Graduate Theses & Dissertations

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Endocannabinoid Treatment for the Behavioural and Histopathological Alterations of Epilepsy
Epilepsy is associated with a variety of cognitive, emotional, and pain-related symptoms, such as impaired memory and learning, increased risk of anxiety and depression, and increased pain sensitivity. Unfortunately, these symptoms are generally untreated with typical pharmacological interventions, which tend to target seizure activity (i.e., ictogenesis) and not the subsequent histopathological and behavioural alterations resulting from epilepsy (i.e., epileptogenesis). Evidence has demonstrated that targeting the endocannabinoid system can alleviate seizure symptoms as well as cognitive, emotional, and pain-related impairments independent of epilepsy. However, research examining the use of endocannabinoid-based treatment for these behavioural symptoms when they are associated with epilepsy is sparse. In the following thesis, two animal models of epilepsy, several behavioural assessments, and immunohistochemical techniques are utilized to assess the effectiveness of endocannabinoid-based treatment for epilepsy’s interictal symptoms. The findings expand our knowledge and offer encouraging evidence for the usefulness of endocannabinoid-based treatment as an epileptogenesis-targeting pharmacological intervention. Author Keywords: animal models, endocannabinoid system, histopathological alterations, interictal symptoms, temporal lobe epilepsy, treatment
Unbridled Potential
Recently, equine assisted learning (EAL) has emerged as a novel approach to building resiliency competencies in at-risk youth. This mixed-methods study presents evaluation results for an 8-week community-based EAL program with 83 young women (age 13-18 years) with a history of interpersonal trauma. Analyses examined changes in self-reported mental health symptoms (posttraumatic, depression) and resiliency factors (sense of mastery, sense of relatedness, emotion regulation) from pre- to post-test and at 1-month and 6-month follow-ups. Changes in outcomes were also correlated with intervention processes (attendance, session ratings) to see if program experiences were associated with differential outcomes. Results showed that EAL has potential in improving resiliency outcomes, at least for those participants who derived greater satisfaction and value from the sessions. Many improvements were sustained over the long term. Participants’ qualitative feedback provided insight into their subjective experiences and highlighted the unique role that horses played in the EAL process. Author Keywords: Emotion Regulation, Equine Assisted Learning, Experiential Learning, Resilience, Sense of Mastery, Sense of Relatedness
Capital Ratios and Liquidity Creation
Using quarterly data from the six largest Canadian banks, we investigate the relationship between regulatory capital ratio and on-balance sheet liquidity created in the Canadian economy by “Big Six”. We find a significant positive relationship between Tier 1 capital ratio and on-balance sheet liquidity creation for Canadian big six banks, implying that large banks in Canada favor risks and rely on capital to fund illiquid assets. In contrast, for smaller banks, the relationship is significantly negative. Our results are robust to dynamic panel regression using 2-Step GMM, two exogenous shocks - COVID-19 crisis and the Global Financial Crisis (2007-2009), mergers & acquisitions activities in the banking industry, and core deposits financing. The COVID-19 pandemic and core deposits adversely impact the Tier 1 capital ratio’s relationship with on-balance-sheet liquidity creation, while the global financial crisis (2007-2009) effect on the association is insignificant. Author Keywords: Big Six, COVID -19, Deposits, Liquidity Creation, Tier 1 Capital Ratio,
Immunotherapies Targeting the Amyotrophic Lateral Sclerosis-Associated Protein TDP-43
Transactive response (TAR) DNA-binding protein of 43 kDa (TDP-43) pathology, including fibrillar aggregates and mutations, develops in amyotrophic lateral sclerosis (ALS) and is characterized by hyperphosphorylation and aggregation patterns, a mechanism largely understudied. In addition, ALS remains without a cure. Herein, in vitro aggregation of phosphorylated TDP-43 was explored, and the anti-TDP-43 antibodies tested for their inhibitor efficacies. Additionally, in vitro phosphorylation of TDP-43 by protein kinases was conducted to identify which protein kinases catalyze phosphorylation. The aggregation of phosphorylated and unphosphorylated full-length TDP-43 protein (pS410) was monitored by transmission electron microscopy (TEM), turbidity absorbance, and thioflavin (ThT) fluorescence spectroscopy. The protein aggregates were largely insoluble, ThT-positive and characterized with heterogeneous morphologies. Antibodies specific to epitopes within the RNA-recognition motifs and the C-terminal domains reduced the formation of β-sheets and insoluble aggregates, with outcomes highly dependent on the type of antibodies, indicating dual functionality. The only protein kinase able to phosphorylate TDP-43 at S410 was MARK4, indicating its role in the onset of PTMs in the protein. Thus, targeting TDP-43 epitopes for inhibition of aggregation and in vitro phosphorylation represent viable biochemical assays for screening protein kinase inhibitors as potential drugs against ALS. Author Keywords: aggregation, ALS, antibody-based inhibition, phosphorylation, protein kinase, TDP-43
