VictorJuiz/thesis huggingface dataset:
Pro-Ana/Mia Performance Ethnography: Remaking Responses to Psychiatric Relations to “Eating Disorders”
Keywords: Affect theory
Critical/cultural disability studies
Eating disorders
Mental health
Performance ethnography
Pro-ana

This dissertation focuses on cultural representations of “pro-ana/mia” as well as people’s responses to these representations. Pro-ana/mia has multiple meanings and can refer to individuals and communities online, self-described as “pro-anorexia”, “pro-bulimia” or “pro-eating disorder”, who communicate about eating, movement and bodies in ways that medical and mental health professionals disapprove, censor, deny or obliterate. Intervening against psychiatry’s assumed authority, my dissertation understands pro-ana/mia as representing a complicated diversity of voices and experiences that we should listen to, and learn from. Through the transformation of my pro-ana/mia research, a play titled Pro-Ana/Mia Embedded was staged. The play was performed for two audiences: those who identified with dis/ordered eating, and professionals who worked with people identifying with dis/ordered eating. Focus groups were held with these participants forming the basis for much of the research encountered here, where I extended my theorizing of responses to pro-ana/mia and “eating disorders” to reveal ableist myths of normalcy and sanist violence. With an interpretivist ontology and attention to the politics of emotion (e.g., Ahmed, 2014; Boler, 2015), my dissertation co-produces knowledge with participants who reify and rupture hegemonic understandings of, and responses to, pro-ana/mia and eating disorders. Participants contributed to the post-performance conversations in ways that de-center the normalcy of the psychiatric and bio-medical model’s tyranny on “mental illness” knowledge production and intervention, narrating the ineffectiveness and harms caused by ED treatment and approaches to recovery. Remarkably, through multiplex stories of dis/order, struggle and recovery, participants themselves do disability studies through creating new meanings of pro-ana/mia as teacher (Titchkosky, 2003a) to learn from, and understand with, disrupting the authoritative monopoly of being explained by “experts” and acted upon by psychiatry. My dissertation embraces the non-violent lessons and possibilities that doing disability studies, with emotion and collaboration, offers for fostering new relations with pro-ana/mia and eating disorder theory and praxis.
B Cell Responses in an Animal Model of Neuroinflammation – Implications for Multiple Sclerosis
Keywords: Antibodies
B cells
Experimental autoimmune encephalomyelitis
Multiple sclerosis
Neuroinflammation

Multiple sclerosis is a complex disease with no definitive cause or cure. Positive clinical trials such as those with anti-CD20 and negative clinical trials such as those with TACI-Ig – all of which deplete B cell subsets – have revealed unexpected complexities with respect to the role of B cells in MS. In this thesis, I use multiple models of experimental autoimmune encephalomyelitis (EAE) to characterize B cells functions during EAE, from antigen-driven activation to trafficking. In chapter 1, using Aicda-/- and Ung-/- mice, I found that class switch recombination is critically required for the full manifestation of B cell-dependent (hMOG) EAE. In chapter 2, using competitive and mixed bone marrow chimeras, I determined that, while mice that lack CCR6 on B cells exhibit an altered germinal center reaction, these mice exhibit normal B cell accumulation in the CNS and unimpaired B cell-dependent (hMOG) EAE. In chapter 3, I showed that MOG35-55-induced EAE is more severe in Aicda-/- mice and this increased severity is associated with alterations in the microbiota. Gaining a better understanding of the function of B cells in EAE provides opportunities to improve B cell directed therapies for patients living with MS.
Full Scale Electric Vehicle Drivetrain-integrated Charging from a Single-phase AC grid and Wireless Power Transfer System
Keywords: AC charging
Drivetrain
Electric Vehicles
Inverter
motor drives
Wireless Charging

