VictorJuiz/thesis huggingface dataset:
The Associations between History of Psychosis, Neuropsychological Performance and Functioning in Remitted Later-life Major Depression
Keywords: Clinical research
Cognition
Cortisol
Functioning
Psychotic depression
Quantitative

Observational studies report that psychotic major depressive disorder (PMD) has poorer functional outcome than non-psychotic major depression (NPMD), but this finding could be explained by less robust recovery and residual symptoms in PMD. In addition, neuropsychological performance is worse in PMD than NPMD, both acutely and in remission. The overarching goal of this research is to examine the relative contributions of a history of psychosis and neuropsychological performance to impaired everyday function in remitted major depressive disorder (MDD). This thesis examined this question via three projects. The first investigated the optimal method to assess functioning in later-life depression through a systematic review of existing assessment instruments. Two instruments, the Performance Assessment of Self-Care Skills and the Late-Life Function and Disability Instrument, were best suited to our measurement needs. In our second and main project, we examined whether history of psychosis is associated with poorer everyday functioning in remitted later-life MDD and, if so, whether this relationship is explained by neuropsychological performance. As hypothesized, history of psychotic features and poorer neuropsychological performance each independently predicted worse functioning, but the association was much stronger for neuropsychological performance, especially processing speed. In comparison to an age and gender-matched group with no history of psychiatric disorder, the effect size of functional impairment in patients with remitted PMD was large, whereas the impairment was small to moderate in NPMD. In our third project, we explored a potential mechanism for vulnerability to psychosis and neuropsychological and functional deficits in depression: sustained hypercortisolemia, measured using hair cortisol concentration and analysed with correlation coefficients. We found no clinically significant relationship between cortisol and history of psychosis, cognition or functioning. To further investigate the mechanism of impaired neuropsychological performance and function in remitted PMD, we propose a line of research examining the microstructure and function of brain white matter.
Deep Reinforcement Learning Approach to Multimodal Adaptive Traffic Signal Control
Keywords: Deep Reinforcement Learning
Multimodal Traffic Signal
Reinforcement Learning
Traffic Signal Control

With perpetually increasing demand for transportation as a result of continued urbanization and population growth, it is essential to increase the existing transportation infrastructure. Optimizing traffic signals in real time, although is one of the primary tools to increase the efficiency of our urban transportation networks, is a difficult task, due to the non-linearity and stochasticity of the traffic system. Deriving a simple model of the intersection in order to design an appropriate adaptive controller is extremely challenging, and traffic signal control falls under the challenging category of sequential decision-making processes. One of the best approaches to resolving issues around adaptive traffic signal control is reinforcement learning (RL), which is model-free and suitable for sequential decision-making problems. Conventional discrete RL algorithms suffer from the curse of dimensionality, slow training, and lack of generalization. Therefore, we focus on developing continuous RL-based (CRL) traffic signal controller that addresses these issues. Also, we propose a more advanced deep RL-based (DRL) traffic signal controller that can handle high-dimensional sensory inputs from newer traffic sensors such as radars and the emerging technology of Connected Vehicles. DRL traffic signal controller directly operates with highly-detailed sensory information and eliminates the need for traffic experts to extract concise state features from the raw data (e.g., queue lengths), a process that is both case-specific and limiting. Furthermore, DRL extracts what it needs from the more detailed inputs automatically and improves control performance. Finally, we introduce two multimodal RL-based traffic signal controllers (MCRL and MiND) that simultaneously optimize the delay for both transit and regular traffic, as public transit is the more sustainable mode of transportation in busy cities and downtown cores. The proposed controllers are tested using Paramics traffic microsimulator, and the results show the superiority of both CRL and DRL over other state-of-practice and state-of-the-art traffic signal controllers. In addition to the advantages of MiND, such as its multimodal capabilities, significantly faster convergence, smaller model, and elimination of the feature extraction process, our experimental results show significant improvements in travel times for both transit and regular traffic at the intersection level compared to the base cases.
Palladium and Nickel Catalyzed Transformations Forming Functionalized Dihydroisoquinolinones, Chromans, Dihydrobenzofurans and Oxindoles
Keywords: Anion Capture Cascade
Carbohalogenation
C-H Activation
Nickel
Palladium

