VictorJuiz/thesis huggingface dataset:
Supercritical Fluid Extraction of Critical Metals from Postconsumer Products: Process Development and Mechanistic Investigation

With the growing awareness to protect the urban environment, the use of green technologies has been widely promoted. These technologies rely upon strategic materials, such as rare earth elements (REEs), lithium, and Cobalt. They are essential in use and subject to supply risk. For building a more sustainable future and enabling the circular economy (make, use, recover), waste valorization and recycling of end-of-life products is imperative.Conventional recycling processes are based on pyrometallurgy or hydrometallurgy. The former is energy intensive, generating greenhouse gas emissions, while the latter relies on large volumes of acids and organic solvents; thus, generating hazardous wastes. There is a need for an environmentally sustainable and efficient process to enable green urban mining of secondary resources. Supercritical fluid extraction (SCFE) is a potential green alternative to convention processes because of the desirable properties of supercritical fluids as solvents. The SCFE is an emerging technology in the field of recycling of metals. There is a limited number of studies that investigated SCFE using end-of-life products as feed materials. The mechanism of SCFE and impacts of adding co-solvents and adducts to supercritical fluid are unclear. The SCFE involves multiple variables, which require a systematic approach for optimization. The main objective of this PhD project is to develop the SCFE process to recover strategic metals from end-of-life products. The first thrust focused on the recovery of rare earth elements (REEs) from neodymium iron boron (NdFeB) magnets and waste fluorescent lamp phosphors using SCFE. The second thrust focused on investigating the effect of organophosphorus ligand on the extraction of REEs from waste NdFeB magnets using SCFE. The third thrust focused on recovering lithium, cobalt, nickel, and manganese from waste lithium-ion battery using SCFE. The fourth thrust focused on elucidating the mechanism governing the complexation process during SCFE, focusing on elucidating the coordination environment of metal upon SCFE using X-ray absorption spectroscopy in collaboration with the Canadian Light Source. The fifth thrust focused on the techonoeconomic assessment of the SCFE process for the recovery of strategic materials from end-of-life products. Each thrust has led (or will lead) to a journal publication.

Advisor: Azimi, Gisele
Organizing Principles of Regulatory Elements and TF Binding Models

Mammalian genomes contain millions of putative regulatory sequences, which are delineated by the binding of multiple transcription factors (TFs). A major question in regulatory element biology is how TFs collaborate to encode cell-specific activity of cis-regulatory DNA. Genomics approaches have given rise to various theories about the organizing principles of individual regulatory elements. The enhanceosome model posits that an individual regulatory element is defined by a combination of TFs that adhere to strict spacing and orientation constraints (SAOCs). In contrast, the billboard model suggests that regulatory DNA has (at best) soft SOACs, and individual TF binding sites are subject to a high rate of 'turnover' during evolution. My thesis work aims to explore two major issues around this topic: First, while various lines of genomic evidence have been used to compel each of these models, a systematic evaluation of how well each model explains the global sequence and biophysical properties of regulatory elements has been lacking. Therefore, I evaluated whether four different regulatory element models incorporating different degrees of SAOC among transcription factor binding sites were broadly consistent with five different global properties of regulatory sequence (length, uniqueness, frequency, turnover, and role of master regulators). Based on my analysis, I conclude that models of transcription factor binding with or without spacing and orientation constraints predict that regulatory sequences should be fundamentally short, unique, and turn over rapidly. Additionally, my analysis suggested that the existence of master regulators may be, in part, a consequence of evolutionary pressure to limit the complexity and increase evolvability of regulatory sites. Second, in order to thoroughly explore multiple TF binding and the regulatory code, I assisted in the identification of binding motifs for the remaining TFs that lack motifs. I systematically compared traditional position weight matrix models of TF specificity to more complex k-mer based approaches like gapped-kmer support vector machine (gkmSVM) both within and across Chip-Seq and HT-SELEX datasets. I discovered that gkmSVM outperforms PWMs in predicting HT-SELEX and Chip-Seq data for almost all TFs tested, suggesting that TF binding may be influenced by flanking sequences and dinucleotide interdependency that are not accounted for by a PWM model. Additionally, I find that cross-comparing models across datasets is critical for identifying systematic biases in these datasets and flagging uninformative experiments. Overall, my research will contribute greatly to our understanding of the regulatory element code and will aid in the understanding of multiple TF binding and individual TF binding.

