Blocking Spinal CCR2 with AZ889 Reversed Hyperalgesia in a Model of Neuropathic Pain
Bibliographic record
Abstract
BACKGROUND: The CCR2/CCL2 system has been identified as a regulator in the pathogenesis of neuropathy-induced pain. However, CCR2 target validation in analgesia and the mechanism underlying antinociception produced by CCR2 antagonists remains poorly understood. In this study, in vitro and in vivo pharmacological approaches using a novel CCR2 antagonist, AZ889, strengthened the hypothesis of a CCR2 contribution to neuropathic pain and provided confidence over the possibilities to treat neuropathic pain with CCR2 antagonists. RESULTS: We provided evidence that dorsal root ganglia (DRG) cells harvested from CCI animals responded to stimulation by CCL2 with a concentration-dependent calcium rise involving PLC-dependent internal stores. This response was associated with an increase in evoked neuronal action potentials suggesting these cells were sensitive to CCR2 signalling. Importantly, treatment with AZ889 abolished CCL2-evoked excitation confirming that this activity is CCR2-mediated. Neuronal and non-neuronal cells in the spinal cord were also excited by CCL2 applications indicating an important role of spinal CCR2 in neuropathic pain. We next showed that in vivo spinal intrathecal injection of AZ889 produced dose-dependent analgesia in CCI rats. Additionally, application of AZ889 to the exposed spinal cord inhibited evoked neuronal activity and confirmed that CCR2-mediated analgesia involved predominantly the spinal cord. Furthermore, AZ889 abolished NMDA-dependent wind-up of spinal withdrawal reflex pathway in neuropathic animals giving insight into the spinal mechanism underlying the analgesic properties of AZ889. CONCLUSIONS: Overall, this study strengthens the important role of CCR2 in neuropathic pain and highlights feasibility that interfering on this mechanism at the spinal level with a selective antagonist can provide new analgesia opportunities.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".