T Helper 17 Cells and Related Cytokines after Allergen Inhalation Challenge in Allergic Asthmatics
Bibliographic record
Abstract
BACKGROUND: T helper (Th)17 cells may play a role in allergic asthma. This study assessed the effect of allergen inhalation challenge on circulating Th17 cells and related cytokines in allergic asthmatics. METHODS: Peripheral blood mononuclear cells were collected from 16 atopic asthmatics before and 24 h after allergen challenge, as well as from 10 atopic nonasthmatics and 10 normal controls. Cells were stained for Th17 cytokines and their receptors (IL-17A, IL-17F, IL-21, IL-22, IL-17R, and IL-23R) using flow cytometry. Cytokine concentrations from cell culture supernatants were quantified using a multiplex assay for IL-17A, IL-17F, IL-21, IL-22, and IL-23. RESULTS: At baseline, asthmatics had a higher percentage of circulating Th17 cells (1.2 ± 0.5%) compared to normal controls (0.9 ± 0.66%, p < 0.001) but not compared to atopic nonasthmatics (1.13 ± 0.5%). There was a significant increase in Th17 cells in asthmatics after allergen challenge to 1.55 ± 0.4% (p < 0.05) and a trend toward significance in IL-17R expression from 3.4 ± 4.3 to 6.86 ± 6.84% after allergen challenge (p = 0.06). There was also a significant reduction in IL-21-positive cells following allergen challenge from 3.46 ± 1.85 to 2.33 ± 1.37% (p < 0.001). There were no significant differences in IL-17F, IL-22 and IL-23R expression. The concentration of IL-17A in culture supernatant was significantly higher in asthmatics compared to normal controls and IL-17A significantly increased 24 h after allergen challenge. CONCLUSIONS: The increase of Th17 cells and IL-17A in atopic asthma after allergen inhalation challenge suggests a possible role for Th17 in allergen-induced airway responses.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".