Medicine and Health Sciences Commons^™

Reactive Chemistries For Protein Labeling, Degradation, And Stimuli Responsive Delivery, Myrat Kurbanov

Doctoral Dissertations

Reactive chemistries for protein chemical modification play an instrumental role in chemical biology, proteomics, and therapeutics. Depending on the application, the selectivity of these modifications can range from precise modification of an amino acid sequence by genetic manipulation of protein expression machinery to a stochastic modification of lysine residues on the protein surface. Ligand-Directed (LD) chemistry is one of the few methods for targeted modification of endogenous proteins without genetic engineering. However, current LD strategies are limited by stringent amino acid selectivity. To bridge this gap, this thesis focuses on the development of highly reactive LD Triggerable Michael Acceptors (LD-TMAcs) …

Evidence Assisted Learning For Clinical Decision Support Systems, Bhanu Pratap Singh Rawat

Doctoral Dissertations

Clinical decision support systems (CDSS) provide intelligently filtered knowledge and patient-specific and population information to the clinicians, nursing staff and healthcare professionals. CDSS can significantly improve the quality, safety, efficiency and effectiveness of health care. Over the last decade, American hospitals have adopted electronic health records (EHRs) widely resulting in a massive collection of clinical notes such as admission notes, physician notes, nursing notes and discharge summaries. For the past couple of decades, most of the work in CDSS has been focused on developing knowledge-based systems using structured data such as medications and ICD codes. In contrast, the EHR notes …

Utilizing Ultra-Performance Chromatography High-Resolution Mass Spectrometry To Investigate Fatty Acid Mediated Antibiotic Tolerance, Brittni Woodall

Doctoral Dissertations

The lipid membrane is the first component necessary to sustain life. To maintain homeostasis, segregate cellular machinery, provide protection from the environment, and reproduce, an organism must establish a boundary in which the processes can occur. Throughout the last two decades, research has propelled our knowledge of lipid membranes much beyond original hypotheses. Once thought of to be static and uniform, the understanding of the lipid membrane has evolved to encompass a structure that is responsive, unique, and intricately constructed by the organism itself. By chance or by choice, organisms adapt the lipid membrane according to the environment for which …

Development Of Surface-Modified Liposomes For Drug Delivery Applications, Megan Louise Qualls

Doctoral Dissertations

Liposomes are spherical vesicles composed of a lipid bilayer membrane that assembles around an internal aqueous core. This duality gives liposomes the ability to encapsulate both hydrophobic cargo within the lipid bilayer and hydrophilic cargo in the aqueous core, making them versatile molecular carriers for drug delivery. Liposome platforms have many advantages and are promising drug delivery carriers, and research is ongoing to improve their designs for continued clinical applications. Many liposome types have been developed, but further work is needed to improve surface modification, site-specific targeting, and triggered cargo release in order to further the therapeutic applications of these …

Intra-Skeletal Variation In Stable Isotopes Through Non-Destructive Approaches: Applications Of The Patterns Of Skeletal Remodeling To Biological Anthropology, Armando Anzellini

Doctoral Dissertations

Stable isotope analysis is a well-established method in biological anthropology used to deliver data on residence, diet, and life history. Samples for these analyses are often collected from the diaphyses of long bones with an assumption of an expected rate of turnover between five and ten years, depending on the skeletal element. However, the biological foundations of this assumption are still uncertain, especially concerning the intra-skeletal and intra-element variation of isotopic signatures that may relate to patterns of remodeling. Exploring these gaps in intra-element isotopic variation requires fine-grained work using multiple bones from multiple individuals, but such work is limited …

Unobtrusive Assessment Of Upper-Limb Motor Impairment Using Wearable Inertial Sensors, Brandon R. Oubre

Doctoral Dissertations

Many neurological diseases cause motor impairments that limit autonomy and reduce health-related quality of life. Upper-limb motor impairments, in particular, significantly hamper the performance of essential activities of daily living, such as eating, bathing, and changing clothing. Assessment of impairment is necessary for tracking disease progression, measuring the efficacy of interventions, and informing clinical decision making. Impairment is currently assessed by trained clinicians using semi-quantitative rating scales that are limited by their reliance on subjective, visual assessments. Furthermore, existing scales are often burdensome to administer and do not capture patients' motor performance in home and community settings, resulting in a …

