist‐treated rats
Bibliographic record
Abstract
A better understanding of the mechanisms linked to chemokine pronociceptive effects is essential for the development of new strategies to better prevent and treat chronic pain. Among chemokines, MCP-1/CCL2 involvement in neuropathic pain processing is now established. However, the mechanisms by which MCP-1/CCL2 exerts its pronociceptive effects are still poorly understood. In the present study, we demonstrate that MCP-1/CCL2 can alter pain neurotransmission in healthy rats. Using immunohistochemical studies, we first show that CCL2 is constitutively expressed by primary afferent neurons and their processes in the dorsal horn of the spinal cord. We also observe that CCL2 is co-localized with pain-related peptides (SP and CGRP) and capsaicin receptor (VR1). Accordingly, using in vitro superfusion system of lumbar dorsal root ganglion and spinal cord explants of healthy rats, we show that potassium or capsaicin evoke calcium-dependent release of CCL2. In vivo, we demonstrate that intrathecal administration of CCL2 to healthy rats produces both thermal hyperalgesia and sustained mechanical allodynia (up to four consecutive days). These pronociceptive effects of CCL2 are completely prevented by the selective CCR2 antagonist (INCB3344), indicating that CCL2-induced pain facilitation is elicited via direct spinal activation of CCR2 receptor. Therefore, preventing the activation of CCR2 might provide a fruitful strategy for treating pain.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".