Full text for dissertations and theses included in this collection dates back to 2011. For older dissertations, check the library’s catalog CatalogUSMAI or Dissertations and Theses database.

Recent Submissions

  • The Association of Antiretroviral Treatment and Early Menopause in Women Aging with the Human Immunodeficiency Virus

    Bozzi, Laura; dosReis, Susan; 0000-0001-5326-6521 (2021)
    Women living with HIV (WLWH) have irregular menses with several periods of prolonged amenorrhea but their risk of early menopause, clinically defined as before age 45 years, is unknown. This is largely because there is no gold standard method to confirm menopause. Antimullerian hormone (AMH) is a biomarker indicative of ovarian reserve; however, no prior study has used this to confirm menopause. This study aimed to 1) confirm menopause using AMH; 2) determine if WLWH are at an increased risk of early menopause compared to at-risk, uninfected women; and 3) evaluate the relationship between time-varying ART use with early menopause in WLWH. Data were derived from the Women’s Interagency HIV Study, which had four enrollment waves from 1994 through 2016 across 11 US clinic sites. Women were followed prospectively from their baseline visit until menopause confirmation, loss to follow up, or end of study (12/31/2018), whichever came first. The study cohort was women ages 18 or older with no history of: menopause; hysterectomy/uterine cancer/double oophorectomy; any type of cancer, except skin cancer. Women were censored if they experienced any aforementioned events in follow-up. The study measures confirm menopause were at least 12 months of amenorrhea without resumption of menses and an undetectable AMH (<0.10ng/mL). Age at menopause was determined upon confirmation of final menstrual period. A Cox Proportional Hazards model determined the risk of early menopause among WLWH relative to at-risk uninfected women. Marginal Structural Cox Proportional Hazards models with stabilized weights estimated the effect of >75% adherence to ART, modeled as a time-varying covariate, on the risk of early menopause. Age at confirmed menopause with undetectable AMH was 48.6±4.3 years as compared to 41.2±5.6 years for women with amenorrhea without menses resumption and detectable AMH. WLWH reached menopause at significantly earlier ages and had a two-fold increased risk of experiencing early menopause than at-risk, uninfected women. There was a non-significant protective effect of ≥75% ART adherence on early menopause. AMH can improve the precision in determining age of menopause, which is an integral part of understanding the risk for early menopausal and future planning for postmenopausal care in WLWH.
  • Bile Acids as Biomarkers and Evolutionary Phenotypes

    Shiffka, Stephanie; Swaan, Peter W.; Kane, Maureen A.; 0000-0002-3571-1836 (2021)
    Bile acids (BAs) are the amphipathic end products of cholesterol metabolism and represent a critical means of cholesterol excretion. BAs have a plethora of functions, including digestive roles, homeostatic feedback loops, energy metabolism, regulation of the microbiome, inflammation, and more. These effects implicate BAs in physiological and pathological processes throughout the body, not just within the enterohepatic circuit. To date, BAs have been linked to the pathogenesis of multiple types of cancer, type 2 diabetes mellitus, metabolic syndrome, and neurological disorders, among others. In health, BA homeostasis is precisely regulated by a process termed enterohepatic circulation (EHC). Several transport proteins are instrumental to this process, and disruptions in any of these transport systems lead to dysregulation of BA homeostasis, further leading to complications such as cholestasis and liver disease. BA metabolism and the EHC are conserved throughout vertebrate evolution, but the BA pool of more modern species has been modified to be more hydrophilic while still retaining properties of digestive surfactants. Though EHC is well-characterized, the understanding of eukaryotic transporters in this process is lacking, especially at the molecular level. Despite the recognition of bile acids as signaling molecules involved in disease progression, there remain numerous BAs that are poorly characterized. This is especially important because BAs are an extremely diverse group of molecules that represent the effects of host and microbiome metabolism. Furthermore, the unique physicochemical properties of these variations confer these molecules with differential levels of cytotoxicity and divergent, sometimes opposing, activation of cell signaling pathways. Thus, the scope of this dissertation is two-fold: first, to further characterize the BA pool in health and injury using cell and animal models; secondly, to use this information in order to probe the transporter responsible for the first step of the enterohepatic circulation, ASBT (SLC10A2). Completion of the first objective yielded improved understanding of BA metabolism in cell culture models and non-human primate laboratory models, as well as in radiation injury in the latter model. Accomplishment of the second objective returned insight into ASBT and BA evolution through the use of multiple vertebrate orthologs.
  • Targeting Zinc Finger Proteins with Exogenous Metals and Molecules: Lessons Learned from Tristetraprolin, a CCCH type Zinc Finger

