VictorJuiz/thesis huggingface dataset:
Public Health Applications of Genomic Epidemiology during the COVID-19 Pandemic

The COVID-19 pandemic has brought the power of genomic epidemiology to the forefront. Harnessing the information stored in genomic sequences supplemented with traditional epidemiological data important questions about the drivers of transmission can be elucidated. In this thesis, we used genomic epidemiological methods for surveillance, understanding transmission in outbreaks, and to create tools to help monitor the spread of SARS-CoV-2 VOCs. We identified potential introductions through returning travellers and characterized the genetic diversity and circulating lineages within the first three months of the pandemic in Ontario. Genomic epidemiology allowed us to discern whether farm outbreaks were seeded by multiple introductions and provided support to suggest that infections in farm outbreaks were acquired locally. Finally, understanding the genomic landscape of the variants of concern (VOC) lineages allowed us to develop an assay that allows for fast identification of VOCs, which is a useful tool in monitoring their spread. The results from each of these investigations can lead to policy changes or new measures to help prevent the spread of SARS-CoV-2.

Advisor: Gubbay, Jonathan
Allen, Upton
Constrained, Curiosity-driven Trajectory Optimization for Learned Quadrotor Control

Quadrotors have become widely used robotic platforms in recent years, but developing controllers can be challenging for difficult-to-model scenarios such as wind or ground effect. Simultaneously, model-based reinforcement learning (MBRL) has been applied to many robot platforms due to the ability to quickly learn a dynamics model and use the model for planning and control via data-driven methods. MBRL has been augmented with probabilistic modelling in order to address model bias concerns. Recent methods have used the variance from model predictions to drive exploration during learning, inspired by curiosity. In this thesis, we show that directly applying these methods to control quadrotors via thrust and rotation rate inputs can lead to stability concerns. We propose using ideas from safety-critical control to alleviate these stability concerns. Our method applies control barrier function (CBF) constraints during planning using an augmented Lagrangian approach. The resulting algorithm restricts exploration to areas of the state space where predictive model uncertainty is within tolerable limits, so predictions are more trustworthy. However, we identify some practical issues which affect optimization feasibility. We propose additional measures to alleviate these issues to enable stable, curiosity-driven exploration for quadrotors.

Keywords: optimal control
quadrotor
reinforcement learning
Advisor: Waslander, Steven L
5G Resource Allocation with Interference and Scarcity: Market Design for Spectrum and Beyond

Spectrum scarcity is a growing concern that has attracted attention from researchers, industry players, and regulators on a global scale. The ability to address it is fundamentally limited by interference, which constrains its occupancy, and the lack of utilization insights available to those who determine long-term allocations for it. This thesis investigates how the advent of network slicing in 5G networks interacts with this problem of spectrum scarcity. After reviewing the problem domain, we develop a competitive resource allocation mechanism that considers interference management and pricing jointly, analyze its economic properties, and show that it improves communication performance. We also show that it can be used to improve fairness. Next, we attack the scarcity problem by developing a market for virtual resources based on a common ownership self-assessed tax. We propose a utilization-based penalty mechanism and analyze the resulting market behaviour under various scenarios.

Keywords: 5G
Interference
Scarcity
Spectrum
Advisor: Adve, Raviraj S.
Characterizing Critical Language Sites Within the Distributed Pediatric Language Network Using MEG and rTMS

The primary objective was to compare MEG connectivity and centrality-based language maps to language rTMS findings. 49 subjects, ages 5-19, completed MEG (story listening), 26 of which completed both MEG and rTMS (object naming). MEG data was used to compute connectivity (COH, ABSIMAG, PLV, WPLI), and centrality (Eigencentrality, Betweenness) within canonical frequency bands. 33 rTMS sites were studied per hemisphere, regularly distributed over the lateral cortex. rTMS sessions were reviewed by two independent raters for language errors, and sites deemed critical based on agreement. MEG and rTMS results were assessed in a common anatomical framework and compared using ROC analyses. Combinations yielding maximal AUC and optimal threshold level were identified. Eigencentrality on coherence in beta band was in maximal agreement with rTMS. Retaining the top 45% of nodes yielded optimal balance between sensitivity and specificity. Thus, sites showing high Eigencentrality are useful for mapping critical language sites in development.

