Surface receptor expression on circulating and airway eosinophils after inhaled allergen challenge
Bibliographic record
Abstract
Rationale: Eosinophilia is an important biomarker for tracking disease severity and the response to therapy in asthmatic patients. However, differences in response to therapy between circulating and airway eosinophils highlight the need to characterize eosinophil phenotypes. Methods: 11 mild allergic asthmatics underwent inhaled allergen and diluent challenges. Whole blood and sputum samples were collected 24hr before challenge and post-challenge at 7hr and 24hr, and stained for eosinophils (CD45+ CD16- CD15+) and surface receptors for cytokines CD125, CD123; chemokines; adhesion molecules VLA-4 (CD49d), L-selectin (CD62L); immunoregulatory receptor Siglec 8; and activation markers (CD66b, CD63, CD69). Eosinophils +ve for each receptor were expressed as a % of total eosinophils. Results: At baseline there was a higher % of eosinophils +ve for CD123, CD62L, CD49d, Siglec 8, CCR3, CD63 and CD69 in blood compared to sputum. Allergen challenge reduced FEV1 by ≥ 20%. Post-allergen challenge, the % of Siglec 8 +ve eosinophils increased in sputum compared to diluent (p<0.05). Compared to pre-allergen baseline the % eosinophils +ve for CD69 and CD123 increased in blood, and CD123 decreased in sputum post-allergen, but these changes were not significantly different than diluent. Conclusion: Receptors to ligands for eosinophil activation and recruitment are downregulated in sputum eosinophils, confirming previous activation of these pathways. Recruitment of Siglec 8 +ve eosinophils to airways post-allergen challenge may be a mechanism for local immunoregulation.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".