VictorJuiz/thesis huggingface dataset:
Modulation of Jaw Muscle Motor Response with Music in Individuals with Muscular Temporomandibular Disorders

Oral behaviours, such as wake-time tooth clenching and awake bruxism, are strongly associated with mood disorders, and are risk factors for temporomandibular disorders (TMD). Guided Music Listening (GML), a complimentary therapy based on mood mediation, reduces anxiety and depression in patients with chronic pain. This study tested the effects of GML on wake-time tooth clenching in individuals with chronic TMD myalgia (mTMD). The electromyographic (EMG) activity of the right masseter of fourteen women with mTMD and fifteen TMD-free controls was recorded during three music (stressful, relaxing, and favorite) and a control (pink noise) tasks. GML affected the EMG amplitude of the masseter in both groups (all p

Keywords: Bruxism
Guided music listening
Oral behaviours
Surface electromyography
Temporomandibular disorders
Wake-time tooth clenching
Advisor: Cioffi, Iacopo
Patient Satisfaction with Dental Services Provided by Dental Students

Patient satisfaction is important in dental care, and has implications for evaluating services, particularly as quality indicator. A cross-sectional study aimed to assess patient satisfaction with services delivered by dental students at the University of Toronto, and to explore differences in satisfaction by personal and demographic characteristics of patients. Data were collected using the Dental Satisfaction Questionnaire (DSQ). Mean differences in satisfaction were explored across the subscales of pain, quality, access and overall DSQ using t-tests and ANOVA. A mean DSQ score of 3.9/5.0 was observed, indicating a generally high level of satisfaction (n=389). Some subscales exhibited differences by gender, education, self-perceived oral health, ethnicity and treatment expectations. Males with less education, those with poor oral health, and ethnic minority groups reported lower satisfaction (p

Advisor: Quiñonez, Carlos
Vertical Transmission of HIV: Comparison of Policies in North and Sub-Saharan Africa

This project aims to investigate the extent to which differences in the design of national prevention of mother to child transmission policies and strategies between North Africa and Sub-Saharan Africa help to explain differences in vertical transmission rates between these two regions. To do so, I selected two case countries, one from each region, and conducted a qualitative document analysis of their HIV prevention policies since 2010, guided by two theoretical frameworks, the Analysis of Determinants of Policy Impacts (ADEPT) model of health promotion and the Health Policy Triangle. This project has revealed the importance of 1) civil society organizations in HIV prevention, 2) sufficient monitoring and evaluation systems and 3) the involvement of Intergovernmental Organizations (IGOs) in the strategic financing of HIV prevention strategies in low- and middle-income countries.

Keywords: Algeria
Comparative policy
HIV
Senegal
Advisor: Allin, Sara
Mothers’ Oral Health Status and its Relationship to Severe Early Childhood Caries (S-ECC) in an Indigenous Population in Canada

Objective: To determine the relationship between Indigenous mothers’ oral health status and severe early childhood caries (S-ECC) in their children and to examine whether mothers’ oral health-related self-efficacy (OHSE) mediates this association. Methods: The study included 544 Indigenous pregnant women in Canada, who underwent a clinical examination and completed a survey. Their children underwent a clinical examination when they were 2 years old. Results: After adjusting for mother’s age, smoking status, area of residence (on First Nations reserve or off reserve) and OHSE using logistic regression, Gingival Index (Odds Ratio 3.2, 95% Confidence Interval 1.5–6.6) and Debris Index (OR 2.4, 95% CI 1.3–4.7) were significantly associated with S-ECC. In the mediation analysis, maternal oral health status measures were negatively associated with OHSE and had a direct effect on S-ECC. Conclusions: Clinical normative measures of Indigenous mothers’ oral health status were significant determinants of S-ECC in their toddlers.