    Ok, Kiwon; Michel, Sarah L. J.; 0000-0002-7724-8860 (2021)
    Zinc (Zn) plays a key role in inflammatory response, including regulating the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathway. Among the signaling proteins involved in the NF-κB pathway, many are known zinc finger proteins (ZFs), including Tristetraprolin (TTP). TTP is a non-classical CCCH-type Zinc Finger protein (ZF), that contains two Cys3His zinc binding domains and is a key regulator of the inflammatory response. TTP is a potential target for exogenous gold (Au) and copper (Cu), as well as hydrogen sulfide, an emerging gasotransmitter. To understand how TTP is targeted by other metals, the interactions of TTP were investigated using a combination of bioinorganic chemistry tools including as optical spectroscopy, native electrospray ionization mass spectrometry (ESI-MS), and X-ray absorption study (XAS). The first metal investigated was Cu(I). I discovered that Cu(I) can bind to the tandem ZF construct of TTP (TTP-2D) and disrupt structure and function. This finding indicates a potential relationship between Cu toxicity and metal-regulation of ZFs. The second metal investigated was Au(III). I discovered that the reactivity of TTP-2D with gold complex leads to Au exchange forming a series of Aux-TTP-2D complexes, with reduction of the gold from Au(III) to Au(I). These protein species are then functionally inactive (no RNA binding). When the same experiments were performed with TTP bound to RNA, the Zn-TTP/RNA complex is not disrupted by the Au-complex suggesting a protective role for RNA. To understand how H2S, a signaling molecule, targets Zn-TTP-2D, its reactivity was determined using a combination of cryo-ESI-MS, fluorescence, and electron paramagnetic resonance (EPR) spectroscopies. We found that the H2S oxidizes the cysteine residues of Zn-TTP via a mechanism that involves atmospheric oxygen, a persulfide intermediate and a radical reaction. The results of these biochemical studies of TTP will be presented in the context of TTP’s biological role. In addition, development of a method to follow Zn speciation in inflammatory cells via liquid chromatography connected to inductively coupled plasma (LC-ICP-MS), will be presented. Here, I use THP-1 cells, which are a human monocyte cell line as a model for inflammation, and demonstrate an approach to separate the zinc-proteome.
  • Use of Machine Learning To Predict COPD Treatments and Exacerbations in Medicare Older Adults: A Comparison of Multiple Approaches

    Le, Tham Thi; Simoni-Wastila, Linda (2021)
    Background: Multiple comorbidities, suboptimal adherence to maintenance medications (MMs), and exacerbations remain clinically important problems among older adults with chronic obstructive pulmonary disease (COPD). To better understand comorbidity profiles and to facilitate risk-based strategies for disease management, this dissertation quantified the prevalence and newly diagnosed rates of comorbidities, and validated predictive models of COPD medication non-adherence and exacerbations in the older Medicare population. Methods: Comorbidities were quantified in COPD beneficiaries and compared with matched non-COPD individuals using multivariable logistic regression. In a cohort of COPD beneficiaries with prevalent and new MM use, logistic and LASSO regressions were used to cross-validate the prediction of one-year non-adherence to MMs using different sets of predictors. A time-varying design was applied to assess improvement in predicting COPD exacerbations of the super learner versus component approaches (logistic regression, elastic net regression, random forest, gradient boosting, and neural network). Results: COPD beneficiaries had significantly increased odds of 40 measured comorbidities relative to matched non-COPD controls. The best-performing models in predicting MM non-adherence were those including initial MM adherence as a predictor, with validated Area Under the ROC Curves (AUC: 0.871-0.881). In predicting COPD exacerbations there were time-varying estimates of predictive accuracy and associations between predictors and the exacerbation outcome. Super learner performed slightly better (AUC: 0.650-0.761) than individual machine learning methods. Conclusions: Comorbidity burden is substantial and increases over time among Medicare older adults with COPD. Generated models achieved good and average discrimination in predicting COPD medication non-adherence and exacerbations, respectively. COPD hospitalization, oxygen supplementation, COPD treatment adherence, and numbers of inpatient visits were the most important predictors of COPD medication non-adherence and exacerbations. Super learner demonstrates a slight improvement compared to component methods, suggesting potential usability in augmenting prediction. Validated models with good discrimination can be adopted using friendly tools to optimizing resources for risk-based management and interventions of COPD.
  • The Creation of Objective Performance Criteria and Generation of Predictive Models among Medical Devices in a Vascular Space

    Gressler, Laura; Shaya, Fadia T.; 0000-0003-2042-2174 (2021)
    Background: Objective Performance Criteria (OPC) have been explored as a tool to address the growing pressures to expedite device approval and enhance active surveillance. Existing data infrastructures can be employed to develop OPC to evaluate the use of devices, and can be further leveraged to develop predictive models. The objective of this dissertation was to: (1) Develop a framework for the creation of OPC, (2) Compare the use of stent, atherectomy, and combination of stent and atherectomy, and (3) Formulate a predictive model used to predict the probability of undergoing a major adverse limb event (MALE) or experiencing death following the aforementioned treatments. Methods: The framework was developed in 3 phases through (1) Review of the literature, (2) Engagement of key stakeholders, and (3) Feedback from an advisory committee. Retrospective cohort studies were conducted using the Vascular Quality Initiative (2010-2018). Logistic regression and the Fine-Gray subdistribution hazard model were used to compare short- and long-term MALE, respectively. A generalized linear model (GLM), a Least Absolute Shrinkage and Selection Operator (LASSO) regularized GLM, a gradient boosted decision tree, and random forest model were compared when used to predict MALE and mortality. Results: The developed framework consisted of 5 elements: (1) Identification of Medical Devices, (2) Engagement of Key Stakeholders, (3) Selection of Data Source, (4) Performance of Appropriate Statistical Analyses, (5) Reporting of Findings. The odds of short-term MALE (0.94;95%CI:0.77-1.14) and hazards of long-term MALE (0.92;95%CI:0.82-1.04) were not significantly different in the combination stent and atherectomy group when compared to stent alone. The most effective predictive model was the gradient boosted decision tree (Area Under the Curve (AUC)= 0.7539) for MALE and the LASSO regularized GLM (AUC=0.7930) for mortality. Conclusions: The developed framework provides a guide and needed foundation for the continued generation of OPC. Applying the identified statistical steps in the framework to an existing data infrastructure showed that patients receiving combination stent and atherectomy do not experience significantly different rates of MALE compared to stent alone. Predictive models generated using the infrastructure demonstrated the ability of machine learning techniques to generate robust predictive models within the vascular space.
  • Excipient Screening and Spray Drying Process Optimization of Cell-based and Protein-based Biologics with Feasibility Demonstration of Oral Delivery

