Matching Items (154)
Description
Diseases have been part of human life for generations and evolve within the population, sometimes dying out while other times becoming endemic or the cause of recurrent outbreaks. The long term influence of a disease stems from different dynamics within or between pathogen-host, that have been analyzed and studied by many researchers using mathematical models. Co-infection with different pathogens is common, yet little is known about how infection with one pathogen affects the host's immunological response to another. Moreover, no work has been found in the literature that considers the variability of the host immune health or that examines a disease at the population level and its corresponding interconnectedness with the host immune system. Knowing that the spread of the disease in the population starts at the individual level, this thesis explores how variability in immune system response within an endemic environment affects an individual's vulnerability, and how prone it is to co-infections. Immunology-based models of Malaria and Tuberculosis (TB) are constructed by extending and modifying existing mathematical models in the literature. The two are then combined to give a single nine-variable model of co-infection with Malaria and TB. Because these models are difficult to gain any insight analytically due to the large number of parameters, a phenomenological model of co-infection is proposed with subsystems corresponding to the individual immunology-based model of a single infection. Within this phenomenological model, the variability of the host immune health is also incorporated through three different pathogen response curves using nonlinear bounded Michaelis-Menten functions that describe the level or state of immune system (healthy, moderate and severely compromised). The immunology-based models of Malaria and TB give numerical results that agree with the biological observations. The Malaria--TB co-infection model gives reasonable results and these suggest that the order in which the two diseases are introduced have an impact on the behavior of both. The subsystems of the phenomenological models that correspond to a single infection (either of Malaria or TB) mimic much of the observed behavior of the immunology-based counterpart and can demonstrate different behavior depending on the chosen pathogen response curve. In addition, varying some of the parameters and initial conditions in the phenomenological model yields a range of topologically different mathematical behaviors, which suggests that this behavior may be able to be observed in the immunology-based models as well. The phenomenological models clearly replicate the qualitative behavior of primary and secondary infection as well as co-infection. The mathematical solutions of the models correspond to the fundamental states described by immunologists: virgin state, immune state and tolerance state. The phenomenological model of co-infection also demonstrates a range of parameter values and initial conditions in which the introduction of a second disease causes both diseases to grow without bound even though those same parameters and initial conditions did not yield unbounded growth in the corresponding subsystems. This results applies to all three states of the host immune system. In terms of the immunology-based system, this would suggest the following: there may be parameter values and initial conditions in which a person can clear Malaria or TB (separately) from their system but in which the presence of both can result in the person dying of one of the diseases. Finally, this thesis studies links between epidemiology (population level) and immunology in an effort to assess the impact of pathogen's spread within the population on the immune response of individuals. Models of Malaria and TB are proposed that incorporate the immune system of the host into a mathematical model of an epidemic at the population level.
ContributorsSoho, Edmé L (Author) / Wirkus, Stephen (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2011
Description
Colorimetric assays are an important tool in point-of-care testing that offers several advantages to traditional testing methods such as rapid response times and inexpensive costs. A factor that currently limits the portability and accessibility of these assays are methods that can objectively determine the results of these assays. Current solutions consist of creating a test reader that standardizes the conditions the strip is under before being measured in some way. However, this increases the cost and decreases the portability of these assays. The focus of this study is to create a machine learning algorithm that can objectively determine results of colorimetric assays under varying conditions. To ensure the flexibility of a model to several types of colorimetric assays, three models were trained on the same convolutional neural network with different datasets. The images these models are trained on consist of positive and negative images of ETG, fentanyl, and HPV Antibodies test strips taken under different lighting and background conditions. A fourth model is trained on an image set composed of all three strip types. The results from these models show it is able to predict positive and negative results to a high level of accuracy.
ContributorsFisher, Rachel (Author) / Blain Christen, Jennifer (Thesis director) / Anderson, Karen (Committee member) / School of Life Sciences (Contributor) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Many studies have shown that access to healthy food in the US is unevenly distributed and that supermarkets and other fresh food retailers are less likely to be located in low-income minority communities, where convenience and dollar stores are more prevalent grocery options. I formed a partnership with Phoenix Revitalization Corporation, a local community development organization engaged in Central City South, Phoenix, to enhance the community's capacity to meet its community health goals by improving access to healthy food. I used a community-based participatory approach that blended qualitative and quantitative elements to accommodate collaboration between both academic and non-academic partners. Utilizing stakeholder interviews, Nutrition Environment Measures Surveys (NEMS), and mapping to analyze the community's food resources, research revealed that the community lacks adequate access to affordable, nutritious food. Community food stores (n=14) scored an average of 10.9 out of a possible 54 points using the NEMS scoring protocol. The community food assessment is an essential step in improving access to healthy food for CCS residents and provides a baseline for tracking progress to improve residents' food access. Recommendations were drafted by the research partnership to equip and empower the community with strategic, community-specific interventions based on the research findings.