Advisor: Hughes, Tim Dr.
Strategies to Align DIA Proteomics Runs Across Multiple LC-MS/MS Setups

Data Independent Acquisition Mass Spectrometry (DIA-MS) is a widely used for proteomics approach given its high-throughput and reproducibility; but ensuring consistent quantification of analytes across large-scale studies of heterogeneous samples such as human plasma remains challenging. Heterogeneity in large-scale studies can be caused by several factors, such as large time intervals between data-acquisition, acquisition by multiple instruments, and normal aging or replacement of parts, such as the liquid chromatography column, all of which affect retention time (RT) reproducibility and, successively, the performance of downstream statistical analyses. Here, I present a novel algorithm, implemented in the DIAlignR package, for RT alignment of DIA-MS runs based on direct alignment of raw MS2 chromatograms using a hybrid dynamic programming approach. The algorithm provides a high alignment resolution which assists in peak-selection in crowded MS2 chromatograms. In addition, it does not impose a chronological order of elution allowing alignment of elution-order-swapped peaks. Furthermore, constraining RT mapping in a certain window around a coarse global fit makes it robust against noise. Successively, the pairwise alignment is extended to multiple runs using both reference-based Star, and reference-free minimum spanning tree (MST) and Progressive alignment approaches. On a gold standard annotated dataset, DIAlignR achieves a threefold reduction in the peak identification error-rate when compared to standard non-aligned DIA results. A similar improvement is achieved from aligning runs acquired at 11 different sites when compared against the current state-of-the-art method, TRIC. Next, on real-world clinical data, the proposed approach outperforms TRIC, mapping 98% of peaks compared with 67% cumulatively. Additionally, DIAlignR reduces alignment error up to 30-fold for extremely distant runs. Finally, when analyzing the 949 plasma runs from a prediabetic cohort, the use of DIAlignR resulted in an increase of 57% and 62% in the number of statistically significant proteins for insulin resistance and respiratory viral infection, respectively, compared to prior analysis without alignment. Hence, DIAlignR fills a gap in analyzing DIA runs acquired in-parallel using different LC-MS/MS instrumentations. The alignment algorithm is freely available at https://github.com/Roestlab/DIAlignR.

Keywords: Data Independent Acquisition
Proteomics
Retention Time Alignment
Advisor: Röst, Hannes
Solitude and Postbellum Literary Culture: Elizabeth Stoddard, William Dean Howells, and Henry Adams

This dissertation tells a new story about the role of solitude in late-nineteenth-century American culture. The figure of the solitary individual informed the consolidation of liberalism and the rise of literary romanticism in the decades leading up to the Civil War. Louis Hartz has famously argued that liberalism came to define America’s “way of life,” while F.O. Matthiessen and Richard Chase have claimed that American literature is effectively romantic. Despite solitude’s importance to American political and aesthetic thought, however, the role of isolation in American culture is under-studied outside the contexts of antebellum romanticism and the existential alienation associated with modernism. My study asks, what happens to discourses of solitude between romanticism and modernism, that is, in “the Age of Realism”? Accordingly, I examine solitude in postbellum literature, exploring how beliefs about the transformative power of solitude change under the pressures of an increasingly industrialized and mechanized society. I argue that solitude becomes an important discourse through which many late-nineteenth-century writers questioned their political assumptions and navigated the meaning of declining republican political values. The authors I consider, Elizabeth Stoddard, William Dean Howells, and Henry Adams, confronted the limitations of liberalism to grapple with a progressively unequal society, and they expressed these limits in often-contradictory celebrations and critiques of solitude. My study reveals an impasse shared by these writers regarding the value of solitude. For them, neither republican, classical liberal, nor romantic valuations of solitude fully survive America’s transition into an industrial modernity. But neither are these outlooks entirely surrendered. My readings of Stoddard, Howells, and Adams disclose an emerging American modernity still partially shaped by powerful inherited discourses of solitude reflecting romantic ideals that prove inadequate to new social and economic conditions. Postbellum realism tries but fails to escape a romantic bind in which these authors’ adherence to discourses of solitude appears to produce the very social and political problems of economic marginalization, inequality, and alienation that they sought to avoid. Complicating critical narratives in which realism develops in reaction to romanticism, this project demonstrates that romantic ideals of solitude shaped realism into the early twentieth century.

Keywords: Liberalism
nineteenth century
Realism
Romance
Solitude
Advisor: Dolan, Neal
Carbonyl Functional Groups in Reaction Development: Carbonylative Cross-Coupling, α-Hydrazination, and C-C Cleavage

