VictorJuiz/thesis huggingface dataset:
Understanding Brain Transcriptome Signatures Associated with Disparate Psychiatric Outcomes in Black American Populations
Keywords: Computational Psychiatry
Health Disparities
Neuropathology
Population Health
Social Genomics
Transcriptomics

The molecular basis underlying disparate schizophrenia (SCZ) outcomes remains unclear, but stress and immune pathways associated with social inequalities are thought to contribute. To address questions about race-specific effects on the brain and in SCZ, I analyzed post-mortem DLPFC RNA-seq data from two racially diverse cohorts in the CommonMind Consortium (235 Black and 546 White; 322 SCZ and 459 controls). Mega-analyses yielded 1514 genes with differential expression (DE) between Black and White-reported individuals and enrichments implicated upregulation in stress and immune pathways in Black individuals. Interaction models showed 109 gene sets DE in a race-specific manner across SCZ, and semantic clustering revealed these sets implicated metabolic and immune pathways. Our results support a molecular mechanism underpinning racial differences in SCZ outcomes involving immune and stress pathways and underscore the importance of diverse cohort ascertainment to capture the diversity of SCZ pathogenesis.
Identifying Potential Imaging Biomarkers of Neuropsychiatric Lupus in Children using Deep Learning
Keywords: Artificial intelligence
Computer vision
Diagnostics
Neuroimaging
Neuropsychiatric disorders
Pediatric lupus

Childhood-onset systemic lupus erythematosus (cSLE) is characterised by a high frequency of nervous system involvement, termed neuropsychiatric SLE (NPSLE). Biomarkers for this disease are lacking, current diagnostic processes are suboptimal, and treatments can be toxic. Deep learning (DL) network applications in medical imaging have seen recent success in identifying nervous system diseases. This thesis aimed to discover features of T1-weighted brain images useful for cSLE vs. non-cSLE classification. Using 163 cSLE and 163 non-cSLE images, we trained four different DL classifiers. We explored transfer learning from pre-trained 2-dimensional models to this 3-dimensional task. During performance testing, 79% of cSLE samples and 89% of NPSLE subsamples were correctly classified by the best model. The visual features of periventricular white matter, intraventricular regions, and the right superior longitudinal fasciculus seemed to guide these predictions. Further study is needed to characterise the mechanisms linking these brain image features to the presence of NPSLE.
Phenological Assortative Mating And The Evolution of Flowering Time
Keywords: evolution

This paper explores the influence of phenological assortative mating on the evolution of flowering time. First we analytically model the evolution of flowering time in a metapopulation of discrete patches of plants that each mate assortatively for flowering time and are subject to different selective optima for flowering time. We show that stronger assortative mating enhances population differentiation and thus local adaptation. Next, we model the combined influence of phenological assortative mating for flowering time and reproductive isolation by distance in a series of individual-based simulations. We show that the combination of these two forms of non-random mating act to enhance the theoretically predicted consequences of each form in isolation. In particular, we demonstrate the emergence of enhanced spatial-genetic structure where individuals are spatially autocorrelated for flowering time trait values. Finally, we present ecological conditions that could act to dampen this tentative synergy
Comparing Body Composition Assessment Methods and Evaluating Physical Activity in Children with Intestinal Failure: Building a Framework for more Personalized and Holistic Care in Pediatric Intestinal Failure
Keywords: Bioelectrical Impedance Analysis
Body composition
Intestinal failure
Parenteral nutrition
Pediatric
Physical activity

Objectives: 1) Compare body composition (BC) measured using bioelectrical impedance analysis (BIA) to that measured using dual-energy x-ray absorptiometry (DXA), 2) Collect data on physical activity (PA), and 3) Assess the relationship between PA and BC in pediatric intestinal failure (IF).Methods: IF patients, 1-18 years, having a DXA as part of clinical monitoring were eligible. BC measured by BIA and DXA, and PA by accelerometry. T-tests examined differences in BC obtained by the two methods and compared PA and BC to norms. Regression analysis assessed the relationship between BC and PA. Results: Sixty-eight children were studied. There was no difference between BC obtained by DXA and BIA (p=0.26). IF patients were less active with higher FM and lower FFM than norms (p<0.05). PA was associated with BC (r2=0.32, p<0.001). Conclusions: BIA is acceptable for assessing BC in pediatric IF. PA interventions and BC assessment should be part of management.
Optical Force Integration in Lab-on-Chip Cell Sorting Techniques
Keywords: biosensors
cell sorting
Lab-on-chip
Optical Tweezers

