Regular salbutamol use increases CXCL8 responses in asthma: relationship to the eosinophil response
Bibliographic record
Abstract
Regular salbutamol use can exacerbate allergen-induced airway eosinophilia in asthmatics, but its effect on airway eosinophil chemokine responses is unknown. Asthmatic subjects (n=14) were treated for 10 days with placebo or salbutamol in a double-blind, cross-over study, then given same-dose allergen challenges. Their sputa were then analysed 1 and 7 h later for a panel of eosinophil-related cytokines. Eosinophils from five test and three control subjects were tested for expression of CXCL8/interleukin (IL)-8, and its receptors and responsiveness to CCL11/eotaxin and CXCL8/IL-8. Sputum CXCL8/IL-8, but not IL-5, CCL5/regulated on activation, T-cell expressed and secreted, CCL7/monocyte chemotactic protein-3, CCL11/eotaxin, granulocyte-macrophage colony-stimulating factor or tumour necrosis factor levels, were increased (42%) by the salbutamol treatments. The CXCL8/IL-8 levels correlated with the proportions of sputum eosinophils and these cells, but not other sputum cells, stained strongly for CXCL8/IL-8. The circulating eosinophils of the tested subjects (n=5) expressed CXCL8/IL-8 receptors and secreted high levels of this chemokine. Neutralisation of sputum CXCL8/IL-8 reduced eosinophil chemotactic responses to these samples by 19 +/- 5%. These data suggest that regular use of salbutamol can augment airway CXCL8/interleukin-8 responses to allergen challenge and that this CXCL8/interleukin-8 could contribute to the airway inflammatory response.
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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) | 0.002 | 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".