Frontiers In The Self-Assembly Of Charged Macromolecules, Khatcher O. Margossian

Doctoral Dissertations

The self-assembly of charged macromolecules forms the basis of all life on earth. From the synthesis and replication of nucleic acids, to the association of DNA to chromatin, to the targeting of RNA to various cellular compartments, to the astonishingly consistent folding of proteins, all life depends on the physics of the organization and dynamics of charged polymers. In this dissertation, I address several of the newest challenges in the assembly of these types of materials. First, I describe the exciting new physics of the complexation between polyzwitterions and polyelectrolytes. These materials open new questions and possibilities within the context …

Design And Development Of The Urban Population Health Observatory To Improve Disease Surveillance And Response, Whitney Brakefield

Doctoral Dissertations

Chronic and infectious diseases have a profound impact on the quality and length of life of populations that suffer from these conditions. Scientists, physicians, and health officials are seeking innovative approaches to decrease the morbidity and mortality of deadly diseases. Incorporating artificial intelligence and data science techniques across the health science domain could improve disease surveillance, intervention planning, and policymaking. In this dissertation, we describe the design and development of the Urban Population Health Observatory (UPHO), an explainable knowledge-based multimodal big data analytics platform. A common challenge for conducting multimodal big data analytics is integrating multidimensional heterogeneous data sources, which …

Deciphering Protein Higher-Order Structure And Interactions Via Diethylpyrocarbonate Labeling-Mass Spectrometry, Xiao Pan

Doctoral Dissertations

The study of protein higher-order structures is vital because it is closely related to the investigation of protein folding, aggregation, interaction and protein therapeutics. Consequently, numerous biochemical and biophysical tools have been developed to study protein higher-order structures in many different situations. The combination of covalent labeling (CL) and mass spectrometry (MS) has emerged as a powerful tool for studying protein structures and offers many advantages over other traditional techniques, such as better structural coverage, high throughput, high sensitivity, and the ability to study proteins in mixtures. This dissertation focuses on diethylpyrocarbonate (DEPC) as an effective CL reagent that can …

Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami

Doctoral Dissertations

We developed decision-analytic models specifically suited for long-term sequential decision-making in the context of large-scale dynamic stochastic systems, focusing on public policy investment decisions. We found that while machine learning and artificial intelligence algorithms provide the most suitable frameworks for such analyses, multiple challenges arise in its successful adaptation. We address three specific challenges in two public sectors, public health and climate policy, through the following three essays. In Essay I, we developed a reinforcement learning (RL) model to identify optimal sequence of testing and retention-in-care interventions to inform the national strategic plan “Ending the HIV Epidemic in the US”. …

High-Dimensional Feature Selection And Multi-Level Causal Mediation Analysis With Applications To Human Aging And Cluster-Based Intervention Studies, Hachem Saddiki

Doctoral Dissertations

Many questions in public health and medicine are fundamentally causal in that our objective is to learn the effect of some exposure, randomized or not, on an outcome of interest. As a result, causal inference frameworks and methodologies have gained interest as a promising tool to reliably answer scientific questions. However, the tasks of identifying and efficiently estimating causal effects from observed data still pose significant challenges under complex data generating scenarios. We focus on (1) high-dimensional settings where the number of variables is orders of magnitude higher than the number of observations; and (2) multi-level settings, where study participants …

Design Of Resposive Oligomeric And Polymeric Interfaces For Sensing And Controlled Release Applications, . Manisha

Doctoral Dissertations

Nature has designed magnificent responsive systems by constructing several interacting molecular level networks for the recognition and propagation of chemical and biochemical information. One of the eminent characteristics of these systems is their capability to quickly transduce molecular scale recognition events into macroscopic or visually observable responses. Inspired by these systems present in nature, we became interested in developing artificial responsive systems with similar capabilities. This dissertation will feature four such systems that employ amphiphilic oligomers and polymers which were chosen as the scaffolds because of their high thermodynamic stability, low critical aggregation concentrations, convenient handles to incorporate functional group …

