- ItemOpen AccessInvestigating the Sexual Dimorphism of Disease Tolerance in Sepsis(2023-12-04) Dobson, Breenna; McDonald, Braedon; Jenne, Craig; Nasser, YasminSepsis is a dysregulated immune response to infection, with mortality rates as high as 30%, however, there are currently no disease-modifying treatments for this disease. One of the reasons why preclinical sepsis discoveries have failed to translate into effective human therapies is that interindividual heterogeneity has historically been neglected in preclinical sepsis research, including the fundamental contributions of biological sex on disease pathogenesis and treatment response. Epidemiologic studies have observed that males have a higher incidence, severity and mortality rate than females in sepsis, however, the mechanisms underlying this bias have not yet been established. This thesis aims to examine potential underlying mediators of the sexual dimorphism within sepsis illness severity. We investigated the impact of biological sex on host defence using a well-established mouse model of sepsis induced by fecal peritonitis. We used this model to study three principal mediators of sex- based immune response differences: the gut microbiota, sex chromosomes and sex hormones. To uncover differences in these mediators we used a transgenic and germ-free mouse model. Further, we aimed to understand the sex-based influence on infection tolerance and resistance. Lastly, we completed preliminary studies on sex-based differences in infection tolerance using a tetracycline antibiotic as a potentiator of mitochondrial tolerance. This project addressed a critical gap within sepsis research and revealed biological sex differences in infection tolerance and potential therapeutic implications.
- ItemOpen AccessUtilizing Statistical and Machine Learning Techniques to Improve Tools Identifying Genetic Basis Underlying Complex Traits(2023-12-05) Bian, Jiayi; Wu, Jingjing; Long, Quan; de Koning, Jason; Chekouo Tekougang, Thierry; Lu, Xuewen; Bureau, AlexandreIn genetic studies, understanding the genetic basis underlying complex traits takes center stage. Modern high-throughput technologies have empowered researchers to generate large amounts of multi-scale omics data that bridge the gap between genotype and phenotype. With the availability of omics data, researchers have successfully identified genetic variants and genes underlying complex traits using genome-wide association studies (GWAS) and other association mapping methods using omics data as mediators, e.g., transcriptome-wide association studies (TWAS). To provide better statistical tools unraveling the genetic basis of complex traits, I have developed three statistical methods: AE-TWAS, edLMM, and Kernel-smoothed permutation, respectively focusing on three stages of association mapping, namely input data denoising, statistical test to detect low-effect variants, and non-parametric generation of small P-values. My first project delves into the limitations of TWAS from the perspective of transcriptomic data denoising by transformation. I introduced AE-TWAS (AutoEncoder-transformed TWAS), which incorporates autoencoder-transformed transcriptome data into a standard TWAS protocol. We showed that AE-TWAS boosts the heritability of low-heritability genes in transcriptomic data and the transformed transcriptome leads to better performance of TWAS. In my second project, I introduced edLMM (expression- directed Linear Mixed Model) that incorporates weights derived from transcriptomic data in a linear mixed model (LMM). These weights provide an alternative estimate of the null hypothesis in an LMM by re-scaling the genetic relationship matrix (GRM). Through real data analysis and simulation studies, we demonstrated that edLMM is more powerful than the benchmark LMM method in GWAS (i.e., EMMAX), especially in its capacity to enhance the identification of genetic variants with low effects. My third project focused on the challenge of accurately estimating small p-values in genetic association studies using permutations when the closed-form distribution of test statistics is unknown. Specifically, I developed Kernel-smoothed permutation, a method that constructs the null distribution of a test statistic through a novel kurtosis-driven Box-Cox transformation, followed by a kernel- based density estimation (KDE). We demonstrated that our approach requires a magnitude of lower rounds of permutations than the conventional Na ̈ıve permutation. Taking together, my thesis contributed meaningful additions to the toolbox of association mapping from three abovementioned aspects, enhancing our ability to identify the genetic basis of complex traits in the cases of low expression heritability genes, low effect-size genetic variants, and low numbers of sampled permutations. These works push the boundary of association mapping to the corners that may be missed by using conventional tools.
