Bibliographic record
Abstract
BACKGROUND: Cystic fibrosis (CF) is characterised by chronic endobronchial bacterial infection and neutrophil mediated inflammation. Neutrophil apoptosis is essential for the resolution of inflammation. This study assessed the relationship between levels of neutrophil apoptosis and sputum microbiology in matched clinically stable patients with CF. METHODS: Sputum was induced from 34 patients (nine with no Gram negative infection, 10 colonised with Pseudomonas aeruginosa, 10 with Burkholderia cenocepacia, and five with other infections). Apoptotic neutrophils measured by flow cytometric Annexin V/propidium iodide staining and morphology were similar in all groups. RESULTS: Patients infected with P aeruginosa or B cenocepacia had a significantly lower percentage of viable neutrophils in the sputum than those with no Gram negative infection (Kruskal-Wallis p = 0.01, median (interquartile range (IQR)) 14.2% (9.4-21.6), 15.8% (12.3-19.5), and 48.4% (23.0-66.4); p = 0.003 and p = 0.002, respectively). They also had significantly higher levels of secondary necrotic granulocytes in sputum than patients with no Gram negative infection (Kruskal-Wallis p<0.0001, median (IQR) 55.5% (48.4-64.5), 50.4% (44.6-61.9), and 24.8% (14.4-30.5); p<0.0001 and p<0.0001, respectively). Neutrophils (x 10(6)/g sputum) in P aeruginosa infected patients (Kruskal-Wallis p = 0.05, median (IQR) 6.3 (3.5-12.7)) and B cenocepacia infected patients (5.7 (1.5-14.5)) were significantly higher than in the group with no Gram negative infection (0.5 (0.5-4.3), p = 0.03 and 0.04, respectively). CONCLUSION: These results suggest that cell death and clearance may be altered in patients with CF colonised with P aeruginosa and B cenocepacia compared with those with no Gram negative infection.
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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".