Structural Analysis Of Protein Therapeutics Using Covalent Labeling – Mass Spectrometry, Patanachai Limpikirati

Doctoral Dissertations

Using mass spectrometry (MS) to obtain information about a higher order structure of protein requires that a protein’s structural properties are encoded into the mass of that protein. Covalent labeling (CL) with reagents that can irreversibly modify solvent accessible amino acid side chains is an effective way to encode structural information into the mass of a protein, as this information can be read-out in a straightforward manner using standard MS-based proteomics techniques. The differential reactivity of proteins under two or more conditions can be used to distinguish protein topologies, conformations, and/or binding sites. CL-MS methods have been effectively used for …

Protein Detection And Structural Characterization By Mass Spectrometry Using Supramolecular Assemblies And Small Molecules, Bo Zhao

Doctoral Dissertations

Mass spectrometry (MS) has played an increasingly prominent role in proteomics and structure biology because it shows superior capabilities in identification, quantification and structural characterization of proteins. To realize its full potential in protein analysis, significant progress has been made in developing innovative techniques and reagents that can couple to MS detection. This dissertation demonstrates the use of polymeric supramolecular assemblies for enhanced protein detection in complex biological mixtures by MS. An amphiphilic random co-polymer scaffold is developed to form functional supramolecular assemblies for protein/ peptide enrichment. The influences of charge density and functional group pK_a on host-guest interactions …

Game-Assisted Rehabilitation For Post-Stroke Survivors, Hee-Tae Jung

Doctoral Dissertations

Stroke is a leading cause of permanent impairments among its survivors. Although patients need to go through intensive, longitudinal rehabilitation to regain function before the stroke, patients show poor engagement and adherence to rehabilitation therapies which hampers their recovery. As a means to enhance stroke survivors' motivation, engagement, and adherence to intensive and longitudinal rehabilitation, the use of games in stroke rehabilitation has received attention from research and clinical communities. In order to realize this, it is important to take a holistic, end-to-end research approach that encompasses 1) the development of game technologies that are not only entertaining but also …

A Computational Study Of Sleep And The Hemispheres Of The Brain, Tera Ashley Glaze

Doctoral Dissertations

"Sleep and sleep cycles have been studied for over a century, and scientists have worked on modeling sleep for nearly as long as computers have existed. Despite this extensive study, sleep still holds many mysteries. Larger and more extensive sleep-wake models have been developed, and the circadian drive has been depicted in numerous fashions, as well as incorporated into scores of studies. With the ever-growing knowledge of sleep comes the need to find more ways to examine, quantify, and define it in the context of the most complex part of the human anatomy -- the brain. Presented here is the …

Detecting, Segmenting And Tracking Bio-Medical Objects, Mingzhong Li

Doctoral Dissertations

"Studying the behavior patterns of biomedical objects helps scientists understand the underlying mechanisms. With computer vision techniques, automated monitoring can be implemented for efficient and effective analysis in biomedical studies. Promising applications have been carried out in various research topics, including insect group monitoring, malignant cell detection and segmentation, human organ segmentation and nano-particle tracking.

In general, applications of computer vision techniques in monitoring biomedical objects include the following stages: detection, segmentation and tracking. Challenges in each stage will potentially lead to unsatisfactory results of automated monitoring. These challenges include different foreground-background contrast, fast motion blur, clutter, object overlap and …

Contribution Of New Thiol Antioxidant In The Treatment Of Acetaminophen Toxicity, Ahdab Naeem Khayyat

Doctoral Dissertations

"Acetaminophen (N-acetyl-p-aminophenol, APAP) is one of the most widely used over-the-counter antipyretic analgesic medications. It is safe at therapeutic doses, but an overdose can result in severe hepato-nephrotoxicity, a leading cause of drug-induced acute liver failure in the U.S. Although a few different mechanisms have been proposed for APAP-induced toxicity, a significant amount of evidence has pointed to the potential involvement of oxidative stress in acetaminophen toxicity. Depletion of glutathione (GSH) is one of the initiating steps in APAP-induced toxicity; therefore, one strategy for restricting organ damage is to restore GSH levels by using GSH prodrugs like N-acetylcysteine (NAC). Although …