Cell sorting is pivotal for diagnosing and treating blood diseases. Recently, microfluidic chip-based methods have streamlined rapid on-chip testing. However, optical force-based cell sorting, utilizing optical tweezers, offers a non-invasive, highly controllable approach. These tweezers trap and manipulate microscopic entities, such as cells, using a focused laser beam. They offer superior sensitivity, non-destructive control, and avert contamination risks. This thesis explores optical tweezers’ physics, highlighting their efficacy in manipulating particles sized 1-10 μm with pico-newton optical forces. Yet, challenges exist, notably the serial analysis limiting throughput. New algorithms, like the Gerchberg-Saxton, address this, while integrating microfluidics enhance automation and efficiency. Beyond biology, optical tweezers find potential in nanotechnology and regenerative medicine, aiding nanoparticle assembly and stem cell manipulation. This research paves the way for revolutionary on-chip blood tests and a deeper understanding of microscopic forces, promising significant biomedical breakthroughs.
Evaluating Inflammatory Cytokine Changes in Participants with Mild Cognitive Impairment or Alzheimer’s Disease in the EXPRESS Study
Keywords: Aerobic Exercise
Alzheimer's
Inflammation
Interleukin-6
Mild Cognitive Impairment
tDCS

Current pharmacotherapies for Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI) lack efficacy and tolerability. The non-pharmacological therapy transcranial direct current stimulation (tDCS) is of interest, as studies have shown improved cognition following tDCS. Neurobiological mechanisms by which tDCS may improve cognition are poorly understood. The inflammatory cytokines Interleukin-6 (IL-6) (primary) and Tumor Necrosis Factor (TNF) (exploratory) were measured in MCI/AD participants (N=39) before and after 3 weeks of aerobic exercise followed by two weeks of exercise+tDCS, exercise+sham, or treatment as usual+tDCS. For IL-6, TIME (F(36)=7.351, p=0.01) and GROUPxTIME (F(36) = 3.852, p=0.03) effects and indicated that IL-6 levels increased from study screening (T0) to endpoint (T2). Exploratory analyses showed TNF was inversely associated with recognition memory. T0 IL-6 and TNF did not predict changes in global cognition or recall or recognition memory. This research suggests that changes in inflammatory cytokines may be related to cognitive outcomes.
Mediating Real-Estate: Understanding Property Platforms in Toronto’s Residential Real-Estate Markets
Keywords: Digital technology
Financialization
Housing
Platforms
Real-estate

Property platforms are promising to reduce the risks, time, and costs associated with finding and securing a home; they are claiming to improve existing real-estate processes and operations using insights derived from spatial and user-data. In light of these claims, this research examines the impacts of these new property platforms on real-estate markets in Toronto, Canada. Though the material implications of these technologies have yet to fully manifest, I argue that property platforms are covertly impacting real-estate markets in three main ways: they are allowing new entrants and intermediaries into the field of real-estate, they are leveraging societal crises to rationalize the development and adoption of their technologies, and they are merging and consolidating out of economic necessity paving the way for monopoly power over spatial data. As these new entrants gain access to real-estate and authority over its processes, I contend that property platforms should be understood as a conduit through which financial and technological actors can assert unilateral power over our spatial and behavioural information. Platforms’ newfound dominion over how we find, valuate, buy, sell, manage, develop, and build real-estate prefigures their potential to exert unprecedented influence and control over physical space.
A Polygenic Risk Score for Hand Grip Strength is Associated with Cognitive Function in Mid-to-Late Life Adults
Keywords: Alzheimer's disease
Cognitive decline
Hand grip strength
Polygenic risk score