The limited range and slow/inaccessible charging infrastructure of electric vehicles (EVs) makes it hard to justify the purchase of new EV. This is exacerbated by the higher cost of EVs compared to traditional internal combustion vehicles. This thesis proposes a drivetrain-integrated charging system which addresses some of the barriers hindering the widespread adoption of EVs. A drivetrain-integrated charging system is an EV charger that resides on-board the vehicle which re-purposes pre-existing components on the vehicle to constitute the required charging circuit. In other words, it leverages the power electronics and electric machine in the drivetrain to serve as part of the high voltage battery charging system. The proposed integrated charger is based on the dual-inverter drive, consisting of two traction inverters, two batteries and an open-winding machine. The addition of two extra half-bridge modules enable this drivetrain to directly connect to and charge from a single-phase AC grid at power levels comparable to the power rating of the drivetrain. A further addition of a small capacitor divider enables the charger to also serve as the receiver power electronics in a wireless power transmission system. The developed control schemes allow for regulating the charging rate of both batteries from either source with excellent efficiency. Bidirectional operation is also possible during single-phase AC charging, in order to provide grid support or to supply external loads, such as appliances, tools or even other EVs or homes. Simulation and full-scale experimental testing validated single-phase AC and wireless charging. Single-phase AC charging is demonstrated up to 19.2kW with peak efficiency over 97%. Wireless charging is demonstrated up to 6.6kW with a peak efficiency of over 95%. Practical considerations, such as user safety (and standards compliance) was verified experimentally using the full-scale system considering all applicable parasitic elements. Overall, the developed integrated charging solution can save cost and space on-board the vehicle while offering additional/improved functionalities compared to existing discrete solutions in use today. This can make EVs more attractive for potential adopters.
Nonhuman Social Actors in Daily and Ritual Activities of the Andes: Human-Animal Interactions among the Moche in the Middle Horizon, Jequetepeque Valley, Peru (CE 600-1000)
Keywords: Andean Archaeology
Human-Animal Interactions
Isotope Analysis
Middle Horizon
Pastoralism
Zooarchaeology

This dissertation examines how animals formed part of daily, economic, sociopolitical, and ceremonial practices among Middle Horizon period (CE 600-1000) communities of the North Coast of Peru. I focus on the Late Moche period (CE 600-850) to examine how animal depiction, co-habitation and value were variably manifested in daily and ritual practices at the site of Huaca Colorada in the Jequetepeque Valley. This project is guided by posthumanism and indigenous scholarship to interpret the role of animals in quotidian activities, sociopolitical structures, and identity formation.I examine the role of animals across a large Late Moche center to investigate the spatial distribution of animal taxa, the sharing of their meat and the symbolic significance of different species in interment events. My analysis also considers the briefer Transitional period (CE 850-1000) occupation of Huaca Colorada and the adjacent Transition site of Tecapa to realize the continuity of traditional ecological knowledge, lifeways, and religious aesthetics. The persistent consumption of camelids and coastal taxa throughout the Middle Horizon reveals that southern Jequetepeque Valley communities employed commensal strategies to advance their own interests and legitimize their political standing in ritual practices. Feasting also provided a medium for non-local, possibly highland communities to be involved in large-scale, seasonal events. I reconstruct the life histories of animals and humans from Huaca Colorada through three interrelated approaches: (1) the iconographic or idealized depictions of animals; (2) the osseous patterns of life and death among animals and humans, and (3) the biographies of nonhuman and human animals as reflected in their diets and mobility. The objective of this dissertation is to interpret the roles of different animals as social actors in the mediation of the changing sacred and political landscapes of the southern Jequetepeque Valley. This dissertation demonstrates the essential involvement of animals in daily and ceremonial activities both as animate living beings and as butchered and consumed resources. The results of this investigation emphasize that Moche period ecological knowledge and deeply embedded ideologies about the cosmological cycles of the world were believed to depend on nonhuman beings and ensured the survival and prosperity of human societies.
Investigating Heterogeneity and Overlapping Clinical and Neurobiological Features across Early Psychosis and Neurodevelopmental Disorders in Children and Adolescents
Keywords: Clustering
Factor Analysis
Neurodevelopmental disorders
Neuroimaging
Psychosis
Youth

