VictorJuiz/thesis huggingface dataset:
Exploring the Chemoselective Transformations of Boryl Carbonyls, Heterocycles, Peptide Macrocycles, and Boron Migration Processes

Developing novel and efficient methods towards the synthesis of azacycles and macrocycles are subject to increased attention due to their applications in natural product synthesis and pharmaceutical drug design. This dissertation outlines the synthesis of borylated building blocks and heterocycles with applications in the discovery of bioactive molecules. This dissertation also documents the development of chemoselective syntheses of thioamide-containing macrocycles and novel boron transfer processes. An introduction to heterocyclic chemistry and boryl carbonyl molecules (Chapter 1) is followed by the synthetic and biological applications of novel borylated small molecules (Chapters 2–4). Chapter 2 details the synthetic applications of borylated enamines, enamides, and sulfamate esters. These boron-containing molecules were efficient in the synthesis and exploration of the B–C–N and B–C–C–N motifs towards borylated heterocycles such as thiazoles. The boryl enamides were also utilized as linchpin intermediates for the construction of polycyclic isoindolinone scaffolds. Chapter 3 documents the synthesis of bench-stable acyl boronates towards borylated thiazoles, imidazopyridines, and indolizines. These compounds mildly introduce the boronate moiety onto azacycles in a regioselective manner. The boronate group also provides a handle for the construction of boron-containing oxadiazaboroles and triazaboroles. Chapter 4 outlines the efficient synthesis of substituted oxalyl boronates and borylated imidazoles. The borylated imidazoles were subjected to optimized Suzuki-Miyaura cross-coupling conditions to complete a modular synthesis of 2,4,5-trisubstituted imidazoles. Select imidazole substrates were found to be potent chemical probes for the protein kinase STK10. Chapter 5 explores the potential chemoselective thionation of peptide macrocycles and the effect of thioamide incorporation to the peptide conformation through photochemistry. Preliminary results showed mixtures of mono- and di-thionated cyclic peptides and the photochemically-induced cyclization of thionated dipeptides to diketopiperazines. Finally, Chapter 6 delves into the experimental and computational efforts towards understanding the boron transfer reactions we observed in certain chemical systems. The hemilability of the ligand attached to boron mechanistically played a key role in boron acting like a proton or a hydride in certain transfer processes. Several novel boron migration reactions were developed based on mechanistic findings and will continue to prompt further synthetic applications of boron-containing molecules.

Advisor: Yudin, Andrei K.
Sleep Apnea Caused by Rostral Fluid Shift: Identifying Risk Factors and Developing a Treatment Using Calf Muscle Electrical Stimulation

Rationale: Fluid accumulation in the legs due to a sedentary lifestyle can increase overnight fluid shifting from the legs and into the neck (i.e. rostrally) when lying down to sleep. Rostral fluid shift can increase pressure on the pharyngeal airway and severity of obstructive sleep apnea (OSA). This thesis contains three studies that together investigate risk factors for neck fluid accumulation when lying down, and explores a therapy of calf muscle electrical stimulation (ES) for reducing daytime leg fluid accumulation to treat OSA caused by fluid shift. Methods:The first study used data previously collected on the time-course of fluid shift from the legs and into the neck while lying supine for 90-minutes. Using demographic, anthropometric and fluid-based data captured before lying down, risk factors for increased neck fluid accumulation while supine were identified. Study two was a sham-controlled trial into the effects of using calf muscle ES while seated for two-and-a-half hours on leg fluid accumulation, consequent rostral fluid shift when supine, as well as OSA and snoring. Study three explored the time-course of seated leg fluid accumulation between sham and active calf muscle ES conditions to identify the optimal time-period for using the device to reduce leg fluid accumulation. Results: Study one found that male sex and greater leg and neck fluid volumes prior to lying down increased risk for neck fluid accumulation when lying down. Study two demonstrated that compared to sham ES, active calf muscle ES reduced seated leg fluid accumulation by 46%. Consequently, rostral fluid shift out of the legs and into the neck reduced by 17% and 31%, respectively. Lastly, while OSA severity did not change after ES, calf muscle ES reduced snoring index. Study three did not identify an optimal time-period for using calf muscle ES, but found the effectiveness in reducing leg fluid accumulation increases with time. Conclusion: The thesis shows that calf muscle ES is an effective therapy for reducing leg fluid accumulation and consequent pharyngeal narrowing likely through reduction of overnight neck fluid accumulation. Future work should explore the effects of long-term use of calf muscle ES on OSA severity.