Lower muscular fitness is a risk factor for Alzheimer's disease (AD). Hand grip strength (HGS) is a heritable predictor of cognitive decline in aging, however, the genetic component of HGS and its impact on cognitive decline remains unexplored. To test the innate biological influence of HGS on cognition in large populations, we calculated a polygenic risk score (PRS) for HGS (PRSHGS) and evaluated its direct and mediated effects on cognitive function, cross-sectionally and longitudinally, in two independent mid-to-late life cohorts. Findings revealed that genetic predisposition for greater HGS was significantly associated with better cognitive performance. The effects of PRSHGS on cognition were not moderated by levels of physical activity or cardiovascular health and explained variance in cognition beyond the benchmark PRS for AD. Additionally, PRSHGS was not associated with postmortem neuropathologies. These results suggest a direct link between HGS and cognitive performance, independent of lifestyle factors and AD-related neuropathology.
Advancing Wildfire Research Through Big Data, Artificial Intelligence and Emerging Image Processing Algorithms
Keywords: automated machine learning
deep learning
forest fire
Google Earth Engine
LandTrendR
wildfire severity

More and larger wildfires in northern Canada are causing environmental damage, releasing stored carbon, and forcing residents to relocate. With climate change factors such as warmer winters and broader spread of damaging insects, Yukon is experiencing earlier, longer, and more intense wildfire seasons. This paper furthers our understanding of wildfire severity mapping by: (1) assessing advancements in remote sensing data, cloud geoprocessing platforms and emerging image processing algorithms for wildfire burned area mapping, (2) conducting a driver analysis of wildfire severity in Yukon using the LandTrendR temporal segmentation algorithm, the Google Earth Engine cloud geoprocessing platform, and a deep neural network, and (3) analyzing the influences that a diverse series of climate, topographic, ecological and fire history variables had on wildfire severity. These new techniques and tools, enhancing the accuracy of burn severity models, could improve Canadian and global forest management practices, potentially reducing the impact of severe wildfires on humans.
Promoting Online Learning in Primary Schools in Rural China
Keywords: K-12 Education
Online Education
Primary School Education
Rural Online Education in China

In response to the global impact of the Covid-19 pandemic, China introduced a national online education program catering to students in both urban and rural areas. The abrupt transition from traditional in-person education to online learning has posed numerous challenges, especially concerning the quality of learner-instructor interactions. This study explored the role of instructional design in enhancing these interactions and, consequently, improving the online learning experience for rural primary school students. Additionally, the research investigated the specific challenges rural primary school students and their instructors face while adapting to online education. By providing insights into how instructional design can be harnessed to address these challenges, this study contributed to the field of online education, particularly for rural primary schools. The findings offered guidance to policymakers, educators, and instructional designers working to enhance online learning experiences in similar contexts.
A Tailored Fit: Design and Evaluation of a Website Structure Self-Tailoring Option for Older Adults
Keywords: Empirical study that tells us about how people use a system
Human-Computer Interaction
Information Architecture
Older Adults
User Experience Design
Website Design

Older adults are increasingly turning to online sources for health information. In doing so they face unique combinations of barriers which must be considered when creating websites. Linear and matrix information architecture structures can be used to address certain barriers faced by older adults. This thesis describes the design and evaluation of a health information website which allows older adults to choose, or self-tailor, between a linear and matrix structure. The study also evaluated the role that user involvement, in the form of a focus group, had on users’ satisfaction and experience with the final website design. The findings indicate that older adults are able to successfully select their preferred structure when self-tailoring and that having the option to self-tailor gives older adults a greater sense of control over their experience. The findings also demonstrate that the focus group led to design changes which were received positively by subsequent website users.
Locating the Political and Spiritual in Three Plays by Métis/Dene Playwright Marie Clements: the Unnatural and Accidental Women, Copper Thunderbird, and Tombs of the Vanishing Indian
Keywords: Clements
Dramaturgy
Indigenous
Performance
Playwriting

