Matching Items (156)
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Description
Dividing the plane in half leaves every border point of one region a border point of both regions. Can we divide up the plane into three or more regions such that any point on the boundary of at least one region is on the border of all the regions? In

Dividing the plane in half leaves every border point of one region a border point of both regions. Can we divide up the plane into three or more regions such that any point on the boundary of at least one region is on the border of all the regions? In fact, it is possible to design a dynamical system for which the basins of attractions have this Wada property. In certain circumstances, both the Hénon map, a simple system, and the forced damped pendulum, a physical model, produce Wada basins.
ContributorsWhitehurst, Ryan David (Author) / Kostelich, Eric (Thesis director) / Jones, Donald (Committee member) / Armbruster, Dieter (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2013-05
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Description
This thesis shows analyses of mixing and transport patterns associated with Hurricane Katrina as it hit the United States in August of 2005. Specifically, by applying atmospheric velocity information from the Weather Research and Forecasting System, finite-time Lyapunov exponents have been computed and the Lagrangian Coherent Structures have been identified.

This thesis shows analyses of mixing and transport patterns associated with Hurricane Katrina as it hit the United States in August of 2005. Specifically, by applying atmospheric velocity information from the Weather Research and Forecasting System, finite-time Lyapunov exponents have been computed and the Lagrangian Coherent Structures have been identified. The chaotic dynamics of material transport induced by the hurricane are results from these structures within the flow. Boundaries of the coherent structures are highlighted by the FTLE field. Individual particle transport within the hurricane is affected by the location of these boundaries. In addition to idealized fluid particles, we also studied inertial particles which have finite size and inertia. Basing on established Maxey-Riley equations of the dynamics of particles of finite size, we obtain a reduced equation governing the position process. Using methods derived from computer graphics, we identify maximizers of the FTLE field. Following and applying these ideas, we analyze the dynamics of inertial particle transport within Hurricane Katrina, through comparison of trajectories of dierent sized particles and by pinpointing the location of the Lagrangian Coherent Structures.
ContributorsWake, Christian (Author) / Tang, Wenbo (Thesis director) / Moustaoui, Mohamed (Committee member) / Kostelich, Eric (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2012-12
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Description
Tumor associated microglia-and-macrophages (TAMS) may constitute up to 30% of the composition of glioblastoma. Through mechanisms not well understood, TAMS are thought to aid the progression and invasiveness of glioblastoma. In an effort to investigate properties of TAMS in the context of glioblastoma, I utilized data from a PDGF-driven rat

Tumor associated microglia-and-macrophages (TAMS) may constitute up to 30% of the composition of glioblastoma. Through mechanisms not well understood, TAMS are thought to aid the progression and invasiveness of glioblastoma. In an effort to investigate properties of TAMS in the context of glioblastoma, I utilized data from a PDGF-driven rat model of glioma that highly resembles human glioblastoma. Data was collected from time-lapse microscopy of slice cultures that differentially labels glioma cells and also microglia cells within and outside the tumor microenvironment. Here I show that microglia localize in the tumor and move with greater speed and migration than microglia outside the tumor environment. Following previous studies that show microglia can be characterized by certain movement distributions based on environmental influences, in this study, the majority of microglia movement was characterized by a power law distribution with a characteristic power law exponent lower than outside the tumor region. This indicates that microglia travel at greater distances within the tumor region than outside of it.
ContributorsJuliano, Joseph Dominic (Author) / Kostelich, Eric (Thesis director) / Nagy, John (Committee member) / Swanson, Kristin (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2013-12
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Description
Using weather data from the Weather Research and Forecasting model (WRF), we analyze the transport of inertial particles in Hurricane Katrina in order to identify coherent patterns of motion. For our analysis, we choose a Lagrangian approach instead of an Eulerian approach because the Lagrangian approach is objective and frame-independent,

Using weather data from the Weather Research and Forecasting model (WRF), we analyze the transport of inertial particles in Hurricane Katrina in order to identify coherent patterns of motion. For our analysis, we choose a Lagrangian approach instead of an Eulerian approach because the Lagrangian approach is objective and frame-independent, and gives results which are better defined. In particular, we locate Lagrangian Coherent Structures (LCS), which are smooth sets of fluid particles which are locally most hyperbolic (either attracting or repelling). We implement a variational method for locating LCS and compare the results to previous computation of LCS using Finite-Time Lyapunov Exponents (FTLE) to identify regions of high stretching in the fluid flow.
ContributorsDeibel, Angelica Rae (Author) / Tang, Wenbo (Thesis director) / Moustaoui, Mohamed (Committee member) / Kostelich, Eric (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Physics (Contributor)
Created2013-05
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Description
In this research we consider stochastic models of Glioblastoma Multiforme brain tumors. We first look at a model by K. Swanson et al., which describes the dynamics as random diffusion plus deterministic logistic growth. We introduce a stochastic component in the logistic growth in the form of a random growth

