Matching Items (147)
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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

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
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Description
Telomerase ribonucleoprotein is a unique reverse transcriptase that adds telomeric DNA repeats to chromosome ends. Telomerase RNA (TER) is extremely divergent in size, sequence and has to date only been identified in vertebrate, yeast, ciliate and plant species. Herein, the identification and characterization of TERs from an evolutionarily distinct group,

Telomerase ribonucleoprotein is a unique reverse transcriptase that adds telomeric DNA repeats to chromosome ends. Telomerase RNA (TER) is extremely divergent in size, sequence and has to date only been identified in vertebrate, yeast, ciliate and plant species. Herein, the identification and characterization of TERs from an evolutionarily distinct group, filamentous fungi, is presented. Based on phylogenetic analysis of 69 TER sequences and mutagenesis analysis of in vitro reconstituted Neurospora telomerase, we discovered a conserved functional core in filamentous fungal TERs sharing homologous structural features with vertebrate TERs. This core contains the template-pseudoknot and P6/P6.1 domains, essential for enzymatic activity, which retain function in trans. The in vitro reconstituted Neurospora telomerase is highly processive, synthesizing canonical TTAGGG repeats. Similar to Schizosaccharomycetes pombe, filamentous fungal TERs utilize the spliceosomal splicing machinery for 3' processing. Neurospora telomerase, while associating with the Est1 protein in vivo, does not bind homologous Ku or Sm proteins found in both budding and fission yeast telomerase holoenzyme, suggesting a unique biogenesis pathway. The development of Neurospora as a model organism to study telomeres and telomerase may shed light upon the evolution of the canonical TTAGGG telomeric repeat and telomerase processivity within fungal species.
ContributorsQi, Xiaodong (Author) / Chen, Julian (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Chaput, John (Committee member) / Arizona State University (Publisher)
Created2011
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Description
The bleomycins are a family of glycopeptide-derived antibiotics isolated from various Streptomyces species and have been the subject of much attention from the scientific community as a consequence of their antitumor activity. Bleomycin clinically and is an integral part of a number of combination chemotherapy regimens. It has previously been

The bleomycins are a family of glycopeptide-derived antibiotics isolated from various Streptomyces species and have been the subject of much attention from the scientific community as a consequence of their antitumor activity. Bleomycin clinically and is an integral part of a number of combination chemotherapy regimens. It has previously been shown that bleomycin has the ability to selectively target tumor cells over their non-malignant counterparts. Pyrimidoblamic acid, the N-terminal metal ion binding domain of bleomycin is known to be the moiety that is responsible for O2 activation and the subsequent chemistry leading to DNA strand scission and overall antitumor activity. Chapter 1 describes bleomycin and related DNA targeting antitumor agents as well as the specific structural domains of bleomycin. Various structural analogues of pyrimidoblamic acid were synthesized and subsequently incorporated into their corresponding full deglycoBLM A6 derivatives by utilizing a solid support. Their activity was measured using a pSP64 DNA plasmid relaxation assay and is summarized in Chapter 2. The specifics of bleomycin—DNA interaction and kinetics were studied via surface plasmon resonance and are presented in Chapter 3. By utilizing carefully selected 64-nucleotide DNA hairpins with variable 16-mer regions whose sequences showed strong binding in past selection studies, a kinetic profile was obtained for several BLMs for the first time since bleomycin was discovered in 1966. The disaccharide moiety of bleomycin has been previously shown to be a specific tumor cell targeting element comprised of L-gulose-D-mannose, especially between MCF-7 (breast cancer cells) and MCF-10A ("normal" breast cells). This phenomenon was further investigated via fluorescence microscopy using multiple cancerous cell lines with matched "normal" counterparts and is fully described in Chapter 4.
ContributorsBozeman, Trevor C (Author) / Hecht, Sidney M. (Thesis advisor) / Chaput, John (Committee member) / Gould, Ian (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The Cape Floral Region (CFR) in southwestern South Africa is one of the most diverse in the world, with >9,000 plant species, 70% of which are endemic, in an area of only ~90,000 km2. Many have suggested that the CFR's heterogeneous environment, with respect to landscape gradients, vegetation, rainfall, elevation,

