The Lung Tissue Microbiome in Chronic Obstructive Pulmonary Disease
Bibliographic record
Abstract
RATIONALE: Based on surface brushings and bronchoalveolar lavage fluid, Hilty and coworkers demonstrated microbiomes in the human lung characteristic of asthma and chronic obstructive pulmonary disease (COPD), which have now been confirmed by others. OBJECTIVES: To extend these findings to human lung tissue samples. METHODS: DNA from lung tissue samples was obtained from nonsmokers (n = 8); smokers without COPD (n = 8); patients with very severe COPD (Global Initiative for COPD [GOLD] 4) (n = 8); and patients with cystic fibrosis (CF) (n = 8). The latter served as a positive control, with sterile water as a negative control. All bacterial community analyses were based on polymerase chain reaction amplifying 16S rRNA gene fragments. Total bacterial populations were measured by quantitative polymerase chain reaction and bacterial community composition was assessed by terminal restriction fragment length polymorphism analysis and pyrotag sequencing. MEASUREMENT AND MAIN RESULTS: Total bacterial populations within lung tissue were small (20-1,252 bacterial cells per 1,000 human cells) but greater in all four sample groups versus the negative control group (P < 0.001). Terminal restriction fragment length polymorphism analysis and sequencing distinguished three distinct bacterial community compositions: one common to the nonsmoker and smoker groups, a second to the GOLD 4 group, and the third to the CF-positive control group. Pyrotag sequencing identified greater than 1,400 unique bacterial sequences and showed an increase in the Firmicutes phylum in GOLD 4 patients versus all other groups (P < 0.003) attributable to an increase in the Lactobacillus genus (P < 0.0007). CONCLUSIONS: There is a detectable bacterial community within human lung tissue that changes in patients with very severe COPD.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".