Keywords: Edema
Electrical stimulation
Fluid shift
Sleep apnea
Snoring
Advisor: Yadollahi, Azadeh
Fernie, Geoff R
Identification and Control of 3D Mechanical Stimulation Conditions for Heart Valve Tissue Engineering using Microdevice Arrays

Tissue engineered heart valves have the potential to meet the growing need for valve replacement for pediatric patients, adolescents, and active adult patients with congenital defects, rheumatic fever, and valve disease, respectively. Currently engineered valve replacements are not durable post-implantation often due to cell-mediated tissue retraction and subsequent regurgitation. This limitation is largely due to the lack of knowledge required to inform the effective design of engineered tissues, and lack of platforms to efficiently investigate the integrative effects of multiple microenvironmental cues particularly including heart valve-relevant 3D mechanical stimulation on cell functions. Specifically, the optimization of mechanical loading protocols and methods for monitoring of tissue functional properties remain as primary challenges and priority for heart valve tissue engineering. In this thesis, a platform was presented that enabled 3D dynamic mechanical stretch of arrayed cell-laden hydrogel constructs and simultaneous continuous stiffness measurement of the hydrogel constructs in situ with integrated strain sensors. Cell-seeded polyethylene glycol norbornene (PEG-NB) hydrogels were bound to deformable membranes via a thiol-ene reaction with off-stoichiometry thiol-ene based polydimethylsiloxane as the membrane material. Dynamic 3D mechanical stimulation of human mesenchymal stromal cells (MSCs)-seeded PEG-NB significantly promoted myofibroblast differentiation. As captured by the on-chip strain sensors, significant evolution in the stiffness of cell-hydrogel constructs during culture due to cell-mediated remodeling was also confirmed. In addition, a proof-of-concept study to screen and identify the optimal 3D mechanical stimulation combination for promoting collagen expression by MSCs was demonstrated, using factorial experimental design and regression parametric modeling. For the first time, a significant mechanical stimulation interaction effect was revealed that dominantly determined collagen production by cells. The precisely controllable biomaterial and biochemical properties of the PEG-NB system also make this platform readily amenable to include other relevant microenvironmental cues for comprehensive combinatorial screening studies, and has the potential to identify strategies to predictably control the construction of functional engineered tissues in vitro. This platform with on-chip strain sensing also represents a promising approach to address the limitation of end-point analysis, enables exploration of bioprocess control strategies, and would provide insights otherwise not available into the engineered tissue development.

Keywords: Hydrogel
Mechanical stimulation
Mesenchymal stromal cell
Microdevice
On-chip strain sensing
Tissue stiffness monitoring
Advisor: Simmons, Craig A.
Sun, Yu
Programming the Gut Microbiota-Bone Axis by Early Life Exposure to Vitamin D in Mice in the Context of an Obesogenic Diet

Vitamin D has anti-inflammatory effects, and in the context of obesity, may reduce systemic inflammation and impaired bone health. Maternal vitamin D status may program offspring health, and is positively associated with offspring bone mass. Serum lipopolysaccharide (LPS) concentration is lower in healthy male mouse offspring exposed to high maternal vitamin D. Although, the programming effects on healthy female offspring, nor its effects within the context of obesity for either sex, have been studied. The overall thesis objective was to investigate the programming effects of vitamin D on the gut microbiota-bone axis in the context of a chronic high fat and sucrose (HFS) diet in male and female mice. Dams were fed high (H, 5000 IU/kg of diet) or low (L, 25 IU/kg of diet) vitamin D during pregnancy and lactation. At weaning, offspring remained on their damâ s diet (HH and LL groups) or were switched (HL and LH groups), and fed a high fat (44%) and sucrose (20%) diet until 7 months of age. High maternal dietary vitamin D resulted in lower intestinal permeability (p=0.010), serum LPS concentrations (dam diet, p=0.011), higher colonic percent Bacteroides (p