    Lu, Yuwei; Hoag, Stephen W.; 0000-0001-7081-3611 (2021)
    Biologics-based therapeutics, such as proteins and cells, have gained increasing popularity over the past few years. Formulation and process strategies have been applied to achieve quality biologics products, prioritizing desired efficacy and safety over shelf –life. In this thesis research, spray drying formulation development strategies were developed for a novel biotherapeutics ABAB antibody producing Sb-ABAB cells for the treatment of Clostridium difficile infection (CDI) and a recombinant human serum albumin (rHSA) using carbohydrate, protein-based, or other excipients and excipient combinations. Excipient functionality was explored using spectroscopy-based chemometrics investigation. In addition, novel mass spectroscopy based in cell-fast photochemical oxidation of proteins (ICFPOP-MS) was used in combination with homology labeling to probe the excipient - protein interactions. In addition, excipients and water activity effects on the storage stability of the Sb-ABAB spray dried product were explored to optimize shelf life. Subsequently, multivariate data analysis and design of experiments (DOE) were applied to explore the effects of spray dry process parameters on critical quality attributes of the protein- based and cell-based biological products. The spray dried protein/cell powders were further developed into oral dosage forms acceptable for patient use, such as tablets and capsules. The feasibility of developing oral protein tablets using IgG as model protein and enteric-coated Sb-ABAB capsules were explored. For example, compression force, particle size and storage relative humidity effects on the stability of the IgG tablets were investigated via analytical and biophysical analysis. In addition, colon targeted delivery of the Sb-ABAB minicapsules was developed and in vitro release assay was conducted to evaluate the enteric coating efficiency. In conclusion, cell-based and protein-based therapeutics were successfully spray dried while achieving desirable stability during the drying process. Furthermore, protein tablets and controlled release Sb-ABAB capsules were successfully developed, offering a novel alternative delivery approach to biologics products.
  • Optimizing Pain Management in Medically Complex Long-Term Care Residents

    Kuzucan, Aida; Simoni-Wastila, Linda; 0000-0003-0893-7028 (2021)
    Problem statement: While much needed clinical research has emphasized appropriate opioid stewardship in the general population, the needs of long-term nursing home care (LTC) residents remain largely ignored. Methods: This dissertation identified emerging trends in opioid therapy and initial opioid dosing patterns among LTC Medicare beneficiaries using Medicare Parts A, B and D claims, the Minimum Data Set 3.0 (MDS) and LTCFocus datasets. Aim 1 is a repeat cross-section study using resident and facility adjusted generalized estimating equations (GEE) to examine patterns of opioid use alone and in conjunction with pain-adjuvant medications among general, hospice, cancer, non-cancer chronic pain and dementia-related LTC stays from 2011 to 2015. Aim 2 identifies common patterns of average morphine equivalent daily dosing (MEDD) across six 30-day intervals starting with the first opioid prescription using latent class growth modeling (LCGM). Multivariate multinomial regression quantifies associations between different opioid use patterns over time and resident characteristics. Aim 3 accesses the odds of falls among residents with the highest probability of belonging to each of the commonly identified opioid dosing patterns with a facility clustered GEE model. Results: From 2011 to 2015, adjusted analyses found no constant significant changes in dose, duration, or frequency of opioid use. Increased use of anticonvulsant and skeletal muscle relaxants in opioid-related stays, particularly among residents with dementia, were found. LCGM identified four common opioid dosing patterns; extended high, short-term, intermittent and restart. Almost half of LTC residents received extended high opioid dosing. Multinomial regression found significant associations between sex, race, U.S. geographical region, pain diagnosis and receipt of other pain treatments with receipt of extended high dose therapy. Fall odds were found to be similar in the extended high and short-term groups. Models did find increased odds of falls in groups with less opportunity to develop tolerance (i.e., the restart and intermittent groups). Findings were not consistently significant in stratified analyses. Conclusions: Opioid use varies by resident characteristics. Opioid dosing varies over the course of therapy. More research on what factors lead to decisions regarding pain treatment and the impact of opioid dosing strategies on health-related outcomes are warranted.
  • Targeting the Activator Protein-1 Complex to Inhibit Airway Smooth Muscle Cell Hyperproliferation in Asthma

    Defnet, Amy Elizabeth; Shapiro, Paul, Ph.D.; Kane, Maureen A. (2021)
    Hyperproliferation of airway smooth muscle (ASM) cells leads to increased ASM mass causing airway obstruction in inflammatory diseases such as asthma. Currently, there are no effective therapies to modulate ASM cell proliferation that contributes to debilitating bronchoconstriction in severe asthmatics. Previous studies suggest that activator protein-1 (AP-1) transcription factor expression is upregulated in airway cells in asthma and inhibition of AP-1 could mitigate the hyperproliferation of ASM cells. AP-1 activity has been shown to be enhanced by upstream extracellular signal-regulated kinase (ERK1/2) signaling or antagonized by retinoic acid receptor (RAR)-mediated signaling. The overall goal of the current study was to evaluate the therapeutic potential of a combination therapy of an ERK1/2 inhibitor and RAR agonist to modulate AP-1 complex formation and activation. Aim 1 studies tested the hypothesis that a novel function-selective ERK1/2 inhibitor, referred to as SF-3-030, would mitigate off-target toxicity while regulating platelet-derived growth factor (PDGF) induced AP-1 activity and ASM cell proliferation. In Aim 2 studies we evaluated the role of retinoids in controlling AP-1 complex formation and identified a RARγ isoform-specific agonist, CD1530, as a potential therapeutic option for inhibition of AP-1 activity and ASM cell hyperproliferation. Aim 3 studies determined whether a polypharmacological approach of combining ERK1/2 inhibition and RAR agonism to target two different aspects of the AP-1 complex activation and formation would have an additive effect in preventing ASM hyperproliferation. Overall, these studies help further our understanding of how AP-1 signaling causes the hyperproliferation of ASM cells while elucidating possible therapeutic treatment options through ERK1/2 inhibition and RAR agonism.
  • Targeting Aberrant alpha-Helix Mediated Protein-Protein Interactions with Densely Functionalized Heterocycles