Advisor: Kadis, Darren
Depression Interacts with Allostatic Load to Predict Cognitive Decline in Middle Age

Allostatic load (AL) indicates the cumulative impact of stress on homeostatic mechanisms. Depression and AL have been associated with cognitive deficits, but it is unclear if they do so independently.Using data from middle-aged participants in the observational Midlife in the United States study (n=704, 57.5% female, 63.8±10.6 years old in 2014), we assessed whether the effect of prior depression in 1995 on cognitive decline (via the Brief Test of Adult Cognition by Telephone) between 2004 and 2013 was moderated by AL Z-scores in 2004 (calculated from blood, urine, and electrocardiography biomarkers). A significant depression × AL interaction predicted a decline in a composite cognitive (β=-0.066, SE=0.029, p=0.024) and executive function (β=-0.068, SE=0.025, p=0.007) scores. Depression predicted a decline in composite cognition among those with AL Z-scores above -0.055. Among AL subdomains, inflammation was the strongest moderator. Here we present evidence that depression and high AL predict cognitive decline interactively.

Keywords: allostatic load
cognition
depression
inflammation
moderation
stress
Advisor: Swardfager, Walter
Exogenous IL-4 and IL-10 Improve the Viability of Primary Hepatocyte Cultures

Most classical culture models fail to recapitulate the liver microenvironment, lacking the immune cell and factor interactions linked to regeneration in-vivo. We hypothesize that immunoregulatory cytokines IL-10, IL-4, and IL-22, secreted by hepatic macrophages and other liver cells, will maintain hepatocyte viability in primary hepatocyte monolayer culture by better mimicking the healthy in-vivo microenvironment. To assess this contribution, we determined a baseline measure of monolayer viability and function. Once established, we supplemented cells in culture with single cytokines at varying concentrations, or with a cytokine cocktail. Without cytokine supplementation, viability of hepatocyte cultures decreased significantly after 4 days, as measured via ATP secretion from metabolically active cells. We found that IL-4 supplementation at 50 ng/mL and the cytokine cocktail (IL-10, IL-4, and IL-22, 10 ng/mL each) prolonged hepatocyte viability to day 7. Optimizing these monolayer cultures using mouse livers will provide a framework for adapting this system to human liver tissue with the goal of guiding interventions that will promote human liver regeneration.

Keywords: Hepatocyte
Hepatocyte Monolayer
Immunoregulatory Cytokine
Liver
Macrophage
Advisor: MacParland, Sonya A
Factors Associated with End of Treatment Quality of Life, Cardiac Function and Cardiorespiratory Fitness and the Effect of Exercise in Women with Breast Cancer

Women with human epidermal growth factor receptor-2 positive (HER2+) breast cancer are at increased risk of cardiovascular disease (CVD), CVD mortality, reductions in cardiorespiratory fitness and quality of life due to pre-existing CVD risk factors, cardiotoxic cancer therapies and lifestyle habits. Risk factors associated with lower cardiac function and cardiorespiratory fitness at end of treatment and strategies to mitigate this decline remain unclear. The goals of this thesis were to explore (1) pre-treatment and during treatment clinical and imaging factors that are associated with end of treatment cardiac function and cardiorespiratory fitness; (2) the effects of physical activity on cardiovascular outcomes, and quality of life during and at the end of treatment and cardiorespiratory fitness at end of treatment and; (3) the quality of evidence for cardiac rehabilitation in cancer survivors to improve cardiovascular outcomes.

Keywords: Breast Cancer
Cardiac Function
Cardiovascular Disease
Exercise
Physical Activity
Quality of Life
Advisor: Thavendiranathan, Paaladinesh
Treatment Modifications in Chronic Hepatitis B

As chronic hepatitis B continues to affect more than 250 million individuals, new treatment plans aim toward better viral suppression, safety, and functional cure. In Study I, we studied the kinetics of two new serum biomarkers, HBV RNA and HBcrAg, and their potential role as predictors for clinical applicability and treatment response after nucleosi(t)ide analog (NA) treatment withdrawal. Detectable levels of HBcrAg were associated with increased retreatment after treatment withdrawal (p<0.005, HR: 4.83), albeit with limited associations in virological and clinical relapse outcomes. In Study II we studied the efficacy and safety of switching from tenofovir disoproxil fumarate (TDF) to newer tenofovir alafenamide fumarate (TAF)-based regimens in HIV/HBV co-infected patients. TAF switch led to greater ALT normalizations in those with elevated ALT (p=0.03), and significantly halted eGFR decline compared to time on TDF (slope difference p=0.01). No significant changes in lipid profiles were observed.

