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The Impact of Repetitive, Low-Dose Alpha Particle Irradiation on Cell Model Systems and in Human Populations
No full textLung cancer is the leading cause of cancer-related death in North America. It is caused overwhelmingly by inhaling carcinogens such as combustion particulates in tobacco smoke or air pollution, and/or the repetitive inhalation of radioactive radon (222Rn) gas and its decay products. Radon is a major source of alpha particle radiation exposure for humans, a type of ionizing radiation (IR) categorized as “high Linear Energy Transfer” (high-LET). High-LET radiation sources produce dense tracks of clustered DNA damage in biological tissue that are difficult for cells to repair without introducing genetic errors, leading to an accumulation of potentially cancer-causing mutations. Many buildings retain radioactive radon gas so that indoor air can contain harmfully high levels, repetitively exposing occupants to alpha particle IR emissions over many years that increases lifetime lung cancer risk. While exposure to large enough doses of high- or low-LET IR can induce cancer in anyone, some people are predisposed towards sensitivity due to their genetic ancestry. Thus, a critical question to answer for those exposed to alpha particle IR is: what is my personal risk of developing lung cancer following repetitive, low doses of alpha particles from environmental radon inhalation? It is my CENTRAL HYPOTHESIS that variations in DNA repair capacity may confer differences in tolerance to alpha particle irradiation compared to other mutagens, and that repetitive, low-dose alpha particle exposure is associated with unique accumulation and persistence of DNA double strand breaks and epigenetic alterations compared to acute exposure. To assess my hypothesis, cell fate differences following exposure to either alpha particle or gamma ray IR were measured using yeast and human cell model systems. A panel of yeast mutants altered for DNA damage response and repair pathways was used to screen for sensitivity following repetitive alpha particle radiation, with notable results further explored in the context of repair defects in human cells. I also delivered repetitive, low doses of particle radiation in primary lung fibroblast and epithelial cells in order to assess DNA damage responses that are more characteristic of this exposure versus an acutely delivered IR dose. Finally, the proportion of lung cancer cases which can be attributed to radon gas exposure was estimated using population characteristics from the most current Canadian census, relative risk of lung cancer, and radon concentration data collected through the Evict Radon National Study in combination with data from across Canada
Investigating the Role of Serrate RNA Effector Molecule (SRRT) in Driving Advanced Prostate Cancer: An In Silico and In Vitro Analysis
No full textResearch across multiple cancers implicates Serrate RNA Effector Molecule (SRRT) as a potential oncogene, with studies in glioblastoma showing that high SRRT expression reduces patient survival and promotes proliferation through mechanisms involving microRNA (miR)-6798-3p and monoacylglycerol lipase (MAGL)-mediated prostaglandin E2 (PGE2) production. In liver cancers like cholangiocarcinoma and hepatocellular carcinoma, SRRT overexpression correlates with worsened prognosis, with its knockdown leading to increased PTEN levels and reduced cell proliferation via miR-21 suppression. SRRT also facilitates proliferation in acute myeloid leukemia by modulating miR-6734-3p and in breast cancer through altered splice variants linked to metastasis, while being upregulated in HPV-positive and -negative head and neck cancers. In prostate cancer, SRRT expression is elevated compared to benign tissues and progressively increases in more severe disease subtypes, correlating with worse overall survival and associations with Erythroblast transcription specific (ETS)-related gene (ERG), tumour protein P53 (TP53), and prostate-specific antigen (PSA) levels. Additional studies found higher SRRT levels in tumour-adjacent stroma of high Gleason score prostate cancers compared to those with lower Gleason scores. In this study, high expression of SRRT in prostate cancer was correlated with adverse clinical outcomes, including significantly reduced disease-free survival and higher Gleason group classifications, indicating its role as a negative prognostic marker. Mechanistic studies validate that SRRT controls expression of ERG, a transcription factor protein that is overexpressed in prostate cancer and responsible for driving its progression. Additionally, inhibition of SRRT triggers suppression of oncogenic signaling pathways such as protein kinase B (AKT) and mitogen-activated protein (MAP) kinase, which are critical for survival and proliferation of cells. In vitro studies validate that suppression of SRRT expression triggers a significant loss of proliferative activity in prostate cancer cells. Also, knockdown of SRRT disables metastatic activity of cancer cells profoundly through inhibition of migration and invasion capabilities. Overall, these observations validate SRRT to be a key modulator of prostate cancer progression and metastasis, and its utility in acting as a therapeutic target for suppression of malignant behavior and improvement in prognosis