This work examines the dramaturgical relationship between the political and spiritual layers of three of Marie Clements’ plays: the Unnatural and Accidental Women, Copper Thunderbird, and Tombs of the Vanishing Indian. I introduce the playwright and the three plays, my relationship to the plays, Clements’s craft and Indigenous dramaturgy, Indigenous spirituality as it pertains to the play, and my political approach, which includes Marxist-influenced feminist materialism. I then separate the three plays into the spiritual and political narratives for a close and individual reading of each. I argue that by bringing the spirit world directly onstage and weaving together both traditional and material worlds, Clements provides her characters with a timeless connection to the wisdom of ancestors and history with which to confront the consequences of colonialism and settler capitalism on their lives. In doing so, she alleviates her characters’ isolation and dislocation, allowing them (and the audience) to transcend their circumstances and (re) imagine an Indigenous futurity.
A Net-Decomposing Parallel Field-Programmable Gate Array Router
Keywords: CAD
EDA
FPGA
parallel routing

Routing is the final step in the FPGA CAD tool flow and has a significant impact on runtime and quality of results. The most common algorithm used for FPGA routing, PathFinder, has proven difficult to accelerate by parallelization since it was introduced in 1995. We introduce two parallel routers extending the PathFinder-based AIR router in VPR 8, which is the fastest serial routerto date. The baseline router is based on the widely applied technique of recursive bi-partitioning. The improved router applies a range of novel net decomposition methods on top of recursive bi-partitioning to increase scalability. We obtain a speedup of 1.42x with 4 threads compared to VPR 8 on the Titan benchmark set with the baseline router and a speedup of 1.72x with 4 threads with the improved one (with 1.1% increase in critical path delay). The improved router is able to obtain a speedup of 1.82x with 4 threads with 1.4% increase in critical path delay when flat, or combined inter- and intra-cluster routing is enabled. Both routers are deterministic and serially equivalent. Implementations are made available as a part of the open-source VTR framework.
Investigating Heterogeneity in the Long-term Maintenance of Cellular Phenotype Following Ionizing Radiation
Keywords: DNA damage
fate tracking
heterogeneous fate
ionizing radiation
single cell

Ionizing radiation (IR) is commonly used to kill cancer cells by causing DNA damage. Cells initiate DNA repair pathways and cell cycle arrests to suppress cell death, and the differential activation of these pathways can lead to several distinct fates in neighbouring irradiated cells. Some cells die rapidly by apoptosis, some proliferate indefinitely, while others activate another mode of cell death or permanently exit the cell cycle into senescence. We established scRNA-seq data analysis pipelines for tracing transcriptionally heterogeneous fates in vitro, and my preliminary data demonstrate separable gene expression when a homogeneous cell population (MCF10A cells) is irradiated. My work is focused on establishing a long-term live-cell imaging assay for tracing the diverse fates of irradiated cells at the single-cell level. Using this system, the timepoint, frequency, and state of cell divisions can be observed in normal and pharmacologically modified conditions, and we traced fate outcomes in cells irradiated during different cell cycle phases as DNA damage burden increases, as classical DNA damage response kinases are inhibited, and when cell fate is artificially directed towards different modes of death. Through fate mapping of single-cells, I envision this system as an aid to establishing novel deterministic features of IR-induced cell fate outcomes, identifying candidate pathways associated with fate emergence for further investigation, and guiding novel avenues for rationally shaping heterogeneity in fate following IR. This will provide a deeper understanding of why some cells are responsive to treatment, activating favorable modes of cell death, while others are left behind to repopulate a tumor and drive local cancer recurrence after treatment.
The FORWomen Qualitative Study: Substance Use Treatment Experiences of Forensic and Non-Forensic Women
Keywords: forensic mental health
lived experiences
qualitative
secure services
substance use
women's health

