VictorJuiz/thesis huggingface dataset:
Development and Application of Novel in Vitro Assays to Advance Drug Discovery for Arrhythmogenic Cardiomyopathy and Respiratory Syncytial Virus Infection

The research described in this thesis is focused on the development of in vitro assays to better study human disease and advance drug discovery, specifically in the context of arrhythmogenic cardiomyopathy (ACM) and respiratory syncytial virus (RSV) infection. Despite the functional distinction between these diseases, they both share the issue of inadequate treatment options for patients. Dysfunction of gap junctions is thought to underlie the development of fatal ventricular arrhythmias early in ACM disease progression. Existing methods of studying gap junction function are low-throughput, technically challenging, and have poor reproducibility. Chapter II outlines the development of a robotic cell microinjection assay to quantify gap junction permeability. Human cardiomyocytes with knockdown of PKP2, a protein commonly mutated in ACM, were screened against a library of drugs using the robotic assay. Five compounds were found to enhance gap junction function in vitro, one of which reduced beating irregularity in a mouse model of ACM. Respiratory syncytial virus (RSV) is the leading cause of acute respiratory tract infections necessitating hospitalization in infants and young children. There are currently no vaccines for the virus and treatment options are limited to supportive care. Chapter III describes the development of a high content assay to rapidly quantify RSV infection rates. Application of this assay towards drug screening led to the identification of several viral inhibitors and host pathways targeted by the virus. Functional enrichment analyses revealed an interaction between the virus and lipid metabolic pathways, prompting further investigation into the antiviral mechanism of statins–a top screening hit. Chapter IV takes a closer look at the function of statins and mevalonate pathway metabolites during viral infection. Statins were shown to inhibit RSV through a combination of cholesterol and isoprenoid-mediated effects. Notably, statin treatment negated virus-induced increases to the prenylation and activation of Rho GTPases. A primary outcome of the conducted research was the identification therapeutic drugs and pathways for two unique diseases with limited treatment options. The obtained results also highlight the utility of each assay, and demonstrate the potential of applying this work towards future studies on other viral or gap junction-mediated diseases.

Advisor: Maynes, Jason T.
Investigating the Dynamic CFTR Interactome using the Mammalian Membrane Two-hybrid (MaMTH) platform

Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) is a chloride channel found in secretory epithelia with a plethora of known interacting proteins found throughout its life cycle. Over 2,100 mutations have been reported in the CFTR gene associated with Cystic Fibrosis (CF), a complex disease that leads to progressive respiratory illness and other complications of phenotypic variance resulting from perturbations of its protein interaction network. To date, four FDA-approved drugs have provided promising clinical effects on modulating functional expression of the most common CFTR mutations. However, treatments that can modulate one type of mutation in CFTR have been shown not to work for others, leading to diverse classification of CFTR modulators. Furthermore, high variance in drug response within patients of the same genotype, including those who are refractory to the treatment, has been attributed to the presence of secondary genetic modifiers and environmental factors. For these reasons, therapies that solely target the CFTR protein itself have not had therapeutic payoffs matching research input. Studying the collection of CFTR interacting proteins and the differences between the interactomes of mutant and wildtype CFTR may be an effective way to address this problem, providing a comprehensive view of the disease and identifying novel drug targets that may allow for more patient-specific therapeutic regimens. Using the Mammalian Membrane Two-Hybrid (MaMTH) protein fragment complementation assay developed in our lab, my thesis focuses on systematic, high-throughput identification of CFTR-interacting proteins to provide additional insight into CFTR regulation and function. Through a collaborative initiative involving clinicians, biochemists and bioinformaticians, we developed a High-Throughput Screening pipeline (MaMTH-HTS) to identify and functionally validate numerous novel interactors of CFTR in multiple disease models including patient-derived intestinal organoid cultures. In parallel to these studies, we applied the MaMTH assay as part of a drug discovery platform (MaMTH-DS) and screened multiple small molecule libraries to identify compounds that can stabilize CFTR’s interaction with our most promising interaction partner 14-3-3 gamma. Lastly, we performed proof-of-concept screening of a comprehensive set of SLC transporters against CFTR and discovered an unusually high number of interactions suggesting an intricate network of PPIs that remains to be discovered.