- ItemOpen AccessDirectly Deposited Solid Polymer Electrolyte for Enhanced Electrochemical Carbon Conversion(2023-12-05) Adnan, Muflih Arisa; Kibria, Md Golam; Gates, Ian Donald; Mahinpey, Nader; Trudel, Simon; Guay, DanielIt has become evident in recent years that we need to accelerate our transition to a net-zero future. The dwindling price of low-carbon renewable electricity has been an enabler to develop technologies that relies on low-carbon electrons. Electrochemical carbon conversion (i.e., CO2 electroreduction i.e., CO2R or CO electroreduction i.e., COR) is one of such emerging technologies that allows converting CO2 or CO into various chemical and fuel using low-carbon electricity and water. I begin this thesis with a comprehensive technoeconomic and life cycle analysis for the production of methanol using electrochemical route and the conventional one. This study showed that under current market conditions, the levelized cost of methanol from electrolysis routes is 2 to 4 folds higher than the market price due to the low performance of electrochemical CO2 conversion to methanol. I showed that to achieve market competitiveness, some key performance metrics has to be achieved for the CO2R approach, including energy efficiency >40%, stability >8000 hours, and current density >130 mA/cm2 (CO2-to-CH3OH) or >360 mA/cm2 (CO2-to-CO). I then performed experimental analysis to investigate the key challenges in CO2R using membrane electrode assembly (MEA). The key challenge on CO2R comes from the competing carbonate formation reaction in the cathode which directly depletes the CO2 utilization for CO2R. Furthermore, the carbonate crosses over to the anodes when using the anion exchange membrane (AEM). Alternatively, cation exchange membrane (CEM) or bipolar membrane (BPM) can suppress carbonate crossover. However, CEM or BPM leads to either cation crossover and excessive water transport (promotes salt formation) or proton flooding (promotes Hydrogen Evolution Reaction (HER)) to the cathode, respectively. To overcome the challenge in commercial pre-made standalone AEM and CEM, I developed a direct membrane deposition approach using a simple spray-based coating approach. This direct deposition approach eliminates the need for a pre-made standalone membrane and offer improved stability of the catalyst and cathode. Using this patent-pending approach, I then designed a thin (~3 μm as opposed to over 50 μm commercial membrane) cation infused solid polymer electrolyte (CISPE) which enables bidirectional ion transport mechanism. The use of thin CISPE substitutes the use of standalone membrane and consequently suppresses salt formation and cathode flooding. I found that this approach enables high full cell energy efficiency of 28% at 100 mA/cm2 for one step CO2R to C2H4, which results in a record low overall energy cost (i.e., CO2 capture, electrolysis, CO2 separation and carbonate regeneration) for C2H4 production of 290 GJ per ton C2H4. The use of CISPE also allowed 160 hours of stable operation for continuous production of C2H4. While the direct CO2 electrolysis to C2+ products require further development due to carbonate formation, a CO2-to-carbon monoxide (CO) electrolysis has been commercially deployed. Taking advantage of the high technology maturity of CO2-to-CO electrolysis, I investigated the possibility of CO electrolysis (COR) as an intermediate step for converting CO2 into hydrocarbon. While the salt formation issue is absent in COR, the cation crossover still hinders the COR selectivity as it diminishes the CO availability at the cathode surface. To suppress the cation crossover via both electromigration and water diffusion (diffusion of hydrated cation), I implemented and optimized the direct deposition of a thin (~0.7 μm) CISPE on the surface of the Cu cathode catalyst. This thin CISPE suppressed K+ transport to the cathode, which led to improved CO availability and partial current density to ethylene. This approach enables stable operation at 100 mA/cm2 for over 200 hours with an energy efficiency toward C2H4 of 21%, which can be translated into an overall energy consumption of 218 GJ per ton C2H4. I also reported a high energy efficiency toward ethanol (C2H5OH) production of 17%. Another reason for the low CO availability is the low solubility of CO in the aqueous electrolytes. Then, I carried out a theoretical investigation of CO mass transport at different temperatures. I found that low operating temperature facilitates high CO availability on the catalyst surface due to high CO solubility and less cathode flooding which enhances the current density toward COR product. From the experimental studies on COR at different temperatures (10 to 50oC), I observed that the low-temperature (10oC) COR enables high partial current density towards the C2+ products (657 mA/cm2). The combination of CuNP and NiFe layered double hydroxide (LDH) anode showed excellent Faradaic efficiency of ~87% at 450 mA/cm2 towards C2+ products with a CO single pass conversion of ~90% for 150 hours of stable operation. From the brief technoeconomic analysis, I found that the pressurized electrolysis system (e.g., 10 atm) requires 2.4 folds higher capital cost and 1.5 higher operating cost than the ambient pressure electrolysis cell at low temperature (e.g., 10oC). I concluded this thesis with key findings and recommended future works to address the remaining challenges in electrochemical carbon conversion, including carbonate cross-over, stability etc. Successful demonstration of this technology will enable electrification of chemical industries to produce sustainable chemicals and fuels.