Characterizing Lipid-Protein Interactions and Cellular Membrane Properties Using Computational Methods
No full textBiological membranes are dynamic structures composed of lipids and proteins, acting as selective barriers in living cells. Modern research has transformed our understanding of these systems from passive barriers to active participants in cellular processes, with lipid-protein interactions emerging as critical regulators of membrane properties and cellular signaling pathways. Molecular dynamics simulations offer powerful tools for studying these complex systems at the molecular level. During my PhD, I leveraged Martini coarse-grained models for large-scale simulations of biomembranes over extended timescales. First, we characterized lipid distribution patterns around structurally diverse membrane embeddings in asymmetric bilayers, revealing how lipid distribution is influenced by protein geometry and surface properties. Building on these insights, we developed a comprehensive cardiomyocyte sarcolemma model with ten vital membrane proteins each embedded in physiologically relevant lipid compositions. We identified unique lipid signatures around each protein, stable interactions between anionic lipids and protein domains, while also mapping novel cholesterol and diacylglycerol distribution patterns. Next, we incorporated endocannabinoids into our membrane models to investigate their effects on Kir2.1 potassium channels. Combining computational and experimental methods, we demonstrated that endocannabinoids alter channel conductance by modifying membrane physical properties rather than through direct binding. Finally, we examined how different lipid environments affect the yeast transcription factor Mga2. The results showed that Mga2 senses lipid packing and responds to edelfosine, a lysoPC analog. Deep learning predicted Mga2 conformations solely from lipid distributions, highlighting lipid fingerprints' predictive power. These findings advance membrane biology understanding and suggest new avenues for drug discovery and therapies targeting membrane processes
Exploring Simplicity Limits in Electrical Distribution Systems Modeling for Voltage Sensitivity Estimation
No full textAccurate real-time estimation of load voltage sensitivity is critical in distribution systems for understanding load behavior and maintaining system operational efficiency and reliability. However, existing estimation techniques are computationally intensive and/or depend on high network observability with extensive measurement requirements. These requirements make state-of-the-art less practical for real-world online applications, where computational bandwidth and system observability are often limited. Despite a large body of prior art, there is next to no precedent in exploring the limits of effective minimalism in the voltage sensitivity estimation framework, i.e., under what assumptions and operational conditions a simple radial model may be adequate to reflect the voltage sensitivity behavior of electrical distribution systems. Thus, this thesis evaluates the adequacy of a simplified feeder model consisting of a short line feeding an aggregated exponential load in capturing the nuances of voltage sensitivity. This radial feeder is used as a surrogate physics-informed system and is modeled in both the time- and phasor-domains. The models are validated against PSCAD, a widely adopted high-fidelity time-domain simulation platform. The verified surrogate network is used in a data-driven process to estimate the aggregated load voltage sensitivity and feeder parameters using only voltage and current measurements at the head of the feeder. The estimation process leverages Optuna, a state-of-the-art parameter tuning framework, to minimize the error between measured and modeled responses. The accuracy of the estimated parameters and the generalizability of the proposed models are evaluated through a range of system configurations and disturbance scenarios, using synchrowaveform data generated from simulation as well as measured in the field. In addition to estimating parameters, the study assesses the models' ability to predict system response to future disturbances, thereby exploring the temporal transferability of the estimated parameters. A detailed comparison between the time-domain and phasor-domain models is conducted to highlight performance trade-offs, particularly in scenarios involving different voltage disturbances. Results demonstrate the practical feasibility of the proposed approach for real-time application in low-observability environments
