Distribution of airway smooth muscle remodelling in asthma: Relation to airway inflammation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Pathological phenotypes of asthma have been based predominantly on inflammation, rather than airway wall remodelling. Differences in the distribution of airway smooth muscle (ASM) remodelling between large and small airways may affect clinical outcomes in asthma. The aim of this study was to examine the distribution of ASM remodelling and its relation to airway inflammation. METHODS: Post-mortem cases of asthma (n = 68) were categorized by the distribution of increased thickness of the ASM layer (relative to nonasthmatic controls, n = 37), into 'large only' (LO, n = 15), 'small only' (SO, n = 4) 'large/small' (LS, n = 24) or no increase (NI, n = 25). Subject characteristics, ASM and airway wall dimensions and inflammatory cell numbers were compared between groups. RESULTS: Apart from reduced clinical severity of asthma in NI cases (P = 0.002), subject characteristics did not distinguish asthma groups. Compared with control subjects, ASM cell number, reticular basement membrane thickness, airway wall thickness, percent muscle shortening and eosinophil number were increased (P < 0.05) in both large and small airways in LS cases and only the large airways in LO cases. Increased numbers of neutrophils were observed only in the small airways of LO cases. CONCLUSIONS: Distinct distributions of ASM remodelling are seen in asthma. Pathology limited to the small airways was uncommon. Increased thickness of the ASM layer was associated with airway remodelling and eosinophilia, but not neutrophilia. These data support the presence of distinct pathological phenotypes based on the site of increased ASM.
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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 it