VictorJuiz/thesis huggingface dataset:
Metformin Alters the Neuroinflammatory Response of Mcroglia following Neonatal Stroke
Keywords: Ablation
Astrocytes
Metformin
Microglia
Neonatal stroke

Neonatal stroke is a devastating disorder with long-term consequences for children and caregivers. Microglia and astrocytes mediate the neuroinflammatory response after injury which can exacerbate damage. Metformin is an antidiabetic drug which has been shown to improve functional impairments and promote neural repair after neonatal brain injury. Herein, we investigated metformin's potential role in regulating the neuroinflammatory response after neonatal stroke. Stroke-injured mice showed brain region-specific microglia and astrocyte activation and metformin treatment after stroke was sufficient to reduce microglia activation, without affecting the astrocyte response. Given the correlation with reduced microglia activation and improved functional outcomes, we established a microglia ablation model using Plexxikon 5622. This resulted in significant microglia depletion without effects on astrocytes or motor behaviour. This study is the first to characterize the spatiotemporal aspects of the neuroinflammatory response after neonatal stroke and metformin treatment and establish a model of microglia ablation in neonatal mice.
The Therapeutic Potential of HMGB1 Inhibition in the Development of Systemic Sclerosis-associated Pulmonary Arterial Hypertension
Keywords: fibroblast
HMGB1
pulmonary arterial hypertension
systemic sclerosis

High mobility group box-1 (HMGB1), a danger-associated molecular pattern, is gaining recognition as a mediator of pulmonary arterial hypertension (PAH). Unfortunately, current studies fail to address therapeutic interventions for pulmonary arterial hypertension associated with systemic sclerosis (SSc-PAH), which is a devastating subset of PAH. Our understanding of this entity is hampered by the lack of a readily available, high-fidelity animal model. Herein, we sought to assess the Tight Skin mouse (Tsk), which possesses many features of SSc, as a model of SSc-PAH, and to test the effect of HMGB1 inhibition upon the development of pulmonary hypertension (PH) in this model.Our data provide the first description of the hypoxic Tsk model of SSc-PAH. Mechanistically, our results indicate a key role for HMGB1, released in response to cellular damage, in the pathogenesis of PH in this model, potentially acting upon the pulmonary artery adventitial fibroblast.
The Genetic Basis of Natural Variation in Algal Neutral Lipid Accumulation
Keywords: adaptation
Chlamydomonas reinhardtii
natural selection
neutral lipid
nitrogen starvation
population genetics

Neutral lipids are known to be involved in an algal adaptation to cold, light, and nutrient stress, but the extent of intraspecific variation and the mechanisms maintaining the variation in this economically important trait are unclear. I predict algal strains from different latitudes will vary in neutral lipid accumulation because many of the stressor associate with climate. Inducing neutral lipid accumulation using nitrogen (N) starvation in 26 natural isolates of Chlamydomonas reinhardtii revealed genetic variation but no latitudinal pattern in neutral lipid accumulation. A further experiment demonstrated latitudinal variation in neutral lipid accumulation induced by cold shock and light deprivation. By analyzing molecular evolution of 473 lipid-candidate genes, I inferred stronger purifying selection and higher rates of positive selection driving genetic divergence in the lipid-associated genes. From this, I suggest the possibility that neutral lipid accumulation is an adaptive trait in C. reinhardtii under positive selection.
An Interactive Machine Learning Approach to Integrating Physician Expertise into Delirium Prediction Model Development
Keywords: Healthcare
Machine Learning

