Intracellular <i>Pseudomonas aeruginosa</i> within the Airway Epithelium of Cystic Fibrosis Lung Tissues
Bibliographic record
Abstract
Abstract Rationale Pseudomonas aeruginosa is the major bacterial pathogen colonizing the airways of adult patients with cystic fibrosis (CF) and causes chronic infections that persist despite antibiotic therapy. Intracellular bacteria may represent an unrecognized reservoir of bacteria that evade the immune system and antibiotic therapy. Although the ability of P. aeruginosa to invade and survive within epithelial cells has been described in vitro in different epithelial cell models, evidence of this intracellular lifestyle in human lung tissues is currently lacking. Objectives To detect and characterize intracellular P. aeruginosa in CF airway epithelium from human lung explant tissues. Methods We sampled lung explant tissues from patients with CF undergoing lung transplantation and non-CF lung donor control tissue. We analyzed lung tissue sections for the presence of intracellular P. aeruginosa using quantitative culture and microscopy, in parallel to histopathology and airway morphometry. Measurements and Main Results P. aeruginosa was isolated from the lungs of seven patients with CF undergoing lung transplantation. Microscopic assessment revealed the presence of intracellular P. aeruginosa within airway epithelial cells in three of the seven patients analyzed at a varying but low frequency. We observed those events occurring in lung regions with high bacterial burden. Conclusions This is the first study describing the presence of intracellular P. aeruginosa in CF lung tissues. Although intracellular P. aeruginosa in airway epithelial cells is likely relatively rare, our findings highlight the plausible occurrence of this intracellular bacterial reservoir in chronic CF infections.
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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 | 0.000 |
| 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 | 0.000 |
| 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 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".