MP71-09 <i>IN VITRO</i> EVALUATION OF NOVEL SURFACE MODIFYING MOLECULES TO PREVENT BACTERIAL ADHESION TO UROLOGICAL DEVICES
Bibliographic record
Abstract
You have accessJournal of UrologyInfections/Inflammation/Cystic Disease of the Genitourinary Tract: Kidney & Bladder I (MP71)1 Apr 2019MP71-09 IN VITRO EVALUATION OF NOVEL SURFACE MODIFYING MOLECULES TO PREVENT BACTERIAL ADHESION TO UROLOGICAL DEVICES Christopher Munday*, Alexandra Piotrowicz, Kyle MacDonald, Antonio Cillero, Jeannette Ho, John Denstedt, and Jeremy Burton Christopher Munday*Christopher Munday* More articles by this author , Alexandra PiotrowiczAlexandra Piotrowicz More articles by this author , Kyle MacDonaldKyle MacDonald More articles by this author , Antonio CilleroAntonio Cillero More articles by this author , Jeannette HoJeannette Ho More articles by this author , John DenstedtJohn Denstedt More articles by this author , and Jeremy BurtonJeremy Burton More articles by this author View All Author Informationhttps://doi.org/10.1097/01.JU.0000557121.99973.c9AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVES: Bacterial adhesion and biofilm formation on urological devices such as stents and catheters is an undesirable phenomena that can lead to device-related infection and other co-morbidities. A range of potential technologies utilizing both passive mechanisms and active antimicrobials have been developed to combat this issue, but clinical efficacy remains limited. The objective of this study was to investigate the ability of a novel passive surface modification technology using fluorinated surface modifying molecules (SMMs) to address this clinical need. METHODS: Polyurethane control and SMM-modified prototypes for testing (rods or catheter tubing) were prepared using standard melt extrusion processes. X-ray photoelectron spectroscopy confirmed the presence of SMMs at device surfaces. Efficacy of devices to resist bacterial adhesion was assessed using both static and flow models. Static experiments consisted of sample incubation in bacterial inoculum followed by sonication to detach adhered bacteria and quantification by plate counts. Flow experiments were conducted using a custom circulating flow system with artificial urine. RESULTS: SMM-modified prototypes showed up to 2 log lower microbial adhesion compared to unmodified controls after 2h incubation in buffer inoculated with various gram positive, gram negative bacteria or yeast. The anti-adhesive property of SMM prototypes was confirmed in both artificial and human urine with three uropathogens (Escherichia coli, Enterococcus faecalis, Proteus mirabilis), as well as in clinical urine samples from patients with ureteral stents, where SMM-modified samples showed reduced attachment of mixed bacterial populations after 24h of incubation. Experiments under flow demonstrated potential of SMM-modified surfaces to resist adhesion in dynamic environments and for extended time frames, with 5 log lower attachment of E. coli observed on SMM-modified tubing vs controls at both 1 and 3 days post inoculation. Corresponding reductions in biofilm formation were confirmed with crystal violet staining and scanning electron microscopy. CONCLUSIONS: Modification of urological devices with SMMs may be an effective strategy to reduce bacterial adhesion and biofilm formation. The passive nature of the SMMs is advantageous as it provides a stable surface not subject to depletion or de-activation of the functional entity over time, as may be the case for surfaces modified with eluting or active antimicrobials. Source of Funding: Mitacs Accelerate Postdoctoral Fellowship London, Canada; Toronto, Canada; London, Canada; Toronto, Canada; London, Canada© 2019 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 201Issue Supplement 4April 2019Page: e1049-e1049 Advertisement Copyright & Permissions© 2019 by American Urological Association Education and Research, Inc.MetricsAuthor Information Christopher Munday* More articles by this author Alexandra Piotrowicz More articles by this author Kyle MacDonald More articles by this author Antonio Cillero More articles by this author Jeannette Ho More articles by this author John Denstedt More articles by this author Jeremy Burton More articles by this author Expand All Advertisement PDF downloadLoading ...
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 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".