ContributorsCrouch, Carolyn (Author) / Harlan, Sharon (Thesis advisor) / Eakin, Hallie (Committee member) / Aftandilian, David (Committee member) / Arizona State University (Publisher)
Created2011
Description
The dynamics of urban water use are characterized by spatial and temporal variability that is influenced by associated factors at different scales. Thus it is important to capture the relationship between urban water use and its determinants in a spatio-temporal framework in order to enhance understanding and management of urban water demand. This dissertation aims to contribute to understanding the spatio-temporal relationships between single-family residential (SFR) water use and its determinants in a desert city. The dissertation has three distinct papers to support this goal. In the first paper, I demonstrate that aggregated scale data can be reliably used to study the relationship between SFR water use and its determinants without leading to significant ecological fallacy. The usability of aggregated scale data facilitates scientific inquiry about SFR water use with more available aggregated scale data. The second paper advances understanding of the relationship between SFR water use and its associated factors by accounting for the spatial and temporal dependence in a panel data setting. The third paper of this dissertation studies the historical contingency, spatial heterogeneity, and spatial connectivity in the relationship of SFR water use and its determinants by comparing three different regression models. This dissertation demonstrates the importance and necessity of incorporating spatio-temporal components, such as scale, dependence, and heterogeneity, into SFR water use research. Spatial statistical models should be used to understand the effects of associated factors on water use and test the effectiveness of certain management policies since spatial effects probably will significantly influence the estimates if only non-spatial statistical models are used. Urban water demand management should pay attention to the spatial heterogeneity in predicting the future water demand to achieve more accurate estimates, and spatial statistical models provide a promising method to do this job.
ContributorsOuyang, Yun (Author) / Wentz, Elizabeth (Thesis advisor) / Ruddell, Benjamin (Thesis advisor) / Harlan, Sharon (Committee member) / Janssen, Marcus (Committee member) / Arizona State University (Publisher)
Created2013
Description
Solution methods for certain linear and nonlinear evolution equations are presented in this dissertation. Emphasis is placed mainly on the analytical treatment of nonautonomous differential equations, which are challenging to solve despite the existent numerical and symbolic computational software programs available. Ideas from the transformation theory are adopted allowing one to solve the problems under consideration from a non-traditional perspective. First, the Cauchy initial value problem is considered for a class of nonautonomous and inhomogeneous linear diffusion-type equation on the entire real line. Explicit transformations are used to reduce the equations under study to their corresponding standard forms emphasizing on natural relations with certain Riccati(and/or Ermakov)-type systems. These relations give solvability results for the Cauchy problem of the parabolic equation considered. The superposition principle allows to solve formally this problem from an unconventional point of view. An eigenfunction expansion approach is also considered for this general evolution equation. Examples considered to corroborate the efficacy of the proposed solution methods include the Fokker-Planck equation, the Black-Scholes model and the one-factor Gaussian Hull-White model. The results obtained in the first part are used to solve the Cauchy initial value problem for certain inhomogeneous Burgers-type equation. The connection between linear (the Diffusion-type) and nonlinear (Burgers-type) parabolic equations is stress in order to establish a strong commutative relation. Traveling wave solutions of a nonautonomous Burgers equation are also investigated. Finally, it is constructed explicitly the minimum-uncertainty squeezed states for quantum harmonic oscillators. They are derived by the action of corresponding maximal kinematical invariance group on the standard ground state solution. It is shown that the product of the variances attains the required minimum value only at the instances that one variance is a minimum and the other is a maximum, when the squeezing of one of the variances occurs. Such explicit construction is possible due to the relation between the diffusion-type equation studied in the first part and the time-dependent Schrodinger equation. A modication of the radiation field operators for squeezed photons in a perfect cavity is also suggested with the help of a nonstandard solution of Heisenberg's equation of motion.
