Epithelial cell alarmin cytokines: Frontline mediators of the asthma inflammatory response
Bibliographic record
Abstract
The exposure of the airway epithelium to external stimuli such as allergens, microbes, and air pollution triggers the release of the alarmin cytokines IL-25, IL-33 and thymic stromal lymphopoietin (TSLP). IL-25, IL-33 and TSLP interact with their ligands, IL-17RA, IL1RL1 and TSLPR respectively, expressed by hematopoietic and non-hematopoietic cells including dendritic cells, ILC2 cells, endothelial cells, and fibroblasts. Alarmins play key roles in driving type 2-high, and to a lesser extent type 2-low responses, in asthma. In addition, studies in which each of these three alarmins were targeted in allergen-challenged mice showed decreased chronicity of type-2 driven disease. Consequently, ascertaining the mechanism of activity of these upstream mediators has implications for understanding the outcome of targeted therapies designed to counteract their activity and alleviate downstream type 2-high and low effector responses. Furthermore, identifying the factors which shift the balance between the elicitation of type 2-high, eosinophilic asthma and type-2 low, neutrophilic-positive/negative asthma by alarmins is essential. In support of these efforts, observations from the NAVIGATOR trial imply that targeting TSLP in patients with tezepelumab results in reduced asthma exacerbations, improved lung function and control of the disease. In this review, we will discuss the mechanisms surrounding the secretion of IL-25, IL-33, and TSLP from the airway epithelium and how this influences the allergic airway cascade. We also review in detail how alarmin-receptor/co-receptor interactions modulate downstream allergic inflammation. Current strategies which target alarmins, their efficacy and inflammatory phenotype will be discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".