Delirium is an acute neurocognitive disorder which affects up to half of older hospitalized patients, leading to dementia, longer hospital stays, increased health costs, and death. While delirium can be prevented and treated, it is difficult to identify and predict. Within the GEMINI study, a detailed manual review of medical records has been conducted on nearly 4000 admissions at six hospitals in the Greater Toronto Area, of which approximately 25% have been labeled as having delirium. Using the data collected from this study, we develop machine learning (ML) models with, and without, expert knowledge. By comparison, physician expertise indeed improves delirium status prediction performance and the performance is found to be stable over time. Based on the experimental findings, we further discuss the potential value of using such interactive machine learning (iML) approaches in general healthcare ML applications. Overall, this thesis provides a new perspective on developing delirium prediction models.
Functional Neuroimaging Biomarkers of Anhedonia Response to Adjunct Aripiprazole Treatment for Major Depressive Disorder
Keywords: anhedonia
aripiprazole
biomarkers
depression
neuroimaging
precision medicine

Anhedonia is a common, yet often overlooked symptom of major depressive disorder (MDD). Currently, there are no approved treatments for this symptom. Aripiprazole, an adjunct treatment for MDD, may be a potential treatment. Aripiprazole increases activity of dopamine, the main neurotransmitter implicated in anhedonia. In the current study, the effectiveness of aripiprazole for treating anhedonia, and potential resting-state functional neuroimaging biomarkers of improvement in anhedonia after aripiprazole treatment, were explored. Eighty-six participants with MDD were treated with eight-weeks of aripiprazole. Aripiprazole was associated with a significant improvement in anhedonia symptoms. Increased functional connectivity between the salience and default mode networks; and between the nucleus accumbens and brain regions implicated in neural transmission predicted improvement in anhedonia. Therefore, aripiprazole may represent an effective treatment for anhedonia as part of MDD. Further, particular functional connectivity patterns in the brain may be able to identify who will or will not respond to aripiprazole.
Graph Learning Perspective on EEG-based Human Identification
Keywords: Biometrics
Electroencephalogram
Functional connectivity
Graph Convolutional Neural Network
Graph Learning
Graph Variational Auto Encoder

EEG-based user identification is an emerging field in biometric systems. EEG signals promise more secure recognition technology than other biometric traits because EEG waves are more robust to forgery and replication. Two of the main challenges of EEG biometric systems are the sensibility to a number of electrodes and instability to different human conditions during recording. We address these two problems by considering brain regions' connections and observing EEG signals from a graph perspective.In this thesis, we explore graph learning as a new approach for extracting brain features. First, graph convolutional neural network benchmarks and their power for EEG-based identification are studied. Second, we have developed a novel graph variational auto-encoder (GVAE) for deriving EEG embeddings. This generative model learns graphs' stochastic probabilities with a low computational cost. We illustrate that GVAE features discriminate the EEG signals of different subjects with high accuracy for both small and large graphs.
Harm Reduction Ethics in Crisis (Work): The Manifestation of Spiritual Pain in the Everyday Practice of Street Outreach Work
Keywords: Collective Ethics
Harm Reduction
Organizational relations
Outreach work
Spiritual Pain

From the accounts of street outreach workers in Toronto, Ontario, this critical qualitative study reveals the disjuncture between a street outreach worker’s harm-reduction ethics and their crisis work. Semi-structured interviews were conducted with seven street outreach workers who self-identified as working from a harm reduction ethic. This study sought to situate the everyday experiences of street outreach workers who engage in crisis work within the often-invisible realm of organizational and environmental influences, such as program funding, restrictive health care policies and processes, and the criminalization of people who use drugs. Through the lens of spiritual pain and collective ethics, the findings explicate how workers come to accept, consent, and resist ethical tensions present in their practice of crisis work and create a discussion for the implications of spiritual pain on workplace sustainability. In doing so, the scholarship of workplace ethics, harm reduction, and street outreach work has been bridged.
Investigating the Role of Adipocyte YAP in Glucose Homeostasis and Adipose Tissue Fibrosis
Keywords: Adipose tissue
Fibrosis
Glucose metabolism
Insulin sensitivity
Obesity
YAP