    Conlon, Ivie; Fletcher, Steven; 0000-0002-8269-299X (2020)
    Protein-protein interactions (PPIs) play crucial roles in cell proliferation, differentiation, and apoptosis. Apoptosis is a highly regulated process of cell death and its dysregulation can lead to a multitude of different pathophysiologies, such as cancer. In particular, the overexpression of pro-life Bcl-2 proteins, such as Bcl-2, Bfl-1, and Mcl-1, has been linked to cancer progression and tumorigenesis, as well as chemoresistance to a number of different chemotherapeutics. The binding counterparts of these proteins, pro-death Bcl-2 proteins such as Bim, and p53 transactivation domain (TAD), exert their effects through α-helix mediated PPIs with key residues i, i+ 3/4, and i+ 7 oriented on one side of the helix. In addition, HDM2, the E3 ubiquitin protein ligase responsible for the degradation of p53, is upregulated in numerous cancers, and given the similarities of the recognition profiles of Bim-BH3 and p53TAD, we have designed α-helix mimetic inhibitors that target Mcl-1 and HDM2. The first generation of compounds included various heterocyclic scaffolds, including isoxazoles, pyrazoles, and thiazoles, that project functional groups in a similar manner to the native α-helices. In addition, bicyclic scaffolds have been utilized in Mcl-1 selective inhibition. Therefore, we developed a second generation of compounds of isoxazoles, pyrazoles, and functionalized indoles to further explore the binding interface of Mcl-1. The recent resurgence of covalent inhibition and targeted protein degradation has led to the development of successful Bcl-2 family inhibitors. We have designed two tris-aryl α-helix mimetic scaffolds targeting the Bfl-1 pro-life protein. A unique surface-accessible cysteine within the BH3 domain allows for the development of reversible and irreversible small molecule covalent inhibitors. In addition, we have also designed a venetoclax-based PROTAC targeting Bcl-2.
  • From Nanoparticles to Zinc Finger Proteins to Electronic Nicotine Delivery Systems: The Clinical and Biomolecular Evaluation of Potentially Toxic Heavy Metals

    Brandis, Joel; Michel, Sarah L. J.; 0000-0003-2163-5243 (2020)
    Physicochemical Properties of Sodium Ferric Gluconate There are concerns that differences in iron release between brand sodium ferric gluconate (SFG) (Ferrlecit) and generic SFG (generic SFG) intravenous (IV) iron nanoparticle drugs, which are used to treat chronic kidney disease can be caused by differences in the products’ physicochemical properties. However, a standardized, SFG product specific, physicochemical measurement regulatory guidance is not available. Iron core measurements including optical spectroscopy, ICP-MS, XRPD, 57Fe Mössbauer spectroscopy, and XAS, found both products’ cores to be similar ferric-iron-oxide structures. Measurements focused on the carbohydrate shell including forced acid degradation, concentration dependent DLS, AUC, and GPC found differences in particle size, acid stability/iron lability, and molecular weight distribution, that may impact iron release. Cadmium Targeting of Tristetraprolin Zinc finger (ZF) proteins regulate inflammation and are a potential target for cadmium. Zinc bound double Cys3His domain ZF protein tristetraprolin (TTP) regulates inflammation by binding to AU-rich cytokine mRNA. Using a TTP peptide (TTP-2D), Zn2-TTP-2D, cadmium was observed to displace Zn in a concentration dependent manner by spin-filter/ICP-MS coupled to native ESI-MS. Cadmium was also found to displace zinc from RNA bound Zn2-TTP-2D complex (Zn2-TTP-2D/RNA) by ESI in a concentration dependent manner, resulting in Cd1Zn1-TTP-2D/RNA and Cd2-TTP-2D/RNA complexes. Using fluorescence anisotropy cadmium displacement of zinc from Zn2-TTP-2D/RNA complex did not disrupt RNA binding. E-Cig E-liquid Matrix’s Effect on Metal Aerosolization Potentially toxic levels of metals, such as chromium, nickel, copper, and lead, have been reported in e-liquids (liquids composed primarily of a mixture of propylene glycol (PG), glycerol (G)) and nicotine, and generated aerosols of electronic nicotine delivery systems (ENDS). However, the variables that affect metal transfer from the e-liquid to the aerosols are unknown. Using a custom ENDS aerosolization device and aerosolization approach, following CORESTA 81 guidance, the aerosolization of metal spiked model e-liquids (PG and G) were measured. Using ICP-MS to measure aerosol metal content to determine the effect of e-liquid on chromium, nickel, copper, and lead, it was found that all four metals are more readily aerosolized in PG dominant e-liquids than G dominant e-liquids.
  • Development of Fast Photochemical Oxidation of Proteins for in Vivo Modification in Caenorhabditis elegans

