Airway remodeling and eosinophilic asthma
Bibliographic record
Abstract
Background: Excessive airway narrowing, the cause of asthma symptoms, may arise from different mechanisms in cases of asthma with eosinophils (EA) or without eosinophils (NEA). Aim: To compare the ratio of the airway lumen occupied by mucus (MOR), percent airway smooth muscle shortening (PMS) and airway wall dimensions in cases of EA (n=38), NEA (n=43) and control subjects (n=48). Methods: On sections of airway taken from post-mortem lungs, the area densities of eosinophils and neutrophils within the inner airway wall were calculated (H&E, 5μm). Asthmatics with a mean eosinophil density >5cells/mm 2 were classified as EA. On the same section, MOR, PMS and airway wall dimensions were determined. Results: There were no significant differences in duration, age of onset of asthma or smoking history between case groups, however EA had more severe asthma (more cases of fatal versus nonfatal asthma) than NEA. The thickness of the airway smooth muscle layer was significantly increased in EA cases compared with control subjects in all airway size groups (p<0.05). The thickness of the inner airway wall and reticular basement membrane, MOR, PMS and neutrophil area density were increased in medium and large airways in the EA cases compared with control subjects (p<0.05). These differences persisted when fatal and nonfatal cases were analysed separately. Conclusion : Eosinophilic asthma is characterized by airway wall and airway smooth muscle remodeling with increased mucus within the airway lumen and increased percent muscle shortening. Support: NHMRC of Australia Project Grant #618700.
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 | 0.000 | 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) | 0.002 | 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".