Demographic history and conservation genomics of caribou (Rangifer tarandus) in Québec
Genetic variation is the raw material and basis for evolutionary changes in nature. The loss of genetic diversity is a challenge many species are facing, with genomics being a potential tool to inform and prioritize decision making. Whole genome analysis can be an asset to conservation biology and the management of species through the generation of more precise and novel metrics. This thesis uses whole genome re-sequencing to characterize the demographic history and quantify genomic metrics relevant to conservation of caribou (Rangifer tarandus) in Québec, Canada. We calculated the ancestral and contemporary patterns of genomic diversity of five representative caribou populations and applied a comparative population genomics framework to assess the interplay between demographic events and genomic diversity. When compared to the census size, NC, the endangered Gaspésie Mountain caribou population had the highest ancestral Ne:NC ratio which is consistent with recent work suggesting high ancestral Ne:NC is of conservation concern. These ratios were highly correlated with genomic signatures (i.e. Tajima’s D) of recent population declines and explicit demographic model parameters. Values of contemporary Ne, estimated from linkage-disequilibrium showed Gaspêsie having among the highest contemporary Ne:NC ratio. Importantly, classic conservation genetics theory would predict this population to be of less concern based off this metric alone. Inbreeding measures suggested nuanced patterns of inbreeding and correlated to the demographic models. This study suggests that while the Québec populations are all under decline, they harbour enough ancestral genetic variation to replenish any lost diversity, if conservation decisions are made in favour of these populations, specifically supporting NC. Author Keywords:
Assessing the environmental correlates of a lethal amphibian pathogen, Batrachochytrium dendrobatidis, in Ontario wetlands
Many emerging infectious diseases are caused by pathogens that possess free-living life stages, in which they interact with the environment directly rather than through the mediation of a host. These diseases represent major impediments to wildlife conservation; however, the dynamics of their interaction with the environment are poorly studied, often due to the difficulty of detecting these microscopic pathogens in environmental samples. One of these pathogens is Batrachochytrium dendrobatidis (Bd), a fungus that has been linked to declines in many amphibian species. In this thesis I use an emerging technique, environmental DNA detection (eDNA), to detect and quantify Bd in the water of southern Ontario (Canada) wetlands and examine its correlation with a variety of aspects of water quality, surrounding habitat, and seasonal timing. My purpose was to inform not only on potential environment-pathogen dynamics for Bd in northern environments, but to provide insight into the use of eDNA as a disease surveillance tool. I found that not only was there high geographic variation in Bd detection and intensity, but also high temporal variation within the same site on time scales as low as two weeks. While Bd prevalence was not strongly correlated with any of the variables tested, intensity showed strong correlation with canopy cover, with greater canopy cover over a waterbody correlating to lower Bd intensity. My results present several promising avenues for further examination of Bd in northern ecosystems, and indicate that, while caution is warranted in its implementation, eDNA may become an important tool in amphibian pathogen surveillance. Author Keywords: amphibian disease, Batrachochytrium dendrobatidis, disease monitoring, environment-pathogen dynamics, environmental DNA, wildlife disease
Evidence for hybrid breakdown in the cattail (Typha) hybrid swarm in southern Ontario
Heterosis, expressed as phenotypic superiority over parental species, typically peaks in first generation hybrids (F1s), while later generations (F2 +) exhibit lower fitness. The decrease in hybrid fitness is called hybrid breakdown. The overall incidence of hybrid breakdown in invasive hybrid zones remains poorly understood. The Laurentian Great Lakes (LGL) region contains a hybrid zone comprised of: native Typha latifolia, Typha angustifolia, and hybrid Typha × glauca. F1 T. × glauca display heterosis and are invasive, while later generation hybrids are relatively rare. To investigate possible hybrid breakdown, I compared seed germination and plant growth of backcrossed and advanced-generation (F2) hybrids to F1s and T. latifolia. I found evidence for hybrid breakdown in F2s and backcrossed hybrids, expressed as reduced growth and germination rates. Expression of hybrid breakdown in F2s and backcrosses may explain their relative rarity in the LGL hybrid zone. Author Keywords: Advanced-generation hybrids, Backcrossed hybrids, Hybridization, introgression, Invasive species, plant competition
