Early wound infection monitoring via headspace O2 micro-respirometry

A luminescence based, inexpensive, 3D printed O<sub>2</sub> indicator is incorporated into a commercial, clear, occlusive wound dressing, which allows the %O<sub>2</sub> in the headspace above a simulated wound to be monitored. Two wound models are used to evaluate this micro-respirometry-based system for monitoring wound infection namely, a simple 'agar plug' model and a wounded porcine skin model. Inoculation of either wound model with E. coli, E. cloacae, or A. baumannii, produces the typical 'S'-shaped, τ vs incubation time, t, profiles, associated with micro-respirometry, due to the decrease in %O<sub>2</sub> in the headspace above the wound. A threshold value for the lifetime, τ<sub>TT</sub>, of 21.1 μs, is identified at which the bacterial load is equal to the critical colonization threshold, CCT, ca. 10<sup>6</sup> colony forming units, CFU/mL, above which infection is highly likely. The agar plug wound model/O<sub>2</sub> indicator combination is used to identify when the CCT is reached for a wide range of inoculant concentrations, spanning the range 10<sup>8</sup>-10<sup>1</sup> CFU/mL, for all three microbial species. The O<sub>2</sub> indicator is also successfully evaluated using a porcine skin wound model inoculated with E. coli. The results of this work are compared to other reported, usually invasive, smart wound monitoring systems. The possible use of this new, non-invasive smart-wound dressing technology, both at the point of care and at home, are discussed briefly.

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Publication Details

Journal
Biosensors and Bioelectronics
Published
2024-09-06
DOI
https://doi.org/10.1016/j.bios.2024.116751
Citations
4
Primary Topic
Wound Healing and Treatments
Type
article
Field-Weighted Citation Impact
1.00

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article

Early wound infection monitoring via headspace O2 micro-respirometry

Andrew Mills, Dilidaer Yusufu, Christopher O’Rourke, Michaella Watson
4 citations
Biosensors and Bioelectronics
Wound Healing and Treatments
1.00
article

Early wound infection monitoring via headspace O2 micro-respirometry

Andrew Mills, Dilidaer Yusufu, Christopher O’Rourke, Michaella Watson
article en
4 citations

Abstract

A luminescence based, inexpensive, 3D printed O<sub>2</sub> indicator is incorporated into a commercial, clear, occlusive wound dressing, which allows the %O<sub>2</sub> in the headspace above a simulated wound to be monitored. Two wound models are used to evaluate this micro-respirometry-based system for monitoring wound infection namely, a simple 'agar plug' model and a wounded porcine skin model. Inoculation of either wound model with E. coli, E. cloacae, or A. baumannii, produces the typical 'S'-shaped, τ vs incubation time, t, profiles, associated with micro-respirometry, due to the decrease in %O<sub>2</sub> in the headspace above the wound. A threshold value for the lifetime, τ<sub>TT</sub>, of 21.1 μs, is identified at which the bacterial load is equal to the critical colonization threshold, CCT, ca. 10<sup>6</sup> colony forming units, CFU/mL, above which infection is highly likely. The agar plug wound model/O<sub>2</sub> indicator combination is used to identify when the CCT is reached for a wide range of inoculant concentrations, spanning the range 10<sup>8</sup>-10<sup>1</sup> CFU/mL, for all three microbial species. The O<sub>2</sub> indicator is also successfully evaluated using a porcine skin wound model inoculated with E. coli. The results of this work are compared to other reported, usually invasive, smart wound monitoring systems. The possible use of this new, non-invasive smart-wound dressing technology, both at the point of care and at home, are discussed briefly.

Biosensors and BioelectronicsVol. 267
Queen's University Belfast (GB), Stranmillis University College (GB), Queens University (BD)
Engineering and Physical Sciences Research Council
Good health and well-being
Openalex Percentile: Top 21%
Wound Healing and Treatments
1.00
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Early wound infection monitoring via headspace O2 micro-respirometry — Andrew Mills, Dilidaer Yusufu, et al. · Biosensors and Bioelectronics (2024) | TGRS Research Map | TGRS