abstract: Circular RNAs (circRNAs) are a class of endogenous, non-coding RNAs that are formed when exons back-splice to each other and represent a new area of transcriptomics research. Numerous RNA sequencing (RNAseq) studies since 2012 have revealed that circRNAs are pervasively expressed in eukaryotes, especially in the mammalian brain. While their functional role and impact remains to be clarified, circRNAs have been found to regulate micro-RNAs (miRNAs) as well as parental gene transcription and may thus have key roles in transcriptional regulation. Although circRNAs have continued to gain attention, our understanding of their expression in a cell-, tissue- , and brain region-specific context remains limited. Further, computational algorithms produce varied results in terms of what circRNAs are detected. This thesis aims to advance current knowledge of circRNA expression in a region specific context focusing on the human brain, as well as address computational challenges. The overarching goal of my research unfolds over three aims: (i) evaluating circRNAs and their predicted impact on transcriptional regulatory networks in cell-specific RNAseq data; (ii) developing a novel solution for de novo detection of full length circRNAs as well as in silico validation of selected circRNA junctions using assembly; and (iii) application of these assembly based detection and validation workflows, and integrating existing tools, to systematically identify and characterize circRNAs in functionally distinct human brain regions. To this end, I have developed novel bioinformatics workflows that are applicable to non-polyA selected RNAseq datasets and can be used to characterize circRNA expression across various sample types and diseases. Further, I establish a reference dataset of circRNA expression profiles and regulatory networks in a brain region-specific manner. This resource along with existing databases such as circBase will be invaluable in advancing circRNA research as well as improving our understanding of their role in transcriptional regulation and various neurological conditions. / Dissertation/Thesis / Appendix file containing list of enriched pathways and functions identified in Chapter 4 / Doctoral Dissertation Biomedical Informatics 2018

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Doctor of Philosophy / Department of Chemistry / Duy H. Hua / Three research projects were carried out and they are described below. The synthesis of substituted phenolic compounds including halogenated di- and trihydroxybenzenes, aminophenols, and substituted di-tert-butylphenols are described. Redox potentials of the synthesized molecules along with various known laccase substrates were measured, and an inverse relationship between the oxidation potential and the efficiency of oxidation by laccase of halogenated hydroxybenzenes and aminophenols is demonstrated. The synthesized substituted phenols were found to be substrates but not inhibitors of laccase. We discovered a new class of di-tert-butylphenols compounds that inhibits the growth of mosquito larvae at low concentrations. Compound 17, 2,4-di-tert-butyl-6-(3-methyl-2-butenyl) phenol caused greater than 98% mortality of third-instar larvae of Anopheles gambiae in the concentration of 0.18 µM. These compounds do not inhibit laccases. It appears that they affect a new target of the mosquito that is different from those of currently existing pesticides. Two anti-Alzheimer molecules, CP2 and TP70, discovered in our laboratory were studied for their pharmacokinetics and distribution. The distribution of CP2 and TP70 in mouse brain region and various tissues of mice were examined. HPLC analysis revealed that CP2 treatment in primary neurons accumulates in mitochondria fraction. Similarly, the amount of CP2 in the brain tissue from wild type and APP/PS1 mice treated with 25 mg/kg/daily for 2 months also have the highest concentration in the mitochondria fractions in the hippocampus. The results show that CP2 and TP70 can penetrate the blood brain barrier and accumulate in the tissue in significant amounts. Pharmacokinetics and bioavailability of compound TP70 were determined. Area under the curve and bioavailability value F were calculated, and data show that TP70 has a good PK profile and bioavailability. For the preparation of a novel tripeptidyl norovirus 3C-like protease (3CL[superscript]pro) inhibitor, the P3 unnatural amino acid, (S)-3-hydroxyphenylalanine was synthesized. The P3 is designed to increase the polarity with the addition of the alcohol group. After combining the P3 unnatural amino acid with the P1 and P2 to form the novel tripeptidyl compound, a study comparing the relations between the structure and its activity (SAR) will confirm whether prediction is correct in our pursuit for an antiviral therapeutic drug in the form of a protease inhibitor.

A standard Neurofeedback approach to mitigate the working memory decline in some fragile groups (elderly, subjects affected by stroke or Alzheimer's disease) can be suboptimal for some patients. The goal of this research is to investigate which visual stimulus (among colour, geometrical shape, direction, and symbol) is the most suited for each of the six healthy participants and which brain areas are the most discriminative, during the maintenance of a presented stimulus in a retro-cue-based working memory experiment. In order to identify the most discriminative stimulus, the single-trial classification accuracies of some Support Vector Machines, trained on the theta, alpha and beta electroencephalography power bands, have been compared; while, in order to identify the most involved brain regions, three machine learning feature reduction techniques have been explored: the first based on a massive univariate analysis, the second based on multivariate filtering and wrapping, and the last one based on Frequency-based Common Spatial Pattern. The results have shown that the univariate approach, more than the others, managed to clearly identify for each participant at least one preferential type of stimulus and a brain region of discriminative electrodes during the maintenance of the stimulus. These promising results can be interpreted as a further step to optimize the Neurofeedback working memory enhancement through a personalised approach.