Pseudomonas aeruginosa aggregation and Psl expression in sputum is associated with antibiotic eradication failure in children with cystic fibrosis
Bibliographic record
Abstract
We previously demonstrated that P. aeruginosa isolates that persisted in children with cystic fibrosis (CF) despite inhaled tobramycin treatment had increased anti-Psl antibody binding in vitro compared to those successfully eradicated. We aimed to validate these findings by directly visualizing P. aeruginosa in CF sputum. This was a prospective observational study of children with CF with new-onset P. aeruginosa infection who underwent inhaled tobramycin eradication treatment. Using microbial identification passive clarity technique (MiPACT), P. aeruginosa was visualized in sputum samples obtained before treatment and classified as persistent or eradicated based on outcomes. Pre-treatment isolates were also grown as biofilms in vitro. Of 11 patients enrolled, 4 developed persistent infection and 7 eradicated infection. P. aeruginosa biovolume and the number as well as size of P. aeruginosa aggregates were greater in the sputum of those with persistent compared with eradicated infections (p < 0.01). The amount of Psl antibody binding in sputum was also greater overall (p < 0.05) in samples with increased P. aeruginosa biovolume. When visualized in sputum, P. aeruginosa had a greater biovolume, with more expressed Psl, and formed more numerous, larger aggregates in CF children who failed eradication therapy compared to those who successfully cleared their infection.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".