Evidence map›Paper›PMID 27842360›Full record

ArticleJournal of visualized experiments : JoVE2016

High-throughput Identification of Bacteria Repellent Polymers for Medical Devices.

Seshasailam Venkateswaran, Peter J Gwynne, Mei Wu, Ailsa Hardman, Annamaria Lilienkampf, Salvatore Pernagallo, Garry Blakely, David G Swann, Mark Bradley, Maurice P Gallagher

Abstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Seshasailam VenkateswaranSchool of Chemistry, EaStCHEM, University of Edinburgh.
Peter J GwynneSchool of Biological Sciences, University of Edinburgh.
Mei WuSchool of Chemistry, EaStCHEM, University of Edinburgh.
Ailsa HardmanSchool of Biological Sciences, University of Edinburgh.
Annamaria LilienkampfSchool of Chemistry, EaStCHEM, University of Edinburgh.
Salvatore PernagalloSchool of Chemistry, EaStCHEM, University of Edinburgh.
Garry BlakelySchool of Biological Sciences, University of Edinburgh.
David G SwannCritical Care, NHS Lothian, Royal Infirmary of Edinburgh.
Mark BradleySchool of Chemistry, EaStCHEM, University of Edinburgh; Mark.Bradley@ed.ac.uk.
Maurice P GallagherSchool of Biological Sciences, University of Edinburgh; mp.gallagher@ed.ac.uk.

Funding

Biotechnology and Biological Sciences Research CouncilMedical Research Council
6 · The paper itself

Abstract

Medical devices are often associated with hospital-acquired infections, which place enormous strain on patients and the healthcare system as well as contributing to antimicrobial resistance. One possible avenue for the reduction of device-associated infections is the identification of bacteria-repellent polymer coatings for these devices, which would prevent bacterial binding at the initial attachment step. A method for the identification of such repellent polymers, based on the parallel screening of hundreds of polymers using a microarray, is described here. This high-throughput method resulted in the identification of a range of promising polymers that resisted binding of various clinically relevant bacterial species individually and also as multi-species communities. One polymer, PA13 (poly(methylmethacrylate-co-dimethylacrylamide)), demonstrated significant reduction in attachment of a number of hospital isolates when coated onto two commercially available central venous catheters. The method described could be applied to identify polymers for a wide range of applications in which modification of bacterial attachment is important.

Indexed as

BacteriaEquipment and SuppliesEquipment ContaminationPolymersBacterial AdhesionPolymers

Identifiers

PMID27842360
PMCPMC5226084

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.