    Espino, Jessica; Jones, Lisa M.; 0000-0002-7203-9145 (2020)
    Mass spectrometry (MS) has become widely used for the characterization of protein structure and protein-protein interactions (PPI). Unlike many commonly used structural methods, MS is not limited by the size of molecules, thus allowing for the study of a wide range of purified protein complexes, cells, tissues, and complex organisms. Instrumentation advancements have also decreased the need for large sample concentrations and have increased mass accuracy and resolution. In the past decade, MS-based protein footprinting has become increasingly utilized for the determination of higher-order protein structure and provides residue-level analysis on PPI interaction sites, protein-ligand interactions, and regions of conformational change by covalently modifying the solvent-accessible surface area (SASA) of proteins through the use of a small chemical label. The hydroxyl radical protein footprinting (HRPF) method, fast photochemical oxidation of proteins (FPOP), utilizes hydroxyl radicals (•OH) to oxidatively modify solvent-accessible amino acid side chains. These radicals are generated via hydrogen peroxide photolysis using a KrF excimer laser at a 248 nm wavelength. To date, most applications of FPOP have been performed in vitro in relatively pure protein systems. Most notably, it has been applied for antibody epitope mapping, protein folding, and protein aggregation. This work focuses on the extension of FPOP for in vivo protein structural analysis in Caenorhabditis elegans, a method entitled in vivo FPOP (IV-FPOP). FPOP is particular suited for in vivo protein studies because of the irreversible nature of the modification, which mitigates time constraints with respect to sample preparation, proteomic digestion, and sample processing. Additionally, the •OH generated can label 19 out of 20 amino acids allowing for the study of multiple proteins regardless of protein sequence or cellular location. Given the complexity of the platform, numerous parameters required optimization for maximum labeling efficiency including the development of a microfluidic flow system for the labeling of worms by IV-FPOP, hydrogen peroxide concentration optimization, and the addition of chemical penetration enhancers to increase hydrogen peroxide uptake by the worm, and the implementation of a multiplexing proteomics platform increased throughput of IV-FPOP oxidatively modified peptides.
  • Determining the Mechanism and Regulation of the Heme Assimilation System (Has) in Pseudomonas aeruginosa Heme Signaling and Acquisition

    Dent, Alecia T.; Wilks, Angela; 0000-0002-6376-7482 (2020)
    Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen that causes infections in immunocompromised populations including patients with cystic fibrosis, surgical site wounds and pneumonia. Like most other bacterial pathogens, Pseudomonas requires iron for survival and virulence and has adapted several mechanisms including utilizing heme as an iron source. P. aeruginosa encodes two nonredundant heme uptake systems, the heme assimilation system (has) and Pseudomonas heme utilization (phu) pathways. Proteomic and RNA seq analysis of P. aeruginosa show the Has pathway is one of the most upregulated during infection and knockout strains of HasR reduce the pathogenicity of the bacteria in mice elevating it as a potential drug target. Despite previous studies of the S. marcescens Has pathway there has been no comprehensive study of the molecular mechanism by which heme is sensed and transported by the Has pathway. The work herein utilizes a combination of site-directed mutagenesis of the extracellular hemophore HasAp, allelic exchange, quantitative PCR analyses, immunoblotting and 13C-heme uptake studies to elucidate both the mechanism of heme release from HasAp to HasR and its requirement for initiation of the extracellularcytoplasmic function (ECF) HasIS sigma/anti-sigma factor system. Furthermore, I show in contrast to the S. marcescens system the hasIS operon is not subject to autoregulation by HasI, but rather post-transcriptional regulation through modulation of HasAp. Employing similar approaches with the outer membrane receptor HasR, I determined heme capture by H221 on the plug domain of HasR is required for signaling and transport, whereas mutations to the extracellular FRAP/PNPL loop H624 and L8 loop Ile694 are competent to signal but not transport heme. Based on my studies, I propose a model for heme signaling and transport by the P. aeruginosa Has system that provides a foundation for further studies of heme uptake and a starting point for the development of novel antimicrobial strategies.
  • Expanding the Use of FPOP for In Vitro and In Cell Studies

    Chea, Emily E.; Jones, Lisa M. (2020)
    Studying higher order protein structure is crucial to better understand protein interactions and functions. Mass spectrometry (MS) has been an invaluable tool to better understand protein structure. Several techniques, like protein footprinting, are coupled with mass spectrometry to gain information on protein structure and changes in protein-protein and protein-ligand interactions. Hydroxyl radical protein footprinting (HRPF) utilizes hydroxyl radicals to irreversibly label solvent-exposed side chains of 19 out of the 20 amino acids. Traditionally, modified regions are detected using bottom-up proteomics and with MS/MS analysis, residue level information can be obtained. There are a handful of techniques to generate hydroxyl radicals, one is fast photochemical oxidation of proteins (FPOP). FPOP generates hydroxyl radicals through the photolysis of hydrogen peroxide using a 248 nm excimer laser. My research aims to expand the use of FPOP for in vitro and in cell studies. For in-vitro FPOP the first objective was to validate the use of FPOP to study proteins in their native structure. In all protein footprinting techniques, it is crucial to label while the protein remains in its native structure and ensure labeling does not take place if the protein begins to unfold. To confirm FPOP probed proteins in their native state, the enzymatic activity of proteins were measured before and after FPOP. The second objective was to combine FPOP with native MS, ion mobility separation (IMS), and top-down proteomics to gain additive structural information. Next, the use of in-cell FPOP (IC-FPOP) as a tool for proteome wide structural biology (PWSB) was expanded to characterize drug interactions in cells. First, IC-FPOP was used to highlight the differing effect of Gleevec in triple negative breast cancer (TNBC) for a European ancestry (TNBC-EA) and African ancestry (TNBC-AA) cell line. Finally, IC-FPOP efficacy in probing methotrexate’s effects in a chronic myelogenous leukemia (CML) was compared to cellular thermal shift assay (CETSA). CETSA is a recognized method that can be used to track drug interactions across the full proteome. However, there are some limitations to using CETSA which IC-FPOP can help overcome thus improving the characterization of drug interactions in cells.
  • Mapping Expanded Prostate Cancer Index Composite (EPIC) Questionnaire to EuroQoL-5D (EQ-5D) Utility Weights to Inform Economic Evaluations for Prostate Cancer