Adipose tissue is a dynamic metabolic organ that is essential for the regulation of whole-body glucose homeostasis. Adipose tissue hypertrophy with obesity is positively associated with glucose intolerance and insulin resistance underlying type 2 diabetes. Yes-associated protein 1 (YAP) is a transcription cofactor important in the Hippo signaling pathway. However, the role of YAP in adipose tissue and glucose homeostasis is unknown. We found that YAP protein levels increase in adipose tissue with weight gain and insulin resistance. On a high-fat diet (HFD), adipocyte-specific YAP knockout mice show improved glucose tolerance compared to controls. Additionally, loss of adipocyte YAP protects against obesity-induced adipose tissue fibrosis. Together, these data indicate that YAP increases in adipose tissue with weight gain and disruption of YAP in adipocytes improves glucose tolerance and decreases the development of fibrosis; suggesting that adipocyte YAP plays an important role in modulating glucose homeostasis under metabolic stress conditions.
Construction Techniques for Lowering Embodied GHGs: A Review of Prefabrication and 3D Printed Concrete Mix Designs
Keywords: 3D printing
buildings
Greenhouse Gas emissions
life cycle assessment
prefabrication
uncertainty assessment

With ongoing global urbanization, the construction industry has been steering towards adopting automated construction techniques to enhance efficiency and quality in production with the expectation of lowering greenhouse emissions (GHGs). However, there is a limited understanding of the impacts of using these techniques on GHGs. This thesis investigates two such techniques, prefabrication and 3D printing. It assesses the embodied GHGs of prefabricated buildings and 3D printed concrete (3DPC) mixes and compares them with that of conventional counterparts. A meta-analysis of published life cycle assessment results from prefabricated buildings and a detailed analysis of published 3DPC mixes are undertaken in this research. The findings suggest more similarity in terms of embodied GHGs between prefabricated and conventional buildings than widely reported. Results also show that 3DPC mixes usually have higher emissions compared to cast-in-place concrete due to having higher cement contents, though they also have lower emissions per unit of strength.
The Psychological Consequences of Social Media Uses
Keywords: Online communities
Polarization
Social Media
Well-being

The psychological consequences of social media use have been controversial amongresearchers, partly due to the field’s reliance on global measures and cross-sectional methods. To address that, we ran two studies. In study 1, we develop a scale to measure the different functions of social media use. We ran a factor analysis and ended up with five factors for social media use. The scale was related to personality in predictable ways. In study 2, we used experience sampling to analyze the psychological consequences of Twitter use over time. We found that Twitter use was negatively related to well-being and that most of the variance was within-subjects. With the scale developed in study 1, we found that passive Twitter use was related to decreases in well-being, but active Twitter use was not. Increases in affective polarization were predicted by Twitter use, but the results were not robust.
Investigating the role of the RNA-binding protein CFIM-1 in the germline of Caenorhabditis elegans
Keywords: Alternative polyadenylation
Caenorhabditis elegans
Developmental biology
Germline
Post-transcriptional gene regulation
Transcriptomics

The gene cfim-1 encodes a subunit of the heterotetrameric CFIm complex, which is part of the broader array of core cleavage and polyadenylation (CPA) factors responsible for maturation of pre-mRNAs. In this work, I uncover a novel function for cfim-1 in the germline of Caenorhabditis elegans. Ablation of cfim-1 results in a temperature-sensitive reduction in fecundity with associated morphological changes to the organization of germ cell nuclei. Further analyses imply that the CFIm complex might inhibit recruitment of other factors required for CPA events at 3′ UTRs in a site-selective manner, suggesting a novel regulatory mechanism. In concert, these results highlight how fine-tuning of regulating cleavage and polyadenylation events is crucial in post-embryonic development.
Characterization and Cognitive Rehabilitation Research in Progressive Multiple Sclerosis (MS)
Keywords: Hippocampus
Memory
Multiple Sclerosis
Neurodegeneration
Rehabilitation
Telerehabilitation