Keywords: Bone
Diabetes
Gut microbiota
Obesity
Programming
Vitamin D
Advisor: Comelli, Elena M
Ward, Wendy E
Analysis and Design of Hybrid Divided Power Converters

In this thesis, we report a design methodology for the combination of switched-capacitor (SC) and conventional inductive switch-mode power supplies (SMPS) into new power converters, so-called Hybrid Divided-Power (HDP) converters. These converters present an opportunity to reduce volume while also increasing power processing efficiency by utilizing the increased power density of SC converters and parallelizing power processing to reduce both passive volume and switch blocking voltage. The thesis places these converters in the emerging field of hybrid power converters, a class of converters which combine SC converters and conventional inductive converters. The main results include a switched capacitor converter design methodology based on efficiency and ripple requirements and the principle of operation and design of HDP converters. Two novel converters based on the stacked HDP configuration for LED driving applications are shown. The design of a third novel converter based on the differential HDP configuration is also shown. This differential HDP converter is a multiple output LED driver for mobile applications. A current balancing technique based on charge matching is developed for the converter. Practical experimental results from these novel topologies confirm reduction in passive volume around 70% compared to conventional topologies while also increasing efficiency over the whole range. In particular light-load efficiency is improved up to 20%. The efficacy of the charge matching control presented in this thesis is confirmed through simulation results, achieving matching within 2% over the operating range. This work indicates that HDP converters are a promising new class of converters to investigate.

Keywords: Current Balancing
Hybrid Converter Topologies
LED Lighting
Power Division
Power Electronics
Switched Capacitor Converters
Advisor: Prodic, Aleksandar
Semi-autonomous Control of Multi-robot Teams in Urban Search and Rescue Applications

Urban search and rescue (USAR) has been a significant application in robotics because the deployment of rescue robots in these life-risking tasks can help reduce the personal risks of human rescue workers and increase the speed of emergency response. Furthermore, the incorporation of multi-robot rescue teams consisting of a group of heterogeneous rescue robots is advantageous since it allows shorter robot deployment times, provides situational awareness from multiple locations, and introduces redundancy and fault-tolerance to this time-critical mission. While promising, the control of multi-robot rescue teams is a challenging task. In particular, decisions need to be made regarding which rescue tasks should be executed and by which robot in a specific scenario. This thesis focuses on the development of semi-autonomous control architectures for multi-robot USAR teams in order to address the challenges in human-robot coordination and multi-robot cooperation in USAR applications. A learning-based semi-autonomous control architecture is developed for multi-robot teams in USAR environments, allowing a team of rescue robots to learn and make decisions regarding which rescue tasks need to be carried out at a given time. The task sharing between rescue robots and human operators can reduce the stress and mental workload of the operators, while allowing rescue robots to benefit from a human operator’s experience and knowledge. Furthermore, the cooperation between different rescue robots enables fast exploration of cluttered USAR scenes by minimizing overlap or repeated revisits of an explored area, as well as improve the reliability of the overall search and rescue mission. This thesis further addresses the high-level task allocation challenge for a large heterogeneous multi-robot team. A hierarchical supervisory control architecture is proposed allowing effective task sharing amongst the multi-robot team based on the dimension, mobility and sensing capabilities of individual robots. The developed approach can also handle the changes to team size due to robot failures and the need for robot repair during a USAR mission. The developed multi-robot task allocation approach allows a single operator to control a large team of heterogeneous rescue robots in USAR applications. Simulations and experiments in simulated USAR environments verified the performance of the proposed supervisory controller.