Developing An Optimal Model For Infant Home Visitation, Isaac Atuahene

Doctoral Dissertations

The United States, Great Britain, Denmark, Canada and many other countries have accepted home visitation (HV) as a promising strategy for interventions for infants after births and for their mothers. Prior HV studies have focused on theoretical foundations, evaluations of programs, cost/benefit analysis and cost estimation by using hospital/payer/insurance data to prove its effectiveness and high cost. As governments and private organizations continue to fund HVs, it is an opportune time to develop and formulate operations research (OR) models of HV coverage, quality and cost so they might be used in program implementation as done for adult home healthcare (HHC) …

Evaluating The Effects Of Standardized Patient Care Pathways On Clinical Outcomes, Anna V. Romanova

Doctoral Dissertations

The main focus of this study is to create a standardized approach to evaluating the impact of the patient care pathways across all major disease categories and key outcome measures in a hospital setting when randomized clinical trials are not feasible. Toward this goal I identify statistical methods, control factors, and adjustments that can correct for potential confounding in observational studies. I investigate the efficiency of existing bias correction methods under varying conditions of imbalanced samples through a Monte Carlo simulation. The simulation results are then utilized in a case study for one of the largest primary diagnosis areas, chronic …

Population Modeling For Resource Allocation And Antimicrobial Stewardship, Jason Bintz

Doctoral Dissertations

This dissertation contains two types of population models with applications in conservation biology and epidemiology. In particular, it considers models for resource allocation and antimicrobial stewardship.

In a population model with a parabolic differential equation and density dependent growth, we study the problem of allocating resources to maximize the net benefit in the conservation of a single species while the cost of the resource allocation is minimized. The net benefit is measured in terms of maximizing population abundance and the goal of maximizing abundance is divided between the goal of maximizing the overall abundance across space and time and the …

Model-Based Guidance For Human-Intensive Processes, Stefan Christov

Doctoral Dissertations

Human-intensive processes (HIPs), such as medical processes involving coordination among doctors, nurses, and other medical staff, often play a critical role in society. Despite considerable work and progress in error reduction, human errors are still a major concern for many HIPs. To address this problem of human errors in HIPs, this thesis investigates two approaches for online process guidance, i.e., for guiding process performers while a process is being executed. Both approaches rely on monitoring a process execution and base the guidance they provide on a detailed formal process model that captures the recommended ways to perform the corresponding HIP. …

Evaluating Predictors Of An Individual’S Dietary Intake Latent Value Under Different Mixed Models, Shuli Yu

Doctoral Dissertations

The accurate estimation of an individual’s usual dietary intake is important since the estimates are essential to uncover the diet-disease relationships. This study explores a more accurate method to estimate an individual’s latent value of usual dietary intake when it is repeatedly measured using a 24-hour dietary recall (24HR) and seven day dietary recall (7DDR), accounting for random measurement error and bias. The performance of the (empirical) predictor of subject’s latent value obtained under the finite population mixed model (FPMM) framework is compared with those obtained under the usual mixed model and the measurement error model through a simulation study. …

Ligand-Receptor Interactions For Supramolecular Disassembly With Applications In Screening And Drug Delivery, Diego Amado Torres

Doctoral Dissertations

Proteins have the capacity to bind specific sets of compounds known as ligands, these are small molecules with a recurrent theme in their molecular design that is a characteristic exploited here to (i) identify particular affinities of small molecules for proteins with the aim of using them as ligands, inhibitors, or targeting moieties in more complex systems by means of a methodology that screens small molecules based on protein affinity; (ii) decorate a self-assembling supramolecular system at different positions, making it responsive to a complementary protein with the aim of exploring differences in disassembly and sensitivity of the release of …

Associations Of Total Activity Counts And Physical Activity Intensity Levels With The Metabolic Syndrome: A Structural Equation Modeling Approach, Dana Lizbeth Wolff

Doctoral Dissertations

To clarify the protective benefits of physical activity (PA), epidemiologists and public health researchers continue to seek improved methods of assessing PA. In particular, accelerometers have gained acceptance with researchers as they provide reliable estimates of PA and can record both the amount and intensity of ambulatory movement. However, there is concern that accelerometer data reduction techniques may not provide quantitatively accurate measurements of time spent in various PA intensity categories. One way to circumvent these inaccuracies is to use the accelerometer-derived total activity counts (TAC), which is a more direct expression of what the monitor records.