Keywords: chronic hepatitis B
HBV
hepatitis B
stopping therapy
TAF
viral hepatitis
Advisor: Janssen, Harry LA
Eddy Current Damping of Magnetically Actuated Neurosurgical Instruments

Magnetically actuated minimally invasive neurosurgical tools tend to oscillate for an extended period of time due to lack of avenues for energy removal from the system. After determining target damping coefficients ($4.31*10^{-9} $ Ns m$^{-1}$ for a 2% settling time less than 0.3 s and $2.01* 10^{-6} $ Ns m$^{-1}$ for critical damping), a feasibility study was conducted by approximating the damping coefficient using adapted equations from Hahn, Donoso, Mehrtash, and Sodano et al. This resulted in 0.11 Ns m$^{-1}$, 2.75*10$^{-5}$ Ns m$^{-1}$, 2.02*10$^{-4} $Ns m$^{-1}$, 0.01 Ns m$^{-1}$ respectively. An experimental study was then performed to validate the values and relationships from the feasibility study. Six measurements were taken at gap sizes (between the magnet and conductor) of $0 \mu$m, $100 \mu$m, $200 \mu$m, $300 \mu$m, $400 \mu$m, $500 \mu$m, $750 \mu$m, $1000 \mu$m, $1500 \mu$m, and $2000 \mu$m with copper conductors of thicknesses 0.005” to 0.025” in 0.005” increments. While it was determined that sufficient damping could be generated experimentally (maximum damping documented is $1.24*10^{-6}$ Ns m$^{-1}$), concrete relationships between each variable with the damping coefficient were inconclusive.

Keywords: Damping
Eddy Current
Magnet
Microrobotics
Neurosurgery
Advisor: Drake, James
Diller, Eric
A Knowledge-based Feature Representation to Discover the Function of Non-coding Sequences

Understanding how non-coding regions of DNA determine gene expression is an important challenge in genome analysis. Deep-learning approaches have aimed to “represent” DNA sequences as high-dimensional vectors, which can be used to predict gene expression. We wondered whether a high-dimensional representation using evolutionary conservation of known binding motifs could predict patterns of gene expression. By taking advantage of publicly available databases of binding motifs and by obtaining large numbers of orthologous non-coding regulatory sequences, we could group genes with similar expression patterns or functional annotations together based only on DNA sequences. Our representation could predict new function for Saccharomyces cerevisiae promoters and rediscover known regulatory function for human promoters. We used this approach to create a representation of 3’UTR sequences of S. cerevisiae using RNA binding motifs and found strong association for sub-cellular localization of mRNA. Our results suggest that global, high-dimensional views are essential to understand the cis-regulatory code.

Keywords: Non-coding DNA
Orthologous Sequences
Predicting Function
Promoters
Representation Learning
Transcription Factors
Advisor: Moses, Alan
Indigenous Resurgence in Colonial Urban Parks: Possibilities and Potential for Urban Indigenous Land-based Practices

This thesis is an exploration of colonial dispossession within cities and specifically urban parks recognizing all parks in so-called Canada exist on the traditional territories of Indigenous peoples. Within this thesis I utilize mixed methods, first conceptual analysis is used to discuss the structural-materialist emergence of urban parks as colonial spaces. Secondly, drawing from my own embodied experience earthworking with Two-Spirit Indigiqueer community in High Park, Tkaronto, I engage with land-based theoretical frameworks including land as pedagogy, kincentric ecologies, and reciprocal restoration to story ongoing Indigenous resurgence and futurities. This research considers the colonization of urban parks, and the possibilities and need for improved access for urban Indigenous peoples to engage in land-based practices. I argue, Indigenous inclusion within urban parks, at various levels, is required for the future ecological sustainability of parks and to create safe and accessible spaces for urban Indigenous peoples to enact land-based cultural practices.

