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Molybdenum (Mo) is a key trace nutrient for biological assimilation of nitrogen, either as nitrogen gas (N2) or nitrate (NO3-). Although Mo is the most abundant metal in seawater (105 nM), its concentration is low (<5 nM) in most freshwaters today, and it was scarce in the ocean before 600 million years ago. The use of Mo for nitrogen assimilation can be understood in terms of the changing Mo availability through time; for instance, the higher Mo content of eukaryotic vs. prokaryotic nitrate reductase may have stalled proliferation of eukaryotes in low-Mo Proterozoic oceans. Field and laboratory experiments were performed to study Mo requirements for NO3- assimilation and N2 fixation, respectively. Molybdenum-nitrate addition experiments at Castle Lake, California revealed interannual and depth variability in plankton community response, perhaps resulting from differences in species composition and/or ammonium availability. Furthermore, lake sediments were elevated in Mo compared to soils and bedrock in the watershed. Box modeling suggested that the largest source of Mo to the lake was particulate matter from the watershed. Month-long laboratory experiments with heterocystous cyanobacteria (HC) showed that <1 nM Mo led to low N2 fixation rates, while 10 nM Mo was sufficient for optimal rates. At 1500 nM Mo, freshwater HC hyperaccumulated Mo intercellularly, whereas coastal HC did not. These differences in storage capacity were likely due to the presence in freshwater HC of the small molybdate-binding protein, Mop, and its absence in coastal and marine cyanobacterial species. Expression of the mop gene was regulated by Mo availability in the freshwater HC species Nostoc sp. PCC 7120. Under low Mo (<1 nM) conditions, mop gene expression was up-regulated compared to higher Mo (150 and 3000 nM) treatments, but the subunit composition of the Mop protein changed, suggesting that Mop does not bind Mo in the same manner at <1 nM Mo that it can at higher Mo concentrations. These findings support a role for Mop as a Mo storage protein in HC and suggest that freshwater HC control Mo cellular homeostasis at the post-translational level. Mop's widespread distribution in prokaryotes lends support to the theory that it may be an ancient protein inherited from low-Mo Precambrian oceans.
ContributorsGlass, Jennifer (Author) / Anbar, Ariel D (Thesis advisor) / Shock, Everett L (Committee member) / Jones, Anne K (Committee member) / Hartnett, Hilairy E (Committee member) / Elser, James J (Committee member) / Fromme, Petra (Committee member) / Arizona State University (Publisher)
Created2011
Description
In 2010, a monthly sampling regimen was established to examine ecological differences in Saguaro Lake and Lake Pleasant, two Central Arizona reservoirs. Lake Pleasant is relatively deep and clear, while Saguaro Lake is relatively shallow and turbid. Preliminary results indicated that phytoplankton biomass was greater by an order of magnitude in Saguaro Lake, and that community structure differed. The purpose of this investigation was to determine why the reservoirs are different, and focused on physical characteristics of the water column, nutrient concentration, community structure of phytoplankton and zooplankton, and trophic cascades induced by fish populations. I formulated the following hypotheses: 1) Top-down control varies between the two reservoirs. The presence of piscivore fish in Lake Pleasant results in high grazer and low primary producer biomass through trophic cascades. Conversely, Saguaro Lake is controlled from the bottom-up. This hypothesis was tested through monthly analysis of zooplankton and phytoplankton communities in each reservoir. Analyses of the nutritional value of phytoplankton and DNA based molecular prey preference of zooplankton provided insight on trophic interactions between phytoplankton and zooplankton. Data from the Arizona Game and Fish Department (AZGFD) provided information on the fish communities of the two reservoirs. 2) Nutrient loads differ for each reservoir. Greater nutrient concentrations yield greater primary producer biomass; I hypothesize that Saguaro Lake is more eutrophic, while Lake Pleasant is more oligotrophic. Lake Pleasant had a larger zooplankton abundance and biomass, a larger piscivore fish community, and smaller phytoplankton abundance compared to Saguaro Lake. Thus, I conclude that Lake Pleasant was controlled top-down by the large piscivore fish population and Saguaro Lake was controlled from the bottom-up by the nutrient load in the reservoir. Hypothesis 2 stated that Saguaro Lake contains more nutrients than Lake Pleasant. However, Lake Pleasant had higher concentrations of dissolved nitrogen and phosphorus than Saguaro Lake. Additionally, an extended period of low dissolved N:P ratios in Saguaro Lake indicated N limitation, favoring dominance of N-fixing filamentous cyanobacteria in the phytoplankton community in that reservoir.
