VictorJuiz/thesis huggingface dataset:
Critical Period, High-acuity Illness, Inequitable Access: Understanding Outcomes following Postpartum Psychiatric Emergency Visits, and the Role of Social Determinants of Health
Keywords: Emergency department
Health services
Postpartum mental health
Social determinants of health

Within the year following childbirth, approximately 1 in 100 postpartum individuals visit an emergency department (ED) for a psychiatric reason. Postpartum psychiatric ED visits are an indication of acute need for mental health care, and an opportunity to coordinate services. This thesis aimed to fill gaps in knowledge about the outcomes of postpartum individuals following psychiatric ED visits, and specifically understand how individual and intersecting social determinants of health relate (1) to inpatient hospital admission from the ED, and for discharged individuals, (2) to outpatient physician follow-up within 30 days, and (3) to subsequent psychiatric admission within 365 days. The thesis is comprised of three projects, all of which use Ontario health administrative data to examine a cohort of postpartum individuals with psychiatric ED visits (2008 to 2020). In each project, social determinants were examined independently, then in intersection using three distinct methods. In Project 1, 16.0% of individuals were admitted to hospital from the initial ED visit and, of the examined social determinants of health, only Chinese ethnicity was associated with an increased risk of admission after adjusting for clinical and other factors. Additive interaction to evaluate for synergistic or antagonistic effects between social determinants was non-significant. In Project 2, 44.8% of discharged individuals saw a physician for mental health care in the 30 days following the ED visit, with less follow-up in younger individuals, those in low-income and rural areas, and immigrants. Conditional inference trees used to examine social determinants in intersection identified patterns not evident from traditional regression (e.g., neighbourhoods diversity related to follow-up only among those aged ≤25 years). In Project 3, 9.5% of those discharged had a subsequent psychiatric admission, with a lower likelihood of admission among younger and immigrant individuals. Latent class analysis identified 4 socially distinct subgroups, which had differing risk of admission. Taken together, this thesis identified gaps in both inpatient and outpatient mental health care in a high-acuity postpartum population. Complexity in the relationships between social determinants and health service access underscore the need for intersectionality-informed approaches to improve equitable postpartum mental health service delivery.
The Political Development of the Treaty System in Canada
Keywords: Anishinaabe
Canadian Constitution
Canadian Political Development
Haudenosaunee
Indigenous Politics
Treaties

Are Crown-Indigenous treaties instruments of dispossession? Or are they best hope for a just political order in Canada? This question has divided Indigenous and anticolonial advocates and scholars. To adequately respond to it, we need a clearer account of what treaties are. Rather than seeing treaties as Indigenous practices of kin-making, nation-to-nation agreements, or real estate contracts, we need to recognize that the treaty system is a complex, multilayered institution that includes each of these elements. The treaty system combines Indigenous, Imperial, and Settler governance traditions. So understood, the treaty system is a fundamental, intersocietal institution of governance in Canada. It provides the overarching framework through which Indigenous and non-Indigenous peoples contest the terms of their territorial co-existence. It follows that treaties are neither instruments of consent nor dispossession; instead, they are sites of contestation and struggle. This dissertation traces the emergence, consolidation, and development of the treaty system from the early modern period to the present. It focuses on the emergence of the treaty system in the mid-eighteenth century, and its transformation into a system of treaty colonialism in nineteenth century Upper Canada. Throughout, I emphasize the simultaneous operation of three treaty traditions: Indigenous relational, Imperial diplomatic, and Settler contractual. These traditions constrained political agents, but they also provided resources that could be mobilized by diversely situated Indigenous and colonial actors, often in surprising ways. The dissertation concludes by endorsing a multi-pronged strategy of treaty renewal, one that simultaneously emphasizes Indigenous relational visions of treaty while strategically deploying the contractual and diplomatic traditions to combat dispossession. In this way, it contributes to debates about the role of treaties in reconciliation and decolonization. It also intervenes in disciplinary debates by insisting that Indigenous institutions, such as treaties, belong at the center of the emerging field of Canadian Political Development
Development of Mn(III) Porphyrins as Gd-free Contrast Agents for Targeted MR Imaging
Keywords: Magnetic Resonance Imaging
Manganese
Porphyrins

