ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- All Subjects: Biology
- Creators: Kang, Yun
- Creators: Roberson, Robert
Description
Mathematical modeling of infectious diseases can help public health officials to make decisions related to the mitigation of epidemic outbreaks. However, over or under estimations of the morbidity of any infectious disease can be problematic. Therefore, public health officials can always make use of better models to study the potential implication of their decisions and strategies prior to their implementation. Previous work focuses on the mechanisms underlying the different epidemic waves observed in Mexico during the novel swine origin influenza H1N1 pandemic of 2009 and showed extensions of classical models in epidemiology by adding temporal variations in different parameters that are likely to change during the time course of an epidemic, such as, the influence of media, social distancing, school closures, and how vaccination policies may affect different aspects of the dynamics of an epidemic. This current work further examines the influence of different factors considering the randomness of events by adding stochastic processes to meta-population models. I present three different approaches to compare different stochastic methods by considering discrete and continuous time. For the continuous time stochastic modeling approach I consider the continuous-time Markov chain process using forward Kolmogorov equations, for the discrete time stochastic modeling I consider stochastic differential equations using Wiener's increment and Poisson point increments, and also I consider the discrete-time Markov chain process. These first two stochastic modeling approaches will be presented in a one city and two city epidemic models using, as a base, our deterministic model. The last one will be discussed briefly on a one city SIS and SIR-type model.
ContributorsCruz-Aponte, Maytee (Author) / Wirkus, Stephen A. (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Camacho, Erika T. (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
There has been important progress in understanding ecological dynamics through the development of the theory of ecological stoichiometry. This fast growing theory provides new constraints and mechanisms that can be formulated into mathematical models. Stoichiometric models incorporate the effects of both food quantity and food quality into a single framework that produce rich dynamics. While the effects of nutrient deficiency on consumer growth are well understood, recent discoveries in ecological stoichiometry suggest that consumer dynamics are not only affected by insufficient food nutrient content (low phosphorus (P): carbon (C) ratio) but also by excess food nutrient content (high P:C). This phenomenon, known as the stoichiometric knife edge, in which animal growth is reduced not only by food with low P content but also by food with high P content, needs to be incorporated into mathematical models. Here we present Lotka-Volterra type models to investigate the growth response of Daphnia to algae of varying P:C ratios. Using a nonsmooth system of two ordinary differential equations (ODEs), we formulate the first model to incorporate the phenomenon of the stoichiometric knife edge. We then extend this stoichiometric model by mechanistically deriving and tracking free P in the environment. This resulting full knife edge model is a nonsmooth system of three ODEs. Bifurcation analysis and numerical simulations of the full model, that explicitly tracks phosphorus, leads to quantitatively different predictions than previous models that neglect to track free nutrients. The full model shows that the grazer population is sensitive to excess nutrient concentrations as a dynamical free nutrient pool induces extreme grazer population density changes. These modeling efforts provide insight on the effects of excess nutrient content on grazer dynamics and deepen our understanding of the effects of stoichiometry on the mechanisms governing population dynamics and the interactions between trophic levels.
ContributorsPeace, Angela (Author) / Kuang, Yang (Thesis advisor) / Elser, James J (Committee member) / Baer, Steven (Committee member) / Tang, Wenbo (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
In 1968, phycologist M.R. Droop published his famous discovery on the functional relationship between growth rate and internal nutrient status of algae in chemostat culture. The simple notion that growth is directly dependent on intracellular nutrient concentration is useful for understanding the dynamics in many ecological systems. The cell quota in particular lends itself to ecological stoichiometry, which is a powerful framework for mathematical ecology. Three models are developed based on the cell quota principal in order to demonstrate its applications beyond chemostat culture.
First, a data-driven model is derived for neutral lipid synthesis in green microalgae with respect to nitrogen limitation. This model synthesizes several established frameworks in phycology and ecological stoichiometry. The model demonstrates how the cell quota is a useful abstraction for understanding the metabolic shift to neutral lipid production that is observed in certain oleaginous species.