Keywords: Indigenous futurities
Indigenous resurgence
Indigenous studies
kincentric ecologies
land-based practices
urban parks
Advisor: Daigle, Michelle
Light-sheet Light-field Fluorescence Brain Imaging Enabled by Implantable Neural Probes

Deep brain fluorescence imaging for freely-behaving animals allows researchers to better understand the function of neural circuitry; however, miniature microscopes capable of high spatial resolution use implantable lenses that cause irreversible tissue damage. To reach the goal of simultaneously achieving high-resolution imaging and less invasive measurements, we developed an implantable lens-less imaging system for volumetric fluorescence brain imaging. The imaging system consists of an implantable light-sheet neural probe integrated with an image fiber bundle to realize light-sheet light-field microscopy for high-contrast, cellular resolution volumetric imaging. Our imaging system shows great promise for in vivo brain experiments and may also have clinical uses in visualizing regions of the body that are difficult to reach.

Keywords: computational imaging
fluorescence brain imaging
implantable neural probes
integrated optics;
light field imaging
light sheet microscopy
Advisor: Poon, Joyce KS
Projecting the Future Prevalence of Childhood Cancer In Ontario using Microsimulation Modeling

Children diagnosed with cancer have lifelong health care needs. The prevalence of childhood cancer has been steadily increasing in Ontario, though no prevalence projections exist to anticipate future health care system demands. A population-based, open-cohort microsimulation model was constructed to project the limited-duration prevalence of childhood cancer in Ontario, by cancer type, for years 2020-2040. Model inputs were derived from health administrative databases, provincial population data sources, and external literature. Beginning with 1970, the model population was updated annually with births, deaths, net migration, and incident cases of childhood cancer. Fifty Monte Carlo simulations were run to vary model inputs and generate median health outcomes with 95% credible intervals (CI). Between 2020 and 2040, annual incidence counts are projected to increase by 33%. In 2040, 25171 (95% CI: 24267-26975) individuals are projected to reside in Ontario who were diagnosed in 1970 or later, 87% of which will be 5-year survivors.

Keywords: Cancer epidemiology
Health system planning
Microsimulation
Pediatric cancer
Prevalence
Advisor: Nathan, Paul C.
Gupta, Sumit
Detecting Driver Drowsiness using Peripheral Physiological Signals

In the context of driving, drowsiness is found to be a major risk factor of vehicle collisions worldwide. An underexplored, yet promising area of research is the use of physiological signals in assessing driver drowsiness. Electroencephalogram (EEG) has dominated the field as the gold standard due to its accuracy in determining changes in wakefulness, but is less applicable in driving scenarios due to introduced noises and its invasiveness for the driver. Consequently, the goal of this thesis project was to analyze and derive a preliminary solution for the detection of drowsiness while driving using physiological signals. Specifically, the focus was on non-EEG measures including electrocardiogram (ECG), respiratory signals, galvanic skin response (GSR) and temperature. We achieved this goal through two main objectives: A systematic review that explored the use of physiological signals, and the creation of both a model as well as system to reliably detect drowsiness.

Keywords: Detection
Driving
Drowsy
Physiological
Advisor: Yadollahi, Azadeh
Comparing the Effects of Cognitive Restructuring, Cognitive Defusion, and Thought Monitoring on Voice-Hearing Distress in Psychosis

Cognitive Behavioural Therapy for psychosis (CBTp) is effective to reduce symptoms of psychosis but effects are typically only moderate. To improve the efficacy of CBTp, it is critical to determine the mechanisms of change. The current study evaluated the effectiveness of cognitive restructuring, cognitive defusion, and thought monitoring in reducing the distress of verbal hallucinations. Twenty-six participants (CR = 8, CD = 9, TM = 9) with a psychotic disorder and verbal hallucinations completed the study. There were no significant time by group interactions or main effects on distress, cognitive restructuring ability, or cognitive fusion. Exploratory and qualitative feedback suggest that cognitive restructuring may be effective at reducing voice-related distress and the cognitive defusion milk exercise may actually increase distress for some individuals. Further research may be warranted to examine the differential effects of CBTp techniques to reduce voice-related distress.