The purpose of this thesis was two-fold: Study 1 aimed to extend known brain-behaviour relationships to the progressive multiple sclerosis (MS) population, specifically lateralization and regiospecificity with regard to hippocampus-dependent memory, and Study 2 aimed to quantitatively and qualitatively evaluate the feasibility and preliminary efficacy of a novel, online allocentric spatial navigation intervention for staving off memory decline in people with progressive MS. As expected, Study 1 found a significant positive correlation between a behavioural proxy for pattern separation and CA3 (r=0.794 p=0.003) and dentate gyrus (r=0.611 p=0.030). No compelling evidence of lateralization, nor subregion specificity for pattern completion was found (all ps > .05). Study 2 showed that the spatial navigation intervention is feasible, though with limited benefits generalizable to everyday life, warranting further investigation in a larger-scale RCT. Key limitations, implications and contributions to a growing field of research on memory impairment and cognitive rehabilitation strategies for progressive MS are discussed.
Prehabilitation Prior to Surgery: A Scoping Review and Pilot Quality Improvement Project
Keywords: Perioperative outcomes
Prehabilitation
Preoperative rehabilitation
Quality improvement
Surgery
Vascular surgery

Frailty and lack of physical fitness are risk factors for poor perioperative outcomes in vascular surgery patients and other surgical populations. Prehabilitation is a multimodal approach to improving patient fitness prior to surgery to promote better coping with the stressors of surgery. We conducted a scoping review to explore the current scope of literature regarding the effect of prehabilitation in surgical populations and to identify gaps in knowledge. We then conducted a pilot quality improvement project to improve the rate of referrals and attendance for prehabilitation prior to vascular surgery. Our review showed that there is a high degree of heterogeneity in the literature related to the effect of prehabilitation on perioperative outcomes and that future work is needed to identify the composition of an optimal prehabilitation program. Although less than our target value, the rate of referrals increased by over 30% from baseline and prehabilitation was well-received by patients.
Towards Assembly of a Multi-layered Cardiac Ventricle In Vitro using Microfabricated Elastomers
Keywords: cardiomyocyte
cardiovascular disease
engineered ventricle
left ventricle
microfabrication
tissue engineering

Despite current efforts in organ-on-chip engineering to construct miniature cardiac models, they often lack many aspects of 3D physiology of the whole heart. This motivates the development of bioartificial left ventricle models that enable mimicking the myofiber orientation of the native ventricle. We describe here an approach relying on microfabricated elastomers that enables hierarchical assembly of 2D aligned cell sheets into a functional conical left ventricle. The width of the micro-grooves was optimized to direct majority of cells towards the grove direction. The scaffold was wrapped around a central mandrel to obtain a conical-shaped left ventricle model comparable in size to a G19 human left ventricle. Cardiomyocytes within the 3D left ventricle constructs showed a high viability in all layers after 7 days of perfusion cultivation around a hollow mandrel. This model was responding to electrical stimulation by synchronous contractions and calcium transients.
Enhancing Physical Activity Discussions of Oncologists for People Living with and Beyond Cancer: Implementing a Webinar Training Module
Keywords: Cancer
Clinical practices
Physical activity promotion

Oncologists hold a unique position to facilitating physical activity (PA) behaviour change in cancer survivors as they are highly trusted. Despite improved PA participation following recommendations by oncologists, many oncologists do not regularly discuss PA with survivors. Oncologists experience low knowledge and confidence with PA discussions, thus there is a need for formal training, targeting these outcomes, to facilitate PA discussions. The purpose of this study was to assess the feasibility of a theory-based webinar for enhancing oncologists’ PA discussion practices. Oncologists and oncology residents/fellows (N=13) attended a single 35-minute or 60-minute webinar. Outcomes were assessed pre- and post- webinar. Results demonstrated the feasibility of both a 35-minute and 60-minute webinar for oncologists and oncology residents/fellows. However, there were advantages unique to the 60-minute group, with the inclusion of discussion activities, that further enhanced the webinar experience. Future interventions should target changes in PA discussion practices with formal training.
Assessing Surgical Teamwork Skills and their Relationship to Adverse Events Using OR Black Box ®
Keywords: black box
healthcare
operating room
surgery
teamwork
teamwork skills

