PHYSIOLOGICAL AND MOLECULAR METHODS OF MAST CELL ACTIVITY IN PATIENTS WITH MODERATE TO SEVERE ASTHMA
Bibliographic record
Abstract
Background: Mast cells are known to play a role in the pathophysiology of asthma. Determining their contribution to the development of asthma symptoms has been difficult as they remain tissue-resident and do not usually migrate into the airway lumen for detection using expectorated sputum. Objectives: We investigated the presence and activity of mast cells in the blood and sputum of healthy controls and patients with moderate to severe asthma and the relationship with clinical characteristics of asthma and their associated microenvironment. Methods: Cell-free sputum supernatant was used to detect levels of soluble tryptase and T2 and non-T2 cytokines by ELISA. RNA/cDNA isolated from sputum cells measured expression levels of eosinophil and mast cell-specific genes by digital PCR. Relevant clinical characteristics and measurements of lung function, airway hyperresponsiveness, FeNO, blood eosinophils, IgE and tryptase were collected. Results: Tryptase was detectable in the fluid phase portions of sputum, irrespective of the inflammation based on the differential cell count, and was significantly different than healthy controls. Eosinophil and mast cell-specific genes were detected in sputum cells at levels significantly different than healthy controls. Sputum tryptase was not associated with any phenotype or severity of asthma but identified some associations with clinical characteristics. It is associated with a unique cytokine signature. Conclusion: Differences were seen between eosinophilic and non-eosinophilic phenotypes in sputum supernatant and sputum cells. Eosinophil and mast cell-specific genes were detected in sputum cells but were not associated with asthma severity. Greater levels of cytokines IL-4 and IL-13 in sputum, suggest presence of mast cells in the airway epithelium that contribute to mucus secretion observed in patients with uncontrolled symptoms of asthma. Further investigations hope to identify the relationship of mast cells with the quantification of mucus in these patients to understand and confirm those with a predominant mast cell component.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".