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A smart bandage for the automatic detection and treatment of P. aeruginosa infections in burns

Infection of thermal injuries by bacteria is a growing concern in the healthcare community, leading to increased rates of morbidity and mortality. P. aeruginosa, a rod-shaped, Gram-negative bacteria is one of the bacterial species most commonly found in infected burns. Detecting infections in burns is still a somewhat archaic process involving visual inspection, in which dressings have to be removed (also causing more pain and discomfort to patients) before samples are sent to a laboratory for analysis. Timely in situ detection systems, which limit disturbances to the wound area, could drastically improve patient comfort and healing outcomes. While established infections, with fully developed biofilms, are difficult to treat, loose bacteria early on in an infection and biofilm formation are more likely to fall easy prey to antibiotics, if the appropriate drugs are administered in a timely manner. In this thesis a smart wound management system, geared towards detecting and eliminating P. aeruginosa infections in burns is presented. Both non-functionalized general purpose electrodes, paired with an affordable open source potentiostat, for electrochemical analysis, and on demand drug releasing elements were developed by layering conductive materials onto everyday cotton threads. The sensing elements were thoroughly characterized with the detection of a P. aeruginosa biomarker over a range of physiologically relevant concentrations and conditions. The ability of the thread based sensors to detect live bacteria and be integrated in textile wound dressings was demonstrated. Controlled drug release was also demonstrated through the development of several drug release profiles. The presented technology has the potential to greatly improve patient outcomes in burn wards and provides a platform for tackling other infectious organisms with the further development of more thread based tools. / Graduate / 2021-08-25

Identiferoai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/12103
Date02 September 2020
CreatorsHamdi, David
ContributorsAkbari, Mohsen
Source SetsUniversity of Victoria
LanguageEnglish, English
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf
RightsAvailable to the World Wide Web

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