VictorJuiz/thesis huggingface dataset:
Investigating Sex Differences In Fetal Antiretroviral Drug Disposition: The Role Of Membrane-associated Transporters and Metabolic Enzyme
Keywords: Antiretroviral Drugs
Drug Transport
HIV
Placenta
Pregnancy
Sex Differences

Antiretroviral (ARV) therapy is effective in reducing risk of vertical HIV transmission during pregnancy, however, the fetal toxicity of ARVs remains poorly understood and existing literature often does not account for fetal sex. New evidence of sex-linked toxicities in ARV-exposed children suggests sex-differential drug disposition, which may be explained by differential expression of membrane-associated drug transporters and metabolic enzymes, which are known to vary with sex. We investigated the effect of fetal sex and ARV treatment on the expression of transporters, metabolic enzymes and other relevant proteins in a mouse model of antiretroviral therapy in pregnancy. We also measured fetal brain and amniotic fluid drug concentrations by LC-MS/MS and assessed correlations between transporter expression and ARV penetration. Both fetal sex and ARV exposure were observed to impact transporter expression in fetal brain and placenta, suggesting an important role for transporters in mediating sex-specific ARV disposition and in utero toxicity.
Computational Evaluation of a Hybrid Electrochemical Reduction-bioproduction System for the Conversion of Carbon Dioxide to Fuels and Chemicals
Keywords: Biofuels
Bioproduction
CO2 Conversion
Electrochemical Reduction
Metabolic Engineering
Metabolic Modeling

The electrochemical reduction of CO2 (eCO2R) can produce a number of one and two carbon (C1/C2) compounds that can serve as sustainable feedstocks for bioproduction processes. The presented research seeks to optimize the integration of these two technologies by evaluating a wide range of eCO2R product-bioproduct pairs. Specifically, the costs of production of the eCO2R system were evaluated for eight C1/C2 eCO2R products, and these costs were combined with metabolic modeling predictions to investigate the most economically feasible pairs when considering more than 1000 bioproduction options (20+ assimilation pathways and 50+ bioproducts). The results suggest that the aerobic bioconversion of C2 products or methanol to highly oxidized products provide the most economically viable option, followed by the anaerobic bioconversion of formate/hydrogen or carbon monoxide/hydrogen to more reduced products. Overall, this analysis highlights areas of interest for future studies, particularly when selecting substrate-product combinations on which to focus experimental efforts.
Deep Mutational Scanning of Missense Variants of SERPINA1, a Gene Involved in Alpha-1 Antitrypsin Deficiency
Keywords: deep mutational scanning
genetics
genomics
high-throughput
multiplex analysis of variant effect
variant effect map

Alpha-1 antitrypsin deficiency (AATD) is a genetic disorder that occurs in about 1 in 2500 individuals. The gene responsible for this condition is SERPINA1, which encodes the alpha-1 antitrypsin protein. This protein is secreted from the liver, and its main function is to inhibit neutrophil elastase activity in the lungs, which if unregulated can lead to inflammation and changes in the extracellular matrix. One of the challenges associated with AATD is that it is often misdiagnosed as chronic obstructive pulmonary disorder or liver disease, and there is a 5-7 year gap between initial symptoms and diagnosis. Thus, there is a need for a proactive map for genetic counselors and physicians to diagnose this condition early. This project will employ deep mutational scanning, a methodology to classify all possible missense variants with a functional assay. The result is a variant effect map that may allow for improved proactive diagnosis of AATD.
Evaluating the Energy Consumption of Battery Electric Vehicles Under a Diverse and Changing Climate
Keywords: battery electric vehicles
climate change
electric grid
electric vehicle charging
passenger vehicles
power demand