Transition metal catalysis has been at the forefront of synthetic organic chemistry as it represents new and powerful methods to forge carbon–carbon in high atom- and step-economy. The Lautens group has been particularly focused on Pd- and Rh-catalysis in stereo- and regioselectively generating functionalized heterocycles. In chapter 1, a Pd- and Ni-catalyzed cycloisomerization reaction of aryl iodides to alkyl iodides, known as carboiodination, is described. In the Pd-catalyzed variant, a diastereoselective Pd-catalyzed carboiodination reaction of enantioenriched carboxamides generating dihydrosioquinolinones is explored. The transformation was the key step in the formal synthesis of (+)-corynoline. In the Ni-catalyzed variant, 3,3-disubstituted oxindoles are generated in excellent yield and an enantioselective variant employing a dual ligand system is disclosed. In chapter 2, a Pd-catalyzed diastereoselective anion-capture cascade reaction is discussed. Building on the Pd-catalyzed carboiodination reaction en route to (+)-corynoline, a Pd-catalyzed aryl cyanation is discussed. The alkyl nitrile was synthesized in high yield and d.r. The second method generates borylated chromans as a single diastereomer in good yield. The alkyl boronate was further functionalized to showcase its utility. In chapter 3, a Pd-catalyzed domino process harnessing carbopalladation, C–H activation and π-system insertion to generate spirocycles is reported. In the first method, benzynes are inserted to give spirodihydrobenzofurans and spirooxindoles. A significant limitation in the first method pertains to the low regioselectivity observed. To circumvent these problems, in the second method, polarized alkynes are inserted in >20:1 r.r.
Dynamic Analysis and Design of Metabolic Networks
Keywords: bistability
identifiability
kinetic models
metabolic engineering
parameter estimation
systems biology

Mathematical models of biological networks play an important role in metabolic engineering through their ability to provide a complete systems level understanding of the numerous interactions that govern metabolism, and consequently cellular function. Models of metabolism are extensively used to design these networks to achieve various engineering and pharmacological objectives. Constraint-based models of metabolism assume that metabolism operates under a pseudo steady state and represent them only in terms of their reaction stoichiometry and fluxes. The numerous regulatory interactions that constitute metabolism are not considered, and the dynamics of the networks cannot be deciphered using constraint-based models. In contrast, kinetic models can represent all of the interactions in the metabolic network, and also facilitate studying the dynamic characteristics of metabolism. Nonetheless, computational limitations encountered during various stages of kinetic model development and use limit their widespread adoption for model-based prediction and design. This thesis aims to address some of these limitations using the metabolism of Escherichia coli as an example. First, we demonstrate the use of kinetic models to characterize the steady state behaviour of a bistable metabolic network with a positive feedback loop, and to design this bistable network to produce at the highest possible steady state. Next, we explore the use of metabolic network topology and structure to assess the ability of the network to exhibit more than one steady state. We also show how this assessment can be used to design networks with either monostable or multistable topologies. Finally, we develop two scalable frameworks to assess the structural identifiability and estimability of parameters in a kinetic model of a metabolic network, based on steady state data. The application of these frameworks to determine the quality and quantity of experiments necessary to generate the steady state data required for estimating all model parameters is also shown. The methods developed and demonstrated in this thesis aim to improve the adoption of kinetic models to design metabolic networks exhibiting bistability. They also provide alternative avenues for parameter estimation in kinetic models using steady state data, while reducing the quantity of time course data needed for kinetic model parameter estimation.
The Effects and Outcomes of Simple Bone Cysts
Keywords: Bone Cyst
Children
Mixed Methods
Outcomes
Qualitative Research

