Swarming of <i>Proteus mirabilis</i> over Ureteral Stents: A Comparative Assessment
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Encrustation on indwelling ureteral stents is commonly related to the presence of urease-producing bacteria that elevate the pH of the urine through the hydrolysis of urea, resulting in the precipitation of calcium and magnesium salts. Using a model previously shown to measure accurately the ability of Proteus mirabilis to swarm over catheter surfaces (Eur J Clin Microbiol Infect Dis 1999;18:206), we investigated the ability of this organism to swarm over three ureteral stents with potential encrustation-resistance properties. MATERIALS AND METHODS: Three commercially available ureteral stents were selected for evaluation: a low surface-energy stent, a hydrogel-coated stent, and a silicone stent. Ten-microliter aliquots of a 4-hour culture of P. mirabilis 296 in Trypticase soya (TSA) broth was inoculated 5 mm from a 1-cm channel cut out from TSA plates. Ten-millimeter stent sections were placed as bridges across the central channel adjacent to the inocula. Time to pathogen crossing was measured. RESULTS: The mean time (+/- SD) to pathogen migration across the three test materials was 15.9 +/- 6.1, 19.8 +/- 9.5, and 29.7 +/- 14.3 hours for the low surface-energy, hydrogel-coated, and silicone stents, respectively. Statistical analysis revealed significant differences between the crossing times of the low surface-energy (P = 0.001) and hydrogel-coated (P = 0.034) stents compared with silicone but not between the low surface-energy and hydrogel-coated stents (P = 0.387). CONCLUSION: Migration of P. mirabilis 296 across silicone stents was significantly reduced compared with low surface-energy and hydrogel-coated stents. These findings suggest that P. mirabilis may have a lower affinity for silicone stents, which may translate into a reduced risk of infection with P. mirabilis and associated stent encrustation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".