Matching Items (83)
Description
Yersinia enterocolitica is a major foodborne pathogen found worldwide that causes approximately 87,000 human cases and approximately 1,100 hospitalizations per year in the United States. Y. enterocolitica is a very unique pathogen with the domesticated pig acting as the main animal reservoir for pathogenic bio/serotypes, and as the primary source of human infection. Similar to other gastrointestinal infections, Yersinia enterocolitica is known to trigger autoimmune responses in humans. The most frequent complication associated with Y. enterocolitica is reactive arthritis - an aseptic, asymmetrical inflammation in the peripheral and axial joints, most frequently occurring as an autoimmune response in patients with the HLA-B27 histocompatability antigen. As a foodborne illness it may prove to be a reasonable explanation for some of the cases of arthritis observed in past populations that are considered to be of unknown etiology. The goal of this dissertation project was to study the relationship between the foodborne illness -Y. enterocolitica, and the incidence of arthritis in individuals with and without contact with the domesticated pig.
ContributorsBrown, Starletta (Author) / Hurtado, Ana M (Thesis advisor) / Chowell-Puente, Gerardo (Committee member) / Hill, Kim (Committee member) / Arizona State University (Publisher)
Created2015
Description
Despite the safe and effective use of attenuated vaccines for over fifty years, measles virus (MV) remains an insidious threat to global health. Problematically, infants less than one year of age, who are the most prone to severe infection and death by measles, cannot be immunized using current MV vaccines. For this dissertation, I generated and performed preclinical evaluation of two novel MV vaccine candidates. Based on data from clinical trials that showed increasing the dosage of current MV vaccines improved antibody responses in six-month-old recipients, I hypothesized that increasing the relevant antigenic stimulus of a standard titer dose would allow safe and effective immunization at a younger age. I generated two modified MVs with increased expression of the hemagglutinin (H) protein, the most important viral antigen for inducing protective neutralizing immunity, in the background of a current vaccine-equivalent. One virus, MVvac2-H2, expressed higher levels of full-length H, resulting in a three-fold increase in H incorporation into virions, while the second, MVvac2-Hsol, expressed and secreted truncated, soluble H protein to its extracellular environment. The alteration to the virion envelope of MVvac2-H2 conferred upon that virus a measurable resistance to in vitro neutralization. In initial screening in adult mouse models of vaccination, both modified MVs proved more immunogenic than their parental strain in outbred mice, while MVvac2-H2 additionally proved more immunogenic in the gold standard MV-susceptible mouse model. Remarkably, MVvac2-H2 better induced protective immunity in the presence of low levels of artificially introduced passive immunity that mimic the passive maternal immunity that currently limits vaccination of young infants, and that strongly inhibited responses to the current vaccine-equivalent. Finally, I developed a more physiological infant-like mouse model for MV vaccine testing, in which MV-susceptible dams vaccinated with the current vaccine-equivalent transfer passive immunity to their pups. This model will allow additional preclinical evaluation of the performance of MVvac2-H2 in pups of immune dams. Altogether, in this dissertation I identify a promising candidate, MVvac2-H2, for a next generation measles vaccine.
ContributorsJulik, Emily (Author) / Reyes del Valle, Jorge (Thesis advisor) / Chang, Yung (Committee member) / Blattman, Joseph (Committee member) / Hogue, Brenda (Committee member) / Nickerson, Cheryl (Committee member) / Arizona State University (Publisher)
Created2016
Description
The 2009-10 influenza and the 2014-15 Ebola pandemics brought once again urgency to an old question: What are the limits on prediction and what can be proposed that is useful in the face of an epidemic outbreak?
This thesis looks first at the impact that limited access to vaccine stockpiles may have on a single influenza outbreak. The purpose is to highlight the challenges faced by populations embedded in inadequate health systems and to identify and assess ways of ameliorating the impact of resource limitations on public health policy.
Age-specific per capita constraint rates play an important role on the dynamics of communicable diseases and, influenza is, of course, no exception. Yet the challenges associated with estimating age-specific contact rates have not been decisively met. And so, this thesis attempts to connect contact theory with age-specific contact data in the context of influenza outbreaks in practical ways. In mathematical epidemiology, proportionate mixing is used as the preferred theoretical mixing structure and so, the frame of discussion of this dissertation follows this specific theoretical framework. The questions that drive this dissertation, in the context of influenza dynamics, proportionate mixing, and control, are:
I. What is the role of age-aggregation on the dynamics of a single outbreak? Or simply speaking, does the number and length of the age-classes used to model a population make a significant difference on quantitative predictions?