The presence of psychosis symptoms in childhood and adolescence is associated with impaired daily functioning and the later development of more severe psychotic and non-psychotic psychiatric disorders. Evidence is emerging that neurodevelopmental disorders, such as autism spectrum disorder (ASD), or attention deficit hyperactivity disorder (ADHD) are themselves risk factors for psychosis symptoms and psychotic disorders. Heterogeneity within these disorders is well-established, as well as that they share overlapping clinical and biological features. In addition, such disorders share common genetic and neural circuit substrates with psychotic disorders. However, the relationship between these disorders including their heterogeneity and comorbidities, as well as underlying neurobiology is still unclear. This thesis applies multivariate, machine learning, and factor analytic approaches and magnetic resonance imaging to investigate neurobiology and other risk factors, such as biological sex, associated with overlapping psychopathology in children and adolescents. In study one, cortico-striatal-thalamic-cortical circuit structure and connectivity is examined in children and adolescents experiencing psychosis spectrum symptoms, as well as how differences vary with age and sex. In study two, novel data-driven subgroups across children with obsessive-compulsive disorder (OCD), attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are identified based on integrated multimodal structural imaging and behavior measures. In study three, factor structure underlying a wide range of psychopathology symptoms is investigated in children using ten dimensional instruments from both child and parent informants and a novel modeling approach. Together, the work presented in this thesis highlights heterogeneity within and similarities across children and youth experiencing early psychosis symptoms and neurodevelopmental disorders (ASD, ADHD, and OCD) in neurobiology and behavior. By improving our understanding of different neurobiological profiles of youth within and across diagnostic categories and how these map onto behavior, we can better understand the pathophysiology of mental illnesses, identify biomarkers of risk that can be used to predict illness/outcome trajectories, and provide opportunities to develop more individualized interventions.
Advancing Microfluidic Tumour-on-a-chip Technologies by Integrating Multicellular Tumour Spheroids and Angiogenic Vessels
Keywords: 3D cell culture
angiogenesis
endothelial sprouting
microfluidic cell culture
tumour-vasculature co-culture

Angiogenesis, the development of new blood vessels from existing vasculature, is a key mechanism in cancer progression. Solid tumours that are depleted of nutrients induce angiogenesis to recruit blood vessels for access to nutrients and a pathway for metastasis. Anti-angiogenic therapies have been developed, but toxicities, resistance, and limited efficacy have been reported and there remains a strong need for development of in vitro platforms that can model tumour-induced angiogenesis to conduct fundamental and clinical research. Traditional in vitro assays include 2D cell cultures that do not recapitulate cellular functions that are unique to a 3D geometry and are therefore unsuitable for investigations of complex phenomena such as tumour angiogenesis. Microfluidic technology has emerged as a popular tool for 3D cell cultures such as tumour-on-a-chip models that recapitulate the physiological complexities of a tumour microenvironment. The development of a microfluidic model for tumour-induced angiogenesis would facilitate fundamental research on the underlying cellular mechanisms, and clinical research to develop new drug candidates. To accomplish this, a deeper understanding of the microfluidic cell culture components is needed, along with a device design that is well suited for analysis of tumour-induced angiogenesis. The objective of this thesis was to examine the elements of a microfluidic model of tumour-endothelial interactions and develop a microfluidic cell culture where tumour-induced angiogenesis can be observed and quantified. We first characterized 3D spheroids, revealing correlations between external, internal, and secretory profile characteristics of 3D tumour spheroids as they relate to angiogenic potential. Next, we sought to understand how best to incorporate fibroblasts for their critical role in achieving 3D sprout morphology. We identified the utility of fibroblast configuration for influencing the extent of endothelial response in microfluidic co-culture. Finally, we introduced a new microfluidic device for spheroid-endothelial co-cultures where spheroid-induced sprouting was demonstrated using multiple spheroid types and quantified using image analysis. Overall, these studies have developed insights on the characteristics of 3D tumour spheroids, fibroblasts, and endothelial sprouts that allow these cell culture features to be wielded as biological tools, and demonstrated the utility of microfluidics for complex cell cultures to study tumour angiogenesis and cancer progression.
Towards Precision Medicine: Characterizing and Predicting Antidepressant Remission Heterogeneity in Late-life Depression Using Genetic Data
Keywords: Antidepressant response
Genome-wide association study
Late-life depression
Machine Learning
Pharmacogenetics
Venlafaxine

