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Record W2964229188 · doi:10.1089/end.2019.0009

Application of Novel 3,4-Dihydroxyphenylalanine-Containing Antimicrobial Polymers for the Prevention of Uropathogen Attachment to Urinary Biomaterials

2019· article· en· W2964229188 on OpenAlexaff
Roderick A. MacPhee, Justin T. Koepsel, Thomas Tailly, Sai K. Vangala, Liam Brennan, Peter A. Cadieux, Jeremy P. Burton, Chris Wattengel, Hassan Razvi, Jeffrey L. Dalsin

Bibliographic record

VenueJournal of Endourology · 2019
Typearticle
Languageen
FieldChemistry
TopicAntimicrobial agents and applications
Canadian institutionsFanshawe CollegeWestern UniversityUniversity of TorontoLawson Health Research Institute
Fundersnot available
KeywordsMedicineAntimicrobialUrinary systemDihydroxyphenylalanineInternal medicineMicrobiology

Abstract

fetched live from OpenAlex

Introduction and Objective: Urinary catheters and stents are frequently prone to catheter-associated urinary tract infections (CAUTI) through biofilm formation. Several strategies have been evaluated in search of a stent coating to reliably prevent adherence of bacteria and biofilm. Previous in vivo and in vitro research with methoxylated polyethylene glycol 3,4-dihydroxyphenylalanine (DOPA) copolymer as a candidate coating showed promising results to reduce the bacterial attachment. We aimed to further enhance this antimicrobial activity by adding antimicrobial agents to newly synthesized DOPA-based copolymers. Materials and Methods: Building on our previous experience, novel copolymers were engineered based on DOPA. Quaternary ammonium groups and silver particles were added by cross-linking to increase the antimicrobial activity through both kill-by-contact and planktonic killing. After coating polyurethane sheets and measuring contact angles, all candidate coatings were challenged in vitro with an Escherichia coli culture. The most promising coatings were then further evaluated against a panel of seven clinically relevant uropathogens and planktonic killing, and microbial attachment was determined. Results: Initially, seven coatings were developed, referred to as Surphys 093–099. The most significant increase in contact angle was identified in Surphys-095 and -098. Surphys coatings S-094, S-095, and S-098 were cross-linked with silver and exhibited profound antimicrobial properties when challenged with E. coli . Further testing demonstrated S-095 to have antimicrobial efficacy against gram-positive and gram-negative bacteria at different silver-loading concentrations. The final coating, consisting of a 2 mg/mL solution of S-095 cross-linked with 0.25 mg/mL AgNO 3 , appeared to be highly bactericidal showing a ≥99.9% bacterial killing effect while remaining below cytotoxicity levels. Conclusions: We were able to engineer DOPA-based copolymers and add quaternary ammonium and silver particles, thus increasing the bactericidal properties of the coating. These coatings have exhibited a biologically significant ability to prevent uropathogens from attaching to biomaterials and represent a realistic opportunity to combat CAUTI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.287
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2019
Admission routes1
Has abstractyes

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