Advisor: Best, Michael
Magnetic Resonance Imaging Schedule Optimization at JDMI

The Joint Department of Medical Imaging (JDMI) is the largest academic medical imaging department in Canada. Long Magnetic Resonance Imaging (MRI) wait times for lower priority patients remain a critical issue at JDMI. There is, however, also a particular focus given to the wait time equity and MRI access discrepancies between patient sub-populations. An MRI scheduling framework is therefore proposed to: 1) maximize machine utilization through efficient shift scheduling using Branch-and-Price (B&P); and 2) ensure clinical MRI machine capacity remains aligned with incoming ordered scan demand, maximizing patient wait time equity. Schedule flexibility is successfully captured using the proposed B&P shift scheduling model through staff configuration scenarios. Additionally, the number of different scan types performed by MRI technologists across a week is considered during MRI capacity re-alignment. We demonstrate an average 22% improvement in exposure to different scan types per technologist compared to current MRI capacity allocation.

Keywords: Health care
Magnetic Resonance Imaging
Optimization
Scheduling
Staff Satisfaction
Wait time
Advisor: Carter, Michael MC
Do Digital Tools Support a Diversity of Patient Values? A Qualitative Study using the Genetics Adviser

Aim: To explore the range of values raised when selecting incidental findings (IF) from whole exome sequencing (WES) and how these are supported by the Genetics Adviser (GA).Methods: Qualitative interpretive descriptive study using semi-structured interviews conducted with participants undergoing WES and receiving IFs as part of the GARCT. Results: Sixteen participants were interviewed. Participants expressed that their decision was predetermined and occurred within a ‘black box’ before using the GA. Three values emerged from unpacking this ‘black box’: family stewardship, information imperative, and preserving agency. While the GA did not play an active role in eliciting these values, participants valued having the tool confirm their decision by clarifying, contextualizing, and instilling confidence in it. Conclusions: Participants entered decision-making with a predetermined decision guided by three core values. The GA supported them by reinforcing it. These findings can inform how digital tools can better support a diversity of patient values.

Keywords: genomics health services
health services research
health technology assessment
Advisor: Bombard, Yvonne
COVID-19 and Mobility Data Analysis with Poisson Mixed Effects Regression Models to Account for Spatial and Temporal Correlations

Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 is a worldwide pandemic. We conducted a study to estimate the relationship and time lag between population mobility and COVID-19 infection curves based on weekly and census tractlevel aggregated data (i.e. BlueDot mobility data, iPHIS surveillance data, and census data) in Greater Toronto Area (2020.03.15-2021.02.07). COVID-19 weekly confirmed new cases (i.e. weekly cases) was the outcome and proportion of time outside the home (i.e. mobility) was the primary predictor. We used the Poisson mixed effects models with a first-order autoregressive ( AR(1)) structure to estimate mobility effect and applied a modified K-fold cross validation to find an optimal time lag. The results show that the optimal time lag is around six week. Mobility has significant and negative effects on COVID-19 weekly cases during an epidemic wave. During a flat period, the mobility effect is not strong.

Keywords: COVID-19
cross validation
mixed effects model
population mobility
serial correlation
time lag
Advisor: Kustra, Rafal RK
Mishra, Sharmistha SM
School Based Health Care: A Model for Improving Educational Achievement for Children in Underserved Communities in Toronto, Canada.

Even though Canada is a developed country with universal health care, there are still populations in Canada who are at risk for health disorders that may go undetected and/or untreated due to challenges to health care access. This can harm a child's academic achievement and long-term well-being. School Based Health Centres (SBHCs) were established in Canada to address health-care access concerns. However, no quantitative study examining the impact of SBHCs on educational achievement has been undertaken in Canada. In my thesis, I examine the benefits of early intervention and management, especially for children at-risk for developmental disorders. I describe the health-care systems in Canada and the United States, the challenges to health-care access and the SBHC model that was developed to address these challenges. I also share a study I conducted examining whether having access to SBHCs improves academic achievement and wait time for accessing physician’s assessments.

Keywords: academic achievement
accessibility
School Based Health Centres
wait time
Advisor: Sgro, Michael