II. What would the age-specific optimal influenza vaccination policies be? Or, what are the age-specific vaccination policies needed to control an outbreak in the presence of limited or unlimited vaccine stockpiles?
Intertwined with the above questions are issues of resilience and uncertainty including, whether or not data collected on mixing (by social scientists) can be used effectively to address both questions in the context of influenza and proportionate mixing. The objective is to provide answers to these questions by assessing the role of aggregation (number and length of age classes) and model robustness (does the aggregation scheme selected makes a difference on influenza dynamics and control) via comparisons between purely data-driven model and proportionate mixing models.
This thesis looks first at the impact that limited access to vaccine stockpiles may have on a single influenza outbreak. The purpose is to highlight the challenges faced by populations embedded in inadequate health systems and to identify and assess ways of ameliorating the impact of resource limitations on public health policy.
Age-specific per capita constraint rates play an important role on the dynamics of communicable diseases and, influenza is, of course, no exception. Yet the challenges associated with estimating age-specific contact rates have not been decisively met. And so, this thesis attempts to connect contact theory with age-specific contact data in the context of influenza outbreaks in practical ways. In mathematical epidemiology, proportionate mixing is used as the preferred theoretical mixing structure and so, the frame of discussion of this dissertation follows this specific theoretical framework. The questions that drive this dissertation, in the context of influenza dynamics, proportionate mixing, and control, are:
I. What is the role of age-aggregation on the dynamics of a single outbreak? Or simply speaking, does the number and length of the age-classes used to model a population make a significant difference on quantitative predictions?
II. What would the age-specific optimal influenza vaccination policies be? Or, what are the age-specific vaccination policies needed to control an outbreak in the presence of limited or unlimited vaccine stockpiles?
Intertwined with the above questions are issues of resilience and uncertainty including, whether or not data collected on mixing (by social scientists) can be used effectively to address both questions in the context of influenza and proportionate mixing. The objective is to provide answers to these questions by assessing the role of aggregation (number and length of age classes) and model robustness (does the aggregation scheme selected makes a difference on influenza dynamics and control) via comparisons between purely data-driven model and proportionate mixing models.
ContributorsMorales, Romarie (Author) / Castillo-Chavez, Carlos (Thesis advisor) / Mubayi, Anuj (Thesis advisor) / Towers, Sherry (Committee member) / Arizona State University (Publisher)
Created2016
Description
Extraordinary medical advances have led to significant reductions in the burden of infectious diseases in humans. However, infectious diseases still account for more than 13 million annual deaths. This large burden is partly due to some pathogens having found suitable conditions to emerge and spread in denser and more connected host populations, and others having evolved to escape the pressures imposed by the rampant use of antimicrobials. It is then critical to improve our understanding of how diseases spread in these modern landscapes, characterized by new host population structures and socio-economic environments, as well as containment measures such as the deployment of drugs. Thus, the motivation of this dissertation is two-fold. First, we study, using both data-driven and modeling approaches, the the spread of infectious diseases in urban areas. As a case study, we use confirmed-cases data on sexually transmitted diseases (STDs) in the United States to assess the conduciveness of population size of urban areas and their socio-economic characteristics as predictors of STD incidence. We find that the scaling of STD incidence in cities is superlinear, and that the percent of African-Americans residing in cities largely determines these statistical patterns. Since disparities in access to health care are often exacerbated in urban areas, within this project we also develop two modeling frameworks to study the effect of health care disparities on epidemic outcomes. Discrepant results between the two approaches indicate that knowledge of the shape of the recovery period distribution, not just its mean and variance, is key for assessing the epidemiological impact of inequalities. The second project proposes to study, from a modeling perspective, the spread of drug resistance in human populations featuring vital dynamics, stochasticity and contact structure. We derive effective treatment regimes that minimize both the overall disease burden and the spread of resistance. Additionally, targeted treatment in structured host populations may lead to higher levels of drug resistance, and if drug-resistant strains are compensated, they can spread widely even when the wild-type strain is below its epidemic threshold.
