Blockade of S100A8 and S100A9 Suppresses Neutrophil Migration in Response to Lipopolysaccharide
Bibliographic record
Abstract
Recently, proinflammatory activities had been described for S100A8 and S100A9, two proteins found at inflammatory sites and within the neutrophil cytoplasm. In this study, we investigated the role of these proteins in neutrophil migration in vivo in response to LPS. LPS was injected into the murine air pouch, which led to the release of S100A8, S100A9, and S100A8/A9 in the pouch exudates that preceded accumulation of neutrophils. Passive immunization against S100A8 and S100A9 led to a 52% inhibition of neutrophil migration in response to LPS at 3 h postinjection. Injection of LPS was also associated with an increase in peripheral blood neutrophils and the presence in serum of S100A9 and S100A8/A9. Intravenous injection of S100A8, S100A9, or S100A8/A9 augmented the number of circulating neutrophils and diminished the number of neutrophils in the bone marrow, demonstrating that S100A8 and S100A9 induced the mobilization of neutrophils from the bone marrow to the blood. Finally, passive immunization with anti-S100A9 inhibited the neutrophilia associated with LPS injection in the air pouch. These results suggest that S100A8 and S100A9 play a role in the inflammatory response to LPS by inducing the release of neutrophils from the bone marrow and directing their migration to the inflammatory site.
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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 | 0.000 | 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".