The Cape Floral Region (CFR) in southwestern South Africa is one of the most diverse in the world, with >9,000 plant species, 70% of which are endemic, in an area of only ~90,000 km2. Many have suggested that the CFR's heterogeneous environment, with respect to landscape gradients, vegetation, rainfall, elevation, and soil fertility, is responsible for the origin and maintenance of this biodiversity. While studies have struggled to link species diversity with these features, no study has attempted to associate patterns of gene flow with environmental data to determine how CFR biodiversity evolves on different scales. Here, a molecular population genetic data is presented for a widespread CFR plant, Leucadendron salignum, across 51 locations with 5-kb of chloroplast (cpDNA) and 6-kb of unlinked nuclear (nuDNA) DNA sequences in a dataset of 305 individuals. In the cpDNA dataset, significant genetic structure was found to vary on temporal and spatial scales, separating Western and Eastern Capes - the latter of which appears to be recently derived from the former - with the highest diversity in the heart of the CFR in a central region. A second study applied a statistical model using vegetation and soil composition and found fine-scale genetic divergence is better explained by this landscape resistance model than a geographic distance model. Finally, a third analysis contrasted cpDNA and nuDNA datasets, and revealed very little geographic structure in the latter, suggesting that seed and pollen dispersal can have different evolutionary genetic histories of gene flow on even small CFR scales. These three studies together caution that different genomic markers need to be considered when modeling the geographic and temporal origin of CFR groups. From a greater perspective, the results here are consistent with the hypothesis that landscape heterogeneity is one driving influence in limiting gene flow across the CFR that can lead to species diversity on fine-scales. Nonetheless, while this pattern may be true of the widespread L. salignum, the extension of this approach is now warranted for other CFR species with varying ranges and dispersal mechanisms to determine how universal these patterns of landscape genetic diversity are.
ContributorsTassone, Erica (Author) / Verrelli, Brian C (Thesis advisor) / Dowling, Thomas (Committee member) / Cartwright, Reed (Committee member) / Rosenberg, Michael S. (Committee member) / Wojciechowski, Martin (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Surface plasmon resonance (SPR) has emerged as a popular technique for elucidating subtle signals from biological events in a label-free, high throughput environment. The efficacy of conventional SPR sensors, whose signals are mass-sensitive, diminishes rapidly with the size of the observed target molecules. The following work advances the current SPR

Surface plasmon resonance (SPR) has emerged as a popular technique for elucidating subtle signals from biological events in a label-free, high throughput environment. The efficacy of conventional SPR sensors, whose signals are mass-sensitive, diminishes rapidly with the size of the observed target molecules. The following work advances the current SPR sensor paradigm for the purpose of small molecule detection. The detection limits of two orthogonal components of SPR measurement are targeted: speed and sensitivity. In the context of this report, speed refers to the dynamic range of measured kinetic rate constants, while sensitivity refers to the target molecule mass limitation of conventional SPR measurement. A simple device for high-speed microfluidic delivery of liquid samples to a sensor surface is presented to address the temporal limitations of conventional SPR measurement. The time scale of buffer/sample switching is on the order of milliseconds, thereby minimizing the opportunity for sample plug dispersion. The high rates of mass transport to and from the central microfluidic sensing region allow for SPR-based kinetic analysis of binding events with dissociation rate constants (kd) up to 130 s-1. The required sample volume is only 1 μL, allowing for minimal sample consumption during high-speed kinetic binding measurement. Charge-based detection of small molecules is demonstrated by plasmonic-based electrochemical impedance microscopy (P-EIM). The dependence of surface plasmon resonance (SPR) on surface charge density is used to detect small molecules (60-120 Da) printed on a dextran-modified sensor surface. The SPR response to an applied ac potential is a function of the surface charge density. This optical signal is comprised of a dc and an ac component, and is measured with high spatial resolution. The amplitude and phase of local surface impedance is provided by the ac component. The phase signal of the small molecules is a function of their charge status, which is manipulated by the pH of a solution. This technique is used to detect and distinguish small molecules based on their charge status, thereby circumventing the mass limitation (~100 Da) of conventional SPR measurement.
ContributorsMacGriff, Christopher Assiff (Author) / Tao, Nongjian (Thesis advisor) / Wang, Shaopeng (Committee member) / LaBaer, Joshua (Committee member) / Chae, Junseok (Committee member) / Arizona State University (Publisher)
Created2013
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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