ContributorsPatterson-Lomba, Oscar (Author) / Castillo-Chavez, Carlos (Thesis advisor) / Towers, Sherry (Thesis advisor) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2014
Description
Urban scaling analysis has introduced a new scientific paradigm to the study of cities. With it, the notions of size, heterogeneity and structure have taken a leading role. These notions are assumed to be behind the causes for why cities differ from one another, sometimes wildly. However, the mechanisms by which size, heterogeneity and structure shape the general statistical patterns that describe urban economic output are still unclear. Given the rapid rate of urbanization around the globe, we need precise and formal mathematical understandings of these matters. In this context, I perform in this dissertation probabilistic, distributional and computational explorations of (i) how the broadness, or narrowness, of the distribution of individual productivities within cities determines what and how we measure urban systemic output, (ii) how urban scaling may be expressed as a statistical statement when urban metrics display strong stochasticity, (iii) how the processes of aggregation constrain the variability of total urban output, and (iv) how the structure of urban skills diversification within cities induces a multiplicative process in the production of urban output.
ContributorsGómez-Liévano, Andrés (Author) / Lobo, Jose (Thesis advisor) / Muneepeerakul, Rachata (Thesis advisor) / Bettencourt, Luis M. A. (Committee member) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2014
Description
The increased number of novel pathogens that potentially threaten the human population has motivated the development of mathematical and computational modeling approaches for forecasting epidemic impact and understanding key environmental characteristics that influence the spread of diseases. Yet, in the case that substantial uncertainty surrounds the transmission process during a rapidly developing infectious disease outbreak, complex mechanistic models may be too difficult to be calibrated quick enough for policy makers to make informed decisions. Simple phenomenological models that rely on a small number of parameters can provide an initial platform for assessing the epidemic trajectory, estimating the reproduction number and quantifying the disease burden from the early epidemic phase.
Chapter 1 provides background information and motivation for infectious disease forecasting and outlines the rest of the thesis.
In chapter 2, logistic patch models are used to assess and forecast the 2013-2015 West Africa Zaire ebolavirus epidemic. In particular, this chapter is concerned with comparing and contrasting the effects that spatial heterogeneity has on the forecasting performance of the cumulative infected case counts reported during the epidemic.
In chapter 3, two simple phenomenological models inspired from population biology are used to assess the Research and Policy for Infectious Disease Dynamics (RAPIDD) Ebola Challenge; a simulated epidemic that generated 4 infectious disease scenarios. Because of the nature of the synthetically generated data, model predictions are compared to exact epidemiological quantities used in the simulation.
In chapter 4, these models are applied to the 1904 Plague epidemic that occurred in Bombay. This chapter provides evidence that these simple models may be applicable to infectious diseases no matter the disease transmission mechanism.
Chapter 5, uses the patch models from chapter 2 to explore how migration in the 1904 Plague epidemic changes the final epidemic size.
The final chapter is an interdisciplinary project concerning within-host dynamics of cereal yellow dwarf virus-RPV, a plant pathogen from a virus group that infects over 150 grass species. Motivated by environmental nutrient enrichment due to anthropological activities, mathematical models are employed to investigate the relevance of resource competition to pathogen and host dynamics.
Chapter 1 provides background information and motivation for infectious disease forecasting and outlines the rest of the thesis.
In chapter 2, logistic patch models are used to assess and forecast the 2013-2015 West Africa Zaire ebolavirus epidemic. In particular, this chapter is concerned with comparing and contrasting the effects that spatial heterogeneity has on the forecasting performance of the cumulative infected case counts reported during the epidemic.
In chapter 3, two simple phenomenological models inspired from population biology are used to assess the Research and Policy for Infectious Disease Dynamics (RAPIDD) Ebola Challenge; a simulated epidemic that generated 4 infectious disease scenarios. Because of the nature of the synthetically generated data, model predictions are compared to exact epidemiological quantities used in the simulation.
In chapter 4, these models are applied to the 1904 Plague epidemic that occurred in Bombay. This chapter provides evidence that these simple models may be applicable to infectious diseases no matter the disease transmission mechanism.
Chapter 5, uses the patch models from chapter 2 to explore how migration in the 1904 Plague epidemic changes the final epidemic size.
The final chapter is an interdisciplinary project concerning within-host dynamics of cereal yellow dwarf virus-RPV, a plant pathogen from a virus group that infects over 150 grass species. Motivated by environmental nutrient enrichment due to anthropological activities, mathematical models are employed to investigate the relevance of resource competition to pathogen and host dynamics.