ContributorsSawyer, Tyler R (Author) / Neuer, Susanne (Thesis advisor) / Childers, Daniel L. (Committee member) / Sommerfeld, Milton (Committee member) / Arizona State University (Publisher)
Created2011
Description
Sinaloa, a coastal state in the northwest of Mexico, is known for irrigated conventional agriculture, and is considered one of the greatest successes of the Green Revolution. With the neoliberal reforms of the 1990s, Sinaloa farmers shifted out of conventional wheat, soy, cotton, and other commodities and into white maize, a major food staple in Mexico that is traditionally produced by millions of small-scale farmers. Sinaloa is now a major contributor to the national food supply, producing 26% of total domestic white maize production. Research on Sinaloa's maize has focused on economic and agronomic components. Little attention, however, has been given to the environmental sustainability of Sinaloa's expansion in maize. With uniquely biodiverse coastal and terrestrial ecosystems that support economic activities such as fishing and tourism, the environmental consequences of agriculture in Sinaloa are important to monitor. Agricultural sustainability assessments have largely focused on alternative agricultural approaches, or espouse alternative philosophies that are biased against conventional production. Conventional agriculture, however, provides a significant portion of the world's calories. In addition, incentives such as federal subsidies and other institutions complicate transitions to alternative modes of production. To meet the agricultural sustainability goals of food production and environmental stewardship, we must put conventional agriculture on a more sustainable path. One step toward achieving this is structuring agricultural sustainability assessments around achievable goals that encourage continual adaptations toward sustainability. I attempted this in my thesis by assessing conventional maize production in Sinaloa at the regional/state scale using network analysis and incorporating stakeholder values through a multicriteria decision analysis approach. The analysis showed that the overall sustainability of Sinaloa maize production is far from an ideal state. I made recommendations on how to improve the sustainability of maize production, and how to better monitor the sustainability of agriculture in Sinaloa.
ContributorsBausch, Julia Christine (Author) / Eakin, Hallie (Thesis advisor) / Bojórquez-Tapia, Luis (Committee member) / Childers, Daniel L. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Rabies disease remains enzootic among raccoons, skunks, foxes and bats in the United States. It is of primary concern for public-health agencies to control spatial spread of rabies in wildlife and its potential spillover infection of domestic animals and humans. Rabies is invariably fatal in wildlife if untreated, with a non-negligible incubation period. Understanding how this latency affects spatial spread of rabies in wildlife is the concern of chapter 2 and 3. Chapter 1 deals with the background of mathematical models for rabies and lists main objectives. In chapter 2, a reaction-diffusion susceptible-exposed-infected (SEI) model and a delayed diffusive susceptible-infected (SI) model are constructed to describe the same epidemic process -- rabies spread in foxes. For the delayed diffusive model a non-local infection term with delay is resulted from modeling the dispersal during incubation stage. Comparison is made regarding minimum traveling wave speeds of the two models, which are verified using numerical experiments. In chapter 3, starting with two Kermack and McKendrick's models where infectivity, death rate and diffusion rate of infected individuals can depend on the age of infection, the asymptotic speed of spread $c^\ast$ for the cumulated force of infection can be analyzed. For the special case of fixed incubation period, the asymptotic speed of spread is governed by the same integral equation for both models. Although explicit solutions for $c^\ast$ are difficult to obtain, assuming that diffusion coefficient of incubating animals is small, $c^\ast$ can be estimated in terms of model parameter values. Chapter 4 considers the implementation of realistic landscape in simulation of rabies spread in skunks and bats in northeast Texas. The Finite Element Method (FEM) is adopted because the irregular shapes of realistic landscape naturally lead to unstructured grids in the spatial domain. This implementation leads to a more accurate description of skunk rabies cases distributions.
