Eosinophil-mucus interplay in severe asthma: Implications for treatment with biologicals
Bibliographic record
Abstract
Airway mucus is a hydrogel with unique biophysical properties due to its primary water composition and a small proportion of large anionic glycoproteins or mucins. The predominant mucins in human mucus, MUC5AC and MUC5B, are secreted by specialized cells within the airway epithelium both in normal conditions and in response to various stimuli. Their relative proportions are correlated with specific inflammatory responses and disease mechanisms. The dysregulation of mucin expression is implicated in numerous respiratory diseases, including asthma, COPD, and cystic fibrosis, where the pathogenic role of mucus has been extensively described yet often overlooked. In airway diseases, excessive mucus production or impaired mucus clearance leads to mucus plugging, with secondary airway occlusion that contribute to airflow obstruction, asthma severity and poor control. Eosinophils and Charcot Leyden crystals in sputum contribute to the mucus burden and tenacity. Mucin may also contribute to eosinophil survival. Other mechanisms, including eosinophil-independent IL-13 release, mast-cell activation and non-type-2 (T2) cytokines, are also likely to participate in mucus pathobiology. An accurate assessment of mucus and its clinical and functional consequences require a thorough approach that includes evaluation of cellular predominance in sputum, airway cytokines and other inflammatory markers, mucus characteristics and composition and structural and functional impact measured by advanced lung imaging. This review, illustrated with clinical scenarios, provides an overview of current methods to assess mucus and its relevance to the choice of biologics to treat patients with severe asthma.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".