Proglacial Retrogressive Thaw Slumping in the Scott Turnerbreen Forefield, Svalbard
No full textThe Arctic is currently experiencing warming at a higher rate than the global average, which has led to rapid changes within the cryosphere, including glacial retreat and permafrost thaw. These climate-driven alterations are reshaping proglacial environments, with the thaw of ice-cored moraines in particular accelerating landscape evolution through retrogressive thaw slumps (RTS). Although topographical changes caused by thawing ice-cored moraines have been studied in the Arctic, there is a notable lack of studies on this topic using high-temporal UAV data during a single thaw season to assess the intra-seasonal changes. In this study, we present an analysis of RTS progression by quantifying the magnitude of change, identifying its primary drivers, and assessing whether similar processes are occurring elsewhere. A UAV was used to derive models of two glacial forefields in central Svalbard, Scott Turnerbreen (STB) and Longyearbreen (LYB), where six aerial photogrammetric surveys were flown over the course of three weeks, providing a high temporal resolution for three specific RTSs (STB1, STB2, and STB3) and the forefields themselves. Previous UAV imagery captured in 2018 allowed for a greater range of temporal frequencies. Furthermore, using Ground Penetrating Radar (GPR), sites that exhibited movement, as observed in the aerial surveys, were surveyed to determine if the cause of activity could be directly correlated with the melting of massive ice. The photogrammetric surveys conducted in July 2024 revealed that the STB RTSs underwent significant change due to massive ice melt, resulting in almost 2,000 m3 of growth. Additionally, since 2018, the Scott Turnerbreen forefield experienced a net volumetric loss of ~189,530 m³, with one-ninth (22,011 ± 2,909 m³) of that volumetric change attributed to the three RTSs observed in this study. During the same period, about two-thirds (55,448 ± 6,159 m³) of the change in LYB volume was caused by RTS activity, indicating that similar issues are occurring outside of STB. This study offers an examination of thaw slump activity and headwall erosion in two glacial forefields, utilizing both remote sensing and geophysical techniques to observe surface and subsurface mechanics of RTS growth at high spatial and temporal resolution
Postsecondary Business Mathematics Students’ Motivation to Learn in an e-Learning Environment
No full textThis study aimed to identify the potential relationships between the perceptions of first-year business students’ experiences in an asynchronous online business mathematics course and their intrinsic motivation. Intrinsic motivation was primarily
understood through the lens of Self-Determination Theory (SDT), focusing on the psychological needs of autonomy, competence, and relatedness, and students’ perspectives on instructional strategies supporting these needs. The research utilized an exploratory case study methodology to uncover the psychological needs of post-secondary business students and the instructional strategies that are needed to support them. The participants in the study are 19 students from various first-year postsecondary business mathematics courses. Data was collected through surveys, in addition to three participants completing journaling activities, and one participant completing an interview. The collected data was analyzed with a focus on the students' psychological needs. The instructional strategies identified from the data analysis were specifically tailored to support the psychological needs discovered among the study participants. The findings of the study suggested there is an underlying cultural factor that could influence the participants’ participation and intrinsic motivation. Furthermore, the findings indicated that the participants’ psychological needs do affect their intrinsic motivation to learn. Finally, the findings suggest that there are instructional strategies that instructors can use to support their students’ psychological needs
Modelling Stroke at a Miniature Scale: A Novel Framework Targeting Mitochondria