ContributorsVega-Guzmán, José Manuel, 1982- (Author) / Sulov, Sergei K (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Platte, Rodrigo (Committee member) / Chowell-Puente, Gerardo (Committee member) / Arizona State University (Publisher)
Created2013
Description
V(D)J recombination is responsible for generating an enormous repertoire of immunoglobulins and T cell receptors, therefore it is a centerpiece to the formation of the adaptive immune system. The V(D)J recombination process proceeds through two steps, site-specific cleavage at RSS (Recombination Signal Sequence) site mediated by the RAG recombinase (RAG1/2) and the subsequent imprecise resolution of the DNA ends, which is carried out by the ubiquitous non-homologous end joining pathway (NHEJ). The V(D)J recombination reaction is obliged to be tightly controlled under all circumstances, as it involves generations of DNA double strand breaks, which are considered the most dangerous lesion to a cell. Multifaceted regulatory mechanisms have been evolved to create great diversity of the antigen receptor repertoire while ensuring genome stability. The RAG-mediated cleavage reaction is stringently regulated at both the pre-cleavage stage and the post-cleavage stage. Specifically, RAG1/2 first forms a pre-cleavage complex assembled at the boarder of RSS and coding flank, which ensures the appropriate DNA targeting. Subsequently, this complex initiates site-specific cleavage, generating two types of double stranded DNA breaks, hairpin-ended coding ends (HP-CEs) and blunt signal ends (SEs). After the cleavage, RAG1/2 proteins bind and retain the recombination ends to form post-cleavage complexes (PCC), which collaborates with the NHEJ machinery for appropriate transfer of recombination ends to NHEJ for proper end resolution. However, little is known about the molecular basis of this collaboration, partly attributed to the lack of sensitive assays to reveal the interaction of PCC with HP-CEs. Here, for the first time, by using two complementary fluorescence-based techniques, fluorescence anisotropy and fluorescence resonance energy transfer (FRET), I managed to monitor the RAG1/2-catalyzed cleavage reaction in real time, from the pre-cleavage to the post-cleavage stages. By examining the dynamic fluorescence changes during the RAG-mediated cleavage reactions, and by manipulating the reaction conditions, I was able to characterize some fundamental properties of RAG-DNA interactions before and after cleavage. Firstly, Mg2+, known as a physiological cofactor at the excision step, also promotes the HP-CEs retention in the RAG complex after cleavage. Secondly, the structure of pre-cleavage complex may affect the subsequent collaborations with NHEJ for end resolution. Thirdly, the non-core region of RAG2 may have differential influences on the PCC retention of HP-CEs and SEs. Furthermore, I also provide the first evidence of RAG1-mediated regulation of RAG2. Our study provides important insights into the multilayered regulatory mechanisms, in modulating recombination events in developing lymphocytes and paves the way for possible development of detection and diagnotic markers for defective recombination events that are often associated immunodeficiency and/or lymphoid malignancy.
ContributorsWang, Guannan (Author) / Chang, Yung (Thesis advisor) / Levitus, Marcia (Committee member) / Misra, Rajeev (Committee member) / Anderson, Karen (Committee member) / Arizona State University (Publisher)
Created2012
Description
Introduction: Human papillomavirus (HPV) infection is seen in up to 90% of cases of cervical cancer, the third leading cancer cause of death in women. Current HPV screening focuses on only two HPV types and covers roughly 75% of HPV-associated cervical cancers. A protein based assay to test for antibody biomarkers against 98 HPV antigens from both high and low risk types could provide an inexpensive and reliable method to screen for patients at risk of developing invasive cervical cancer. Methods: 98 codon optimized, commercially produced HPV genes were cloned into the pANT7_cGST vector, amplified in a bacterial host, and purified for mammalian expression using in vitro transcription/translation (IVTT) in a luminescence-based RAPID ELISA (RELISA) assay. Monoclonal antibodies were used to determine immune cross-reactivity between phylogenetically similar antigens. Lastly, several protein characteristics were examined to determine if they correlated with protein expression. Results: All genes were successfully moved into the destination vector and 86 of the 98 genes (88%) expressed protein at an adequate level. A difference was noted in expression by gene across HPV types but no correlation was found between protein size, pI, or aliphatic index and expression. Discussion: Further testing is needed to express the remaining 12 HPV genes. Once all genes have been successfully expressed and purified at high concentrations, DNA will be printed on microscope slides to create a protein microarray. This microarray will be used to screen HPV-positive patient sera for antibody biomarkers that may be indicative of cervical cancer and precancerous cervical neoplasias.
ContributorsMeshay, Ian Matthew (Author) / Anderson, Karen (Thesis director) / Magee, Mitch (Committee member) / Katchman, Benjamin (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Mortality of 1918 influenza virus was high, partly due to bacteria coinfections. We characterize pandemic mortality in Arizona, which had high prevalence of tuberculosis. We applied regressions to over 35,000 data points to estimate the basic reproduction number and excess mortality. Age-specific mortality curves show elevated mortality for all age groups, especially the young, and senior sparing effects. The low value for reproduction number indicates that transmissibility was moderately low.
ContributorsJenner, Melinda Eva (Author) / Chowell-Puente, Gerardo (Thesis director) / Kostelich, Eric (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Background: While research has quantified the mortality burden of the 1957 H2N2 influenza pandemic in the United States, little is known about how the virus spread locally in Arizona, an area where the dry climate was promoted as reducing respiratory illness transmission yet tuberculosis prevalence was high.