evolutionary ecology of Alaska's mountain goats with management implications
The integration of genetic and environmental information can help wildlife managers better understand the factors affecting a species’ population structure and their response to disturbance. This thesis uses genetic techniques to assess the broad and fine scale population structure of mountain goats in Alaska. The first chapter aims to determine the number of genetically distinct subpopulations and model the demographic history of mountain goats in Alaska. The second chapter investigates the population structure and demographic history of mountain goats in Glacier Bay National Park and examines the impact that climate change will have on these mountain goats. My results indicate that Alaska has eight subpopulations which diverged during the Wisconsin glaciation. In Glacier Bay, population structure is reflective of the landscape during colonization, and mountain goat population density and movement corridors are likely to decline due to future climate change. Author Keywords: Alaska, biogeography, gene flow, landscape genetics, mountain goat, population genetic structure
Anthropogenic particles and microplastics in headwater lake catchments in Muskoka-Haliburton, Canada
Microplastics, plastic particles less than 5 mm in diameter, are ubiquitous in the environment. This study estimated the abundance of microplastics (MP) in atmospheric deposition from four background monitoring stations in Muskoka-Haliburton, south-central Ontario, Canada and quantified the fate of microplastics to three background headwater lake catchments in Muskoka-Haliburton. Microplastics were observed across all sample media with polyethylene terephthalate and polyamide being predominant. The average atmospheric deposition of anthropogenic particles was 57 particles/m2/day with a plastic deposition rate of 7 MP/m2/day. Atmospheric deposition represented the highest daily microplastic flux rate to the three headwater lake catchments compared, 1.5 to 4 times greater than the flux rate for the inflow streams suggesting that atmospheric deposition can account for all the inflowing microplastics. A large fraction of the microplastics from atmospheric deposition (41 – 73%) were retained in the terrestrial catchment and there was a high retention of microplastics in each of the study lakes (1.44 – 7.39 million MP/day; 30 – 45%) suggesting that a large fraction of the terrestrial catchment export is retained by the lakes and that lakes are a reservoir for microplastics. Author Keywords: Atmospheric deposition, Microplastics, Ontario, Plastic pollution, Sinks, Sources
Electrochemical Biosensors for Neurodegenerative Disease Biomarkers
The onset of neurodegenerative diseases such as Alzheimer’s disease (AD) and amyotrophic lateral sclerosis (ALS) are typically characterised by the aggregation of protein biomarkers into cytotoxic fibrils. Novel means of analysing these biomarkers are needed to expand the literature toward earlier diagnosis of these conditions. Electrochemical sensors could offer the sensitivity and selectivity needed for specialised analysis, including potential point-of-care applications. The AD biomarker Tau, and ALS biomarker TDP-43 proteins are explored here by using a label-free electrochemical sensors. Tau protein was covalently bound to gold electrode surface to study the in vitro mechanisms of aggregation for this protein. An immunosensor to TDP-43 was developed by covalently binding primary TDP-43 antibodies (Abs) on gold electrode surface. A novel direct ELISA sensor for TDP-43 with visual detection and electrochemical quantification was also developed. The results validated the experimental designs toward specialised and selective analysis of these biomarkers and their aggregation mechanisms. Author Keywords: ALS, Alzheimer's, Biosensors, Electrochemistry, Tau, TDP-43
Time Series Algorithms in Machine Learning - A Graph Approach to Multivariate Forecasting
