21–26 Jun 2026
U. Ottawa - Learning Crossroads (CRX) Building
America/Toronto timezone
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Differentiation of Bacterial Species in Biomedical Specimens Using Laser-Induced Breakdown Spectroscopy

22 Jun 2026, 14:15
15m
U. Ottawa - Learning Crossroads (CRX) Building

U. Ottawa - Learning Crossroads (CRX) Building

100 Louis-Pasteur Private, Ottawa, ON K1N 9N3
Oral Competition (Undergraduate Student) / Compétition orale (Étudiant(e) du 1er cycle) Physics in Medicine and Biology / Physique en médecine et en biologie (DPMB-DPMB) (DPMB) M2-8 | (DPMB)

Speaker

Ms Lauren Dmytrow (University of Windsor)

Description

Our research group has previously demonstrated the ability to detect bacteria within numerous types of biological media to a high degree of accuracy using laser-induced breakdown spectroscopy (LIBS). This presentation will describe our efforts to differentiate several bacterial species using this spectroscopic method in addition to detection. Experiments were conducted on Escherichia coli, Staphylococcus aureus, Mycobacterium smegmatis, Enterobacter cloacae, and Streptococcus salivarius. These pathogens were chosen as they can induce bacterial meningitis, a life-threatening infection of the membranous tissue surrounding the spinal cord and brain. There is a need for a rapid, convenient, and accessible diagnostic technique capable of accurately distinguishing between bacterial species in cases of such infection. This would allow physicians to prescribe appropriate antibiotic therapy in a timely manner.

Known aliquots of the aforementioned bacteria were spiked into blood, urine, and artificial cerebral spinal fluid (aCSF). A custom centrifugation system deposited a thin bacterial film onto a nitrocellulose medium. Optical emission spectra were produced by ablating the bacterial film with a 1064 nm, 9 ns Nd:YAG laser, creating a high-temperature microplasma. Approximately 26,500 cells were ablated with each laser pulse.

Classification of bacterial species based on their LIBS spectra was accomplished with various chemometric methods, namely partial least squares discrimination analysis (PLS-DA) and an artificial neural network with principal component analysis preprocessing (PCA-ANN). Two separate datasets were used in the analysis. For PCA-ANN, the full optical spectrum, ranging from 205 nm to 590 nm, was utilized. For PLS-DA, the intensities of 15 emission lines from Ca, Mg, Na, C, and P and ratios of those intensities formed datasets with 107 total variables.

The classification accuracies of the resulting analyses will be presented, providing insight into the usefulness of LIBS in discriminating between bacterial species when they are present in human specimens.

Keyword-1 Laser spectroscopy
Keyword-2 Bacteria
Keyword-3 Medical diagnostics

Authors

Ms Lauren Dmytrow (University of Windsor) Mr Abdullah Mustafa (University of Windsor)

Co-authors

Rachel Chevalier Matteo Pontoni Ms Simona Brezeanu (University of Windsor) Ms Jasmine Fric (University of Windsor) Ms Katherine Keller (University of Windsor) Ms Emma Pesce (University of Windsor) Prof. Steven Rehse (University of Windsor)

Presentation materials

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