Late-life depression (LLD), diagnosed as major depressive disorder in older adults (≥ 60 years), is a heterogeneous disorder characterized by a unique constellation of clinical symptoms and risk factors associated with ageing, including comorbidities such as cerebrovascular disease, which impact symptomatology and response to antidepressant medication. Towards precision medicine, this thesis traverses methodologies in pharmacogenetics to identify variants associated with, and predictive of, response in older adults, specifically among those treated with the commonly used antidepressant, venlafaxine.First, using a candidate-gene approach, we show an association of the norepinephrine transporter gene (SLC6A2) with LLD remission (OR = 1.67 [1.13, 2.42], p = 0.009), which is a validated target of venlafaxine. In addition, we identify variants in novel genes of interest, particularly in the PIEZO-type mechanosensitive ion channel component 1 gene (PEIZO1; OR = 0.33 [0.21, 0.51], p = 1.42×10^-6), which implicates cardiovascular and inflammatory processes in LLD and antidepressant response. Given our interest in predicting antidepressant response, we evaluate the predictive capacity of data-driven, machine learning models which integrate clinical and genome-wide data. Compared to baseline models using only clinical features, integrated models show decreased performance due to noise added by genetic features. Furthermore, integrated models do not achieve clinical significance (remission, AUC = 0.68, Sensitivity = 0.53, Specificity = 0.75, Accuracy = 65.0%, p = 5.08×10^-6; end-of-treatment depression severity, RMSE = 7.93, Pearson’s ρ = 0.22, p = 0.033). Our results present several implications, including (1) the need for larger clinical studies targeted towards the development of inferential and predictive pharmacogenetic models; (2) the further need for leveraging in silico databases to characterize and understand the biological relevance of associated variants; and, (3) a better understanding of the computational and statistical implications for machine learning models integrating high-dimensional genome-wide and clinical data for the prediction of complex psychiatric outcomes. Ultimately, such predictive models will aid the development of decision support tools to identify older adults at high risk for inadequate response to antidepressant treatment who may benefit from additional or alternative interventions to reduce the overall healthcare burden and improve patient quality of life.
The Importance of Thermal Preferences in Governing Fish Productivity, Foraging Behaviour, and Interactions in a Changing World
Keywords: climate change
fisheries
freshwater
species interactions

Fisheries are an important source of food, income, and recreation across the world, yet they are vulnerable to exploitation and environmental change. As ectotherms, a fish’s environment directly affects how it acquires and metabolizes energy. Energy acquisition and metabolism differ among fish species based on their unique diets, behaviours, and habitat preferences, resulting in differential (or asynchronous) responses to environmental change. Therefore, natural resource managers must learn these unique qualities and responses to create adaptive policies under changing conditions and protect fisheries into the future. However, research about the simultaneous effects of multiple interacting environmental factors on multiple interacting species is still at its infancy. My research seeks to understand the effects of environmental factors on the productivity of multiple fish species (referred to as fish productivity for the remainder of this thesis), as well as their behaviours, and interactions. First, I show that species-specific fish productivity (g·ha-1·yr-1) in inland lakes is differentially influenced by various abiotic (e.g. temperature, dissolved organic carbon, habitat area) and biotic (e.g. presence of predators and invasive species) factors. Second, I use stable isotopes to show that behavioural foraging (i.e., trophic position and habitat use) is mediated by local and broad-scale habitat conditions but does not necessarily reflect fish productivity. Third, I used a temperature-dependent food web model to study how thermal guild interactions are altered by changing environmental conditions, which may lead to unexpected outcomes of a species-removal management strategy. Together, my research suggests that fish species respond asynchronously to different environmental conditions. This means that some species may behave differently and be more or less productive than others when exposed to new conditions, which will manifest in unique species interactions and food web dynamics. Such information will be crucial for assessing the effectiveness of adaptive management policies in a changing climate.
Ideological Intergroup Conflict and Cooperation
Keywords: Conflict Resolution
Cooperation
Ideology
Intergroup Relations
Political Attitudes
Threat