Biopsychosocial factors influence women’s substance use (SU), like sex differences, higher rates of concurrent mental illnesses, and sociocultural expectations affecting treatment engagement, resulting in a more vulnerable profile compared to men. Furthermore, women involved with the criminal justice system (CJS) experience more complex trauma, leading to higher rates of post-traumatic stress disorder and other challenges. This project aims to identify barriers to treatment-seeking, useful/inconvenient components of treatment, perspectives on women-only group settings, and other opinions on treatment. Forensic and non-forensic women from the Center for Addiction and Mental Health in Toronto, Canada were interviewed using qualitative semi-structured interviews. Ten overarching themes were identified: (1) SU history; (2) Barriers to help-seeking; (3) Facilitators for treatment initiation; (4) Knowledge on SU and mental health; (5) Addressing practical difficulties to attendance; (6) Intervention components; (7) Peers and group settings; (8) Influence of staffing; (9) Gender-specific concerns, and; (10) Supporting long-term recovery.
Cryopreservation of Myoblasts in Paper-based Scaffolds for Inter-laboratory Studies of Skeletal Muscle Health
Keywords: Cryopreservation
Drug Discovery
Higher-Throughput
In Vitro
Regeneration
Skeletal Muscle

Three-dimensional tissue-engineered models are poised to facilitate progress in understanding skeletal muscle pathophysiology and identify novel therapeutic agents to improve muscle health. Yet, barriers to widespread adoption of such models include: methodology complexity, limited throughput, and requirement of cell culture expertise and/or specialized instruments, reagents, or software. To alleviate these barriers, our group engineered a 24-well model to study muscle endogenous repair (MEndR) that can be easily imaged and integrates with semi-automated image analysis pipelines. However, MEndR still requires user seeding experience and a high number of cells, reducing its throughput. Therefore, I first demonstrate our work scaling MEndR to a 96-well footprint (mini-MEndR), augmenting its ease-of-use and throughput. Second, I develop a standard operating procedure for the cryopreservation of muscle cell progenitors in mini-MEndR and validate that it preserves cell viability, differentiation, and function. Taken together, cryopreservation in mini-MEndR offers researchers an “off-the-shelf” platform for studying skeletal muscle health.
Linearly-scalable R-2R Multiply-and-accumulate Architecture for AI Edge Devices
Keywords: Analog Computation
Artificial Intelligence
CMOS
In-memory

From the cloud to the user-end, Artificial Intelligence (AI) edge devices have been receiving increasing attention thanks to its benefits including privacy, low latency, and efficient use of bandwidth. However, traditional computing architectures such as CPU and some existing AI accelerator cannot meet the tight energy budget of future AI edge applications. Researchers have been focusing on an emerging computing architecture, computation-in-memory (CIM), which improves both memory access and computation efficiency. This thesis presents a current-domain compute-in-memory (CIM) architecture for acceleration of AI edge inferencing. A novel multiply-and-accumulate (MAC) scheme is introduced by exploiting the R-2R resistor ladder as a binary-weighted current recombiner. The area and power of the proposed scheme scale linearly as numerical precision increases for both input activation and weight. Computation latency is maintained single cycle. A prototype in 22nm FD-SOI CMOS process achieves 2.2ns system latency, 56TOPS/W energy efficiency and 4TOPS/mm2 area efficiency with 6-bit input activation and 8-bit weight.
Breakdown of the Apical Spectrin Network Leads to Endothelial Dysfunction and Vascular Stiffening in Pulmonary Arterial Hypertension
Keywords: Breakdown
Endothelial Dysfunction
Pulmonary Hypertension
Spectrin

Recently, a critical role for a spectrin cytoskeletal network in sensing of shear and regulation of vascular stiffness has been described in systemic endothelial cells. The loss of spectrin resulted in the disappearance of apical caveolae, dysregulated eNOS activation, and a lack of calcium response to shear. Since spectrin can be broken down in vivo by calpain, which is activated in pulmonary arterial hypertension, I hypothesized that spectrin breakdown may represent a key mechanism underlying endothelial dysfunction.I report an increased prevalence of spectrin digesting proteases and spectrin breakdown products in the lungs of monocrotaline treated rats, along with decreased levels of caveolin-1 and a reduction in apical caveolae, a trend that was reversed by administration of calpeptin, a calpain inhibitor. Calpeptin was also shown to be protective against severe pulmonary hypertension in MCT rats. Furthermore, I determined that the knockdown of spectrin in endothelial cells results in internalization of caveolin-1 and impaired endothelial responses to shear. My studies detail a critical role for the spectrin cytoskeleton in the development of endothelial dysfunction and highlight the therapeutic potential of preventing its breakdown via calpain inhibition.