Keywords: dental caries
Early childhood caries
Indigenous
maternal oral health behaviors
oral health
self-efficacy
Advisor: Lawrence, Herenia P
Risk of Any Hypoglycemia with New Antihyperglycemic Agents in Patients with Type 2 Diabetes: A Systematic Review and Meta-analysis

Background: Evaluation of hypoglycemia risk relative to placebo with new antihyperglycemic agents (AHA) including the dipeptidyl peptidase-4 inhibitors (DPP4i), glucagon-like peptide-1 receptor agonists (GLP1RA) and sodium-glucose co-transporter-2 inhibitors (SGLT2i) remains inconclusive. Objective: This systematic review and meta-analysis aimed to assess risk of any and severe hypoglycemia with new AHA relative to placebo by excluding studies with background sulfonylureas and insulin. Methods: Randomized, placebo-controlled studies, 12 weeks or greater in duration were considered for inclusion. Studies allowing background use of any other AHA, apart from metformin, were excluded. This study is registered with PROSPERO (CRD42018095458). Results: 141 studies included in the meta-analysis demonstrate that relative to placebo, risk of any and severe hypoglycemia did not significantly differ for any new AHA.

Keywords: antihyperglycemic agents
diabetes
hypoglycemia
meta-analysis
Advisor: Tobe, Sheldon W
Design, Development, and Testing of the Command and Data Handling Subsystem for Microsatellite Missions

A spacecraft is composed of multiple subsystems that work together to accomplish the mission objectives. One of the most vital subsystems is termed the “brain” of the spacecraft, more formally known as the command and data handling subsystem, which is responsible for commanding all other subsystems and managing all data sent and received by the spacecraft. This thesis describes the author’s contributions to the various aspects of the command and data handling subsystem for two microsatellite missions, with focus on work that can be extended for use and implemented on future space missions at the Space Flight Laboratory. Particular emphasis is given to the author’s work on design of a new serial interface board, optimization of both ground and satellite software related to payload data handling, and development of various application threads on satellite on-board computers and ground control interfaces.

Keywords: Command and Data Handling
Microsatellite
NEMO-HD
NorSat-3
Satellite
Software
Advisor: Zee, Robert E
Opioid Prescribing after Surgery among Chronic Opioid users in Ontario: A Population-based Cohort Study

Patients who chronically use opioids may undergo surgery; it is unclear if surgery alters the trajectory of opioid consumption in these patients. We sought to determine if exposure to surgery is associated with opioid discontinuation among chronic users, and factors associated with opioid discontinuation after surgery. The study included 4,755 surgical and 14,265 matched non-surgical patients with chronic opioid use. After adjusting for patient characteristics, surgery was associated with an increased likelihood of opioid discontinuation (aHR: 1.34 95%CI: 1.27, 1.42). Among surgical patients, factors associated with a reduced odds of discontinuation included a mean preoperative opioid dose >90 morphine milligram equivalents (aOR: 0.39 95%CI:0.31, 0.49), preoperative oxycodone prescriptions (aOR: 0.74 95%CI:0.55, 0.98), and a diagnosis of chronic obstructive pulmonary disease (aOR: 0.75 95%CI: 0.64, 0.88) or dementia (aOR: 0.58 95%CI: 0.37, 0.91). Further research is needed to evaluate interventions that can influence post-operative opioid discontinuation, particularly in high risk patients.

Keywords: Anesthesiology
Opioids
Pain
Advisor: Wunsch, Hannah
Minimizing the Completion Time of Distributed Learning Workloads via Deep Reinforcement Learning

Large-scale machine learning models are routinely trained in a distributed fashion due to their increasing complexity and data sizes. Distributed learning is therefore proposed to reduce the completion time of a machine learning workload by leveraging parallelism. However, distributed learning workloads are time-consuming and resource-intensive in general. Consequently, we study the problem of minimizing the completion time of distributed learning workloads under two different settings within this thesis. The first is a shared cluster handling multiple distributed learning workloads with a parameter server framework, while the second is a distributed learning method called Federated Learning. Inspired by the recent advances in deep reinforcement learning, we use an experience- driven approach to solve these two problems. Our extensive array of simulation results have shown clear evidence of the effectiveness of our proposed methods.