Passenger vehicles contribute considerably to global energy consumption and greenhouse gas emissions. Battery electric vehicles (BEVs) are one form of climate change mitigation through their higher efficiency compared to internal combustion engine vehicles as well as their use of electricity, which has potential to be less carbon intensive than fossil fuels. However, passenger vehicle energy consumption is affected by operating conditions provided by weather and climate variability.This thesis presents a review of known relationships between climate variables and passenger vehicle energy consumption, with an emphasis on BEVs. The impacts of rising global temperatures on passenger vehicle energy consumption in North America is also estimated. Finally, the impacts of BEV charging on electricity demand and peak demand were estimated for the Greater Toronto and Hamilton Area while taking ambient temperature into account. The results illustrate the importance of taking climate and climate change into account when conducting BEV impact analyses.
Loss of Bat3 on T Cells Impairs Response to Viral Infection via Altered T cell-NK Cell Crosstalk
Keywords: Bat3
LCMV
NK cell
regulation
RIP-gp
T cell

Factors regulating T cell and innate lymphoid cell (ILC) cross-talk ensure coordinated immune responses. Human leukocyte antigen-B-associated transcript 3 (Bat3) protects T cells from Tim-3-induced exhaustion and regulates human Natural Killer (NK) cells. Herein, we use Bat3flox/flox CD4-cre mice in the RIP-gp model to demonstrate that loss of Bat3 on T cells impairs CD8+ T cell-mediated tissue destruction and reduces CD4+ T cells proliferation, expression of activation markers, and TNF- and IFN- production. Furthermore, we show mice lacking T cell-expressed Bat3 have a CD49b+NK1.1+ ILC population that expresses high levels of Galectin-9 and IL-22, and expands following viral infection. Depletion of NK1.1+ cells or ILCs (Nfil3-/-) restores normal T cell activity in vivo, and T cell proliferation and activation marker expression is restored in Bat3flox/flox CD4-cre Nfil3-/- mice. Collectively, this thesis provides evidence that NK cell regulation of anti-viral T cell responses is influenced by T cell expression of Bat3.
Development and Analysis of Phase Change Slurries for Geothermal Energy Systems
Keywords: Emulsions
Geothermal energy
Phase change material
Phase change slurry
Rheology
Thermal energy storage

Geothermal energy provides continuous baseload power, in contrast to the intermittent and seasonal capacity of other renewables. Closed loop geothermal (CLG) systems harvest thermal energy using a continuously circulating working fluid and enable the use of novel fluids to enhance thermal energy recovery. In this thesis, phase change material (PCM) based slurries (PCS) are developed and assessed for their suitability as a CLG working fluid. PCS enable enhanced thermal storage by capturing energy in both sensible and latent heat. First, non-encapsulated and microencapsulated based PCS are assessed based on their stability, flow behaviour and thermal properties. The impacts of surfactants and sub-surface contaminants are assessed. Next, a deep analysis into the flow behaviour of these fluids is performed. PCS are optimized and found to be suitable for use over many cycles in a geothermal system. The key properties impacting PCS flow behaviour are demonstrated, enabling their optimization for flow-based applications.
Assessment of the Impact of Antegrade Enema Insertion on Health Care Utilization in Pediatric Patients with Constipation: A Population-based Cohort Study
Keywords: Antegrade enema
Constipation
Gastroenterology
Health care utilization
Motility
Pediatric

Constipation is a common condition in the pediatric population which leads to high patient morbidity and a large burden on health care systems. Children with medically refractory constipation may undergo placement of an antegrade enema. We performed a population-based study to assess the impact of antegrade enema insertion on health care utilization. We identified that in pediatric patients following antegrade enema insertion, health care utilization remains stable for most forms of care, although emergency department health care use increases, in part secondary to device-related visits. Some forms of constipation-related care may decrease following antegrade enema insertion specifically in patients with functional constipation, though further work is needed to explore these findings. This thesis expands our understanding of the clinical success and financial impact of antegrade enemas and will aid clinical decision making for children with medically refractory constipation and allocation of health resources to manage these patients.
Retention of Third Molars Pose a Risk for Delay in Cancer Therapy; A New Perspective on the Relative Need for Extraction of Impacted Third Molars in Young Adults
Keywords: cancer
head and neck
third molars
wisdom teeth