No full textStroke remains a leading cause of disability and death worldwide, with ischemic stroke accounting for most of these cases (Kirichok et al., 2004). Despite extensive research, effective treatment options remain limited for many individuals who have experienced an ischemic stroke (Bathla et al., 2023). One potential factor hampering the discovery of new pharmaceutical interventions for ischemic stroke is the lack of ischemic stroke models that simultaneously provide real-time analysis of cellular processes and a scalable platform suitable for high-throughput experiments. To address this gap, this thesis utilizes new tools in cellular biology, such as Mito-Photo-DNP—a mitochondria-targeting, photo-activated proton shuttle—to model ischemic stroke on a miniature scale. Mitochondria dysfunction plays a central role in ischemic stroke pathology and is the aspect this thesis attempts to mimic (Jia et al., 2021). Upon UV stimulation, Mito-Photo-DNP disrupts the mitochondrial membrane potential (Δψm), which is key for cellular energy production and maintaining calcium homeostasis (Disha et al., 2024). This Mito-Photo-DNP induced mitochondrial dysfunction and ischemic stroke both cause bioenergetic failure, increased production of reactive oxygen molecules, calcium dysregulation, and if severe enough, cell death (Chalmers et al., 2012; Kirichok et al., 2004). Combining Mito-Photo-DNP photo-activation with primary neuronal cultures creates a miniature stroke model, offering a previously unattainable spatiotemporal resolution for investigating the molecular mechanisms underlying stroke pathophysiology. Furthermore, its suitability for high-throughput experiments positions it as a valuable tool for screening potential candidate drugs for their ability to improve cell viability and growth
The Impact of Proximity to Care on Outcomes in Pituitary Adenoma Surgery
No full textBackground: Pituitary adenomas are common neoplasms, representing 10-25% of intracranial tumors. Although typically benign, they can cause disabling visual deficit and endocrinopathies which can result in serious systemic abnormalities. Care for patients with pituitary adenoma requires a complex multidisciplinary team which can be challenging to coordinate, especially for patients who live rurally with challenging access to tertiary care services. Aims: We aimed to assess whether proximity to a tertiary care centre in Calgary, Alberta (Foothills Medical Centre (FMC)), impacts the quality of life and surgical outcomes of patients with pituitary adenomas in Southern Alberta, after adjusting for confounding variables. Methods: This was a combined retrospective and prospective cohort study utilizing a consecutive database of patients with pituitary adenoma treated surgically at FMC between June 2012- June 2022. The primary exposure variable was geographic proximity to tertiary care, defined as urban or rural based on patient postal code. The primary outcome was prospectively collected health-related quality of life (HRQOL), measured through the EQ-5D-5L utility score in all patients, and disease-specific HRQOL questionnaires. Secondary outcomes were post-operative complications including cerebrospinal fluid leak, post-operative hemorrhage, diabetes insipidus and adrenal insufficiency. Multivariable linear regression was performed to assess the relationship between living location and EQ-5D-5L utility score. Results: 175 patients were consented and interviewed and represented all adenoma subtypes (98 nonfunctioning, 40 acromegaly, 26 Cushing disease, 9 prolactinoma, 2 thyrotrophinoma). The mean EQ-5D-5L utility score for the cohort was 0.82 (95% CI: 0.80-0.84), and there was a statistically significant difference between the mean utility score of nonfunctioning adenoma patients (0.85, 95% CI: 0.82-0.88) and Cushing disease patients (0.75, 95% CI: 0.70-0.81) (p=0.02). Adenoma size (p=0.05) and adenoma subtype (p=0.01) were significantly associated with EQ-5D-5L utility score in univariate analysis. In multivariable analysis, EQ-5D-5L utility was not significantly associated with geographic living location after adjusting for relevant confounding variables (p=0.87). Conclusion: In a single-centre sample from the Canadian healthcare system, rural versus urban living location was not associated with worse HRQOL following pituitary adenoma surgery after adjusting for relevant confounding variables. Further research is needed to understand whether this finding is unique to the Canadian healthcare system and persists across Canada
Three Essays on the Economics of Immigration
No full textIn the first chapter, I examine how growing up in neighbourhoods with large immigrant populations influences the future labour market outcomes of immigrant children. Estimating these effects is challenging due to endogenous spatial sorting of immigrants and unobserved confounding factors. To address these challenges, I propose a novel identification strategy that combines between-siblings analysis with a shift-share instrument. This approach compares the outcomes of immigrant siblings who experienced different shares of immigrants in their childhood neighbourhoods, where the actual share is predicted by the interaction between the past spatial distribution of immigrants and the current national immigrant inflows. Using administrative data from Canada, I find that a one-percentage-point increase in the average share of immigrants in childhood