Effect of intranasal corticosteroid treatment on allergen‐induced changes in group 2 innate lymphoid cells in allergic rhinitis with mild asthma
Bibliographic record
Abstract
Abstract Background Allergic rhinitis is characterized by rhinorrhea, nasal congestion, sneezing and nasal pruritus. Group 2 innate lymphoid cells (ILC2s), CD4 + T cells and eosinophils in nasal mucosa are increased significantly after nasal allergen challenge (NAC). Effects of intranasal corticosteroids (INCS) on ILC2s remain to be investigated. Methods Subjects ( n = 10) with allergic rhinitis and mild asthma were enrolled in a single‐blind, placebo‐controlled, sequential treatment study and treated twice daily with intranasal triamcinolone acetonide (220 µg) or placebo for 14 days, separated by a 7‐day washout period. Following treatment, subjects underwent NAC and upper airway function was assessed. Cells from the nasal mucosa and blood, sampled 24 h post‐NAC, underwent flow cytometric enumeration for ILC2s, CD4 + T and eosinophil progenitor (EoPs) levels. Cell differentials and cytokine levels were assessed in nasal lavage. Results Treatment with INCS significantly attenuated ILC2s, IL‐5 + /IL‐13 + ILC2s, HLA‐DR + ILC2s and CD4 + T cells in the nasal mucosa, 24 h post‐NAC. EoP in nasal mucosa was significantly increased, while mature eosinophils were significantly decreased, 24 h post‐NAC in INCS versus placebo treatment arm. Following INCS treatment, IL‐2, IL‐4, IL‐5 and IL‐13 were significantly attenuated 24 h post‐NAC accompanied by significant improvement in upper airway function. Conclusion Pre‐treatment with INCS attenuates allergen‐induced increases in ILC2s, CD4 + T cells and terminal differentiation of EoPs in the nasal mucosa of allergic rhinitis patients with mild asthma, with little systemic effect. Attenuation of HLA‐DR expression by ILC2s may be an additional mechanism by which steroids modulate adaptive immune responses in the upper airways.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".