Personalized medicine requires precision diagnosis, and a targeted medical imaging method addressing this requirement is highly anticipated. Targeted magnetic resonance imaging (MRI) requires a contrast agent (CA) capable of detecting specific cellular or molecular biomarkers in a sensitive and selective manner. Currently, mainstream MRI CAs are Gd(III)-based, which is limited by low contrast efficiency (r1) and toxicity of free Gd(III) upon metal dissociation. To address these limitations, we are developing a new class of Gd(III)-free CAs based on the biocompatible Mn(III) porphyrin (MnP), which is desirable for their high r1 at high fields, stability against metal dissociation, and versatility for structural modification to achieve functional diversity. In this thesis, the development of MnP-based CAs for targeted MRI is explored. In chapter 2, we studied MnP2, the first MnP-based blood pool agent (BPA) on its binding behavior with its target, human serum albumin (HSA). We unexpectedly discovered a novel sequential binding model, in which MnP2 binds first to a kinetically favorable site, followed by migration to a thermodynamically favorable hydrophobic site (subdomain IB), causing r1 decrease in MnP2, possibly due to limited water accessibility. Based on the crucial findings, in chapter 2, a series of MnPs designed to overcome the water accessibility issue, either by twisting MnP2’s geometry (chapter 3) or incorporating smaller, more polar functional groups (chapter 4) were developed as next-generation BPAs. Amongst them, MnTriCPP especially showed significant r1 increase at high fields upon HSA binding (chapter 4). In chapter 5, MnTriCP-B(OH)2 was developed as a saccharide-targeted CA based on boronic acid-diol interactions, and the binding was found to be pH dependent. In chapter 6, MnTriCP-NTA was designed to target His-tag, a post-translational modification widely utilized in protein purification. Finally, in chapter 7, MnMOB and MnEOB were developed as MRI probes for organic anion transport proteins (OATPs). In vitro and in vivo evaluations show that MnEOB is highly specific and sensitive towards OATP uptake, demonstrating its potential for targeted liver imaging as well as gene reporting. Overall, MnP is a stable, sensitive, and flexible platform for next generation CAs for targeted molecular imaging.
Assessment and Application of Subclonal Reconstruction for Profiling Tumour Evolution
Keywords: Genomics
Retinoblastoma
Subclonal reconstruction
Tumour evolution

Tumour evolution is fundamental to cancer biology. As cells proliferate and successively acquire mutations, they can establish subpopulations which largely share a common genotype (subclones). Over time, successive mutation accumulation and selection can lead to tumourigenesis and intra-tumoural heterogeneity, which can have important clinical consequences. While many approaches exist for profiling subclonal heterogeneity, identifying subclones using the frequency of mutations in DNA-sequencing reads (subclonal reconstruction) can be an effective and broadly applicable method. This is a computationally ambiguous task and upstream errors from read alignment and variant calling can propagate into it. I co-developed a framework to assess the accuracy of subclonal reconstruction and characterized its error profiles. I then applied subclonal reconstruction and complementary approaches to understand the evolutionary impact of a common driver event. Characterizing algorithm accuracy and error is critical for effectively carrying out and interpreting subclonal reconstruction. To profile the accuracy of subclonal reconstruction algorithms, I first developed a pipeline to simulate a benchmark dataset of 50 realistic tumour BAMs with subclonal structure as well as a scoring framework. I then used a subset of these tumours, downsampled to five depths, to benchmark the accuracy of 576 mutation caller-depth-subclonal reconstruction algorithm pipelines and demonstrate the efficacy of a wide range of pipelines past a minimum effective read depth. I then evaluated 31 crowd-sourced algorithms on 50 simulated tumour BAMs. This analysis further highlighted the importance of effective read depth for subclonal reconstruction accuracy, emphasized the limitations of single sample data for phylogeny reconstruction and characterized common algorithmic biases. Finally, I applied subclonal reconstruction and comparative mutational landscape analysis to study the evolutionary consequences of the functional abrogation of RB1 through DNA mutations. I first contrasted the mutational profiles of RB1- and MYCN-driven retinoblastoma and then compared tumours with the early loss of one or both RB1 copies and RB1-wildtype tumours pan-cancer. In both analyses, I discovered weak, probabilistic contingencies of RB1 inactivation in shaping tumour evolution. Together, these studies provide a benchmark for subclonal reconstruction and a template for linking it to detailed tumour evolution studies from single sample NGS data.
Health Utilities in People with Chronic Hepatitis C
Keywords: health economics
health utilities
hepatitis C
patient preferences
patient-reported outcomes
quality of life

