A longitudinal characterization of the Non-Cystic Fibrosis Bronchiectasis airway microbiome
Bibliographic record
Abstract
Abstract A diverse microbiota exists within the airways of individuals with non-cystic fibrosis bronchiectasis (nCFB). How the lung microbiome evolves over time, and whether changes within the microbiome correlate with future disease progression is not yet known. We assessed the microbial community structure of 133 serial sputa and subsequent disease course of 29 nCFB patients collected over a span of 4–16 years using 16S rRNA paired-end sequencing. Interestingly, no significant shifts in the microbial community of individuals were observed during extended follow-up suggesting the microbiome remains relatively stable over prolonged periods. Samples that were Pseudomonas aeruginosa culture positive displayed markedly different microbial community structures compared to those that were positive for Haemophilus influenzae . Importantly, patients with sputum of lower microbial community diversity were more likely to experience subsequent lung function decline as defined by annual change in ≥−1 FEV 1 % predicted. Shannon diversity values <1 were more prevalent in patients with FEV 1 decline (P = 0.002). However, the relative abundance of particular core microbiota constituents did not associate with risk of decline. Here we present data confirming that the microbiome of nCFB individuals is generally stable, and that microbiome-based measurements may have a prognostic role as biomarkers for nCFB.
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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 | 0.000 | 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 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".