In this research we consider stochastic models of Glioblastoma Multiforme brain tumors. We first look at a model by K. Swanson et al., which describes the dynamics as random diffusion plus deterministic logistic growth. We introduce a stochastic component in the logistic growth in the form of a random growth rate defined by a Poisson process. We show that this stochastic logistic growth model leads to a more accurate evaluation of the tumor growth compared its deterministic counterpart. We also discuss future plans to incorporate individual patient geometry, extend the model to three dimensions and to incorporate effects of different treatments into our model, in collaboration with a local hospital.
ContributorsManning, Michael Clare (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Gardner, Carl (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Letters and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2013-12
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Description

Five immunocompetent C57BL/6-cBrd/cBrd/Cr (albino C57BL/6) mice were injected with GL261-luc2 cells, a cell line sharing characteristics of human glioblastoma multiforme (GBM). The mice were imaged using magnetic resonance (MR) at five separate time points to characterize growth and development of the tumor. After 25 days, the final tumor volumes of

Five immunocompetent C57BL/6-cBrd/cBrd/Cr (albino C57BL/6) mice were injected with GL261-luc2 cells, a cell line sharing characteristics of human glioblastoma multiforme (GBM). The mice were imaged using magnetic resonance (MR) at five separate time points to characterize growth and development of the tumor. After 25 days, the final tumor volumes of the mice varied from 12 mm3 to 62 mm3, even though mice were inoculated from the same tumor cell line under carefully controlled conditions. We generated hypotheses to explore large variances in final tumor size and tested them with our simple reaction-diffusion model in both a 3-dimensional (3D) finite difference method and a 2-dimensional (2D) level set method. The parameters obtained from a best-fit procedure, designed to yield simulated tumors as close as possible to the observed ones, vary by an order of magnitude between the three mice analyzed in detail. These differences may reflect morphological and biological variability in tumor growth, as well as errors in the mathematical model, perhaps from an oversimplification of the tumor dynamics or nonidentifiability of parameters. Our results generate parameters that match other experimental in vitro and in vivo measurements. Additionally, we calculate wave speed, which matches with other rat and human measurements.

ContributorsRutter, Erica (Author) / Stepien, Tracy (Author) / Anderies, Barrett (Author) / Plasencia, Jonathan (Author) / Woolf, Eric C. (Author) / Scheck, Adrienne C. (Author) / Turner, Gregory H. (Author) / Liu, Qingwei (Author) / Frakes, David (Author) / Kodibagkar, Vikram (Author) / Kuang, Yang (Author) / Preul, Mark C. (Author) / Kostelich, Eric (Author) / College of Liberal Arts and Sciences (Contributor)
Created2017-05-31
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Description
In oxygenic photosynthesis, Photosystem I (PSI) and Photosystem II (PSII) are two transmembrane protein complexes that catalyze the main step of energy conversion; the light induced charge separation that drives an electron transfer reaction across the thylakoid membrane. Current knowledge of the structure of PSI and PSII is based on