Background: Hepatitis C virus infection is associated with reduced quality of life. One way to measure the quality of life of hepatitis C patients is using health utilities. Health utilities provide insight into not only the state of a patient’s health but also the strength of preference for that health state. This is a meaningful metric that can be used to measure individual and population-level health as well as conduct cost-utility analysis. Methods: We conducted three studies on health utilities in hepatitis C patients: 1) a systematic review and meta-analysis; 2) a clinical study measuring hepatitis C patients’ health utilities in hospital and community health centre settings; and 3) a population-level health utility study using linked survey and healthcare administrative data. Results: The results of these three studies support the observation that hepatitis C is associated with a reduced quality of life. The meta-analysis found that hepatitis C virus infection is associated with impaired health utility. We observed that experimental study designs yield higher health utilities than observational study designs—an effect not previously documented. We also concluded that more research is needed in socioeconomically marginalized hepatitis C patients. The clinical study attempted to address this gap by recruiting marginalized hepatitis C patients from a community-based program. This study found that marginalized patients attending the community-based program had lower health utilities than patients recruited in hospital settings, where clinical research is most commonly conducted. Lastly, the study using administrative data found that the trends observed in the first two studies held true for a larger population-based sample from across Ontario: those with hepatitis C had a reduced quality of life as measured by health utilities, and socioeconomically marginalized individuals with hepatitis C had even lower health utilities. Conclusion: These three studies extend our understanding of health utilities and quality of life in hepatitis C patients, particularly in the context of marginalized populations who face a disproportionate burden. The utility estimates generated by these studies can be incorporated into cost-utility analyses of hepatitis C programs, including cost-utility analyses assessing different models of care for marginalized hepatitis C patients.
Training a Covert Speech Brain-Computer Interface Through the Passive Perception of Speech
Keywords: Brain-computer interface
Machine learning
Speech neuroscience

Covert speech (CS), the mental imagery of speaking, is a ubiquitous trait of human cognition that has received increasing amounts of attention in brain-computer interface (BCI) research. However, collecting large amounts of data are challenging due to fatigue resulting from repeated mental rehearsal. Therefore, a more user-friendly paradigm is needed. Fortunately, investigations have revealed a linkage between CS and speech perception (SP) incurring spatiotemporal similarities. However, it remains unclear whether these correlations can be leveraged to decode CS based on data from SP during online BCI operation. Therefore, the overall goal of the thesis was to train a model to distinguish CS based on SP. Due to the lack of knowledge on how information is processed during CS, the first study compared the neural oscillatory characteristics between SP and CS using a studentized continuous wavelet transform (t-CWT) and phase-amplitude coupling (PAC). Across ten participants, the absence of within task PAC in CS and the presence of cross-task PAC between SP-CS suggested that θ activity was not the latent variable linking SP and CS, but rather that it is the γ-bands (30-60 Hz) that produce the shared features. Using the same data, in Study 2, this interaction was further investigated by measuring phase-coding, a theory of temporal encoding in the brain. Here, significant spatial correlations were observed in the γ-band synchrony profiles as well as in PAC, reinforcing the idea that the γ and θ-bands likely subserve, respectively, shared and distinct encoding processes across tasks. Given the identified correlations in how SP and CS temporally encode information, the objective of Study 3 was to produce an online BCI. Here, utilizing a unique dyadic protocol whereby SP and CS trials were presented in pairs, CS data were linearly transformed using SP and subsequently classified during online BCI operation. Across 10 participants, ternary online accuracies reached up to 93% and averaged at 75% ± 9.02 across all participants. Moreover, model performance correlated to γ-band correspondence between tasks. Collectively, the three studies demonstrated that the shared characteristics between SP and CS can be leveraged to train a CS BCI based on simply hearing words.
Towards Automated Metabolic Model Reconstruction with Application to Parasite Evolution
Keywords: Apicomplexa
Metabolic reconstruction
Mixed-integer linear programming
Parasite evolution
Sequence analysis

An organism’s metabolic reactions, catalyzed by enzymes, produce key molecules like DNA and are thus key to its survival. Drugs targeting metabolic capacities of pathogens have been developed, and bacterial strains with desired bioproduction capacities have been engineered through wet lab experiments. Key to these applications is knowing the metabolic capacities of the organism of interest. Biochemical experiments being time-consuming, sequence analysis techniques have increasingly been applied to infer an organism’s metabolism. Moreover, since visually inspecting (complex) metabolic networks is impractical, mathematical optimizations through constraints-based simulations are instrumental in further propelling these studies. Sequence similarity, typically used to annotate a protein sequence with an enzymatic activity, has poor specificity. Indeed, the enzyme annotation tool DETECT, released in 2010, further attributed the results of these searches with confidence scores. In this thesis, I improve DETECT by further computing enzyme-specific cutoffs, whose use in annotation yields better tradeoff between precision and recall than its predecessor. However, DETECT can only predict large enzyme classes. Thus, I present Architect, a method which uses an ensemble approach that combines predictions from multiple enzyme annotation tools to predict a wider range of metabolic capacities with demonstrably higher accuracy than individual tools. Architect also uses these annotations to automatically produce metabolic models that can readily be used in constraints-based simulations. I show that while accurate prediction of a wider range of metabolic capacities can positively impact simulation results, the quality of these results also depends on other parameters (such as reaction directionality). Finally, I apply Architect in the metabolic reconstruction of four apicomplexan parasites and a sister species to understand the role of host environment on the evolution of the parasites' remarkably reduced metabolism. I develop a mixed-integer linear programming formulation which predicts possible parasitic networks (through minimal model computation) from an approximation of a free-living ancestor’s metabolism; I also employ various strategies to decrease the problem’s computational complexity. While predictions mostly do not overlap with the metabolism of extant parasites, I propose that this framework may serve as a stepping stone for answering further questions about these parasites as well as other organisms.
Heterogeneous Water Transport in Fuel Cell Materials
Keywords: Contact angle
Electrochemistry
Fuel cells
Heterogeneity
Tomography
Water management

