Up‐regulation of interleukin‐6 induced by prostaglandin E<sub>2</sub> from invading macrophages following nerve injury: an <i>in vivo</i> and <i>in vitro</i> study
Bibliographic record
Abstract
The mechanisms underlying neuropathic pain caused by nerve injury are not well understood. Inflammatory responses in injured nerves are likely to be key contributing factors in the generation and maintenance of neuropathic pain. The pro-inflammatory cytokine interleukin-6 (IL-6) is up-regulated in invading macrophages and has been implicated in the development of neuropathic pain. We previously demonstrated that invading macrophages up-regulate cyclooxygenase 2 (COX2) and prostaglandin E2 (PGE2) receptors EP1 and EP4, suggesting that PGE2 may affect macrophage function via autocrine or paracrine mechanisms. This study was undertaken to determine whether PGE2 is involved in the up-regulation of IL-6 in invading macrophages. Two weeks following partial sciatic nerve ligation, numerous IL-6 immunoreactive (IR) cell profiles were present in injured nerves. Colocalization of IL-6 with the invading macrophage marker ED1 or with COX2 was frequently observed. IL-6-IR, COX2-IR and ED1-IR cells were present only in cultures derived from injured nerve segments. PGE2 and IL-6 release from cultured cells derived from injured nerves was increased significantly compared with uninjured nerves. Non-selective and selective COX2 inhibitors suppressed PGE2 and IL-6 release. Treatment with PGE2 further enhanced IL-6 release in a concentration- and time-dependent manner. A selective EP4 receptor antagonist L-161982 was able to suppress IL-6 release, whereas an EP1 receptor antagonist, SC19220, was ineffective. Moreover, a protein kinase C inhibitor, calphostin C, dramatically suppressed IL-6 release, whereas a protein kinase A inhibitor H-89 and a Ca2+ chelator EGTA failed. Taken together, our data suggest that PGE2 is involved in mediating the up-regulation of IL-6 occurring in invading macrophages. This action is mediated through an EP4 receptor and the protein kinase C signaling pathway.
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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) | 0.000 | 0.001 |
| 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".