The carbonyl motif (C=O) is embedded in various abundant functional groups such as carboxylic acids, ketones, aldehydes, and many more. The reactivity of the carbonyl group has contributed to several milestones in organic synthesis in the past century including the discovery of solid-phase peptide synthesis, carbonylation reactions, and most recently, in organocatalysis. Development of new synthetic methodologies is vital in advancing the field of organic synthesis and expanding our toolbox as synthetic chemists in order to create novel molecular scaffolds. This thesis describes my efforts in developing methodologies in carbonylative cross-coupling and α-hydrazination utilizing boron-containing carbonylated building blocks originating from the Yudin lab. In addition, a novel transformation that combines the concepts of C-C bond cleavage and strained ring synthesis is presented. Chapter 1 provides a brief overview on the carbonyl motif including the synthesis and various transformations that are pertinent to this thesis. Chapter 2 describes the use of carboxy-MIDA-boronate (MIDA = N-methyliminodiacetic acid) as an efficient in situ CO surrogate in the Pd-catalyzed carbonylative cross-coupling reactions to afford amides, esters, ynones, and biaryl ketones. NMR kinetic studies reveal the base catalyzed nature in the decomposition of carboxyboronate under relevant cross-coupling conditions. Chapter 3 outlines the synthesis of α-boryl-α-hydrazinoacetic acid. Subsequent transformations to boromethylated N-heterocycles, and other α-boryl-α-hydrazino scaffolds were achieved. In addition, efforts towards effecting the oxidative rearrangement of the BMIDA scaffold is described, and two rearranged molecules containing the α-aminoboron connectivity are reported. Chapter 4 contains work on the C-C cleavage-enabled ring-closure of β-hydroxy oximes to amido-epoxynitriles. Mechanistic studies suggest the stereospecific nature of the process which is in alignment with the ring-closure of halohydrins to yield epoxides.

Keywords: BMIDA
Boron
Epoxynitrile
Iminologous
Iminology
Reaction development
Advisor: Yudin, Andrei
Teachers’ Perspectives on Nutrition and Physical Education Teaching Practices

This qualitative study investigates Nutrition and Physical Education and its role in student empowerment as a precondition for subsequent healthy habits and lifestyle, drawing on teachers’ perspectives in the province of Ontario, where the researcher is based. The teacher perspective is distinguished, as it is these ground level experts who are in the best position to discuss the education carried out, as well as evaluate the outcome for their students, and identify the specific challenges of the process. The critical value lens of empowerment is operationalized to investigate the lasting impact of the education upon the students. To this end, the dynamic interaction of policy, teachers and students is of interest, during the respective teacher practice process, filtering through the challenges, to produce the final outcome of student empowerment for healthy habits and lifestyle. Accordingly, the respective past and current teachers are considered, their backgrounds, workplaces and communities, their particular Health Education programs, as well as any challenges experienced by them. Specifically, a Questionnaire and several interviews explore which factors inform the teacher practice of nutrition and physical education teaching, what influences what the teachers do pedagogically when they teach nutrition and physical education, how the teachers evaluate effectiveness of the education they provide, what are the challenges encountered by the teachers during this process, and what are the teachers’ perspectives about the relationship between their teaching practices and student empowerment in the formation of healthy habits, and subsequently, a healthy lifestyle? Findings of the investigation point to a wide range of factors which directly and indirectly inform the teacher practice of nutrition and physical education teaching; numerous important direct and indirect conditions impacting the teaching practice of the participants are observed; various types of instruments employed for evaluation purposes are identified; and many challenges of direct and indirect nature encountered by the teachers during this process are uncovered. Nonetheless, the participants confirm the belief that Health Education provided leads to the formation of healthy habits and a healthy lifestyle. In conclusion, implications for policy, practice, and theory are discussed, as well as recommendations are offered for future research.

Keywords: Empowerment
Advisor: Bascia, Nina
Joint Multistate Models for Correlated Disease Processes: Extending Approaches for Interval-Censoring, Mixed Observation Schemes, and Multiple Longitudinal Outcomes

In diabetes and other lifelong diseases, it is not always known with certainty how chronic correlated non-fatal disease processes co-develop over time. It is also not obvious how to analyze this complex multivariate statistical problem. This thesis reviews and proposes methods that allow for the simultaneous modelling of several such processes. In a tutorial setting, it is shown that multistate and joint modelling approaches are useful for the overall research objective. Multistate models are found to be particularly applicable for questions surrounding the order and timing of disease-related processes. However, they require discretization of outcome data and possibly a very complex state space when more than two processes are modelled. In contrast, joint models can account for variations of continuous biomarkers over time and are particularly designed for modelling complex multivariate association structures. It would therefore be useful to combine elements of multistate and joint models, and the next part of the thesis develops this framework. Shared random effects can be used to link multistate and longitudinal processes, but most existing approaches assume that the multistate transition times are exactly observed. This renders them unsuitable for interval cohort studies, which are one of the most popular study designs for questions surrounding the natural history of complications. In interval cohort studies, participants are intermittently observed at regular intervals and are thus subject to mixed observation schemes where certain events are interval-censored and others are exactly observed. A novel shared random effects joint model for a longitudinal outcome and a multistate process under a mixed observation scheme is thus proposed. An appropriate likelihood function is defined and the model is fitted using a maximum likelihood framework with adaptive Gaussian quadrature. The model is assessed using simulation studies and is applied to 30-year data from the Diabetes Control and Complications Trial and Epidemiology of Diabetes Interventions and Complications study. The model is then extended to accommodate multiple longitudinal outcomes via Bayesian estimation using Hamiltonian Monte Carlo. In the end, it is shown that the novel joint multistate model gives greater insight into the natural history of a full complications process.