ContributorsPell, Bruce (Author) / Kuang, Yang (Thesis advisor) / Chowell-Puente, Gerardo (Committee member) / Nagy, John (Committee member) / Kostelich, Eric (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2016
Description
Public mass shootings occur at a rate in the U.S. that is higher than any other developed country. These event initiate wide spread media attention. The media attention these events achieve have shown to impact the public behavior (e.g., increased firearm sales). However, the impact public mass shootings have on firearm storage and carry habits of the public is not well understood. Using data collected from the Transportation Security Administration, this study examines how mass shootings have led to moral panics occurring within the U.S. through the examination of the firearm carrying habits among the population immediately following mass shootings. The results indicate that loaded firearms with rounds in the chamber detected by the TSA have significantly increased since 2012. Further, firearms detected immediately following a public mass shooting had a higher proportion of firearms loaded with a round in the chamber relative to 7 days prior to the shooting. Moreover, the increase in proportions of firearms found loaded with a round in the chamber exponentially decays as days past the initial shooting, these events occur at a higher rate than the decay rate can normalize these occurrences. I conclude that in the wake of these shootings a moral panic ensues that is partially responsible for the change in the general public’s arming configuration habits. Further research is needed in to determine the impact on crime, and public health related issues due to this change in the public’s firearm carrying habits.
ContributorsCordova, Richard Donald (Author) / Reisig, Michael (Thesis advisor) / Towers, Sherry (Committee member) / Wang, Xia (Committee member) / Holtfreter, Kristy (Committee member) / Arizona State University (Publisher)
Created2018
Description
Head and neck squamous cell carcinoma (HNSCC), the sixth most common cancer
type worldwide, accounts for more than 630,000 new cases and 350,000 deaths
annually. Drug-resistance and tumor recurrence are the most challenging problems
in head and neck cancer treatment. It is hypothesized that a very small fraction
of stem-like cells within HNSCC tumor, called cancer stem cells (CSCs), is
responsible for tumor initiation, progression, resistance and recurrence. It has also
been shown that IL-6 secreted by head and neck tumor-associated endothelial cells
(ECs) enhances the survival, self-renewal and tumorigenic potential of head and
neck CSCs. In this study we will use a mathematical multi-scale model which operates
at the intracellular, molecular, and tissue level to investigate the impacts of
EC-secreted IL-6 signaling on the crosstalk between tumor cells and ECs during
tumor growth. This model will be calibrated by using the experimental in vivo
data.
Eventually the model will be modified to explore the responses of head and neck
cancer cells to combination therapy involving Tocilizumab (an anti-IL-6R antibody)
and Cisplatin (the most frequently used chemotherapy for head and neck
cancer). The model will be able to predict the final proportion of CSCs in response
to endothelial cell-secreted IL-6 and drug therapies. The model will be validated
by directly comparing the experimental treatment data and the model predictions.
This could potentially provide a condition under which we could control enlargement
of the head and neck CSC pool and tumor recurrence. It may also suggest
the best bounds for Cisplatin and/or Tocilizumab dose and frequency to be tested
in the clinical trial.
type worldwide, accounts for more than 630,000 new cases and 350,000 deaths
annually. Drug-resistance and tumor recurrence are the most challenging problems
in head and neck cancer treatment. It is hypothesized that a very small fraction
of stem-like cells within HNSCC tumor, called cancer stem cells (CSCs), is
responsible for tumor initiation, progression, resistance and recurrence. It has also
been shown that IL-6 secreted by head and neck tumor-associated endothelial cells
(ECs) enhances the survival, self-renewal and tumorigenic potential of head and
neck CSCs. In this study we will use a mathematical multi-scale model which operates
at the intracellular, molecular, and tissue level to investigate the impacts of
EC-secreted IL-6 signaling on the crosstalk between tumor cells and ECs during
tumor growth. This model will be calibrated by using the experimental in vivo
data.
Eventually the model will be modified to explore the responses of head and neck
cancer cells to combination therapy involving Tocilizumab (an anti-IL-6R antibody)
and Cisplatin (the most frequently used chemotherapy for head and neck
cancer). The model will be able to predict the final proportion of CSCs in response
to endothelial cell-secreted IL-6 and drug therapies. The model will be validated
by directly comparing the experimental treatment data and the model predictions.
This could potentially provide a condition under which we could control enlargement
of the head and neck CSC pool and tumor recurrence. It may also suggest
the best bounds for Cisplatin and/or Tocilizumab dose and frequency to be tested
in the clinical trial.