Next a producer-grazer model is developed based on the cell quota model and nutrient recycling. The model incorporates a novel feedback loop to account for animal toxicity due to accumulation of nitrogen waste. The model exhibits rich, complex dynamics which leave several open mathematical questions.
Lastly, disease dynamics in vivo are in many ways analogous to those of an ecosystem, giving natural extensions of the cell quota concept to disease modeling. Prostate cancer can be modeled within this framework, with androgen the limiting nutrient and the prostate and cancer cells as competing species. Here the cell quota model provides a useful abstraction for the dependence of cellular proliferation and apoptosis on androgen and the androgen receptor. Androgen ablation therapy is often used for patients in biochemical recurrence or late-stage disease progression and is in general initially effective. However, for many patients the cancer eventually develops resistance months to years after treatment begins. Understanding how and predicting when hormone therapy facilitates evolution of resistant phenotypes has immediate implications for treatment. Cell quota models for prostate cancer can be useful tools for this purpose and motivate applications to other diseases.
First, a data-driven model is derived for neutral lipid synthesis in green microalgae with respect to nitrogen limitation. This model synthesizes several established frameworks in phycology and ecological stoichiometry. The model demonstrates how the cell quota is a useful abstraction for understanding the metabolic shift to neutral lipid production that is observed in certain oleaginous species.
Next a producer-grazer model is developed based on the cell quota model and nutrient recycling. The model incorporates a novel feedback loop to account for animal toxicity due to accumulation of nitrogen waste. The model exhibits rich, complex dynamics which leave several open mathematical questions.
Lastly, disease dynamics in vivo are in many ways analogous to those of an ecosystem, giving natural extensions of the cell quota concept to disease modeling. Prostate cancer can be modeled within this framework, with androgen the limiting nutrient and the prostate and cancer cells as competing species. Here the cell quota model provides a useful abstraction for the dependence of cellular proliferation and apoptosis on androgen and the androgen receptor. Androgen ablation therapy is often used for patients in biochemical recurrence or late-stage disease progression and is in general initially effective. However, for many patients the cancer eventually develops resistance months to years after treatment begins. Understanding how and predicting when hormone therapy facilitates evolution of resistant phenotypes has immediate implications for treatment. Cell quota models for prostate cancer can be useful tools for this purpose and motivate applications to other diseases.
ContributorsPacker, Aaron (Author) / Kuang, Yang (Thesis advisor) / Nagy, John (Committee member) / Smith, Hal (Committee member) / Kostelich, Eric (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
The cyanobacterium Synechocystis sp. PCC 6803 performs oxygenic photosynthesis. Light energy conversion in photosynthesis takes place in photosystem I (PSI) and photosystem II (PSII) that contain chlorophyll, which absorbs light energy that is utilized as a driving force for photosynthesis. However, excess light energy may lead to formation of reactive oxygen species that cause damage to photosynthetic complexes, which subsequently need repair or replacement. To gain insight in the degradation/biogenesis dynamics of the photosystems, the lifetimes of photosynthetic proteins and chlorophyll were determined by a combined stable-isotope (15N) and mass spectrometry method. The lifetimes of PSII and PSI proteins ranged from 1-33 and 30-75 hours, respectively. Interestingly, chlorophyll had longer lifetimes than the chlorophyll-binding proteins in these photosystems. Therefore, photosynthetic proteins turn over and are replaced independently from each other, and chlorophyll is recycled from the damaged chlorophyll-binding proteins. In Synechocystis, there are five small Cab-like proteins (SCPs: ScpA-E) that share chlorophyll a/b-binding motifs with LHC proteins in plants. SCPs appear to transiently bind chlorophyll and to regulate chlorophyll biosynthesis. In this study, the association of ScpB, ScpC, and ScpD with damaged and repaired PSII was demonstrated. Moreover, in a mutant lacking SCPs, most PSII protein lifetimes were unaffected but the lifetime of chlorophyll was decreased, and one of the nascent PSII complexes was missing. SCPs appear to bind PSII chlorophyll while PSII is repaired, and SCPs stabilize nascent PSII complexes. Furthermore, aminolevulinic acid biosynthesis, an early step of chlorophyll biosynthesis, was impaired in the absence of SCPs, so that the amount of chlorophyll in the cells was reduced. Finally, a deletion mutation was introduced into the sll1906 gene, encoding a member of the putative bacteriochlorophyll delivery (BCD) protein family. The Sll1906 sequence contains possible chlorophyll-binding sites, and its homolog in purple bacteria functions in proper assembly of light-harvesting complexes. However, the sll1906 deletion did not affect chlorophyll degradation/biosynthesis and photosystem assembly. Other (parallel) pathways may exist that may fully compensate for the lack of Sll1906. This study has highlighted the dynamics of photosynthetic complexes in their biogenesis and turnover and the coordination between synthesis of chlorophyll and photosynthetic proteins.
