Bacterial immune evasion via an IL-10 mediated host response, a novel pathophysiologic mechanism for chronic rhinosinusitis
Bibliographic record
Abstract
BACKGROUND: Staphylococcus aureus is a frequently implicated pathogen in chronic rhinosinusitis (CRS). S. aureus may promote commensalism by downregulating pro-inflammatory T cell host responses via an IL-10 mediated pathway. This finding, coupled with the observation that S. aureus and CD8+ T cell numbers are inversely correlated in CRS mucosa, suggests that S. aureus may evade immune destruction via IL-10 induction. To support this hypothesis, we evaluated i) whether IL-10 levels differ in CRS compared to controls (CTL) using microarray and immunohistochemistry and ii) whether IL-10 levels correlate with S. aureus and CD8+ T cell levels. METHODOLOGY: Sinus epithelial brush samples from 12 patients undergoing ESS for CRS and 10 CTLs underwent microarray analysis of IL-10 gene expression. Microarray results were verified on simultaneously obtained surgical biopsy samples by immunohistochemistry staining for IL-10. Potential mechanisms were assessed by immunohistochemistry for CD8+ T cells and S. aureus. RESULTS: IL-10 gene expression was significantly higher in CRS vs CTL subjects at the time of surgery. Immunohistochemistry confirmed increased levels of intraepithelial IL-10. A strong inverse correlation was observed between intraepithelial IL-10 and CD8+ T cell levels as was intraepithelial IL-10 and S. aureus. CONCLUSION: Elevated IL-10 levels in sinus mucosa may be a potential pathophysiologic feature of CRS in association with a significant downregulation of host CD8+ T cell levels. While S. aureus is believed to play a role in IL-10 induction, a comparatively weaker relationship between S. aureus and IL-10 levels suggests other bacterial species may also induce IL-10 production as a common survival strategy in CRS.
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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 | 0.000 |
| 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".