ContributorsNazari, Fereshteh (Author) / Jackson, Trachette L. (Thesis advisor, Committee member) / Castillo-Chavez, Carlos (Committee member) / Towers, Sherry (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2017
Description
Many Fic domain proteins, through catalyzing post translational modifications (PTM) of protein substrates, functionally contribute to bacterial pathogenesis and the regulation of bacterial growth. Furthermore, one form of Fic-mediated regulation is the Fic toxin-antitoxin system, whereby an antitoxin interacts with and inhibits the Fic toxin. This study sought to determine the functional importance of Mycobacterium tuberculosis Fic and its putative antitoxin protein, Rv3642c. Using M. tuberculosis H37Rv genetic deletion mutants, fic and Rv3642c were demonstrated to promote intracellular survival in human THP-1 macrophage-like cells. Unlike other Fic toxins, of Fic toxin-antitoxin systems, Fic did not inhibit bacterial growth in vitro in the absence of Rv3642c. Notably, Fic demonstrated in vitro AMPylation of a THP-1 cell extract protein as shown by immunodetection. Fic also exhibited auto-AMPylation activity. Interestingly, a mutation of the conserved histidine in the Fic domain motif, a residue previously shown to be critical for AMPylation, had no effect on Fic-mediated ATP hydrolysis or AMPylation activity. Rv3642c was demonstrated to form a complex with Fic when co-expressed in Escherichia coli, indicating a toxin-antitoxin interaction. Screening M. tuberculosis protein fractions and culture filtrate with α-Fic and α-Rv3642c rabbit antisera did not detect monomers of Fic or Rv3642c, thus the cellular localization of Fic and the Rv3642c-Fic complex remains unclear. The results of this study provide insight into the function of M. tuberculosis Fic, and suggest that Fic and Rv3642c are important for M. tuberculosis survival in the intracellular macrophage environment. Furthermore, these findings challenge the current dogma that Fic domain catalysis is dependent on the conserved histidine of the Fic motif.
ContributorsLaMarca, Ryan (Author) / Haydel, Shelley (Thesis advisor) / Lake, Douglas (Committee member) / Nickerson, Cheryl (Committee member) / Arizona State University (Publisher)
Created2017
Description
Understanding how microorganisms adapt and respond to the microgravity environment of spaceflight is important for the function and integrity of onboard life support systems, astronaut health and mission success. Microbial contamination of spacecraft Environmental Life Support Systems (ECLSS), including the potable water system, are well documented and have caused major disruption to spaceflight missions. The potable water system on the International Space Station (ISS) uses recycled wastewater purified by multiple processes so it is safe for astronaut consumption and personal hygiene. However, despite stringent antimicrobial treatments, multiple bacterial species and biofilms have been recovered from this potable water system. This finding raises concern for crew health risks, vehicle operations and ECLSS system integrity during exploration missions. These concerns are further heightened given that 1) potential pathogens have been isolated from the ISS potable water system, 2) the immune response of astronauts is blunted during spaceflight, 3) spaceflight induces unexpected alterations in microbial responses, including growth and biofilm formation, antimicrobial resistance, stress responses, and virulence, and 4) different microbial phenotypes are often observed between reductionistic pure cultures as compared to more complex multispecies co-cultures, the latter of which are more representative of natural environmental conditions. To advance the understanding of the impact of microgravity on microbial responses that could negatively impact spacecraft ECLSS systems and crew health, this study characterized a range of phenotypic profiles in both pure and co-cultures of bacterial isolates collected from the ISS potable water system between 2009 and 2014. Microbial responses profiled included population dynamics, resistance to silver, biofilm formation, and in vitro colonization of intestinal epithelial cells. Growth characteristics and antibiotic sensitivities for bacterial strains were evaluated to develop selective and/or differential media that allow for isolation of a pure culture from co-cultures, which was critical for the success of this study. Bacterial co-culture experiments were performed using dynamic Rotating Wall Vessel (RWV) bioreactors under spaceflight analogue (Low Shear Modeled Microgravity/LSMMG) and control conditions. These experiments indicated changes in fluid shear have minimal impact on strain recovery. The antimicrobial efficacy of silver on both sessile co-cultures, grown on 316L stainless steel coupons, and planktonic co-cultures showed that silver did not uniformly reduce the recovery of all strains; however, it had a stronger antimicrobial effect on biofilm cultures than planktonic cultures. The impact of silver on the ability of RWV cultured planktonic and biofilm bacterial co-cultures to colonize human intestinal epithelial cells showed that, those strains which were impacted by silver treatment, often increased adherence to the monolayer. Results from these studies provide insight into the dynamics of polymicrobial community interactions, biofilm formation and survival mechanisms of ISS potable water isolates, with potential application for future design of ECLSS systems for sustainable human space exploration.
ContributorsKing, Olivia G (Author) / Nickerson, Cheryl (Thesis advisor) / Barrila, Jennifer (Committee member) / Ott, C (Committee member) / Yang, Jiseon (Committee member) / Arizona State University (Publisher)
Created2019