neighbourhoods reduces the adult income rank of immigrant children by 0.8 percentile points. The negative impact is driven by increased residential segregation between natives and immigrants and the declining income of their childhood neighbours. Further evidence suggests that these locational changes may impede immigrant children’s development of social networks and unobservable skills, thereby reducing their likelihood of attaining high-paying jobs. In the second chapter, I study how exposure to conflict affects the long-term labour market outcomes of refugees in Canada. Using administrative data alongside global conflict data, I find that conflict exposure during adolescence significantly reduces employment in adulthood by 3.3 to 3.6 percentage points and annual earnings by 2,000 to 2,200 Canadian dollars. The negative effects persist across the life cycle, from the mid-20s through the early 50s. Further heterogeneity analysis reveals a larger negative impact on women and on refugees with relatively low educational attainment at the time of resettlement. In the third chapter, I study a Canadian policy reform that relaxed post-graduation work restrictions for international students. Using administrative data, I analyze the labour market outcomes of native graduates in response to the reform. I find that regions with a history of greater exposure to international graduates experienced a more substantial influx of international graduates after the reform. Using the uneven regional effects, I document that more international graduates prolonged the job search and lowered the earnings among native graduates
Beyond the Surface: Navigating Students’ Identities through the ABC’s Model
No full textIn our contemporary multicultural society, Canadian schools face the complexities presented by a diverse immigrant demographic. Traditional ways of teaching often made multilingual students, either newcomers or second-generation immigrants, feel left out, which made it hard for them to grow academically and develop their sense of self. To address this, educators are increasingly turning to culturally responsive pedagogies that celebrate and affirm diverse cultural backgrounds. This research introduced an intervention designed for sixth-grade students, with the objective of fostering self-awareness, celebrating diversity, and promoting identity exploration through narrative and multimodal approaches. While the project was conducted in a regular classroom setting with the involvement of all students, the primary emphasis was on students from diverse backgrounds, including newcomers to the country categorized as English Language Learners (ELLs) and second-generation immigrants. The study was guided by Ruggiano Schmidt's ABC’s model of cultural understanding and communication (1998), which stands for autobiography (A), biography (B), and cross-cultural comparison (C), to evaluate its influence on the development of personal identity. The aim was to cultivate a classroom environment that welcomes diversity and nurtures a sense of belonging. This study explored two research questions: (a) How does the ABC’s model support Grade 6 students from diverse backgrounds, including newcomers or children of immigrant families, in navigating students’ personal identities? (b) What are the affordances of a multimodal approach to exploring students’ personal identities? Employing an action research approach, I collaborated with a sixth-grade teacher to co-design a multimodal ABC’s project for implementation in the classroom. After the implementation phase concluded, I analyzed and reflected upon my observations and students’ final products. The findings were discussed based on the theoretical framework that guided the study: critical literacy and sociocultural perspectives. These theories emphasize that learning happens through conversation in a social setting and that literacy is deeply connected to culture, an understanding that was evident throughout the project. Students reflected on personal experiences such as language, names, special places, childhood stories, and important people in their lives. This reflection enabled them to value their personal identities and recognize the significance of their cultural and linguistic backgrounds. Through collaborative dialogue and peer interactions, students found meaningful connections across differences. They came to understand that they do not need to conform to the dominant culture to feel a sense of belonging; rather, their true selves are appreciated and valued. The ABC’s model offered students a framework for understanding both themselves and others, contributing to stronger interpersonal connections and a more inclusive classroom culture. Ultimately, this project demonstrated how culturally responsive, multimodal pedagogies can empower students, promote mutual respect, and foster lasting bonds among classmates