In order to …

Automated Classification Of Malignant Melanoma Based On Detection Of Atypical Pigment Network In Dermoscopy Images Of Skin Lesions, Nabin K. Mishra

Doctoral Dissertations

“Melanoma causes more deaths than any other form of skin cancer. Early melanoma detection is important to prevent progression to a more deadly stage. Automated computer-based identification of melanoma from dermoscopic images of skin lesions is the most efficient method in early diagnosis. An automated melanoma identification system must include multiple steps, involving lesion segmentation, feature extraction, feature combination and classification. In this research, a classifier-based approach for automatically selecting a lesion border mask for segmentation of dermoscopic skin lesion images is presented. A logistic regression based model selects a single lesion border mask from multiple border masks generated by …

Design And Synthesis Of Novel Sultams As Non-Nucleoside Inhibitors Of Hiv Reverse Transcriptase, Brian Chadwick Lecroix

Doctoral Dissertations

The compound 2-methyl-3-phenyl-2,3-dihydro-1,2-benzisothiazole 1,1-dioxide (NSC 108406) was identified as an HIV-1 reverse transcriptase inhibitor by the National Cancer Institute. Using this lead, the Baker group has developed a series of analogues with various groups at the 3-position that show a spectrum of biological activities. In the end, the substituents used could not compare to the biological activity of the inhibitor efavirenz (Sustiva^® [trademark]), and so it was decided to synthesize sultams with alkylethynyl substituents at the 3-position of the sultams in an attempt to mimic the activity of efavirenz.

Previous research analyzed the proposed novel sultams in the modeling …

Geographic And Temporal Epidemiology Of Campylobacteriosis, Jennifer Weisent

Doctoral Dissertations

Campylobacteriosis is a leading cause of gastroenteritis in the United States. The focus of this research was to (i) analyze and predict spatial and temporal patterns and associations for campylobacteriosis risk and (ii) compare the utility of advanced modeling methods. Laboratory-confirmed Campylobacter case data, obtained from the Foodborne Diseases Active Surveillance Network were used in all investigations.

We compared the accuracy of forecasting techniques for campylobacteriosis risk in Minnesota, Oregon and Georgia and found that time series regression, decomposition, and Box-Jenkins Autoregressive Integrated Moving Averages reliably predict monthly risk of infection for campylobacteriosis. Decomposition provided the fastest, most accurate, user-friendly …

A Comparison Of Two Teaching Methods For Pediatric Medication Administration: Multimedia And Text-Based Modules, Renee Granados

Doctoral Dissertations

A Comparison of Two Teaching Methods for Pediatrics: Multimedia and Text-based Modules to Teach Pediatric Medication Administration

Nurse educators are in a position to design and develop effective methods that consider the cognitive structures and how the mind processes information to teach pediatric medication content to nursing students. The majority of methods teaching medication administration use only one mode: the visual mode. One mode to present leaning material does not take advantage of the additive effects of using two modes to present learning material.

The purpose of the study was to compare the effectiveness of two teaching methods to present …

Development Of A Novel Technique For Predicting Tumor Response In Adaptive Radiation Therapy, Rebecca Marie Seibert

Doctoral Dissertations

This dissertation concentrates on the introduction of Predictive Adaptive Radiation Therapy (PART) as a potential method to improve cancer treatment. PART is a novel technique that utilizes volumetric image-guided radiation therapy treatment (IGRT) data to actively predict the tumor response to therapy and estimate clinical outcomes during the course of treatment. To implement PART, a patient database containing IGRT image data for 40 lesions obtained from patients who were imaged and treated with helical tomotherapy was constructed. The data was then modeled using locally weighted regression. This model predicts future tumor volumes and masses and the associated confidence intervals based …