Purpose: Cancer treatment leads to deleterious effects on oral health. This study investigates the impact of retained third molars in the oncologic patient population. Methods: A 6-year retrospective review of new patients presenting to the Princess Margaret Hospital Dental Oncology clinic was conducted. Cancer patients who were awaiting cancer therapy and who had retained third molars were identified, and data regarding third molar position and problems was collected. Results: 2,431 pre-treatment new cancer patients were identified who had at least one retained third molar. 60% of patients had a third molar-related treatment dilemma. 26% of patients experienced a potential third molar related delay in cancer treatment, and 34% of patients underwent observation-only prior to initiating cancer treatment had an increase in the risk for delayed cancer treatment. Conclusion: There is a high prevalence of potentially problematic retained third molars in oncology patients, which may be a consideration for high-risk patients.
Love Under Lockdown? How a Change in Time Spent Together Impacts Romantic Relationships
Keywords: Attachment style
Commitment
Covid-19 pandemic
Relationship Importance
Romantic relationship
Satisfaction

With the onset of Covid-19, many governments globally implemented strict social distancing and stay-at-home orders to lessen virus spread. Due to pandemic-related lockdowns, individuals may be spending more (or less) time with relationship partners potentially affecting their relationships outcomes. In a pre-registered study, I examined whether attachment style would interact with a change in the amount of time individuals spend with their partner on their commitment, satisfaction, and relationship importance. A multiple regression using 665 participants from Prolific revealed that attachment avoidance significantly interacted with a change in time spent with a partner on outcome variables. Contrary to predictions, more avoidantly attached individuals reported more positive relationship outcomes when they were spending an increased, relative to a decreased, amount of time with their partner. Exploratory analyses revealed stress and individuals’ partner fulfilling their needs mediated the impact of a change in time spent together by couples on their relationship outcomes.
Approximate and Randomized ADMM-LP Decoding using Geometric Information of the Parity Polytope
Keywords: Affine Projection Algorithm
Alternating Direction Method of Multipliers (ADMM)
Layered Decoding
Low-Density Parity Check (LDPC) Codes
Parity Polytope Projection
Randomized Decoding

We present two strategies to reduce the complexity of the alternating direction method of multipliers with linear programming (ADMM-LP) decoder for LDPC codes. The complexity bottleneck of ADMM-LP decoding is projection onto the parity polytope. We propose the sparse affine projection algorithm (SAPA), which projects onto the affine hull of the χ closest local codewords for each check of degree d, where χ can be significantly smaller than d. Unlike exact projection, SAPA does not require a water-filling process, thus can be implemented with lower per-iteration complexity. Furthermore, we present a randomized layered scheduling framework for ADMM-LP decoding. In the randomized schedule, instead of updating all checks in a single iteration, more problematic checks are updated more often by using priors based the location of replica vectors inside or on the parity polytope. We demonstrate the decoder converges significantly faster with this randomized scheduling, thus it is well suited for limited-iteration applications.
Mechanical Design and Development of High-Performance Microsatellite Platforms for Remote Sensing and Technology Demonstration
Keywords: dynamics
isolator
microsatellite
spacecraft
thermal
vibration

Small spacecraft are powerful platforms for hosting specialized space-based payloads. They can service roles such as communications, Earth-observation and technology demonstration. This thesis discusses the engineering development of the NorSat-TD and GHGSat C3, C4 and C5 microsatellite missions at the Space Flight Laboratory (SFL). The NorSat-TD mission will advance the state-of-the-art in small-satellite technology demonstration capability. Based on SFL's DEFIANT microsatellite platform, the spacecraft will perform ship tracking as a primary mission and spacecraft technology demonstration as a secondary mission. The structural dynamics of the spacecraft and the nuanced assembly process is explored. The GHGSat mission is a cluster of Earth-observation satellites built for GHGSat Inc. Based on the NEMO platform, they will detect methane emissions from anthropogenic sources. The mechanical design of subsystems, assembly, and testing are discussed. The development culminated in the successful launch of a mission that pushes the envelope of Earth-observing microsatellite capabilities.
The Application of Dialysis and Metabolomics to Preserve Heart Function During Ex Situ Heart Perfusion
Keywords: dialysis
Ex situ organ perfusion
metabolomics
organ perfusion