Keywords: Cystic Fibrosis
High-throughput screening
Integrative computational biology
Interactome
Mammalian Membrane Two-Hybrid
Protein-protein interactions
Advisor: Stagljar, Igor IS
Reconstructing Complex Cancer Evolutionary Histories from Multiple Bulk DNA Samples

Cancers are composed of genetically distinct subpopulations of malignant cells. By sequencing DNA from cancer tissue samples, we can characterize the somatic mutations specific to each population and build clone trees describing the evolutionary relationships between these populations. These trees reveal critical points in disease development and inform treatment. This thesis describes Pairtree, which is a new method for constructing clone trees using DNA sequencing data from one or more bulk samples of an individual cancer. It uses Bayesian inference to compute posterior distributions over the evolutionary relationships between every pair of identified subpopulations, then uses these distributions in a Markov Chain Monte Carlo algorithm to perform efficient inference of the posterior distribution over clone trees. Pairtree also uses the pairwise relationships to detect mutations that violate the infinite sites assumption. Unlike previous methods, Pairtree can perform clone tree reconstructions using as many as 100 samples per cancer that reveal 30 or more cell subpopulations. On simulated data, Pairtree is the only method whose performance reliably improves when provided with additional bulk samples from a cancer. On 14 B-progenitor acute lymphoblastic leukemias with up to 90 samples from each cancer, Pairtree was the only method that could reproduce or improve upon expert-derived clone tree reconstructions. Beyond describing Pairtree and evaluating it relative to previous methods, we develop extensions for profiling the degree of uncertainty that exists in its solution set, quantifying the degree of heterogeneity that occurs in different cancer samples, and deciding whether two cancer samples are genetically similar. By scaling to more challenging problems, Pairtree supports new biomedical research applications that can improve our understanding of the natural history of cancer, as well as better illustrate the interplay between cancer, host, and therapeutic interventions.

Advisor: Morris, Quaid D
Second Language Writing: A Study of the Learning and Teaching of Academic Writing in a Networked Culture

The traditional notions of contrastive rhetoric conceive L2 writers of English as separate group of people having diverse cultural and rhetorical backgrounds, which interfere with their writing in English. It is assumed that their cultural thought patterns get expressed in their writing in English, thereby making their writing different from that of English writers. However, given the impact of new media and technology and its globalizing spread, L2 writers cannot be fully defined by a culture because they live in a networked culture. So, the relevance of contrastive rhetoric studies needs to be examined to suit the teaching situation, which is both cultural and social product of a given time. Building on the critical studies (Connor, 2002, 2004; Kubota Lehner, 2004; Petric, 2005), this research consolidates the existing dissonances with the traditional notions of contrastive rhetoric by examining the lived experience of graduate students. I also propose networked contrastive rhetoric (NCR) that better theorizes and operationalizes L2 writing theory and pedagogy. Using NCR as a conceptual framework that combines contrastive rhetoric (CR), L1 and L2 similarities and differences, L2 writing pedagogy, genre and academic conventions, discourse community, and networked culture (and their impact on L2 skills development and the familiarization with academic genre), this research does an empirical qualitative study by triangulating some research methods such as L2 student survey questionnaires and semi-structured faculty and L2 student interviews using survey research methodology and proposes some L2 writing pedagogical approaches. The findings show that a) L2 writers have challenges with both linguistic and rhetorical competences; b) they would benefit from more appropriate collegiality and lack institutional supports; c) L2 writers’ performance cannot be generalized as it depends on a lot of factors; d) the lived experiences of the faculty members and students problematize L2 writing as problems assumption and the notion of the expression of cultural thought patterns and transfer theory because networked culture has impacted L2 writing. Incorporating the findings of this research in future teaching may introduce a paradigm shift in L2 writing pedagogies in the ways L2 writing is taught in the classroom because it can have serious pedagogical implications in the multilingual, multiethnic, and cross-cultural context of present L2 writing.

Keywords: Contrastive rhetoric
L2 writing pedagogies
Lived experiences
Networked contrastive rhetoric
Networked culture
Second language writing
Advisor: Labrie, Normand
Exploring the Synthesis and Reactivity of Phosphorus/Boron Frustrated Lewis Pairs and Nitrogen-based Lewis Acids

The definition of frustrated Lewis pairs has been broadened from combinations of sterically encumbered Lewis acids and bases to stable classical Lewis adducts, which opens a new avenue as FLPs in challenging small molecule activation and catalysis. The objective for this thesis is to explore the design and fundamental reactivity of Lewis acid and base pairs featuring group 13 and 15 elements within the realm of frustrated Lewis pair chemistry.An FLP strategy was used in the interception of intermediates in mesityl-N-oxide-mediated phosphine oxidation with stable P/B-based Lewis adducts. The FLP 1,3-addition products were shown to react with strong bases allowing the phosphine oxidation to proceed, which provided experimental data supporting the related phosphine oxidation mechanism proposed by Cummins. Highly electrophilic hydridoboranes, H2B(C6F5)·SMe2 and HB(C6F5)2 were demonstrated to yield bicyclic and cyclic boron species when exposed to carboxylic acids or phosphinic acid. The subsequent reactivity of many of these heterocycles with Lewis bases was investigated. Oxygen-bridging P/B molecules featuring a weak Lewis acid centre were prepared and the FLP reactivity of these species was systematically explored. Such POB-containing intramolecular FLPs were found to effect in the capture of N2-surrogate, diazomethanes, which resulted in the formation of unexpected stable heterocycles. Isomeric nitrenium Lewis acids were prepared from alkylation of spiro[fluorene‐9,3’‐indazole] with tBuCl. The chemical properties of the cations were examined and their reactivity with phosphorus and carbon nucleophiles was explored.