Methods: Using archival death certificates from 1954 to 1961, this study quantified the age-specific seasonal patterns, excess-mortality rates, and transmissibility patterns of the 1957 pandemic in Maricopa County, Arizona. By applying cyclical Serfling linear regression models to weekly mortality rates, the excess-mortality rates due to respiratory and all-causes were estimated for each age group during the pandemic period. The reproduction number was quantified from weekly data using a simple growth rate method and generation intervals of 3 and 4 days. Local newspaper articles from The Arizona Republic were analyzed from 1957-1958.
Results: Excess-mortality rates varied between waves, age groups, and causes of death, but overall remained low. From October 1959-June 1960, the most severe wave of the pandemic, the absolute excess-mortality rate based on respiratory deaths per 10,000 population was 17.85 in the elderly (≥65 years). All other age groups had extremely low excess-mortality and the typical U-shaped age-pattern was absent. However, relative risk was greatest (3.61) among children and young adolescents (5-14 years) from October 1957-March 1958, based on incidence rates of respiratory deaths. Transmissibility was greatest during the same 1957-1958 period, when the mean reproduction number was 1.08-1.11, assuming 3 or 4 day generation intervals and exponential or fixed distributions.
Conclusions: Maricopa County largely avoided pandemic influenza from 1957-1961. Understanding this historical pandemic and the absence of high excess-mortality rates and transmissibility in Maricopa County may help public health officials prepare for and mitigate future outbreaks of influenza.
Methods: Using archival death certificates from 1954 to 1961, this study quantified the age-specific seasonal patterns, excess-mortality rates, and transmissibility patterns of the 1957 pandemic in Maricopa County, Arizona. By applying cyclical Serfling linear regression models to weekly mortality rates, the excess-mortality rates due to respiratory and all-causes were estimated for each age group during the pandemic period. The reproduction number was quantified from weekly data using a simple growth rate method and generation intervals of 3 and 4 days. Local newspaper articles from The Arizona Republic were analyzed from 1957-1958.
Results: Excess-mortality rates varied between waves, age groups, and causes of death, but overall remained low. From October 1959-June 1960, the most severe wave of the pandemic, the absolute excess-mortality rate based on respiratory deaths per 10,000 population was 17.85 in the elderly (≥65 years). All other age groups had extremely low excess-mortality and the typical U-shaped age-pattern was absent. However, relative risk was greatest (3.61) among children and young adolescents (5-14 years) from October 1957-March 1958, based on incidence rates of respiratory deaths. Transmissibility was greatest during the same 1957-1958 period, when the mean reproduction number was 1.08-1.11, assuming 3 or 4 day generation intervals and exponential or fixed distributions.
Conclusions: Maricopa County largely avoided pandemic influenza from 1957-1961. Understanding this historical pandemic and the absence of high excess-mortality rates and transmissibility in Maricopa County may help public health officials prepare for and mitigate future outbreaks of influenza.
ContributorsCobos, April J (Author) / Jehn, Megan (Thesis director) / Chowell-Puente, Gerardo (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution and Social Change (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Background: Measles virus (MV) infections are the main cause of vaccine-preventable death in children younger than 5 years. The World Health Organization (WHO) has estimated there are over 20 million cases of measles every year. Currently, diagnostic methods rely on enzyme immunoassays (EIA) to detect IgM or IgG Abs in serum. These commercial assays measure reactivity against the immunodominant N antigen and can have a false negative rates of 20-30%. Centralized testing by clinical labs can delay rapid screening in an outbreak setting. This study aims to develop a rapid molecular diagnostic assay to detect IgG reactive to five individual MV proteins representing 85% of the measles proteome. Methods: MV genes were subcloned into pANT_cGST vector to generate C-terminal GST fusion proteins. Single MV cistrons were expressed using in vitro transcription/translation (IVTT) with human cell lysate. Expression of GST-tagged proteins was measured using a sandwich ELISA for GST expression using relative light units (RLUs) as readouts. Single MV antigens were used as bait to determine the IgG-dependent reactivity in 12 serum samples obtained from immunized animals with previously determined neutralization titer (NT) and the correlation between NT and ELISA reactivity was determined. Results: Protein expression of five measles genes of interest, M, N, F, H, and L, was measured. L exhibited the strongest protein expression with an average RLU value of 4.34 x 10^9. All proteins were expressed at least 50% greater than control (2.33 x 10^7 RLU). As expected, reactivity against the N was the highest, followed by reactivity against M, F, H and L. The best correlation with NT titer was reactivity against F (R^2 = 0.62). Conclusion: These data indicate that the expression of single MV genes M, N, F, H, and L are suitable antigens for serologic capture analysis of measles immunity.
ContributorsMushtaq, Zuena (Author) / Anderson, Karen (Thesis director) / Reyes del Valle, Jorge (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05