Lack of correlation between in vitro and within patient measures of P. aeruginosa biofilms in cystic fibrosis
Bibliographic record
Abstract
Current in vitro biofilm modelling of the opportunistic pathogen, Pseudomonas aeruginosa (PA) in people with cystic fibrosis (PwCF) is limited in its ability to mimic the complexities of the cystic fibrosis (CF) lung environment. Recent adaptations of the Microbial Identification after Passive CLARITY Technique (MiPACT) in CF research have allowed for the direct imaging of PA biofilm spatial organization and structure in expectorated sputum. Here, we performed a comparative analysis of in vitro and within patient ( ex vivo ) measures of PA biofilms using sputa from new onset infected children with CF. MiPACT-fluorescent in situ hybridization (FISH) and fluorescent anti-Psl monoclonal antibody (mAb) staining was performed to directly visualize PA and Psl (exopolysaccharide in PA biofilm matrix) in 11 CF sputum specimens. Corresponding PA isolates, recovered from the same sputum samples, were grown as biofilms in a glass slide chamber model, then visualized by fluorescent live-cell and anti-Psl mAb staining. We observed that PA biovolume, aggregation and Psl antibody binding (normalized per PA biovolume) in CF sputum did not correlate with the in vitro model, although a trend towards significance in the biovolume relationship was observed with the addition of sputum supernatant to the in vitro model.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".