Upper Airway Alarmin Cytokine Expression in Asthma of Different Severities
Bibliographic record
Abstract
Background: The secretion of alarmin cytokines by epithelial cells, including thymic stromal lymphopoietin (TSLP), interleukin (IL)-25, and IL-33, heralds the onset of the inflammatory cascade and immune effector infiltration in asthma. However, alarmin cytokine expression in the upper airways in asthma remains largely unknown. Methods: We recruited 40 participants with asthma who were categorized into four severity groups as per the Global Initiative for Asthma (GINA) classifications (10 in each group of GINA-1/2, -3, -4, and -5). Cells were derived from buccal, nasal and throat brushings, and intracellular alarmin cytokine expression (TSLP, IL-25, and IL-33) was assessed in cytokeratin 8+ (Ck8+) epithelial cells immediately after collection using flow cytometry with fluorescence minus one (FMO) controls. We assessed differences in alarmin cytokine expressions across asthma severity using quantile regression adjusted for age and sex. Results: Of all patients, 24 (60%) were females with a mean (standard deviation [SD]) age of 41 (16) years. TSLP levels in Ck8+ epithelial cells in nasal samples of GINA-5 patients were significantly (p=0.03) higher than other GINA groups after adjusting for age and sex but did not differ between patients with and without nasal comorbidities. However, we did not find any significant changes in TSLP levels in Ck8+ epithelial cells in buccal and throat samples across GINA groups. IL-25 or IL-33 (obtained from nasal, buccal, and throat epithelial cell samples) were not significantly different across GINA groups. Conclusions: Our study demonstrates for the first time that Ck8+ nasal epithelial cells from GINA-5 asthmatics express elevated levels of TSLP.
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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 | 0.001 |
| 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".