Role of S100A8 and S100A9 in neutrophil recruitment in response to monosodium urate monohydrate crystals in the air‐pouch model of acute gouty arthritis
Bibliographic record
Abstract
OBJECTIVE: To examine the role of chemokines, S100A8, and S100A9 in neutrophil accumulation induced by the causative agent of gout, monosodium urate monohydrate (MSU) crystals. METHODS: MSU crystal-induced neutrophil migration was studied in the murine air-pouch model. Release of chemokines, S100A8, S100A9, and S100A8/A9 in response to MSU crystals was quantified by enzyme-linked immunosorbent assays. Recruited cells were counted following acetic blue staining, and the subpopulations were characterized by Wright-Giemsa staining of cytospins. RESULTS: MSU crystals induced the accumulation of neutrophils following injection in the air pouch, which correlated with the release of the chemokines CXCL1, CXCL2, CCL2, and CCL3. However, none of these was found to play an important role in neutrophil migration induced by MSU crystals by passive immunization with antibodies directed against each chemokine. S100A8, S100A9, and S100A8/A9 were also found at high levels in the pouch exudates following injection of MSU crystals. In addition, injection of S100A8, S100A9, or S100A8/A9 led to the accumulation of neutrophils in the murine air pouch, demonstrating their proinflammatory activities in vivo. Passive immunization with anti-S100A8 and anti-S100A9 led to a total inhibition of the accumulation of neutrophils. Finally, S100A8/A9 was found at high concentrations in the synovial fluid of patients with gout. CONCLUSION: S100A8 and S100A8/A9 are essential to neutrophil migration induced by MSU crystals. These results suggest that they might be involved in the pathogenesis of gout.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".