Introduction: Simple bone cysts (SBCs) are a common benign condition in paediatric orthopaedics. The purpose of this thesis was to investigate the impact of simple bone cysts on children related to social interactions, perceptions and physical activity participation. This thesis additionally set out to investigate the inter-relationship between subjective and objective outcomes using qualitative and quantitative methods to more fully understand the impact of SBC on children and their families. Methods: Qualitative methods were used to investigate the experiences of patients and families with SBC, specifically related to perceptions and activity participation. These results were then combined with patient reported quantitative outcome data related to physical function in a mixed methods study. Next, a series of statistical analyses were used to identify potential predictive patient and cyst features related to subjective and objective outcomes. Finally, a digital software program using pixel intensity was employed to measure an objective outcome of healing typically reported by radiologists. Results: Children perceive their experience of SBC more similar to injury than to an illness; SBCs cause some anxiety for both children and parents; and we identified shortcomings in the decision-making process around SBC treatment. Overall children with SBC achieve good functional outcomes and remain highly active. Function at the time of diagnosis is strongly associated with functional outcomes. Finally, the digital software is able to detect some differences between healed and not healed SBCs but was not able to identify clear ranges of intensities related to healing grades. Conclusions: The use of subjective and objective data provided a better understanding of outcomes of SBC. While some of these finding may be integrated, it is unlikely that a single measure will fully capture the outcomes of the disease. Studying the interrelationships between different types of measurement has led to a more fulsome understanding of the outcomes and effects of SBC in children.
Regulation of Hepatic Drug Transporters Expression in Mice During Acute Inflammation
Keywords: drug transporters
Inflammation
Liver
signaling pathways

Inflammation generated by many disease conditions is known to alter the expression and activity of several hepatic ABC and SLC transporters and drug-metabolizing enzymes. These pronounced changes in hepatic transporters contribute to altered drug disposition; therefore, understanding the molecular mechanisms would aid in identifying potential sources of drug variability in diseases associated with inflammation. Pregnane X receptor (PXR) and nuclear factor-κB (NF-κB) are regarded as key transcriptional factors that are modulated in response to endotoxin and cytokine signaling. This work assesses the role of NF-κB and PXR in the transcriptional regulation of hepatic transporters and elucidate the signaling pathways behind changes in transporter expression. We hypothesized that the regulatory mechanism of hepatic transporter expression following inflammatory stimuli would depend primarily on the NF-κB signaling pathway and that PXR might play a role in this regulation. Inflammation was induced by either endotoxin or proinflammatory cytokine interleukin (IL)-6 administration in wild type PXR (+/+) and knockout PXR (-/-) mice. The mRNA expression of most transporters was downregulated to a similar extent for PXR (+/+) and PXR (-/-) mice following endotoxin administration. NF-κB inhibition attenuated the impact of endotoxin on transporter expression, suggesting that NF-κB is the major signaling pathway involved in endotoxin-mediated downregulation of hepatic transporter, and it appears to act independent of PXR. Conversely, IL-6-mediated downregulation of Abcb11, Abcc2, Slco2b1 and Slc10a1 was seen in PXR (+/+) but not PXR (-/-) mice, suggesting PXR-dependent regulation. Our IL-6 studies demonstrated that STAT3 inhibition attenuated IL-6-mediated downregulation of almost all transporters. However, IL-6-mediated activation of STAT3 stimulated the release of secondary cytokines that further activated NF-κB. Interestingly, NF-κB target genes (IL-6 and IL-1β) showed (35%-100%) higher basal expression in PXR (-/-) versus PXR (+/+) mice, and NF-κB inhibition attenuated IL-6-mediated changes of transporters in PXR (+/+) mice. Since NF-κB inhibition following IL-6 administration demonstrates indirect involvement of NF-κB in transporter expression via secondary cytokines, findings from these studies indicate that NF-κB is an essential regulator of hepatic transporter expression under inflammatory conditions. Thus, targeting NF-κB in diseases associated with inflammatory conditions could provide a strategy for therapeutic intervention.
3D Microscopy of Nanoparticles in Tumours
Keywords: 3D microscopy
Cancer cells
Nanoparticles
Tissue clearing
Tumour

