The characteristics of genetically related <i>Pseudomonas aeruginosa</i> from diverse sources and their interaction with human cell lines
Bibliographic record
Abstract
We investigated a collection of Pseudomonas aeruginosa strains from hospitalised patients (n = 20) and various environmental sources (n = 214) for their genetic relatedness; virulence properties; antibiotic resistance; and interaction with intestinal (Caco-2), renal (A-498), and lung (Calu-3) cell lines. Using RAPD-PCR, we found high diversity among the strains irrespective of their sources, with only 6 common (C) types containing strains from both a clinical and environmental source. Environmental strains belonging to these C-types showed greater adhesion to A-498 cells than did clinical strains (17 ± 13 bacteria/cell versus 13 ± 11 bacteria/cell; p < 0.001), whereas clinical strains showed significantly greater adhesion to Calu-3 and Caco-2 cells than did environmental strains (p < 0.001 for both). The virulence genes and antibiotic resistance profiles of the strains were similar; however, the prevalence of environmental strains carrying both exoS and exoU was significantly (p < 0.0368) higher than clinical strains. While all strains were resistant to ticarcillin and ticarcillin-clavulanic acid, resistance against aztreonam, gentamicin, amikacin, piperacillin, and ceftazidime varied among environmental and clinical strains. These results suggest that environmental strains of P. aeruginosa carry virulence properties similar to clinical strains, including adhesion to various human cell lines, with some strains showing a higher adhesion to specific cell lines, indicating they may have a better ability to cause infection in those sites under predisposing conditions of the host.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".