    Khairnar, Rahul; Palumbo, Francis Bernard, 1945- (2020)
    OBJECTIVES: To develop a mapping algorithm to obtain EuroQoL-5D-3L (EQ5D) health utilities from Expanded Prostate Cancer Index Composite (EPIC) questionnaire. METHODS: This mapping study utilized baseline data from an international, multicenter, randomized controlled trial (NCT00331773) of patients with low-risk prostate cancer. Patient health-related quality-of-life (HRQoL) data were collected using EPIC and health utilities were obtained using EQ5D. Data were divided into an estimation sample (n=765, 70%) and a validation sample (n=327, 30%). The relationship between the instruments was estimated using ordinary least squares (OLS), Tobit, and two-part models. Five-fold cross-validation (in-sample) was used to compare the predictive performance of the estimated models. Final models were selected based on root mean square error (RMSE). OLS models using baseline cross-sectional data, combined data from all assessment periods, and random effects (RE) models that explicitly model the longitudinal nature of the data were estimated to compare predictive ability of algorithms derived from cross-sectional and longitudinal data. Longitudinal predictive performance of OLS models derived using baseline data was examined in the post-intervention data. RESULTS: A total of 565 patients in the estimation sample had complete information on both EPIC and EQ5D questionnaires at baseline. Mean observed EQ5D utility was 0.90±0.13 (range: 0.28-1) with 55% of patients in full health. Low to moderate correlations were found between EQ5D utility and urinary (r=0.38), bowel (r=0.34) and hormonal (r=0.55) domains of EPIC; sexual domain was weakly correlated (r=0.18) with EQ5D utility. OLS models outperformed their counterpart models for all pre-determined model specifications. The best model fit was: “EQ5D utility = 0.248541 + 0.000748*(Urinary Function) + 0.001134*(Urinary Bother) + 0.000968*(Hormonal Function) + 0.004404*(Hormonal Bother) – 0.376487*(Zubrod) + 0.003562*(Urinary Function*Zubrod)”; RMSE was 0.10462. When comparing cross-sectional vs. longitudinal data, a mapping algorithm obtained using combined EPIC subdomain data outperformed other model types. Mean absolute differences (MDs) between reported and predicted were low in general and decreased as the time of assessment increased. CONCLUSIONS: This study identified mapping algorithms to generate EQ5D utilities from EPIC domain or sub-domain scores, with satisfactory longitudinal predictive performance. The study results will help estimate quality-adjusted life-years in future economic evaluations of prostate cancer treatments.
  • Early Symptom Improvement as a Predictor of Antidepressant Response in Children and Adolescents Diagnosed with Depression: Translating Evidence from Randomized Controlled Trials to Community Practice

    Spence, O'Mareen; dosReis, Susan (2020)
    Statement of the Problem: A common problem among children and adolescents diagnosed with depression who receive care in community settings is that antidepressant regimen changes such as psychotropic augmentation may occur soon after starting treatment. This raises the question as to whether such changes are implemented among youth who would otherwise respond to the antidepressant. Thus, the overarching objectives of this dissertation were to 1) distinguish early in treatment children and adolescents who are likely to respond, and 2) empirically evaluate the association between predicted response and psychotropic augmentation or switching in real world settings. Summary of Methods: Using randomized clinical trial (RCT) data, this research applied a Bayesian approach to predict the likelihood of initial (12 week) and sustained (18 week) response to treatment as a function of early changes in depressive symptoms (i.e. mood, somatic, subjective and behavioral) and other demographic and clinical factors. An innovative application of combined sample multiple imputations (CSMI) was used to estimate the 12-week predicted probability of response among commercially insured adolescents who received care in real-world settings. Each adolescent received a probability of treatment response, which was then used to compare the odds of psychotropic augmentation or switch. Results: Early changes in mood and somatic symptoms within the first six weeks of treatment are primary predictors of initial (at 12 weeks) and sustained (at 18 weeks) response to an antidepressant. Baseline depression severity is an important prognostic factor for initial response, and additional, though minimal improvement, in somatic symptoms from weeks 6 to 12 is indicative of sustained response. In a highly selected cohort of adolescents receiving care in community settings, an augmentation or switch occurred similarly among adolescents with a high versus low likelihood of responding to fluoxetine. Conclusion: The results suggest that other factors beyond expected antidepressant response (or lack thereof) might influence current treatment practices. Our findings have clinical and public health implications that support measurement-based care in pediatric depression. Our application of CSMI highlights several key areas of consideration for future pharmacoepidemiologic research aimed at translating RCT evidence to real world data to better understand clinical practices patterns.
  • Follicular Lymphoma Stage at Diagnosis: Determinants, Prediction from Administrative Claims Data and Impact on Healthcare Costs