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
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Description
This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems

This dissertation investigates the condition of skeletal muscle insulin resistance using bioinformatics and computational biology approaches. Drawing from several studies and numerous data sources, I have attempted to uncover molecular mechanisms at multiple levels. From the detailed atomistic simulations of a single protein, to datamining approaches applied at the systems biology level, I provide new targets to explore for the research community. Furthermore I present a new online web resource that unifies various bioinformatics databases to enable discovery of relevant features in 3D protein structures.
ContributorsMielke, Clinton (Author) / Mandarino, Lawrence (Committee member) / LaBaer, Joshua (Committee member) / Magee, D. Mitchell (Committee member) / Dinu, Valentin (Committee member) / Willis, Wayne (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Recombinant protein expression is essential to biotechnology and molecular medicine, but facile methods for obtaining significant quantities of folded and functional protein in mammalian cell culture have been lacking. Here I describe a novel 37-nucleotide in vitro selected sequence that promotes unusually high transgene expression in a vaccinia driven cytoplasmic

Recombinant protein expression is essential to biotechnology and molecular medicine, but facile methods for obtaining significant quantities of folded and functional protein in mammalian cell culture have been lacking. Here I describe a novel 37-nucleotide in vitro selected sequence that promotes unusually high transgene expression in a vaccinia driven cytoplasmic expression system. Vectors carrying this sequence in a monocistronic reporter plasmid produce >1,000-fold more protein than equivalent vectors with conventional vaccinia promoters. Initial mechanistic studies indicate that high protein expression results from dual activity that impacts both transcription and translation. I suggest that this motif represents a powerful new tool in vaccinia-based protein expression and vaccine development technology.
ContributorsFlores, Julia Anne (Author) / Chaput, John C (Thesis advisor) / Jacobs, Bertram (Committee member) / LaBaer, Joshua (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Nucleic acids encode the information required to create life, and polymerases are the gatekeepers charged with maintaining the storage and flow of this genetic information. Synthetic biologists utilize this universal property to modify organisms and other systems to create unique traits or improve the function of others. One of the

Nucleic acids encode the information required to create life, and polymerases are the gatekeepers charged with maintaining the storage and flow of this genetic information. Synthetic biologists utilize this universal property to modify organisms and other systems to create unique traits or improve the function of others. One of the many realms in synthetic biology involves the study of biopolymers that do not exist naturally, which is known as xenobiology. Although life depends on two biopolymers for genetic storage, it may be possible that alternative molecules (xenonucleic acids – XNAs), could be used in their place in either a living or non-living system. However, implementation of an XNA based system requires the development of polymerases that can encode and decode information stored in these artificial polymers. A strategy called directed evolution is used to modify or alter the function of a protein of interest, but identifying mutations that can modify polymerase function is made problematic by their size and overall complexity. To reduce the amount of sequence space that needs to be samples when attempting to identify polymerase variants, we can try to make informed decisions about which amino acid residues may have functional roles in catalysis. An analysis of Family B polymerases has shown that residues which are involved in substrate specificity are often highly conserved both at the sequence and structure level. In order to validate the hypothesis that a strong correlation exists between structural conservation and catalytic activity, we have selected and mutated residues in the 9°N polymerase using a loss of function mutagenesis strategy based on a computational analysis of several homologues from a diverse range of taxa. Improvement of these models will hopefully lead to quicker identification of loci which are ideal engineering targets.
ContributorsHaeberle, Tyler Matthew (Author) / Chaput, John (Thesis director) / Chen, Julian (Committee member) / Larsen, Andrew (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Life Sciences (Contributor)
Created2015-05
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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

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