Keywords: Deep Reinforcement Learning
Distributed Learning
Advisor: Li, Baochun
Liang, Ben
Impact of Air Pollution on Respiratory Infection in Healthy and Cystic Fibrosis micP

Pulmonary infections are a significant cause of morbidity and mortality in patients with cystic fibrosis (CF). Increased pollution level is associated with hospitalization due to respiratory infection, as well as pulmonary exacerbation and earlier acquisition of airway bacteria in CF patients. To validate these findings, we investigated the effect of in vivo inhalation exposure of traffic pollutants on the subsequent Pseudomonas aeruginosa and Staphylococcus aureus lung infection in C57BL/6J and CFTR knockout mice. Prior pollution exposure increased severity of the subsequent lung infection, with an augmented inflammatory response that demonstrated impaired bacterial clearance with decreased lung myeloperoxidase activity. These changes were associated with upregulated pulmonary inflammatory genes Il17a, Cxcl1, Tnf, Il6 and Il1b, as well as altered redox signaling pathways. Our data provide evidence that air pollution is a significant environmental risk factor to respiratory infections, particularly in susceptible populations such as CF patients.

Keywords: Air pollution
Cystic fibrosis
Respiratory infection
Advisor: Chow, Chung-Wai
Development of a Quadrotor Slung Payload System

In this work, a quadrotor unmanned aerial vehicle is investigated for the task of a slung payload delivery. A simplified guidance law is proposed to address the problem of autonomous landing with a slung payload. In addition, a complete development framework is presented. This includes a generic dynamic model for the slung payload system, a simulation environment, and an experimental platform, capable of completing the mission. This framework is used to assess the feasibility of the proposed approach and validate it through flight tests. The proposed guidance law is compared to a controller without guidance, both in simulation and in experimental flight tests. It was found that the guidance law achieved a smooth trajectory with minimal payload swing during the autonomous landing mission segment.

Keywords: Landing
Quadrotor
Slung Payload
UAV
Advisor: Liu, Hugh H.T.
Prevalence and Social Determinants of Overweight and Obesity in Adolescents in Saudi Arabia: A Systematic Review

Background: The prevalence of obesity in adolescents is increasing globally at an alarming rate. Objectives: Our aim was to evaluate the prevalence of overweight and obesity (Ow/Ob) in Saudi adolescents and to construct an ecological model of social determinants of Ow/Ob and evaluate current evidence of their effect on Saudi adolescents. Methods: A systematic review of literature reported up to 31/12/2018 on Ow/Ob and factors that can influence them in Saudi adolescents was conducted. Results: Fifty-one studies with n=97,666 adolescents (56.9% males) were reviewed. The prevalence of Ow/Ob started off high and continued to increase over time. Most of the 49 reviewed social determinants reports, from 19 studies, showed positive association between social determinants and Ow/Ob in Saudi adolescents. Conclusion: Adolescents’ Ow/Ob is a major public health problem in Saudi Arabia and is growing. Social determinants play a significant role in this problem and should be considered in all strategies targeting it.

Keywords: adolescent
obesity
overweight
prevalence
Saudi Arabia
social determinants
Advisor: Bhutta, Zulfiqar A.
Calmodulin Disrupts Plasma Membrane Localization of Farnesylated KRAS4b by Sequestering its Lipid Moiety

KRAS4b is a small GTPase protein that regulates signal transduction pathways, including MAPK signaling. Recently, there has been considerable interest in the mechanisms underlying interactions between RAS and calcium signaling. KRAS4b function requires farnesylation of its C-terminus and recruitment to the plasma membrane, and some studies have suggested that Ca2+-calmodulin (CaM) modulates this localization. Here, we present a crystal structure, supported by NMR data, revealing that the Ca2+-dependent CaM-KRAS4b interaction is anchored by the sequestration of the KRAS4b farnesyl moiety in the hydrophobic pocket of the CaM C-terminal lobe. We engineered FRET-based probes (CaMeRAS) to monitor this interaction in live cells and demonstrate that, upon stimulation of Ca2+ influx by extracellular ligands, KRAS4b reversibly translocates in a Ca2+-CaM dependent manner from the plasma membrane to the cytoplasm in HeLa and HEK293 cells. These results underscore the importance of crosstalk between KRAS4b and Ca2+ signaling pathways and reveal one underlying mechanism.