Keywords: Frustrated Lewis Pair Chemistry
Main Group Chemistry
Nitrogen Lewis Acids
Advisor: Stephan, Doug DWS
Knowledge Representation and Artificial Intelligence for Management of Socio-Technical Risks in Megaprojects

Megaprojects are probabilistically dependent systems prone to progressive failures that are undertaken in significantly incentivized economic and political domains. Current processes in definition, estimation, and financing of these large projects often exclude relevant sources of socio-technical risks with overarching effects on the project. Applications of the artificial intelligence methods in forecasting project performance and outcomes considering socio-technical sources of risks have been mainly ad-hoc solutions catered to specific needs, project types, and data availability. This research proposes a high-level framework for dealing with socio-technical risks by utilizing available sources of data, expert knowledge, and the most applicable analytics methodologies. The framework consists of representation, quantification, and inference connected through a loop of dynamic learning. The representation part defines various sources of risk in an expandable data format and with universal semantics, considering the nature of risk factors as to when and how they should be collected, in conjunction with project performance measures. An ontology is developed for such representation using the linked data and the semantic web format. The quantification aims to measure such sources of risk, which could vary from machine learning algorithms' applications over remote sensing data to pure qualitative judgments in discrete scales. The quantification was exemplified by creating a remoteness risk index, called Nighttime Remoteness Index (NIRI) for risk and resilience assessment of remote projects. The remoteness index takes nighttime satellite imagery as input and produces a remoteness index using machine learning algorithms. The index was validated based on two census bases remoteness indices of Australia and Canada. The inference part aims to incorporate the effects and dependencies of socio-technical risk factors on project outcome variables by defining an expandable object-oriented Bayesian Network (OOBN). The models can be trained based on the collected data from knowledge representation or based on expert knowledge, and different extents of their combinations. The employed methodologies allow for evergreen process of data collection and process optimization in the previous three sections. The framework creates a systematic approach to capturing and modeling project socio-technical risks, enables quality controls across the process, and can be applied to various risk sources such as the Environmental, Social, and Governance (ESG) factors.

Keywords: Artificial Intelligence
Bayesian
Knowledge Representation
Megaprojects
Ontology
Socio-Technical Risks
Advisor: McCabe, Brenda Y
Application of Molecular Tools to Determine Effects of Key Growth Factors on Cultivated Algal Biofilm Communities

Cultivating microalgae as a biofilm may overcome some of the challenges of conventional suspended cultivation for the production sustainable biofuels and bioproducts. However, strategies to enhance the growth of product-producing species within biofilms should be investigated to optimize the profitability of algal bioprocesses. The objective of this thesis was to investigate how biofilm attachment material, wastewater, and inoculation strategy influence the accumulation of algal biofilm biomass and the composition of the community. To achieve specific and accurate quantification of target algal species, quantitative polymerase chain reaction (qPCR) assays were designed to estimate the cell abundance of Chlorella vulgaris and Scenedesmus obliquus. Additionally, a workflow was developed to simultaneously estimate absolute abundance of bacterial and algal taxa by targeting 16S rRNA genes. These tools were used to determine how manipulating the growth factors influence the biomass and composition of biofilms cultivated in a parallel-plate air-lift reactor. Pretreating reactors with wastewater and growing biofilms on cotton increased biofilm biomass by up to a factor of 5.6, and inoculating S. obliquus into cotton attachment materials increased its abundance in biofilms by up to a factor of 13.5. Depending on inoculation strategy or presence of wastewater, biofilm community compositions were distinct from that in their corresponding suspensions and that in the inoculum. In conclusion, the interactions between wastewater, attachment material, and inoculation strategy can have significant, species-specific influences on algal biofilm growth, thus may be exploited to simultaneously increase biomass and the growth of target species in cultivated biofilms. The experimental work described in this thesis contributes to the suite of molecular tools available for the analysis of species in algal biofilms and demonstrates the utility of qPCR and amplicon sequencing for evaluating the performance of algal biofilm cultivation systems, specifically determining the abundance of desired species in biofilms. The developed tools and findings in this thesis can be used to inform, not only the optimization of biofilm cultivation systems for the commercialization of algal products, but also the study of mixed algal communities in the environment.