Keywords: Machine Learning
Multi-Robot Systems
Semi-Autonomous Control
Supervisory Control
Urban Search and Rescue
Advisor: Nejat, Goldie
Dynamic Inventory Optimization with Learning and Model Ambiguity

Classic inventory control problems typically assume that the demand distribution is known a priori. In reality, this assumption is not always satisfied. Motivated by this concern, the joint optimization of learning and control is studied. We first consider the situation where parameters of the demand distribution are not known a priori, but need to be learned using right-censored sales data. A Bayesian framework is adopted for demand learning and the corresponding control problem is analyzed via Bayesian dynamic programming (BDP). Structural results of the optimal policy are established. In particular, we show that the BDP-optimal decisions can be expressed as the sum of a myopic-optimal decision plus a non-negative exploration boost which is proportional to the posterior index of dispersion of the unknown mean demand. This structure clearly articulates the manner in which the statistical learning and inventory control are jointly optimized. Next, we study an optimal inventory control problem in the presence of model miss-specification. In this problem, decision makers account for the miss-specification via solving a worst-case problem against an adversary, ``nature", who has the ability to alter the underlying demand distribution so as to minimize the decision maker's expected reward. We show that the decision maker's robust-optimal decisions are bounded above by the optimal solutions of the nominal model. This structural result clearly explains the trade-off between optimization and risk aversion. In the last chapter, we attempt to incorporate the elements of the Bayesian and robust approaches, namely robust Bayesian optimization. In particular, we are interested in how decision makers can remain robust to model uncertainty while also learning at the same time. We establish an analytical upper bound of the decision maker's optimal decisions, which can be expressed as the sum of a myopic-optimal decision plus an exploration boost and minus a risk aversion adjustment. We then propose a heuristic which is based on the approximation of the first order optimality condition, and the effort of computing this heuristic solution is essentially equal to obtain the robust-optimal and BDP-optimal solutions separately.

Keywords: Bayesian dynamic programming
Bayesian learning
inventory management
Advisor: Kim, Michael J
Representations of Psychological Distress Among Canadian Muslims of South Asian Origin: A Qualitative Study using the Self-regulatory Model

This study sought to gain insight into representations of distress among Canadian Muslims of South Asian origin. It sought to examine whether representations of distress among this population are influenced by Islamic, scientific, and Western representations, the extent to which they differ from those assumed in the prevailing literature on Islamic healing, counselling, psychotherapy, and psychiatry with Muslim populations, and whether individuals attempt to incorporate multiple influences into a single coherent representation, or they construct multiple representations simultaneously. The Self-Regulatory Model of Illness Representation (Leventhal, Brissette Leventhal, 2003) was utilized to understand how the participants made sense of, emotionally responded to, and coped with their experiences of distress. The findings of this study indicated that a common theme among the participants was the belief that their distress was a form of punishment from God due to lack of faith or piety, thereby suggesting a significant religious aspect to their representations of distress. Paradoxically, the participants attempted to cope with their distress through counselling and psychotherapy or pharmacotherapy, which implies an equally strong biomedical aspect to their representations of distress. Reasons for this dual and possibly contradictory nature of participants’ representations of distress are discussed along with the implications of the findings for counselling and psychotherapy.

Keywords: counselling
illness representations
Islam
phenomenology
psychotherapy
self-regulatory model
Advisor: Moodley, Roy
Directed Migration Achieved in Mammalian Cells via Ca2+ Signal Rewiring in Synthetic Protein Chimeras

