Correlations between IL-36 family cytokines in peripheral blood and subjective and objective assessment results in patients with allergic rhinitis
Bibliographic record
Abstract
BACKGROUND: Interleukin (IL)-36 family cytokines have received increasing attention, especially in the fields of inflammation and immunity research. However, whether IL-36 family cytokine levels are correlated with the results of the assessment of allergic rhinitis (AR) and affect the severity of AR remains unknown. Therefore, this study aimed to investigate the correlations between IL-36 family cytokine levels and subjective and objective assessment results and to further analyze the possible mechanisms of IL-36 family cytokines in the development of AR. METHODS: An enzyme-linked immunosorbent assay (ELISA) was used to detect the concentrations of the IL-36 family cytokines IL-36α, IL-36β, IL-36γ, IL-36Ra, and IL-38 in the peripheral blood of patients with AR. The condition of patients with AR was assessed by 22-item sino-nasal outcome test (SNOT-22) score, visual analogue scale (VAS) scores for disease severity, and serum inhalant allergen immunoglobulin E (IgE) detection. Correlations between IL-36 family cytokine levels and subjective and objective assessment results in patients with AR were analyzed. RESULTS: The concentration of IL-36α in the peripheral blood of patients with AR was the highest, and the concentration of IL-36β was the lowest. The concentration of IL-36α was higher in juvenile patients than in adult patients, and there was a difference in the IL-36Ra level between the perennial allergen group and the seasonal allergen group. There was a positive correlation between IL-36α level and IL-36γ level, IL-36γ level and IL-36Ra level, and IL-36Ra level and IL-38 level, and IL-36β level was positively correlated with IL-36Ra and IL-38 levels, respectively. IL-36α level was positively correlated with VAS score for nasal congestion symptom. IL-36β level was positively correlated with the total VAS score for ocular symptoms and VAS scores for ocular itching and eye pain symptoms. However, there was no correlation between the levels of all cytokines in IL-36 family and SNOT-22 score, the number of positive inhaled allergens, or the highest positive intensity of allergen specific immunoglobulin E (sIgE). CONCLUSION: Peripheral blood IL-36 family cytokines play an important role in AR, and the concentrations of IL-36α and IL-36β were related to the severity of symptoms in patients with AR.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".