Keywords: Interval censoring
Joint model
Longitudinal data
Multistate model
Multivariate longitudinal outcomes
Survival analysis
Advisor: Tomlinson, George
Perkins, Bruce A
Epigenetic Profiling and Therapy for Brain Cancer

Brain tumors are aggressive and lethal cancers affecting both children and adults. Genetic alterations in the regulation of epigenetic processes play a critical role in the development of brain tumors. Atypical teratoid rhabdoid tumors (ATRTs) exhibit clinical heterogeneity and a relatively stable genome, suggesting they may comprise distinct molecular subgroups driven by epigenetic mechanisms. Integrated analyses of epigenomic and transcriptional profiling on a large cohort of primary ATRTs defined three molecular subtypes that correlated with distinct clinical features, lineage-specific methylation, and transcriptional patterns. ATRT subgroups exhibited distinct epigenomic landscapes correlated with the expression of cell-lineage and signaling genes. This suggests that different subgroups of ATRTs may have distinct regulatory networks, highlighting the potential for developing treatments tailored to specific subgroups. SMARCB1 inactivating mutations in ATRTs confer an oncogenic dependency on EZH2. We found that EZH2 inhibition (EZH2i) upregulates the expression of genes enriched for intronic and 3’ UTR IR-Alu elements, leading to the formation of intramolecular stem-loop dsRNA and activation of cytosolic dsRNA sensing pathways. EZH2i induces genome instability and cytoplasmic DNA sensing pathways in a process dependent on reverse transcriptase activity. The viral mimicry state underlying the vulnerability of genetically defined, SMARCB1-deficient tumors on EZH2i is mediated via both dsRNA and DNA sensing pathways.DNA methylation patterns can be used to classify different types of brain tumors in molecular pathology, but this typically requires obtaining tissue samples through invasive surgery. To overcome this obstacle, we used a highly sensitive technology called cfMeDIP-seq to profile DNA methylation in the plasma. We found that DNA methylation patterns in the plasma can accurately identify common primary intracranial tumors that may be difficult to differentiate with standard imaging methods and have the similar cell of origins. Altogether, this thesis demonstrates epigenomic profiling as a powerful approach to classifying different brain tumor entities and reveals an important mechanism of targeting EZH2 as a potential therapeutic strategy for the treatment of ATRTs.

Keywords: Atypical teratoid rhabdoid tumors
Brain Cancer
cfMeDIP-seq
Epigenetic Profiling
Epigenetic Therapy
Advisor: De Carvalho, Daniel DDC
Arrowsmith, Cheryl CA
Applying Clinician Macrocognition in Designing a Clinical Decision Support Tool for Congenital Heart Disease

Introduction: When presenting to the emergency department (ED), children with congenital heart disease (CHD) experience higher rates of hospital admission, morbidity, and mortality compared to children without CHD. The burden of residual lesions and the natural history of many CHDs predisposes these children to hemodynamic fragility and altered response to traditional resuscitative measures. Their optimal outcome requires CHD-expertise which is limited in local EDs. Hence, there is an urgent need for a sociotechnical solution to support the evaluation, diagnosis, and management of these patients in ED. Three studies address this need by contributing to the development and evaluation of a clinical decision support system (CDSS) based on the cognitive work of CHD-experts and ED physicians. Methods: In study 1, using the critical decision method, a cognitive task analysis (CTA) of CHD-experts and ED physicians was conducted to understand differences in their macrocognition when managing acutely ill pediatric CHD patients. In study 2, decision centered design was used to identify key decision requirements and design concepts to inform the prototype CDSS. In study 3, scenario-based simulation was used to test the effect of the CDSS on ED physicians’ decision making. Results: The most pertinent differences in decision making between CHD-experts and ED physicians were in sensemaking, anticipation, and managing complexity. Accordingly, the key decision requirements and design concepts incorporated into the prototype CDSS included appreciating the CHD physiology, identifying CHD-specific diagnoses, and selecting appropriate CHD interventions. The use of the CDSS significantly improved ED physicians’ CHD-specific decision-making (M=5.43, 95%CI 3.7-7.2) compared to usual care. Conclusion: These studies reveal differences in CHD-expert and ED physicians’ macrocognition and decision making while also proposing a design approach to develop and evaluate a CHD-specific CDSS. Results and methods presented here can be used by clinicians, developers, and researchers to design sociotechnical solutions beyond pediatric CHD.

Keywords: Artificial Intelligence
Congenital Heart Disease
Decision Centered Design
Decision Support
Human Factors Engineering
Macrocognition
Advisor: Trbovich, Patricia