ContributorsYao, Cheng I Daniel (Author) / Vermaas, Wim (Thesis advisor) / Fromme, Petra (Committee member) / Roberson, Robert (Committee member) / Webber, Andrew (Committee member) / Arizona State University (Publisher)
Created2011
Description
The most advanced social insects, the eusocial insects, form often large societies in which there is reproductive division of labor, queens and workers, have overlapping generations, and cooperative brood care where daughter workers remain in the nest with their queen mother and care for their siblings. The eusocial insects are composed of representative species of bees and wasps, and all species of ants and termites. Much is known about their organizational structure, but remains to be discovered.
The success of social insects is dependent upon cooperative behavior and adaptive strategies shaped by natural selection that respond to internal or external conditions. The objective of my research was to investigate specific mechanisms that have helped shaped the structure of division of labor observed in social insect colonies, including age polyethism and nutrition, and phenomena known to increase colony survival such as egg cannibalism. I developed various Ordinary Differential Equation (ODE) models in which I applied dynamical, bifurcation, and sensitivity analysis to carefully study and visualize biological outcomes in social organisms to answer questions regarding the conditions under which a colony can survive. First, I investigated how the population and evolutionary dynamics of egg cannibalism and division of labor can promote colony survival. I then introduced a model of social conflict behavior to study the inclusion of different response functions that explore the benefits of cannibalistic behavior and how it contributes to age polyethism, the change in behavior of workers as they age, and its biological relevance. Finally, I introduced a model to investigate the importance of pollen nutritional status in a honeybee colony, how it affects population growth and influences division of labor within the worker caste. My results first reveal that both cannibalism and division of labor are adaptive strategies that increase the size of the worker population, and therefore, the persistence of the colony. I show the importance of food collection, consumption, and processing rates to promote good colony nutrition leading to the coexistence of brood and adult workers. Lastly, I show how taking into account seasonality for pollen collection improves the prediction of long term consequences.
The success of social insects is dependent upon cooperative behavior and adaptive strategies shaped by natural selection that respond to internal or external conditions. The objective of my research was to investigate specific mechanisms that have helped shaped the structure of division of labor observed in social insect colonies, including age polyethism and nutrition, and phenomena known to increase colony survival such as egg cannibalism. I developed various Ordinary Differential Equation (ODE) models in which I applied dynamical, bifurcation, and sensitivity analysis to carefully study and visualize biological outcomes in social organisms to answer questions regarding the conditions under which a colony can survive. First, I investigated how the population and evolutionary dynamics of egg cannibalism and division of labor can promote colony survival. I then introduced a model of social conflict behavior to study the inclusion of different response functions that explore the benefits of cannibalistic behavior and how it contributes to age polyethism, the change in behavior of workers as they age, and its biological relevance. Finally, I introduced a model to investigate the importance of pollen nutritional status in a honeybee colony, how it affects population growth and influences division of labor within the worker caste. My results first reveal that both cannibalism and division of labor are adaptive strategies that increase the size of the worker population, and therefore, the persistence of the colony. I show the importance of food collection, consumption, and processing rates to promote good colony nutrition leading to the coexistence of brood and adult workers. Lastly, I show how taking into account seasonality for pollen collection improves the prediction of long term consequences.
