Master of Science, University of Toledo, 2020, Chemistry

Microcystins (MCs) are widespread cyanotoxins present in water sources contaminated with cyanobacteria during harmful algal blooms (HABs), and are compounds of concern due to their hepatotoxicity. Despite the regulation of their allowed concentration in drinking water, humans could be exposed to MCs by water or food consumption, or during recreational activities in affected bodies of water. Therefore, the studies of mechanisms of MC activity, transportation and detoxification pathways are important for the better understanding of both their chronic and acute toxicity. Also, quick and reliable methods of water analysis are needed in order to determine the presence of the toxins and prevent human exposure. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a valuable technique for the visualization of analytes in biological tissues and other media. Herein, MALDI-MSI was applied to investigate the distribution of MC-LR and its metabolites in liver tissue sections obtained from mice exposed to MC-LR. The study was directed on the effect of the chronic MC-LR toxicity below the no observed adverse effect level (NOAEL) on control mice and mice used to model non-alcoholic fatty liver disease (NAFLD). Limits of detection (LOD) of MC-LR with MALDI-MS were determined for on-plate and on-tissue MALDI-MSI experiments. MALDI-MS imaging procedures were also optimized. Different variations of the matrix deposition and sample preparation were examined, and the most effective MALDI-MSI protocol was used for imaging of MC-LR in the liver tissue of the studied mice. MCs are produced within cyanobacterial cells, and their release into water could happen during cell death or water treatment procedures. Thus, cell lysis and MC release and extraction have to be studied and evaluated. At the same time, monitoring of the extracellular MCs in the water sources is an important task and should be rapid and reliable. In the second project, high-pe (open full item for complete abstract)

Committee: Dragan Isailovic (Committee Chair); Eric Findsen (Committee Member); Terry Bigioni (Committee Member) Subjects: Analytical Chemistry; Chemistry

Master of Science (MS), Ohio University, 2018, Chemistry and Biochemistry (Arts and Sciences)

Typically, for measurements with high dynamic range, the range is reduced by using the square root transform. By using non-integer roots coupled with systematic experimental design, improvements to the measurements may be obtained. The effect of using non-integer root transformation was evaluated using high-resolution mass spectrometry (HRMS) combined with nano-electrospray ionization (Nano-ESI) to differentiate 23-samples of Cannabis. The mass spectra were evaluated and classified using different mass resolving powers and non-integer root transformations. Classification was achieved by super partial least squares discriminant analysis (sPLSDA), support vector machine (SVM), and SVM classification tree type entropy (SVMTreeH). The 2.5 root transformation gave the best overall performance at different resolving powers for chemical profiling from a multilevel (4 × 5) factorial experimental design. Response surface modeling using a cubic polynomial model of the sPLS-DA prediction accuracies yielded optima at 0.00407 for resolving power and 2.51 for the root transformation. Root transformation is an important spectral preprocessing tool for decreasing the dynamic range so that the relative variance of smaller but more important features may be inflated.

Committee: Peter Harrington (Advisor); Anthony Stender (Committee Member); Jessica White (Committee Member); Martin Kordesch (Committee Member) Subjects: Chemistry