Cell‐type specific activation of p38 and ERK mediates calcitonin gene‐related peptide involvement in tolerance to morphine‐induced analgesia
Bibliographic record
Abstract
Tolerance to morphine-induced analgesia is a well-established phenomenon, often limiting its usefulness in the long-term treatment of pain. The mechanisms underlying tolerance are not well understood. We previously suggested a possible role for spinal calcitonin gene-related peptide (CGRP) in the development of tolerance to morphine-induced analgesia. In the present study, we demonstrate that CGRP is involved in morphine tolerance by differentially regulating the ERK-dependent up-regulation of IL-1beta, TNF-alpha, and microsomal prostaglandin E synthase-1 (mPGES-1) in astrocytes and p38-dependent up-regulation of IL-6 in microglia in the rat spinal cord. A 7-d treatment with morphine induced tolerance to the antinociceptive effect and increased phosphorylated ERK localized in astrocytes and phosphorylated p38 enriched in microglia, both effects being inhibited by blocking CGRP receptors. Interestingly, the inhibition of the ERK pathway suppressed the development of tolerance and morphine-induced up-regulation of IL-1beta, TNF-alpha, and mPGES-1. Blockade of p38 activity also inhibited the development of tolerance and morphine-induced IL-6 up-regulation. Taken together, these data suggest that chronic morphine induces the synthesis of CGRP, which in turn acts on CGRP receptors located on astrocytes and microglia to stimulate ERK and p38, respectively, leading to increased synthesis and release of proinflammatory mediators resulting in tolerance to morphine-induced analgesia.
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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) | 0.001 | 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".