Involvement of Mast Cells in α7 Nicotinic Receptor Agonist Exacerbation of Freund's Complete Adjuvant–Induced Monoarthritis in Mice
Bibliographic record
Abstract
OBJECTIVE: Activation of antiinflammatory cholinergic (vagal) pathways can reduce inflammation, and in vitro studies support a pivotal role of α7 nicotinic acetylcholine receptors (α7-nAChR), macrophages, and T cells in these events. The aim of this study was to assess α7-nAChR agonists as an antiinflammatory treatment for Freund's complete adjuvant (CFA)-induced monoarthritis. METHODS: Arthritis was induced by intraarticular injection of CFA unilaterally into the knee joints of mice. Animals were treated with α7-nAChR agonists (AR-R17779 or A844606), with or without antagonists (COG133 or methyllycaconitine), and joint inflammation and pain were assessed. Experiments were repeated in c-Kit(W-sh) mast cell-deficient mice, and the effects of an α7-nAChR agonist on mast cell proliferation, migration, and activation by lipopolysaccharide (LPS) were tested. RESULTS: Treatment with α7-nAChR agonists significantly exacerbated CFA-induced arthritis and pain, as gauged by all indices of assessment, the specificity of which was confirmed by coadministration of an nAChR antagonist that attenuated the increase in disease severity. Toluidine blue-positive mast cells were increased in the joint capsule of CFA plus AR-R17779-treated mice, and AR-R17779 enhanced LPS-induced TNF proliferation and migration of a human mast cell line. The AR-R17779-driven increase in severity of CFA-induced arthritis was significantly reduced in mast cell-deficient mice. CONCLUSION: Using CFA to elicit a local inflammatory response, we found that pharmacologic activation of α7-nAChR exacerbated joint inflammation and pain, in part via mast cells, which illustrates the organ- and disease-specific nature of regulatory neuroimmune mechanisms. Thus, α7-nAChR activation may not be uniformly antiinflammatory in all types of inflammatory joint disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".