The relationship between eosinophilia and airway remodelling in mild asthma
Bibliographic record
Abstract
BACKGROUND: Eosinophilia is a marker of corticosteroid responsiveness and risk of exacerbation in asthma; although it has been linked to submucosal matrix deposition, its relationship with other features of airway remodelling is less clear. OBJECTIVE: The aim of this study was to investigate the relationship between airway eosinophilia and airway remodelling. METHODS: Bronchial biopsies from subjects (n = 20 in each group) with mild steroid-naïve asthma, with either low (0-0.45 mm(-2)) ) or high submucosal eosinophil (23.43-46.28 mm(-2) ) counts and healthy controls were assessed for in vivo epithelial damage (using epidermal growth factor receptor staining), mucin expression, airway smooth muscle (ASM) hypertrophy and inflammatory cells within ASM. RESULTS: The proportion of in vivo damaged epithelium was significantly greater (P = 0.02) in the high-eosinophil (27.37%) than the low-eosinophil (4.14%) group. Mucin expression and goblet cell numbers were similar in the two eosinophil groups; however, MUC-2 expression was increased (P = 0.002) in the high-eosinophil group compared with controls. The proportion of submucosa occupied by ASM was higher in both asthma groups (P = 0.021 and P = 0.046) compared with controls. In the ASM, eosinophil and T-lymphocyte numbers were higher (P < 0.05) in the high-eosinophil group than both the low-eosinophil group and the controls, whereas the numbers of mast cells were increased in the high-eosinophil group (P = 0.01) compared with controls. CONCLUSION: Submucosal eosinophilia is a marker (and possibly a cause) of epithelial damage and is related to infiltration of ASM with eosinophils and T lymphocytes, but is unrelated to mucus metaplasia or smooth muscle hypertrophy.
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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 | 0.001 |
| 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) | 0.001 | 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".