Extracellular vesicles in sputum of children with cystic fibrosis pulmonary exacerbations
Bibliographic record
Abstract
Background The aim of this study was to quantify mediators of neutrophilic inflammation within airway extracellular vesicles (EVs) of children treated for a cystic fibrosis (CF) pulmonary exacerbation (PEx). Methods EVs were isolated from stored sputum samples collected before and after antibiotic therapy for PEx between 2011 and 2013, and characterised by nanoparticle tracking analysis (NTA) and transmission electron microscopy (TEM). Western blot analysis of EV protein extracts was used for EV canonical protein markers CD63, CD9 and flotillin-1 (FLOT1), as well as neutrophil elastase (NE), myeloperoxidase (MPO) and interleukin-8. The EV content of NE and MPO were expressed as ratios of NE/FLOT1 and MPO/FLOT1 protein band densities. Results Sputum samples from 21 children aged 13.3 (range 8.0–17.0) years were analysed. NTA showed high concentrations of particles at the size of small EVs (50–200 nm), and typical EV morphology was confirmed by TEM. CD63, CD9 and FLOT1 were detectable in all samples. Median (interquartile range (IQR)) NE/FLOT1 increased from 2.46 (1.68–5.25) before to 6.83 (3.89–8.89, p<0.001) after PEx therapy, and median (IQR) MPO/FLOT1 increased from 2.30 (1.38–4.44) before to 5.76 (3.45–6.94, p<0.01) after, while EV size remained unchanged. Improvement in lung function (percent predicted forced expiratory volume in 1 s (ppFEV 1 )) with PEx therapy correlated with NE EV content (r=0.657, p=0.001). Conclusions Airways of children with CF contain EVs that carry NE and MPO as cargo. The lower NE and MPO content at the time of PEx, compared with after therapy, and the correlation with pulmonary function suggest both a functional role of EVs in CF airway inflammation and the potential of EVs as a biomarker to monitor CF lung disease.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".