Ideological beliefs are strongly held, prescriptive beliefs about how a society should function. Differences in ideological beliefs can be a cause of intergroup conflict and a driver of polarization. This thesis explores how individuals react when encountering people and groups whose ideological beliefs conflict with their own. I find that across a range of ideological beliefs that span the political spectrum, people report similar experiences of ideological threat and intergroup perceptions and intentions. In each chapter, I explore ideological disagreement through the lens of different psychological phenomena. In Chapter 2, I use data-driven methods to build an evidence-based description of the attitudes and characteristics of political moderates. I show that moderates have more diverse and less extreme views than partisans, and confirm existing literature showing they are less prone to negative views and dogmatic ideological beliefs. However, I also show how the American culture war polarizes moderates' attitudes towards certain issues such that they resemble partisans' attitudes in their consistency and extremity. In Chapter 3, I investigate the relationship between perceptions of ideological threat and moral conviction. I find that perceptions of a preferred ideological policy as being under threat is related to higher moral conviction towards that policy. In Chapter 4, I develop a measure of ideological prejudice that captures negative attitudes towards both ideological outgroup members and their beliefs. I find that negative attitudes towards ideological outgroups largely centre around generalized dislike towards outgroup members and condemnation of ideologies that would restrict others' freedom of expression. Finally, in Chapter 5, I identify psychological mechanisms related to cooperative intentions towards ideological outgroup members. I design and test a series of wise interventions leveraging each mechanism. While I do not identify an effective intervention in this chapter, I discuss insight gained from these tests and the identified correlates of cooperation. In this thesis, I seek insight into ideological disagreement through the lens and tools of social psychology. Overall, I find evidence that individual ideological beliefs have great power over perceptions of the social world and engagement with it.
Estimating the Functional Impact of Single Amino Acid Changes Using Machine Learning
Keywords: Balanced Precision
Data quality and quantity
Variants Pathogenicity
Weighted training examples

One of the great challenges in genetics is to accurately separate functional from neutral variation in human genome sequence. Towards more accurate pathogenicity prediction of human genetic variants, it has become possible to experimentally map the fitness landscape of missense mutations for specific targeted human disease-associated proteins. Coupling exhaustive mutagenesis with a deep sequencing read-out of multiplexed yeast functional complementation assays can yield a “variant effect map” covering most of possible amino acid changes in these proteins. The first challenge I wished to address is that for each variant effect map, a substantial minority of missense mutations remain unmeasured. The second challenge is that variant effect maps are available for less than 1% of disease-associated proteins, with a high-quality fully comprehensive experimental atlas of functional missense variation being likely decades in the future. Towards the first challenge, I imputed the functional effect of unmeasured variants using machine learning model trained on variants with experimental measurement, each of which is represented by a list of features including conservation scores, chemical physical proprieties of the residues, and engineered feature derived from the functional effect of similar amino acid substitutions in the same map. Towards the second challenge, I built a computational model VARITY to predict the pathogenicity of all possible missense variants for ~18,000 human proteins. I exploited a larger reservoir of training examples with uncertain accuracy and representativity, each assigned with a differential weight determined via hyperparameter tunning that optimizes predictive performance on a small high-quality set of annotated variants. Performance of the final model (VARITY) exceeds that of all analyzed previously described computational methods.