ContributorsLiu, Hao (Author) / Kuang, Yang (Thesis advisor) / Jackiewicz, Zdzislaw (Committee member) / Lanchier, Nicolas (Committee member) / Smith, Hal (Committee member) / Thieme, Horst (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sustainability visioning (i.e. the construction of sustainable future states) is considered an important component of sustainability research, for instance, in transformational sustainability science or in planning for urban sustainability. Visioning frees sustainability research from the dominant focus on analyzing problem constellations and opens it towards positive contributions to social innovation and transformation. Calls are repeatedly made for visions that can guide us towards sustainable futures. Scattered across a broad range of fields (i.e. business, non-government organization, land-use management, natural resource management, sustainability science, urban and regional planning) are an abundance of visioning studies. However, among the few evaluative studies in the literature there are apparent deficits in both the research and practice of visioning that curtails our expectations and prospects of realizing process-based and product-derived outcomes. These deficits suggests that calls instead should focus on the development of applied and theoretical understanding of crafting sustainability visions, enhancing the rigor and robustness of visioning methodology, and on integrating practice, research, and education for collaborative sustainability visioning. From an analysis of prominent visioning and sustainability visioning studies in the literature, this dissertation articulates what is sustainability visioning and synthesizes a conceptual framework for criteria-based design and evaluation of sustainability visioning studies. While current visioning methodologies comply with some of these guidelines, none adhere to all of them. From this research, a novel sustainability visioning methodology is designed to address this gap to craft visions that are shared, systemic, principles-based, action-oriented, relevant, and creative (i.e. SPARC visioning methodology) and evaluated across all quality criteria. Empirical studies were conducted to test and apply the conceptual and methodological frameworks -- with an emphasis on enhancing the rigor and robustness in real world visioning processes for urban planning and teaching sustainability competencies. In-depth descriptions of the collaborative visioning studies demonstrate tangible outcomes for: (a) implementing the above sustainability visioning methodology, including evaluative procedures; (b) adopting meaningful interactive engagement procedures; (c) integrating advanced analytical modeling, sustainability appraisal, and creativity enhancing procedures; and (d) developing perspective and methodological capacity for long-range sustainability planning.
ContributorsIwaniec, David (Author) / Wiek, Arnim (Thesis advisor) / Childers, Daniel L. (Committee member) / Lant, Timothy (Committee member) / Arizona State University (Publisher)
Created2013
Description
Image resolution limits the extent to which zooming enhances clarity, restricts the size digital photographs can be printed at, and, in the context of medical images, can prevent a diagnosis. Interpolation is the supplementing of known data with estimated values based on a function or model involving some or all of the known samples. The selection of the contributing data points and the specifics of how they are used to define the interpolated values influences how effectively the interpolation algorithm is able to estimate the underlying, continuous signal. The main contributions of this dissertation are three fold: 1) Reframing edge-directed interpolation of a single image as an intensity-based registration problem. 2) Providing an analytical framework for intensity-based registration using control grid constraints. 3) Quantitative assessment of the new, single-image enlargement algorithm based on analytical intensity-based registration. In addition to single image resizing, the new methods and analytical approaches were extended to address a wide range of applications including volumetric (multi-slice) image interpolation, video deinterlacing, motion detection, and atmospheric distortion correction. Overall, the new approaches generate results that more accurately reflect the underlying signals than less computationally demanding approaches and with lower processing requirements and fewer restrictions than methods with comparable accuracy.
ContributorsZwart, Christine M. (Author) / Frakes, David H (Thesis advisor) / Karam, Lina (Committee member) / Kodibagkar, Vikram (Committee member) / Spanias, Andreas (Committee member) / Towe, Bruce (Committee member) / Arizona State University (Publisher)
Created2013
Description
Cancer is the second leading cause of death in the United States and novel methods of treating advanced malignancies are of high importance. Of these deaths, prostate cancer and breast cancer are the second most fatal carcinomas in men and women respectively, while pancreatic cancer is the fourth most fatal in both men and women. Developing new drugs for the treatment of cancer is both a slow and expensive process. It is estimated that it takes an average of 15 years and an expense of $800 million to bring a single new drug to the market. However, it is also estimated that nearly 40% of that cost could be avoided by finding alternative uses for drugs that have already been approved by the Food and Drug Administration (FDA). The research presented in this document describes the testing, identification, and mechanistic evaluation of novel methods for treating many human carcinomas using drugs previously approved by the FDA. A tissue culture plate-based screening of FDA approved drugs will identify compounds that can be used in combination with the protein TRAIL to induce apoptosis selectively in cancer cells. Identified leads will next be optimized using high-throughput microfluidic devices to determine the most effective treatment conditions. Finally, a rigorous mechanistic analysis will be conducted to understand how the FDA-approved drug mitoxantrone, sensitizes cancer cells to TRAIL-mediated apoptosis.
ContributorsTaylor, David (Author) / Rege, Kaushal (Thesis advisor) / Jayaraman, Arul (Committee member) / Nielsen, David (Committee member) / Kodibagkar, Vikram (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2013
Description
Magnetic Resonance Imaging using spiral trajectories has many advantages in speed, efficiency in data-acquistion and robustness to motion and flow related artifacts. The increase in sampling speed, however, requires high performance of the gradient system. Hardware inaccuracies from system delays and eddy currents can cause spatial and temporal distortions in the encoding gradient waveforms. This causes sampling discrepancies between the actual and the ideal k-space trajectory. Reconstruction assuming an ideal trajectory can result in shading and blurring artifacts in spiral images. Current methods to estimate such hardware errors require many modifications to the pulse sequence, phantom measurements or specialized hardware. This work presents a new method to estimate time-varying system delays for spiral-based trajectories. It requires a minor modification of a conventional stack-of-spirals sequence and analyzes data collected on three orthogonal cylinders. The method is fast, robust to off-resonance effects, requires no phantom measurements or specialized hardware and estimate variable system delays for the three gradient channels over the data-sampling period. The initial results are presented for acquired phantom and in-vivo data, which show a substantial reduction in the artifacts and improvement in the image quality.
