A study to define the microbiome of the asthmatic airway
Bibliographic record
Abstract
Background: Asthma is generally well controlled but there is a subpopulation that remains uncontrolled. Recent research has shown that the airway is no longer sterile and has its own microbiome. The aim of our study was to characterise the lower airway microbiota in a cohort of well-defined asthmatics of varying disease severity and by doing so potentially identify alternate therapy strategies. Methods: We recruited 76 patients, stratified by asthma severity to our study (36% GINA 1 and 2; 22% GINA 3 and 42% GINA 4,5). All patients had a detailed clinical evaluation including ACQ-7, spirometry, and eosinophil levels prior to proceeding to bronchoscopy with bronchoalveolar lavage (BAL). Cell differential was performed on BAL, which was further evaluated for the presence of microbes using quantitative polymerase chain reaction (qPCR). Results: Microscopic evaluation of patient BAL demonstrated BAL macrophages (95%) containing numerous microbial species. qPCR demonstrated the presence of bacterial DNA in 71.8% of patients. Analysis found a significant difference between 16sDNA when patients were categorized as having BAL neutrophilia (>3%), (p<0.05). No significant difference was seen when analysed according to BAL eosinophilia. Similarly there was no observable effect of asthma severity (GINA category) or asthma control (ACQ score) on total 16sDNA or total bacteria seen. BAL interleukin-8 was shown to have no relationship with 16sDNA but did show significant correlation with percentage BAL neutrophil count (p<0.05). Conclusions: Our results suggest that BAL neutrophilia is associated with the presence of microbes as well as markers of inflammation. These findings may prove a useful tool in future therapeutic strategies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".