Keywords: Calmodulin
Crystallography
Farnesyl
FRET
KRAS
NMR
Advisor: Ikura, Mitsuhiko
Classification for Healthcare Using Linked and Unlinked Data Sources

Machine learning (ML) can be used to develop decision-making tools that help reduce the costs of healthcare. The data for ML tasks can be broadly categorized as linked (i.e., containing keys that uniquely identify individuals) or unlinked (i.e., lacking unique identifiers). We explore two use-cases where opportunities exist to reduce costs through ML: hospital readmission and high-resource users (HRU) of the health system. In the case of readmission classification, the relevant data is in a linked format, thereby allowing us to evaluate standard supervised learning algorithms. In contrast, the data for classification of HRUs is an unlinked format. We demonstrate that Bayesian networks are an ideal solution that allow us to integrate unlinked data from multiple sources and answer conditional queries useful for decision making. Overall, the results of this thesis allow us to expand upon the current scope of predictive models and the types of data they can leverage.

Keywords: Healthcare
Machine Learning
Advisor: Sanner, Scott
The Role of CD9 in Regulating TNF-α-Induced Expression of A Disintegrin and Metalloprotease 17 (ADAM17) in Aortic Endothelial Cells

ADAM17 is an inducible metalloprotease that cleaves membrane-anchored proteins involved in a variety of homeostatic and pathophysiological processes. The mechanisms responsible for activation and gene expression of ADAM17 are a matter of debate, as they depend on the cellular context. Here we investigate the role of the tetraspanin, CD9, in regulating the shedding activity and gene expression of ADAM17 in human aortic endothelial cells. In contrast to what has been previously reported for other substrates of ADAM17, we found that a deficiency of CD9 did not increase ADAM17-dependent shedding of CX3CL1. Instead, knockdown of CD9 resulted in a reduction in immature and mature ADAM17 protein. This reduction was not caused by an increase in ADAM17 degradation, but rather a decrease in ADAM17 transcription. We found an associated reduction in constitutive and TNF-α-induced NF-κB activation upon knockdown of CD9, which may potentially explain the reduction in its downstream target, ADAM17.

Keywords: ADAM17
Atherosclerosis
CD9
CX3CL1
Metalloprotease
NF-κB
Advisor: Robinson, Lisa
Characterization of Pipeline Exterior and Interior Coating Material

The characterization and performance of protective coatings for both the interior and exterior of pipelines are incorporated into this thesis. For the first part, two epoxy-based coating systems and one magnesium potassium phosphate coating system were assessed for sulfuric acid resistance under immersed pH 2.5 conditions at 38 °C for 21 days. Tests for adhesion strength, abrasion resistance as well as a microscopical assessment of the coating systems in thin sections were performed. Both epoxy-based systems performed well, but the magnesium potassium phosphate coating experienced dissolution. For the second part, protective concrete coatings applied to steel pipelines were characterized using a combined x-ray fluorescence mapping and microscopic fluorescent imaging technique. The images were used as the basis for the production of two-dimensional triangular meshes to be utilized in a finite discrete element model. These models will be used to study fracture networks developed during pipeline placement.

Keywords: Accelerated tests on concrete
Concrete coating characterization
FDEM simulation
Image-based meshing
Mapping fracture network
Microscopic analysis on concrete
Advisor: Peterson, Karl
Grasselli, Giovanni
Wearable Hybrid Brain Computer Interface as a Pathway for Environmental Control

Alternative access pathways offer individuals with severe disabilities forms of environmental control through computerized commands. However, current solutions lack reliability, portability and redundancy. E-textile-based electrooculography (EOG) can offer a fast and reliable pathway but suffers from the Midas Touch Predicament (MTP). Here, we investigate the use of a hybrid brain-computer interface (BCI) to address this shortcoming. First, a subject-independent classifier is trained on two EOG systems. Then, a Riemannian framework is used to discern the “no-look” state from stimuli classes, thereby solving the MTP. Finally, the results are combined in a hybrid BCI classification scheme. The results presented show promise, with EOG classification reaching 90% accuracy between six classes and Riemann classification achieving 66% between five classes. The hybrid scheme results remain inconclusive due to data quality and null state omission from the analysis. This research project provides a basis for further investigation of hybrid systems in the development of access solutions.

