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Background: There is considerable evidence that neuroinflammation plays a significant role in neurodegenerative diseases, hence there is a need for glial activation measurements in Alzheimer's disease (AD) with positron-emission tomography (PET). This thesis aims to 1) explore the quantification approach for novel glial activation tracers, 2) and develop new imaging techniques to evaluate biomarker interactions. Methods: [18F]GE180 and [11C]PBR28 for microglial activation were evaluated in 13 participants with AD and 13 with Mild Cognitive Impairment (MCI). [11C]BU99008 for astroglial activation was studied in 11 AD and MCI. Arterial input functions were acquired and full compartmental modelling, spectral analysis, graphic analysis, cluster analysis and standardized uptake value were evaluated. The VOI (Volume of interest) Prediction Tool (biomarker co-localization) and Individual Correlation Mapping (ICM) (biomarker correlation) were developed to assess biomarker interactions. Results: Based on Akaike Information Criterion, a two-tissue compartmental model demonstrated the best fit for [18F]GE180 and [11C]BU99008, while [11C]PBR28 fitted the two-tissue model with a vascular component. Impulse response function (IRF) generated by spectral analysis, have shown good consistency with compartmental modelling (R2>0.8, p<0.0001). [18F]GE180 revealed high plasma binding and low VT (AD=0.21 ±0.06 mL·cm-3, HC=0.17 ±0.05 mL·cm-3) in the brain. For amyloid-positive patients, I discovered 25% (p<0.01) and 19% (p<0.03) group-level increase in [11C]PBR28 and [11C]BU99008 VT, respectively. The interactive VOI of microglial activation, amyloid and tau has demonstrated a linear prediction model of individual annual cognitive decline (R2=0.86, p<0.0001). ICM demonstrated a positive correlation (R2=0.7, p<0.03) between the volume of biomarker interaction and the severity of the cognitive impairment on individual basis. Conclusion: This work explores the best quantification method for three new tracers and demonstrates elevation of glial activation in patients with neurodegenerative disease. The novel imaging techniques demonstrate an individualized association between biomarker interaction and cognitive performance, indicating the importance of biomarker interactions in AD.

Field isolates of Alternaria alternata from peach were previously characterized for their sensitivity to succinate dehydrogenase (SDH) inhibitor fungicides and the underlying molecular basis of resistance was determined. In the present study we report that isolates resistant to the SDHI fungicide, boscalid, regardless of genotype, were also resistant to pyraclostrobin and thiophanate-methyl. Resistance to pyraclostrobin was due to the G143A mutation in the cytb gene and resistance to thiophanate-methyl was due to a mutation of 167Y in the β-tubulin gene. Representatives of the two most commonly-isolated, SDHI resistance genotypes H277Y in sdh subunit B and H134R in sdh subunit C, as well as genotype D123E in sdh subunit D were selected for fitness evaluations. Genotypes H277Y and H134R suffered no fitness penalties based on mycelial growth on PDA, spore production in vitro, osmotic sensitivity, oxidative sensitivity, germination ability, or the ability to cause disease on peach fruit. Hypersensitivity to oxidative stress and weak sporulation was observed only in genotype D123E. No competitive advantage was detected for sensitive isolates over the course of five consecutive transfers on peach fruit when spores were mixed with genotypes H277Y or H134R. Results suggest that in the absence of fungicide pressure, A. alternata isolates resistant to MBC, QoI, and SDHI fungicides carrying the H277Y mutation in SDHB and the H134R mutation in SDHC may effectively compete with the boscalid-sensitive populations.