Synthetic biology achieves control over cellular behavior by endogenous re-wiring. Ca2+ signals allow cells to regulate diverse processes such as migration, apoptosis, motility and exocytosis. In some receptors (e.g. VEGFR2), Ca2+ signals are generated upon ligand binding (e.g. VEGF-A). Here, firstly we engineered fusion proteins that generate a Ca2+ signal upon ligand binding by creating fusions of domains that oligomerize to the transmembrane domain and the cytoplasmic tail of the VEGFR2. By coupling these chimeric proteins that generate Ca2+ signals with proteins that respond to Ca2+ signals, we re-wired, for example, dynamic cellular blebbing to increases in extracellular free Ca2+. Next, we validated this design strategy in two systems, i.e., inflammatory cytokines such as TNFα and antibodies. A system of proteins was used: an engineered TNFα chimeric receptor (named TNFR1chi), a previously engineered Ca2+-activated RhoA (named CaRQ), VSVG and thymidine kinase. Upon binding TNFα, TNFR1chi generates a Ca2+ signal that in turn activates CaRQ-mediated non-apoptotic blebs allowing migration towards the TNFα source. Next, the addition of VSVG, upon low pH induction, causes membrane fusion of the engineered and TNFα source cells. Finally, post-ganciclovir treatment, cells undergo death via the thymidine kinase suicide mechanism. Hence, this forms the basis of engineering a cell to target inflammatory disease sites characterized by TNFα secretion and a low pH microenvironment. Lastly, we exploited antibodies to bind their antigens exclusively in combination with the ability of the cytoplasmic domain of VEGFR2 to generate a Ca2+ signal upon oligomerization. Using protein fusions between antibody variants (i.e. nanobody, single-chain antibody and the monoclonal antibody) and the VEGFR2 cytoplasmic domain, Ca2+ signals were generated in response to extracellular stimulation with green fluorescent protein, mCherry, tumour necrosis factor alpha and soluble CD14. The Ca2+ signal generation by the stimulus did not require a stringent transition from monomer to oligomer state but instead, only required an increase in the oligomeric state. The Ca2+ signal generated by these classes of antibody-based fusion proteins can be rewired with a Ca2+ indicator or with an engineered Ca2+ activated RhoA to allow for antigen screening or migration to most extracellular ligands, respectively.

Keywords: calcium signaling
chimeras
nano bodies
synthetic biology
TNF alpha
VEGFR2
Advisor: Truong, Kevin
Complex Dynamics of Exploited Populations: Tipping Points, Instability, and Phenological Diversity

Understanding the consequences of complex population dynamics for population persistence, ecosystem functioning, and wildlife management is vital as our biosphere becomes increasingly shaped by anthropogenic change. Exploited populations are commonly recognized to exhibit complex population dynamics, which often affect the harvest of economic and culturally important species. How social learning, harvest, and population diversity shape population dynamics are not well understood, and I therefore undertook studies to investigate their effects. (1) I developed novel theory to assess the population dynamic consequences of migratory homing acquired via social learning, called the adopted migrant life history. Simple mechanistic assumptions led to dynamical behaviours ranging from stable coexistence of local populations to local extirpations, depending on the encounter potential between dispersing juveniles and migrating adults. Local populations were especially vulnerable under unequal adult survival, suggesting that uneven harvest pressure could exacerbate the risk of local collapses that are difficult to reverse. (2) I verified that harvest can increase temporal variability in the abundance of exploited populations by analyzing a harvest experiment on Daphnia magna. Harvest elevated population variability by amplifying deterministic nonlinear dynamics rather than increasing the effect of environmental stochasticity alone. This implies high short-term predictability but also the possibilities of oscillations, tipping points, and hysteresis. (3) I identified a large contraction in Pacific herring spawning phenology between 1951 and 2016 in British Columbia, Canada. Herring are a vital forage fish in northeast Pacific food webs, and support fisheries both directly and indirectly. The contraction represents a type of population diversity loss, which may impact population stability via erosion of portfolio effects. My results show the dynamic consequences of social learning and harvest, and identify a population diversity decline in an important forage fish. Together these results open a new perspective on complex population dynamics in exploited populations.

Keywords: Adopted migrant life history
Daphnia magna
Modeling
Pacific herring
Population ecology
Advisor: Krkosek, Martin