    Albarmawi, Husam; Onukwugha, Eberechukwu (2020)
    Introduction: Follicular lymphoma (FL) stage is an important determinant of survival, treatment options and treatment outcomes. However, the determinants of advanced FL, defined as Ann Arbor stages III and IV, and its impact on the economic burden of FL are unknown. Moreover, for studies that rely on administrative claims data, it is not clear if advanced FL can be accurately predicted from this data source. Methods: Using the linked Surveillance, Epidemiology, and End Results-Medicare database we identified patients newly diagnosed with FL. We estimated a modified Poisson regression to explore the effect of pre-diagnosis healthcare resource utilization patterns and baseline county-level factors on FL stage. We estimated the 1-year and 5-year incremental costs of stages II-IV compared to stage I using generalized linear models. To predict FL stage from claims data, we developed and tested two random forests models. Results: We identified 11,078 patients diagnosed in 2000-2013. Half of the sample had advanced FL. Higher counts of specialist physician visits in the 3 years pre-diagnosis were associated with lower risk of advanced FL (4th quartile vs. 1st quartile: Relative Risk [RR]=0.92; 95% CI=0.86–0.99). The risk of advanced FL was 8% lower among women receiving screening mammography compared to men (RR=0.92; 95% CI=0.88–0.97). Living in counties designated as health professional shortage areas (HPSA) was associated with 7% increased risk of advanced FL (RR=1.07; 95% CI=1.00–1.14, p=0.049). In 2004-2009, FL patients with stages II, III and IV had statistically higher 1-year ($14,911; $15,106; $24,639, respectively, p<0.01) and 5-year costs ($21,590; $23,599; $34,968, respectively, p<0.01) compared to stage I patients. The random forests models exhibited poor accuracy of classifying limited and advanced FL from Medicare claims data (accuracy: ≤64%; sensitivity: ≤72%; specificity: ≤57%). Conclusions: Higher frequencies of specialist physician visits and living in counties with no HPSA can reduce the risk of presenting with advanced FL. Patients with stages II-IV incur significantly higher costs compared to stage I patients. The incremental cost increases with higher FL stage. Predicting advanced FL from claims data may not be feasible and researchers may need to rely on datasets with existing clinical information.
  • Effect of Transient Heat Exposure on Drug Delivery from Transdermal and Topical Products

    Thomas, Sherin; Stinchcomb, Audra L. (2020)
    Heating pads and electric blankets are widely used for relief from pain and to provide warmth, respectively. Their unintentional application simultaneously with a transdermal or topical system can result in unexpected drug levels in systemic circulation. Designing well-characterized in vitro and in vivo methods are vital to understanding the effect of heat and hence can aid in the development and evaluation of these products. The objective of this work was to evaluate the effect of heat on products with the same active pharmaceutical ingredient (API) but different inactive ingredients. Four drug molecules with different physicochemical properties were chosen. For each drug, formulations with different excipients were selected. In vivo serum drug profile and in vitro flux profile data can provide mechanistic understanding of heat effect on these formulations. Four topical diclofenac formulations were evaluated for heat effect in vitro under continuous heat exposure. Their flux profiles demonstrated the influence of formulation design and excipients on drug permeation at elevated skin temperature. Serum profiles of two different oxybutynin formulations evaluated under heat exposure showed very different magnitude of enhancement in serum levels under similar heat exposure conditions. Another objective of this work was establishing an in vitro - in vivo correlation (IVIVC) of heat effect on topical and transdermal formulations. This will help in characterizing and predicting heat effect minimizing the need of clinical trials and support the regulatory evaluation of these dosage forms. For buprenorphine patch, study design for in vitro permeation testing (IVPT) using human skin was well characterized to align with and mimic in vivo conditions of heat exposure. Level A and Level C IVIVC were established under normal as well as elevated temperature conditions. For lidocaine patches, IVIVC was observed for early heat effect. However, poor correlation was observed for late heat effect. The findings from this work determined IVPT studies can correlate with and be predictive of in vivo results under normal temperature conditions. But under suboptimal conditions like heat exposure, IVPT may have limitations and should be used in addition to other methods to evaluate heat effect.
  • Evaluation of the Equivalency of Generic Drugs

    Das, Sharmila; Polli, James E. (2020)
    The objective of this dissertation is to assess the bioequivalence of generic drugs. Patients with epilepsy complain about more seizures and side effects after brand-generic or generic-generic switching of an anti-epileptic drug (AED). Generic brittleness (GB) is the familiar notion that, upon switching between AEDs of pharmaceutical equivalents, a patient experiences negative outcome. Aim 1 is to probe the individual patient attributes thought to predispose a patient to generic brittleness. At the University of Maryland Medical Center, 148 patients from the outpatient epilepsy clinic were recruited for an observational case-control study. An algorithm for being GB (40% of patients) and not GB was devised. A patient with epilepsy was categorized as GB if the patient negatively opined about generics and was taking brand of their most problematic AED when generic was available. Two demographic factors that increased the odds of being GB were a patient currently taking a problem AED and increasing total number of current medications. Interestingly, taking lamotrigine increased and taking any one of six “protective” anti-epileptic drugs decreased the odds of being GB, respectively. Furthermore, no genetic, clinical laboratory or neuropsychiatry tests or their sub-elements differentiated GB patients from not GB patients. Aim 2 involves a comparative pharmacokinetic (PK) analysis upon challenging sixteen GB patients to brand-generic or generic-generic switch of an AED that they are currently on, using a four-way crossover replicate design. For each patient, test and reference PK profiles were the same, despite patients being GB. Aim 3 is to assess the noninferiority of the generic sodium ferric gluconate (SFG) against the reference product Ferrlecit with respect to drug bound iron (DBI), after single dose intravenous administration of brand and generic SFG in 44 healthy volunteers. Using a two-way crossover replicate design, plasma PK profiles of SFG to Ferrlecit were the same across two iron species (e.g. DBI and NTBI), although adverse event rates differed. In conclusion generics of AEDs and intravenous sodium ferric gluconate are bioequivalent to the brand-name drugs. Results support FDA criteria for bioequivalence in regards to AEDs and complex iron products.
  • From Data to Decisions: Utilizing Pharmacometrics to Optimize Clinical Therapeutics and Drug Development in Neuropsychiatry