The structure of solid tumours is a major factor contributing to poor treatment outcomes because it can prevent therapeutics from reaching cancer cells. Nanoparticles are able to increase the accumulation of therapeutics in the tumour as a whole but are not able to deliver therapeutics to cancer cells because of structural barriers within the tumour. However, researchers have been unable to visualize these structures within the tumour and how it impacts nanoparticle distribution because tumours are opaque. Here, I present a series of techniques that allow the structure of the tumour and the distribution of nanoparticles within to be visualized and quantified. I developed methods to 1) render tumour tissues transparent at the scale of 100s of tissues per month needed for biological experiments, 2) quantify and improve the retention of nanoparticles in the tumours after process, 3) label and visualize nanoparticles within the tumours. These methods can now be used to gain a deeper understanding of how the structure of the tumour is organized, how it impacts nanoparticle distribution and how it can be altered to achieve optimal cancer therapy.
Ray-tracing Propagation Models of Complex Guideway Geometries for the Deployment of Train Control Systems
Keywords: Geometrical Optics
Intelligent Transportation Systems
Radiowave Propagation
Ray-Tracing
Wireless Channel Modeling

This thesis presents the work carried out in modeling propagation in complex guideway geometries. The primary motivation of this work is to develop high-fidelity models that can enable improvements in the deployment and performance of train control systems. To that end, a 3-D image-based ray tracing tool is developed. It is validated in a variety of scenarios, including an indoor office hallway, an outdoor open environment with an undulating terrain, and an arched road tunnel. The limitations of the basic image-based algorithm are thoroughly investigated, especially with respect to their failings in modeling segmented approximations of circular and arched tunnels. Due to a lack of any rigorous solution that addresses these issues, a heuristic approach is developed to modify the Fresnel reflection coefficients to systematically weaken the contribution of reflected ray-paths that lead to an overestimation of RSS. This approach is inspired by the scattering of an incident wave by a perfectly conducting finite sized rectangular plate. Enabled with these modifications, the ray tracing tool is used to study propagation in a 3.5 km long real, complex tunnel environment in the London Underground. The estimated RSS is within a mean absolute deviation of 4-6 dB compared to the measurements. The input geometries required for these simulations are derived from point cloud data obtained from a laser survey conducted by Thales Canada, by developing a semi-automated error driven framework which enables a systematic study of the relationship between the accuracy of the simulated RSS and the accuracy of the estimation of the modeled geometry. Finally, physics-based models such as the developed ray tracing tool and others are used to characterize and enhance the performance of train control systems. It is shown that such modeling tools can be quite useful as they enable optimization of access points driven by the estimated network level performance indicators, thereby integrating propagation modeling with network-level system design leading to potential efficiency gains, instead of carrying out these tasks sequentially as is done conventionally.
Ion Permeation and Selectivity in Voltage-gated Sodium Channels
Keywords: computer simulation
electrophysiology
free energy
ion solvation
molecular dynamics
sodium channel