Keywords: Algae
Biofilms
Bioreactors
Community
qPCR
Wastewater
Advisor: Allen, D. Grant
Short, Steven M
Role of Inferior Frontoparietal Structures in Motor Control and Freezing of Gait in Parkinson’s Disease

Freezing of gait (FOG) is a disabling symptom of Parkinson’s disease (PD) in which patients are unable to step forward when desired. Abnormal brain circuits responsible for FOG in PD patients are unclear and experimental paradigms are needed to address this disabling symptom. We hypothesized that motor interruptions of lower limb movements while seated may be related to FOG and may indicate abnormal brain activities. In Study 1, we tested 19 PD patients and 20 healthy controls and showed that motor interruption or cessation of bilateral stepping while sitting correlated with the presence and severity of FOG and this effect persisted in the “on” dopaminergic medication state. In Study 2, we tested how these “lower limb motor blocks” or LLMB are related to changes in 4-30 Hz cortical activities recorded from 64-channel scalp electroencephalography. In 17 PD patients, we found that sporadic LLMB differed from typical steps in the right angular gyrus (RAG, F=154.6, P=0.0185, before and during LLMB>typical steps). LLMB also differed from cued stops in the right inferior frontal gyrus (F=32.0, P=0.0005, before LLMB>cued stops; F=42.0, P=0.0005, during LLMB

Keywords: Angular gyrus
Freezing of gait
Frontoparietal
Inferior frontal gyrus
Motor control
Parkinson's disease
Advisor: Chen, Robert
The Relation between Payroll and Income Tax Avoidance

Payroll taxes, such as contributions mandated through the Federal Insurance Contributions Act (FICA), represent a considerable expense for businesses and are a large source of government revenue. Considering that employers pay approximately 50% of FICA, payroll taxes have a material impact on firm profitability. Despite the large cost, little is known about the determinants of payroll tax avoidance. By misclassifying employees as independent contractors, a firm can avoid their portion of FICA contributions and a variety of other employee related costs. This paper utilizes publicly available compliance action data from the Wage and Hour Division (i.e., WHD) of the United States Department of Labor (i.e., DOL) to identify employee misclassification and to empirically identify whether firms that avoid income taxes also avoid payroll taxes. This paper documents two main results. First, income tax avoidance, proxied by CashETR, is positively related to the likelihood of a successful discovery of a Fair Labor Standards Act (i.e., FLSA) violation during a Wage and Hour Division audit. Second, firms reduce their income tax avoidance following the discovery of FLSA violations.

Keywords: Employee Classification
Non-Income Taxes
Tax Planning
Advisor: Edwards, Alex
Development of a Smartphone Based Point of Care Device for Multiplexed Infectious Disease Diagnosis

Infectious diseases are responsible for a significant portion of mortality and morbidity in the developing world, whose spread can be better controlled by using accurate diagnostic and epidemiological tools. Wireless multiplex point of care diagnostic devices can address the drawbacks of current gold standard diagnostic methods such as ELISA and PCR, while allowing for epidemiological data collection and use through geo-tagging and real-time disease tracking when coupled with cell-phones. Existing cell-phone based point of care diagnostic devices lack sensitivity, portability or adequate multiplexing capabilities. Quantum dot microbead barcoding, Recombinase Polymerase Amplification and fluorescent microscopy are three technological platforms that have been shown through the work of Chan et al. to be ideal for multiplexed point of care detection when integrated with a smartphone. When consolidated with automated fluid handling and electricity-free precise temperature control, it can serve as a proof of concept for a point of care device for multiplexed genomic disease detection. The objective of this thesis is to develop and verify automated fluid handling, barcode readout and electricity-free precise temperature control for an integrated point of care DNA diagnostic platform. Chapter two covers the development and iteration of an approach to automated fluid handling for the quantum dot barcode assay. Chapter three covers the development and iteration of point-of-care quantum dot barcode readout and integration with the automated fluid handling module. Chapter four demonstrates an approach to reducing power consumption of the integrated device while allowing for electricity-free, precise and localized temperature control without damage to surrounding reagents. The successful development and verification of the component modules required for a multiplexed diagnostic device represents a significant step towards the achievement of a consolidated universal point of care multiplex diagnostic device. Translation of this device through clinical validation and iterative design for manufacturing can allow for amelioration of the healthcare infrastructure in resource poor settings through better diagnostic workflows.

Keywords: Chemical Heater
Diagnostics
Advisor: Chan, Warren