    Kalaria, Shamir; Gopalakrishnan, Mathangi (2020)
    At least 50% of clinical trials of neuropsychiatric compounds fail due to an unclear understanding of disease pathophysiology and drug pharmacology. Further, lack of dosing information in special patient populations for approved neuropsychiatric drugs could contribute to suboptimal outcomes. The current research highlights the role of pharmacometrics in (i) optimizing therapeutics in patients receiving antiepileptics and continuous renal replacement therapy (CRRT) and (ii) informing efficient trial design for binge eating disorder (BED). Currently, no dosing recommendations exist for CRRT patients receiving antiepileptics. Real-world clinical studies were conducted to characterize the pharmacokinetics of levetiracetam and lacosamide in patients (N=18) receiving CRRT at the University of Maryland Medical Center. Major determinants for drug clearance were drug-specific extraction coefficient (EC) approximated to fraction unbound (levetiracetam: 0.89, lacosamide: 0.80), effluent flow rate, and preserved non-renal clearance. Ex-vivo models of CRRT were developed using human plasma and normal saline containing albumin solutions. The developed ex-vivo in-vivo correlation model demonstrated an average bias of <15% in predicting in-vivo CRRT clearance for levetiracetam and lacosamide. Similarity in ECs justified the ability to bridge dosing information across CRRT modalities. This research, in combination with a priori knowledge of drug pharmacokinetics, confirms the use of ex-vivo CRRT models to establish dosing recommendations and alleviate the need for CRRT pharmacokinetic studies. The development of BED therapies are challenged by high placebo response and high dropout rates in clinical trials. A comprehensive disease-drug-trial (DDT) model was developed using data from 12 different investigator-led BED clinical trials (N = 578; 6 to 16-week duration) to inform optimal clinical trial design elements. Baseline BED severity metrics were predictors for placebo response and dropouts. Stimulants and anticonvulsants demonstrated 1.8 times higher effect differences as compared to antidepressants. Among the clinical trial designs (placebo run-in, drug run-in, sequential parallel comparison design) evaluated in-silico, placebo-controlled trial of shorter (6-week) duration with model-based analysis demonstrated superior trial design properties (40% lower sample size with 50% lower dropouts) as compared to current 12-week registration trials for BED. The proposed DDT framework can inform efficient trial design and potentially increase the number of therapeutic options for BED.
  • Pharmacometric Approaches to Precision Therapeutic Management for Antimicrobials

    Wang, Hechuan; Ivaturi, Vijay (2020)
    Antimicrobials have been widely used for decades in the treatment of various types of bacterial infections and their properties have been thoroughly characterized in pediatric and adult patients. However, high variability and unpredictability of antimicrobials’ pharmacokinetics (PK) in patients still exist, which reinforces the value of precision dosing. The research in this thesis highlights the role of pharmacometrics in precision therapeutic management of two prototype antimicrobials, gentamicin and rifampin. The first project developed a Bayesian forecasting algorithm for precision dosing of gentamicin in pediatrics. We developed the first population PK model for gentamicin across the whole pediatric age spectrum ranging from 1-day-old newborns to 19-year-old young adults. The model utilized physiologically plausible covariate parameterization driven by principles of allometric scaling. Renal function changes manifested by glomerular filtration were described by postmenstrual age, and serum creatinine was standardized by age. The model was used as a prior in the subsequent full Bayesian analyses in pediatric patients. A full Bayesian analysis-based model-informed precision dosing (MIPD) was introduced for gentamicin dosing in pediatric patients. With a predefined probability of target attainment (PTA) criteria of 70% for both maximum and trough concentrations, the dosing regimens recommended by the empirical dosing guideline NeoFax could achieve the predefined criteria in about 5% of the 1013 patients, in comparison with 90% of the patients when the initial dosing recommendation from the MIPD approach was used. Finally, a workflow was designed for a new patient in a clinical scenario to provide MIPD for initial dosing recommendation and dosing adjustment after TDM level becomes available via a full Bayesian approach. The second project focuses on dose optimization of rifampin in adult patients with tuberculosis through dynamic positron emission tomography (PET) scans. A semi-mechanistic PK-lung-biodistribution model was developed based on plasma and intralesional drug concentration data measured by PET scans. The model could well predict the mass spectrometry data from therapeutic dose and PET data from 11C-labled micro-dose. The developed model was externally validated through exposure predictions in the therapeutic range of 10-35 mg/kg. Based on the projected drug exposure in the cavity walls at higher rifampin doses, the bacterial killing curves obtained from hollow fiber systems were used to predict the clinical cure rates in humans for higher rifampin doses (>600mg). Standard oral rifampin dosing of 10 mg/kg would achieve a 95% probability of cure in 6-9 months of treatment. Similarly, an oral rifampin dose of at least 35 mg/kg would be needed to cure patients in 4 months.

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