Forecasting future values of time series has long been a field with many and varied applications, from climate and weather forecasting to stock prediction and economic planning to the control of industrial processes. Many of these problems involve not only a single time series but many simultaneous series which may influence each other. This thesis provides methods based on machine learning of handling such problems. We first consider single time series with both single and multiple features. We review the algorithms and unique challenges involved in applying machine learning to time series. Many machine learning algorithms when used for regression are designed to produce a single output value for each timestamp of interest with no measure of confidence; however, evaluating the uncertainty of the predictions is an important component for practical forecasting. We therefore discuss methods of constructing uncertainty estimates in the form of prediction intervals for each prediction. Stability over long time horizons is also a concern for these algorithms as recursion is a common method used to generate predictions over long time intervals. To address this, we present methods of maintaining stability in the forecast even over large time horizons. These methods are applied to an electricity forecasting problem where we demonstrate the effectiveness for support vector machines, neural networks and gradient boosted trees. We next consider spatiotemporal problems, which consist of multiple interlinked time series, each of which may contain multiple features. We represent these problems using graphs, allowing us to learn relationships using graph neural networks. Existing methods of doing this generally make use of separate time and spatial (graph) layers, or simply replace operations in temporal layers with graph operations. We show that these approaches have difficulty learning relationships that contain time lags of several time steps. To address this, we propose a new layer inspired by the long-short term memory (LSTM) recurrent neural network which adds a distinct memory state dedicated to learning graph relationships while keeping the original memory state. This allows the model to consider temporally distant events at other nodes without affecting its ability to model long-term relationships at a single node. We show that this model is capable of learning the long-term patterns that existing models struggle with. We then apply this model to a number of real-world bike-share and traffic datasets where we observe improved performance when compared to other models with similar numbers of parameters. Author Keywords: forecasting, graph neural network, LSTM, machine learning, neural network, time series
Population Genetics and Gut Microbiome Composition Reveal Subdivisions and Space Use in a Generalist and Specialist Ungulate
Natural populations are often difficult and costly to study, due to the plethora of confounding processes and variables present. This is of particular importance when dealing with managed species. Ungulates, for example, act as both consumers and prey sources; they also provide economic benefit through harvest, and as such, are of high ecological and economic value. I addressed conservation and management concerns by quantifying subdivision in wild populations and combined movement with non-invasive sampling to provide novel insight on the physiological drivers of space use in multiple species. This thesis explored biological patterns in ungulates using two distinct approaches: the first used molecular genetics to quantify gene flow, while the second examined the relationship between movement and the gut microbiome using high-throughput sequencing and GPS tracking. The goal of the first chapter was to quantify gene flow and assess the population structure of mountain goats (Oreamnos americanus) in northern British Columbia (BC) to inform management. I used microsatellites to generate genotype data and used a landscape genetics framework to evaluate the possible drivers behind genetic differentiation. The same analyses were performed at both a broad and fine scale, assessing genetic differentiation between populations in all of northern BC and in a case management study area northeast of Smithers BC. The results indicated panmixia among mountain goats regardless of scale, suggesting distance and landscape resistance were minimally inhibiting gene flow. Therefore, management at local scales can continue with little need for genetically informed boundaries, but regulations should be tailored to specific regions incorporating data on local access and harvest pressure. My second chapter aimed to determine the extent to which the gut microbiome drives space-use patterns in a specialist (mountain goat) and generalist (white-tailed deer, Odocoileus virginianus) ungulate. Using fecal samples, we generated genomic data using 16S rRNA high-throughput sequencing to evaluate gut diversity and gut microbiome characteristics. Additionally, individuals were fitted with GPS collars so that we could gain insight into movement patterns. Gut microbiome metrics were stronger predictors of space use and movement patterns with respect to home range size, whereas they were weaker predictors of habitat use. Notably, factors of both the gut microbiome and age of a given species were correlated with changes in space use and habitat use. Ultimately, this research linked high-throughput sequencing and GPS data to better understand ecological processes in wild ungulates. Author Keywords: gene flow, genomics, gut microbiome, home range, population genetic structure, ungulates

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Format: 2023/01/28