Surgical teamwork deficiencies are associated with poor clinical outcomes, but the separate influence of individual multidisciplinary team members remains unclear. This thesis aimed to identify the teamwork skills demonstrated by surgical team members and determine if they varied during intraoperative adverse events (IAEs). Seventy laparoscopic procedures were captured using OR Black Box®. Using framework analysis, videos were coded for ‘present’ (i.e., outwardly observed) and ‘absent’ (i.e., expected but not observed) teamwork skills. Trained surgeons identified IAEs. Across four roles (nurses, anesthesiologists, surgeons, and trainees) 3539 skills were observed. While coordination was the skill most present across all roles, aspects of coordination (e.g., check-backs) were often not present when expected. During the 41 IAEs, (versus no IAE), nurses, surgeons and trainees expressed significantly more backup behaviour, conflict management and psychological safety, respectively. Understanding the separate contributions of surgical roles on intraoperative performance provides needed detail to inform targeted interventions.
Enriched Reduced Model Accelerated Level Set Topology optimization
Keywords: Cut-Cell
Finite Element Method
Level-Set
Model Order Reduction
Optimization
Topology Optimization

In this work, we develop level-set topology optimization methods accelerated by projection-based reduced-order models (ROM) constructed on the fly. We extend existing trust-region-based ROM-accelerated topology optimization methods, which are restricted to density-based topology optimization, to level-set cut finite element methods (FEMs), which provide accurate geometry representation and avoid so-called ``ersatz materials'' or ``passive elements''. One challenge to apply ROM to topology optimization based on cut FEM is that the support of the solution snapshots changes with the geometry, which makes the construction of reduced basis difficult particularly near the domain boundaries. To overcome the challenge, we introduce a family of enriched reduced models, which enrich the reduced basis using finite element basis near part or all of the boundaries. We devise various methods to specify the enrichment regions. We assess the methods using two-dimensional structural topology optimization problems. We observe that a multi-stage algorithm which adaptively selects the enrichment region considerably reduces the computational time, especially as the full order model cost increases.
Exploring Urban Residents’ Knowledge and Participation in Green Infrastructure Initiatives in Philadelphia
Keywords: Ecosystem services
Green infrastructure
Philadelphia
Public engagement
Stormwater management

Green infrastructure (GI) is an emerging concept refers to trees and vegetation that provide ecosystem services to humans. Recently, GI has been adopted in urban planning and policy because it provides a nature-based solution for storm water management and many other socio-environmental benefits. Public understanding and engagement are essential for GI development, but few studies have examined residents’ knowledge and attitudes towards GI. This research surveyed residents in Philadelphia, PA, on their understanding of GI and participation in local GI programs. Results indicate residents’ knowledge of GI is limited, and most have minimal concerns about urban flooding, the main focus of Philadelphia’s GI programs. GI program participants are not only more familiar with the concept of GI, but also are more likely to install additional GI features in the future. The thesis ends with a discussion of implicating these findings in the context of GI expansion opportunities in residential landscapes.
Office Hours: A UX investigation on How Might We Improve the Remote Office Hours Experience in Higher Education through Design Thinking
Keywords: design thinking
Digital communication
Higher Education
Office hours
remote learning
user experience design

Instructors and students in higher education experienced abrupt pedagogical changes due to the COVID-19 pandemic. Despite the breadth of new digital products available, instructors and students still experience communication challenges and dissatisfaction during remote learning. This thesis used design-thinking to prototype a digital tool that facilitates remote office hours as an extension of communication between students and instructors outside of the virtual classroom. By following design thinking, the study illustrated the insights synthesized from faculty and students’ user experience during office hours to help the reader to emphasize the challenges, needs, and goals stemming from remote learning. Meanwhile, the thesis aimed to elucidate the best practices for facilitating remote office hours to help faculty and students cultivate meaningful conversations and build a more collaborative work environment in the digital age.