- ItemOpen AccessCapacitance-Resistance Model Connectivity Evaluation Based on Empirical and Heat Transfer Analogy Approaches in Conventional and Heavy Oil Waterfloods(2023-12-05) Morales German, Gabriela; Johnston, Kimberly Adriane; Hejazi, Hossein; Jonhston, Kimberly Adriane; Hejazi, Hossein; Gates, Ian Donald; Jensen, Jerry Lee; Clarkson, Christopher; Camacho-Velazquez, RodolfoInter-well connectivity (IWC) is a key factor for the successful design and operation of waterflooding projects. Thus, connectivity estimation methods such as the Capacitance-Resistance Model (CRM) are continually being improved and developed. The CRM utilizes the injection and production data as input to quantify IWC information through a connectivity parameter (λ). Proposed in 2006, the CRM has been adapted several times to better perform in challenging exploitation projects such as heavy oil waterflooding. Nonetheless, CRM analysis in heavy oil reservoirs yields highly variable λ values during early times. Such a variation and inconsistency make it difficult to readily determine IWC. This research work proposes two novel approaches to improve the CRM analysis by evaluating the uncertainty in the IWC estimates, especially at the early production stage. In the first approach, data generated from reservoir simulations provide input for the CRM to estimate IWC for each injection-production well pair. The objective is to define an equation relating production data and λ behavior patterns for different high mobility ratio cases. The proposed formulation yields acceptable IWC results in homogeneous reservoir cases and provides insight into heterogeneous reservoir evaluations. For the second approach, the analogous behavior of heat conduction and pressure transients is used to complement the CRM analysis. Previous studies suggest that, besides inter-well distance (IWD), IWC estimation might be influenced by injection rate frequency (ω_a) and medium hydraulic diffusivity (D). Sensitivities of those parameters were carried out to determine their effect on IWC. As a result, applying the periodic line source solution (PLSS) for heat conduction, ω_a, D and IWD can all be considered for IWC estimation, and their effects quantified. The PLSS analysis also offered an improvement on a previously proposed method to estimate CRM connectivity prediction errors. The modification includes the effects of ω_a and IWD to provide a better error predictor. A field-case example of the modified method shows the impact of IWD and ω_a in the deviation of CRM- λs. A relevant benefit of this method is its applicability to a wide range of reservoir conditions and fluid types, at any field development stage.
- ItemOpen AccessFraming Policing Image and Reputation: Police Engagement with Social Media as a Tool to Employ Impression Management Tactics(2023-11-10) Dewar, Adriana Lucia; Adorjan, Michael; Van Brunschot, Erin; Mather, CharlesHistorically, policing agencies have had a great deal of control over the information released about them. Prior to social media, information was disseminated through media channels such as newspaper articles or press conferences. This allowed for the information to be carefully tailored to highlight only the positive aspects of police behaviour, which directly benefitted them. Alternatively, police used these channels to regulate the information being presented to the public to maintain the position of gatekeeper of influential information. Social media and instant technologically mediated communications offer profound novel opportunities for police to communicate with the public, but also new risks, such as, losing public confidence, legitimacy, and issues of animosity. This study utilized qualitative methods to capture how police agencies employ social media as a means to engage in impression management tactics to influence the public’s perception. In addition, the study analyzed the public’s attitudes and beliefs about the police and their views on policing as a profession through the type of interactions occurring online. The qualitative data was gathered through in-depth interviews with the communications personnel and current police officers from a police agency in Western Canada. In conjunction with the in-depth interviews, an ethnographic content analysis was performed on the social media accounts (Instagram, Twitter, and TikTok) of police agencies in Vancouver, Calgary, Edmonton, Regina, and Winnipeg. This research uncovered the impression management tactics being used to influence the public’s perception of the police. In addition, this research illuminated points of contention between the police and civilians, as well as methods for increasing positive interactions on various social networking platforms.