ContributorsBhavsar, Payal (Author) / Pipe, James G (Thesis advisor) / Frakes, David (Committee member) / Kodibagkar, Vikram (Committee member) / Arizona State University (Publisher)
Created2013
Description
Coronary computed tomography angiography (CTA) has a high negative predictive value for ruling out coronary artery disease with non-invasive evaluation of the coronary arteries. My work has attempted to provide metrics that could increase the positive predictive value of coronary CTA through the use of dual energy CTA imaging. After developing an algorithm for obtaining calcium scores from a CTA exam, a dual energy CTA exam was performed on patients at dose levels equivalent to levels for single energy CTA with a calcium scoring exam. Calcium Agatston scores obtained from the dual energy CTA exam were within ±11% of scores obtained with conventional calcium scoring exams. In the presence of highly attenuating coronary calcium plaques, the virtual non-calcium images obtained with dual energy CTA were able to successfully measure percent coronary stenosis within 5% of known stenosis values, which is not possible with single energy CTA images due to the presence of the calcium blooming artifact. After fabricating an anthropomorphic beating heart phantom with coronary plaques, characterization of soft plaque vulnerability to rupture or erosion was demonstrated with measurements of the distance from soft plaque to aortic ostium, percent stenosis, and percent lipid volume in soft plaque. A classification model was developed, with training data from the beating heart phantom and plaques, which utilized support vector machines to classify coronary soft plaque pixels as lipid or fibrous. Lipid versus fibrous classification with single energy CTA images exhibited a 17% error while dual energy CTA images in the classification model developed here only exhibited a 4% error. Combining the calcium blooming correction and the percent lipid volume methods developed in this work will provide physicians with metrics for increasing the positive predictive value of coronary CTA as well as expanding the use of coronary CTA to patients with highly attenuating calcium plaques.
ContributorsBoltz, Thomas (Author) / Frakes, David (Thesis advisor) / Towe, Bruce (Committee member) / Kodibagkar, Vikram (Committee member) / Pavlicek, William (Committee member) / Bouman, Charles (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sensitivity is a fundamental challenge for in vivo molecular magnetic resonance imaging (MRI). Here, I improve the sensitivity of metal nanoparticle contrast agents by strategically incorporating pure and doped metal oxides in the nanoparticle core, forming a soluble, monodisperse, contrast agent with adjustable T2 or T1 relaxivity (r2 or r1). I first developed a simplified technique to incorporate iron oxides in apoferritin to form "magnetoferritin" for nM-level detection with T2- and T2* weighting. I then explored whether the crystal could be chemically modified to form a particle with high r1. I first adsorbed Mn2+ ions to metal binding sites in the apoferritin pores. The strategic placement of metal ions near sites of water exchange and within the crystal oxide enhance r1, suggesting a mechanism for increasing relaxivity in porous nanoparticle agents. However, the Mn2+ addition was only possible when the particle was simultaneously filled with an iron oxide, resulting in a particle with a high r1 but also a high r2 and making them undetectable with conventional T1-weighting techniques. To solve this problem and decrease the particle r2 for more sensitive detection, I chemically doped the nanoparticles with tungsten to form a disordered W-Fe oxide composite in the apoferritin core. This configuration formed a particle with a r1 of 4,870mM-1s-1 and r2 of 9,076mM-1s-1. These relaxivities allowed the detection of concentrations ranging from 20nM - 400nM in vivo, both passively injected and targeted to the kidney glomerulus. I further developed an MRI acquisition technique to distinguish particles based on r2/r1, and show that three nanoparticles of similar size can be distinguished in vitro and in vivo with MRI. This work forms the basis for a new, highly flexible inorganic approach to design nanoparticle contrast agents for molecular MRI.
ContributorsClavijo Jordan, Maria Veronica (Author) / Bennett, Kevin M (Thesis advisor) / Kodibagkar, Vikram (Committee member) / Sherry, A Dean (Committee member) / Wang, Xiao (Committee member) / Yarger, Jeffery (Committee member) / Arizona State University (Publisher)
Created2012