In oxygenic photosynthesis, Photosystem I (PSI) and Photosystem II (PSII) are two transmembrane protein complexes that catalyze the main step of energy conversion; the light induced charge separation that drives an electron transfer reaction across the thylakoid membrane. Current knowledge of the structure of PSI and PSII is based on three structures: PSI and PSII from the thermophilic cyanobacterium Thermosynechococcus elonagatus and the PSI/light harvesting complex I (PSI-LHCI) of the plant, Pisum sativum. To improve the knowledge of these important membrane protein complexes from a wider spectrum of photosynthetic organisms, photosynthetic apparatus of the thermo-acidophilic red alga, Galdieria sulphuraria and the green alga, Chlamydomonas reinhardtii were studied. Galdieria sulphuraria grows in extreme habitats such as hot sulfur springs with pH values from 0 to 4 and temperatures up to 56°C. In this study, both membrane protein complexes, PSI and PSII were isolated from this organism and characterized. Ultra-fast fluorescence spectroscopy and electron microscopy studies of PSI-LHCI supercomplexes illustrate how this organism has adapted to low light environmental conditions by tightly coupling PSI and LHC, which have not been observed in any organism so far. This result highlights the importance of structure-function relationships in different ecosystems. Galdieria sulphuraria PSII was used as a model protein to show the amenability of integral membrane proteins to top-down mass spectrometry. G.sulphuraria PSII has been characterized with unprecedented detail with identification of post translational modification of all the PSII subunits. This study is a technology advancement paving the way for the usage of top-down mass spectrometry for characterization of other large integral membrane proteins. The green alga, Chlamydomonas reinhardtii is widely used as a model for eukaryotic photosynthesis and results from this organism can be extrapolated to other eukaryotes, especially agricultural crops. Structural and functional studies on the PSI-LHCI complex of C.reinhardtii grown under high salt conditions were studied using ultra-fast fluorescence spectroscopy, circular dichroism and MALDI-TOF. Results revealed that pigment-pigment interactions in light harvesting complexes are disrupted and the acceptor side (ferredoxin docking side) is damaged under high salt conditions.
ContributorsThangaraj, Balakumar (Author) / Fromme, Petra (Thesis advisor) / Shock, Everett (Committee member) / Chen, Julian (Committee member) / Arizona State University (Publisher)
Created2010
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Description

Over time, tumor treatment resistance inadvertently develops when androgen de-privation therapy (ADT) is applied to metastasized prostate cancer (PCa). To combat tumor resistance, while reducing the harsh side effects of hormone therapy, the clinician may opt to cyclically alternates the patient’s treatment on and off. This method,known as intermittent ADT,

Over time, tumor treatment resistance inadvertently develops when androgen de-privation therapy (ADT) is applied to metastasized prostate cancer (PCa). To combat tumor resistance, while reducing the harsh side effects of hormone therapy, the clinician may opt to cyclically alternates the patient’s treatment on and off. This method,known as intermittent ADT, is an alternative to continuous ADT that improves the patient’s quality of life while testosterone levels recover between cycles. In this paper,we explore the response of intermittent ADT to metastasized prostate cancer by employing a previously clinical data validated mathematical model to new clinical data from patients undergoing Abiraterone therapy. This cell quota model, a system of ordinary differential equations constructed using Droop’s nutrient limiting theory, assumes the tumor comprises of castration-sensitive (CS) and castration-resistant (CR)cancer sub-populations. The two sub-populations rely on varying levels of intracellular androgen for growth, death and transformation. Due to the complexity of the model,we carry out sensitivity analyses to study the effect of certain parameters on their outputs, and to increase the identifiability of each patient’s unique parameter set. The model’s forecasting results show consistent accuracy for patients with sufficient data,which means the model could give useful information in practice, especially to decide whether an additional round of treatment would be effective.

ContributorsBennett, Justin Klark (Author) / Kuang, Yang (Thesis director) / Kostelich, Eric (Committee member) / Phan, Tin (Committee member) / School of Mathematical and Statistical Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description
Tempe Town Lake is the site of fifteen years’ worth of chemical data collection by ASU researchers. In 2018 the dataSONDE, an instrument capable of measuring different water quality parameters every thirty minutes for a month at a time was installed in the lake. The SONDE has the potential to

Tempe Town Lake is the site of fifteen years’ worth of chemical data collection by ASU researchers. In 2018 the dataSONDE, an instrument capable of measuring different water quality parameters every thirty minutes for a month at a time was installed in the lake. The SONDE has the potential to completely reduce the need for sampling by hand. Before the SONDE becomes the sole means of gathering data, it is important to verify its accuracy. In this study, the measurements gathered by the SONDE (pH, dissolved oxygen, temperature, conductivity and colored dissolved organic matter) were compared to measurements gathered using the verified methods from the past fifteen years.
ContributorsSauer, Elinor Rayne (Author) / Hartnett, Hilairy (Thesis director) / Glaser, Donald (Committee member) / Shock, Everett (Committee member) / Historical, Philosophical & Religious Studies (Contributor) / School of Molecular Sciences (Contributor) / School of Life Sciences (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
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Description
Background
Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D,

Background
Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria.
Methodology
We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure.
Principal Findings
We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations.
Conclusions
Our results provide a new perspective on nuclear structure variations associated with malignancy and point to the value of automated quantitative 3D nuclear morphometry as an objective tool to enable development of sensitive and specific nuclear grade classification in breast cancer diagnosis.
Created2012-01-05