Current state-of-the-art fuel cell designs exhibit heterogeneity, e.g., in wettability and pore size distributions in gas diffusion layers (GDLs) or land-channel patterns in flow fields. This inherent heterogeneity impacts liquid water transport and fuel cell performance and durability and needs accurate characterization to enable next-generation designs. Here, we reveal novel insights on how heterogeneity affects a) formation of pore-scale water pathways within GDLs, b) distribution of operando membrane hydration and morphology, and c) fundamental contact angle variation.3-D pore-scale liquid water distribution within the cathode GDL was characterized via operando synchrotron X-ray tomography to capture the early appearance of liquid water pathways. Liquid water only partially fills certain GDL pores, which is attributed to heterogeneous pore sizes and wettability distribution. Liquid water is observed to preferentially flow along some GDL fibers, due to the hydrophilic nature of carbon fiber and the presence of pore-scale mixed wettability within the GDLs. Operando spatiotemporal distributions of six interacting fuel cell components are resolved in high contrast using a novel combination of simultaneous neutron and X-ray tomography (NeXT) and advanced image processing, enabling the highest reported pairwise contrast between these materials (average and median pairwise contrast-to-noise ratio of 9.5). Signal and contrast are enhanced by up to 10 times and 48 times, respectively compared to single-modality imaging with conventional image processing. These drastic contrast enhancements reveal subtle variation in operando microstructural morphology of the catalyst coated membrane and liquid water distribution with respect to flow-field land-channel patterns in fuel cells. Quantitative analysis reveals that local heterogeneity in membrane hydration and interfacial properties are dependent upon operating conditions and geometry of flow-field lands and channels and interfaces such as GDL-gasket interface. Bubble adhesion on a smooth surface is analyzed using a novel mechanics perspective to reveal the existence of a pinning force during thermodynamic non-equilibrium. A new definition proposed here extends the validity of Young and Young-Laplace equations to a wide range of experimentally observed contact angles and lends insights into the fundamental mechanism of contact angle evolution.
Engineered Antibodies for Igsf8 and Tgfbr1 Modulate TGF-β Signals in Melanoma
Keywords: Antibody engineering
Immune-oncology
Melanoma
Phage Display

Comprehensive understanding of molecular pathways will identify the mechanisms underpinning disease. Including cancer progression. TGF-β signals can behave opposingly depending on context, yet key molecular insights of this regulation are still lacking. It is increasingly recognized that functional effects of this pathway are regulated via protein interactions and modifications of peripheral, accessory proteins, in addition to the core TGF-β proteins. Clarifying the contextual regulation of TGF-β signals would support the innovation of life-changing therapies that target TGF-β, given the importance of this pathway in nearly all cancers. Metastatic melanoma is the most aggressive skin cancer, and its invasive progression is primarily driven by TGF-β signals. Recent evidence demonstrates that Igsf8 can negatively regulate TGF-β signals in melanoma, suggesting that Igsf8 may hold a regulatory role for TGF-β signaling that is specific to melanoma. Efforts to target TGF-β in cancer include small molecules, antisense oligonucleotides, and monoclonal antibodies. Antibodies offer numerous advantages including increased target specificity, dose-dependence and modular structure that enables virtually limitless modification via protein engineering methods. Here, I have developed a method to engineer synthetic antibodies targeting multiple protein domains without structural information, using a phage-displayed antibody library. I then characterize antibody specificity, affinity, stability and epitope bins and screen for cell-binding. The cumulation of this data was then used to identify the most promising antibody candidates for Igsf8 with the goal to target the multiple domains of this protein. I then assessed the functional effects of Igsf8 antibody treatment on melanoma cells by setting up a highly sensitive cell signaling assay that detected any TGF-β signaling changes in vitro using a highly metastatic cell line. This assay demonstrated that antibodies binding to the membrane-proximal domain of Igsf8 could influence TGF-β signals, identifying a domain-specific function of Igsf8 in its regulation of TGF-β signaling in melanoma. My work supports a versatile method to develop domain-specific antibodies that can be applied to any member of the proteome, provides the field of Igsf8 research with specific protein tools for this target and advances our current understanding of melanoma by exploring a novel avenue for potentially new melanoma treatments.