The Evolving Cystic Fibrosis Microbiome: A Comparative Cohort Study Spanning 16 Years
Bibliographic record
Abstract
RATIONALE: The cystic fibrosis (CF) airways are infected with a diverse polymicrobial community. OBJECTIVES: Understanding how changes in the CF microbiome have occurred over time, similar to the observed changes in the prevalence of cultured pathogens, is key in understanding the microbiome's role in disease. METHODS: Drawing from a prospectively collected and maintained sputum biobank, we identified 45 patients with sputum samples collected between the ages of 18 and 21 years in three successive cohorts of adults transitioning to our CF clinic: A (1997-2000), B (2004-2007), and C (2010-2013). Patient demographics, clinical status, and medications were collected from detailed chart review. Microbial communities were assessed by Ilumina MiSeq sequencing of the variable 3 (V3) region of the 16S rDNA. RESULTS: The three cohorts were similar with respect to baseline demographics. There was a trend toward improved health and use of disease-modifying therapies in each successive cohort. Shannon diversity increased in the most recent cohort, suggesting an increase in the diversity of organisms between cohorts. Furthermore, the proportion of samples with Pseudomonas-dominated communities decreased over time, whereas Streptococcus increased. Although β-diversity was associated with transition cohort, the greatest predictor of diversity remained lung function. Furthermore, core microbiome constituents were preserved across cohorts. CONCLUSIONS: Modest changes in the composition and structure of the microbiome of three successive cohorts of young adults with CF were observed, occurring in parallel with successive improvements in clinical status. Importantly, however, the core microbiome constituents were preserved across cohorts.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".