Heart failure affects 7.5 million people globally and is the primary cause of death for over 300,000 people annually in North America. The gold standard treatment for eligible end-stage heart failure patients is heart transplantation. However, even with extended donation criteria, there is a mismatch between the number of donors and recipients. Beyond the use of donation after brain death (DBD) organs, hearts obtained from donation after circulatory death (DCD) donors have been proposed as an alternative to expand the donor pool. Ex situ heart perfusion (ESHP) has been developed as a platform to revive hearts outside the body and can be used to evaluate heart function after DCD, prior to transplantation. Unfortunately, heart function declines during prolonged ESHP secondary to edema and altered metabolism. Therefore, we hypothesize that defining the changes in the metabolome during ESHP and the use of hemodialysis may improve heart function during prolonged ESHP. We have demonstrated the use of hemodialysis during ESHP significantly improves left ventricular and coronary vasomotor function. Furthermore, we have shown that carnitine synthesis is significantly impaired in both working mode and nonworking mode ESHP hearts.
An Educational Method for Learning and Assessing Interproximal Dental Caries Diagnosis in Bitewing Radiographs of Children
Keywords: caries diagnosis
computer-assisted instruction
dental education
educational measurement
performance-based learning

Background: Intraoral bitewing radiographs are the gold standard for diagnosing interproximal caries. There are currently no validated methods for assessing this competency in Canadian dental trainees. Objective: A computerized learning tool was developed to measure and improve performance in caries diagnosis from pediatric bitewing radiograph interpretation amongst dental trainees. Methods: In this multi-centre prospective cohort study, diagnostic performance was measured using learning curves and linear regression analysis identified image variables associated with increased interpretation difficulty of bitewing radiographs. Results: 62 participants completed the case set and a significant increase from mean initial to maximal diagnostic performance was observed (p<0.001). Two image-specific variables were associated with a significantly greater image interpretation difficulty score (p<0.001). Conclusion: The computerized learning platform led to effective and feasible skill improvement in diagnostic performance amongst dental trainees. Significance: The platform may be a valuable adjunct to existing educational methods in dentalradiology for dental trainees.
Targeting Acid Ceramidase to Attenuate Kidney Fibrosis
Keywords: acid ceramidase
ceramide
chronic kidney disease
kidney fibrosis

Chronic kidney disease (CKD) affects nearly 1 in 10 Canadians, a condition that in its end-stage has a worse prognosis than most cancers, and results in an annual healthcare cost of $40 billion. Despite fibrosis driving the progression of most forms of CKD, its pathogenesis remains poorly understood. Emerging evidence suggests the important role of acid ceramidase in regulating fibrosis across several organs, including the lung and liver. However, the role of acid ceramidase in the pathogenesis of kidney fibrosis remains largely unknown. Here we demonstrate that acid ceramidase mRNA is increased in fibrotic kidneys, and that inhibition of acid ceramidase with Carmofur reduces renal fibrosis. Furthermore, we provide evidence that acid ceramidase inhibition with Carmofur inhibits the activity of YAP and TAZ, two key pro-fibrotic transcription co-factors. Taken together, these data suggest that acid ceramidase inhibition might be a novel strategy to reduce kidney fibrosis.
A Social Equity Lens on Toronto Transit Network Performance using a Graph Theory Approach: Examining Criticality, Service Redundancy, Transit Delays and Disruptions
Keywords: Public Transit
Transit Delays
Transit Disruptions
Transit Equity
Transit Operations
Transportation Justice

Public transit delays and disruptions are inevitable occurrences in many transit sys- tems. Past studies did not differentiate between different groups of riders when study- ing the disruption impacts and rarely integrated service frequency into their network models. This study adds a social equity layer by determining if different equity- seeking groups were more vulnerable to disruptions or had less resiliency than the general population.Various graph theory measures were used in the analysis, and both a time-expanded and an L-Space or route-map representations of the Toronto transit network were adopted. Census and travel demand survey data were used to determine trip patterns for the equity analysis. The results show that equity-seeking riders had slightly greater vulnerability and less redundancy in hypothetical scenarios of service disruptions compared to the gen- eral population. However, when analyzing real-world disruptions that occurred in 2019-2020, equity seeking riders were more resilient compared to the general population.
Point Density-aware LiDAR 3D Object Detection for Autonomous Vehicles
Keywords: 3D Object Detection
Autonomous Vehicles
Data Augmentation
LiDAR
Point Cloud
Point Density