Voltage-gated sodium channels are responsible for the initiation and propagation of electrical signals in living organisms. Though the function of these channels are well-described in humans, many questions remain at the microscopic level with respect to the relationship between their structure, function, and connection to human health and disease. The elucidation of high-resolution structures of sodium channels enables the use of computational models to connect microscopic biophysical measurements to macroscopic experimental observables. In this work, we present extensive molecular dynamics studies of the bacterial voltage-gated sodium channel NavAb to examine the molecular basis for four key mechanisms underlying the generation of action potentials in excitable cells; ionic conduction, selectivity, gating, and leakage. Our simulations support a molecular mechanism for ionic conduction involving a strong coupling between the conformational isomerization (dunking) of glutamic acid sidechains and ionic conduction. We determined single-point mutations which modulate dunking and ionic conduction and enable experimental validation of this hypothesis. Building on this mechanism, we present a model for Na+ selectivity over K+ in NavAb that results from differences in ionic desolvation penalties within the selectivity filter (SF) and the capability of channel fluctuations to facilitate multi-ion occupancy. The presence of three ions within the SF results in a diffusive free-energy landscape for Na+ whereas K+ conduction is comparatively restricted. We describe a mechanism for Na+ permeation at the intracellular gate wherein fluctuations between a wetted and dewetted state modulate the free-energy of conduction in this region. Lastly, we studied the molecular basis of Na+ leakage in the voltage-sensor of NavAb with analogous mutations linked to the hereditary disease periodic paralysis. Molecular simulations reveal a decrease in the free-energy barrier opposing Na+ permeation within the voltage sensor consistent with leakage, providing a structural basis for this disease that may facilitate treatment. Throughout this work, we quantify and compare the relationship between ionic desolvation and free-energy of ion conduction. Our studies have broad implications for understanding ion transport and permeation across the larger family of ion channels and have relevance to the treatment of patients suffering from diseases that result from abnormal function of channels.
Comparative Efficacy and Safety of Pharmacological and Non-pharmacological Interventions in Persons Living with Dementia
Keywords: cohort study
dementia
interventions
network meta-analysis
neuropsychiatric symptoms
systematic review

Background: Neuropsychiatric symptoms of dementia are treated with pharmacological and non-pharmacological interventions; however, their comparative efficacy and safety is largely unknown. As practice patterns shift because of concerns regarding antipsychotic safety, we need to understand the efficacy and safety of alternative interventions. Methods: Outcomes for this thesis were chosen by dementia care partners. Three studies were conducted: a systematic review and network meta-analysis (NMA) of randomized controlled trials (RCTs) comparing the efficacy of pharmacological and non-pharmacological interventions for treating aggression and agitation in PLWD, a systematic review and NMA of RCTs and non-randomized studies (NRSs) comparing the safety (i.e. fracture, cerebrovascular event, fall, or mortality risk) of pharmacological interventions used to treat neuropsychiatric symptoms in PLWD, and a retrospective cohort study comparing the risk of major osteoporotic fractures, falls, and death associated with trazodone or atypical antipsychotic use in PLWD. Results: Non-pharmacological interventions were as, or more, efficacious than pharmacological interventions for treating aggression and agitation in PLWD. No pharmacological interventions were associated with increased odds of fracture among PLWD. Compared to placebo, cholinesterase inhibitors were associated with decreased odds of death (odds ratio (OR) 0.82, 95% credible interval (CrI) 0.67 to 1), antipsychotics were associated with increased odds of cerebrovascular events (OR 2.19, 95% CrI 1.3 to 3.79), and dextromethorphan-quinidine was associated with increased odds of falls (OR 4.16, 95% CrI 1.47 to 14.22) in NMAs of RCT data. These associations were not seen in NRS data. Compared to atypical antipsychotics, trazodone was associated with a similar rate of falls and major osteoporotic fractures (weighted hazard ratio (HR) 0.89, 95% confidence interval (CI) 0.73 to 1.07); however, it was associated with a lower rate of mortality (weighted HR 0.75, 95% CI 0.66 to 0.85) in PLWD. Conclusion: Non-pharmacological rather than pharmacological interventions should be used for treating aggression and agitation in PLWD. Comparable rates of falls and fractures associated with trazodone or atypical antipsychotic use suggests a shift in prescribing to trazodone may not be entirely approproriate. Data comparing the safety of antipsychotics to other interventions was sparse. More studies comparing antipsychotics to alternative interventions are needed.