Keywords: Brain Computer Interfaces
EEG
EOG
Machine Learning
Riemann Geometry
Wearables
Advisor: Chau, Tom
U of T Works Because We Do! Neoliberalism, the Social Economy, and the University of Toronto

The University of Toronto is one of the most important social economy organizations in Canada. However, this institution has not lived up to the potential that it has for being a powerhouse leader of the Canadian social economy. Furthermore, it's revealed that this failure is a direct result from the decisions taken by the senior administration of the University of Toronto at the expense of students, staff, faculty, and the broader Canadian public.The research presented here uses a social economy framework as an innovative lens to critically evaluate this public sector non-profit institution and is a contribution to the emerging field of inquiry called Critical University Studies. In doing so this research has been conducted by utilizing critical discourse analysis in order to examine the statements and information provided by key stakeholders existing in the academy, and specifically, those existing within the University of Toronto community.

Keywords: Academic Capitalism
Critical University Studies
Education
Higher Education
Neoliberalism
Social Economy
Advisor: Vieta, Marcelo
Sawchuk, Peter
Developing and Validating a Functional Electrical Stimulation Controller for Use with Visual Feedback Training for Standing Balance Therapy in Individuals with Incomplete Spinal Cord Injury

Incomplete spinal cord injury (iSCI) can impair standing balance, increasing fall likelihood. Visual feedback training (VFT) and functional electrical stimulation (FES) have shown promise in iSCI standing balance rehabilitation. Combining VFT and lower-limb FES was hypothesized to yield more effective standing balance therapy. This thesis developed a VFT-complementary FES system for regulating ankle muscles. In my previous work, I have developed a VFT system with another student. For my thesis project, I (1) designed an FES controller, (2) optimized the controller to mimic able-bodied ankle muscle activation data during VFT sessions, and (3) tested the resultant FES controller on able-bodied individuals as they underwent VFT to determine the effects of the FES controller on able-bodied postural control. As expected, the resultant FES-VFT system did not deteriorate able-bodied postural control. The results of this research contribute toward the development of a more effective standing balance rehabilitation system for individuals with iSCI.

Keywords: Balance
Functional Electrical Stimulation
PD Control
Rehabilitation
Spinal Cord Injury
Visual Feedback Training
Advisor: Masani, Kei
Andrysek, Jan
Development and Application of 2D and 3D In vitro Models for Human Brain Development

For decades scientists from various disciplines have partnered to understand the most complex and fascinating organ in the human body, the brain. Despite this, the brain remains the most poorly understood area of human physiology due in large part to the lack of sample availability. Here I describe both 2D and 3D directed differentiation platforms to generate human cortical neurons and cerebral organoids, respectively from Pluripotent Stem Cells (PSCs). Cortical neurons were tested in an in vitro neurite growth assay using an inhibitory growth matrix that recapitulates the glial scar that develops following spinal cord injury. To produce cerebral organoids, I standardized production of early organoid structures and neural induction and was able to achieve reproducible production of hCOs at high efficiency (>80%). The hCOs generated using the optimized pipeline reproduce both ventricle assembly and cellular heterogeneity observed in the embryonic cortex.

Keywords: Cerebral Organoid
Organoids
Pluripotent Stem Cell
Spinal Cord Injury
Advisor: Attisano, Liliana
Wrana, Jeff
In Depth Analysis of Sleep Apnea Severity

Sleep apnea is a respiratory disorder affecting 10% of the adult population. The gold standard assessment of sleep apnea requires full night polysomnography in a sleep laboratory. However, polysomnography is expensive, time consuming, and inconvenient. Consequently, about 85% of adults with sleep apnea remain undiagnosed. Hence, there is a need for a convenient and robust wearable device to diagnose sleep apnea. This thesis investigates the feasibility of diagnosing sleep apnea by analyzing respiratory related movements. Polysomnography data from participants who were referred for an overnight sleep study at Toronto Rehab’s sleep laboratory was used. Simultaneously, an accelerometer attached to participants’ suprasternal notch was used to record respiratory movements. Algorithms were developed to estimate sleep apnea severity from respiratory movements. Results were compared against gold standard polysomnography. Reference intensity of respiratory event-related arousals was also calculated using clustering analysis to develop accelerometer-based arousal intensity estimation in future.

Keywords: Accelerometer
Apnea Hypopnea Index
Deep Learning
Machine Learning
Physiological Features
Portable Sleep Apnea Monitoring
Advisor: Taati, Babak
Yadollahi, Azadeh