LiDAR has become one of the primary 3D object detection sensors used in autonomous driving. However, LiDAR scans in autonomous driving datasets are often skewed and lack training data for objects at farther distances, resulting in a performance degradation as a function of range. Thus, we first introduce pattern-aware ground truth sampling, a data augmentation technique that uses the LiDAR's sampling pattern to simulate realistic objects at farther distances for better performance across range. Next, we explore different point cloud encoding methods for capturing point density variations in LiDAR data. Current methods largely ignore point density as a feature and its predictable relationship with distance from the LiDAR sensor. Our proposed solution, Point Density-Aware Voxel network (PDV), is an end-to-end two stage LiDAR 3D object detection architecture that explicitly accounts for these point density variations, outperforming other state-of-the-art detection methods.
Real-time Location Data to Classify Degree of Cognitive Impariment and Motor Agitation
Keywords: Deep Learning
Dementia classification
Health monitoring technology
Machine Learning
Real-time Location Systems
Walking patterns

Real Time Location Systems can produce spatiotemporal data from people with dementia that might provide information about their cognition and health status. The first study explored a novel method to classify the severity of cognitive impairment (‘No-CI’, ‘Mild-Moderate CI’, ‘Severe CI’) among residents of a care unit using walking path images. The RTLS data was distributed into windows of various durations and transformed into images used in a Convolutional Neural Network that achieved a top accuracy of 87.38%. Class Activation Mapping was used to consolidate an objective score that can reliably distinguish between each class. The second study utilized features of spatiotemporal data with single-instance and multi-instance learning techniques in generalized and personalized models to detect low and high motor agitation. The top performing model achieved 0.71 with the Receiver Operator Characteristic in 5-fold cross validation with an indication that personalized models may require more data for improvement.
Monolithically Integrated Millimeter-Wave Spin-Qubit Control Circuits in FDSOI CMOS
Keywords: FDSOI CMOS
integrated circuits
mm-wave
spin qubit

This thesis investigates design considerations and topologies for spin-qubit control circuits integrated with qubits and readout circuits into one- and two-lane quantum processor test vehicles in a production 22-nm FDSOI process. The control circuits produce millimeter-wave pulses through direct modulation of an externally generated carrier in the DC-to-70-GHz and 140-to-160-GHz frequency ranges. At 2 K, one design featuring a shunt-series-shunt switch achieves 31.1 dB to 77.7 dB of on/off isolation from DC to 27 GHz, while another featuring a distributed switch achieves > 30.2 dB of on/off isolation at 2-46 GHz and 50-70 GHz. The standalone distributed switch shows > 34 dB of on/off isolation over 40-218 GHz at 295 K. These measurements demonstrate not only the possibility of minimizing qubit idling errors with the adopted switch topologies, but also the feasibility of the proposed elevated-temperature (1-7 K) monolithic quantum processor and methodology for designing cryogenic control circuits.
Exploring the Importance of Candida albicans Lipid Metabolism Using Chemical Biology and Functional Genomic Approaches
Keywords: Chemical biology
Drug discovery
Fungi
Genomics
Infectious disease
Pathogens

Fungal infections represent a threat to human health with increasing rates of antifungal resistance impairing the utility of our antifungal arsenal. The opportunistic pathogen Candida albicans is a concerning fungal pathogen, exhibiting mortality rates of ~40%. We conducted a screen of 9,600 synthetic compounds from the University of Tokyo and identified CpdLC-6888 as possessing novel antifungal activity against C. albicans. The research presented in this thesis outlines the spectrum of activity of this compound against numerous fungal pathogens and establishes its impact on C. albicans morphogenesis. We determined CpdLC-6888 targets the ergosterol biosynthetic enzyme Erg11, the target of the azoles, despite structural differences between these two drugs. In parallel, I performed functional genomic analyses to explore the importance of lipid metabolic genes in growth, virulence, and antifungal tolerance in C. albicans. Overall, this project examines the importance of C. albicans lipid metabolism through chemical biology and functional genomic approaches.