ContributorsRodríguez Messan, Marisabel (Author) / Kang, Yun (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Kuang, Yang (Committee member) / Page Jr., Robert E (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2018
Description
A key factor in the success of social animals is their organization of work. Mathematical models have been instrumental in unraveling how simple, individual-based rules can generate collective patterns via self-organization. However, existing models offer limited insights into how these patterns are shaped by behavioral differences within groups, in part because they focus on analyzing specific rules rather than general mechanisms that can explain behavior at the individual-level. My work argues for a more principled approach that focuses on the question of how individuals make decisions in costly environments.
In Chapters 2 and 3, I demonstrate how this approach provides novel insights into factors that shape the flexibility and robustness of task organization in harvester ant colonies (Pogonomyrmex barbatus). My results show that the degree to which colonies can respond to work in fluctuating environments depends on how individuals weigh the costs of activity and update their behavior in response to social information. In Chapter 4, I introduce a mathematical framework to study the emergence of collective organization in heterogenous groups. My approach, which is based on the theory of multi-agent systems, focuses on myopic agents whose behavior emerges out of an independent valuation of alternative choices in a given work environment. The product of this dynamic is an equilibrium organization in which agents perform different tasks (or abstain from work) with an analytically defined set of threshold probabilities. The framework is minimally developed, but can be extended to include other factors known to affect task decisions including individual experience and social facilitation. This research contributes a novel approach to developing (and analyzing) models of task organization that can be applied in a broader range of contexts where animals cooperate.
In Chapters 2 and 3, I demonstrate how this approach provides novel insights into factors that shape the flexibility and robustness of task organization in harvester ant colonies (Pogonomyrmex barbatus). My results show that the degree to which colonies can respond to work in fluctuating environments depends on how individuals weigh the costs of activity and update their behavior in response to social information. In Chapter 4, I introduce a mathematical framework to study the emergence of collective organization in heterogenous groups. My approach, which is based on the theory of multi-agent systems, focuses on myopic agents whose behavior emerges out of an independent valuation of alternative choices in a given work environment. The product of this dynamic is an equilibrium organization in which agents perform different tasks (or abstain from work) with an analytically defined set of threshold probabilities. The framework is minimally developed, but can be extended to include other factors known to affect task decisions including individual experience and social facilitation. This research contributes a novel approach to developing (and analyzing) models of task organization that can be applied in a broader range of contexts where animals cooperate.
ContributorsUdiani, Oyita (Author) / Kang, Yun (Thesis advisor) / Fewell, Jennifer H (Thesis advisor) / Janssen, Marcus A (Committee member) / Castillo-Chavez, Carlos (Committee member) / Arizona State University (Publisher)
Created2016
Description
Variation in living systems and how it cascades across organizational levels is central to biology. To understand the constraints and amplifications of variation in collective systems, I mathematically study how group-level differences emerge from individual variation in eusocial-insect colonies, which are inherently diverse and easily observable individually and collectively. Considering collective processes in three species where increasing degrees of heterogeneity are relevant, I address how individual variation scales to colony-level variation and to what degree it is adaptive. In Chapter 2, I introduce a Markov-chain decision model for stochastic individual quorum-based recruitment decisions of rock-ant workers during house hunting, and how they determine collective speed--accuracy balance. Differences in the average threshold-dependent response characteristics of workers between colonies cause collective differences in decision-making. Moreover, noisy behavior may prevent drastic collective cascading into poor nests. In Chapter 3, I develop an ordinary differential equation (ODE) model to study how cognitive diversity among honey-bee foragers influences collective attention allocation between novel and familiar resources. Results provide a mechanistic basis for changes in foraging activity and preference with group composition. Moreover, sensitivity analysis reveals that the main individual driver for foraging allocation shifts from recruitment (communication) to persistence (independent effort) as colony composition changes. This might favor specific degrees of heterogeneity that best amplify communication in wild colonies. Lastly, in Chapter 4, I consider diversity in size, age, and task for nest defense in stingless bees. To better understand how these dimensions of diversity interact to balance defensive demands with other colony needs, I study their effect on colony size and task allocation through a demographic Filippov ODE model. Along each dimension, variation is beneficial in a certain range, outside of which colony adaptation and survival are compromised. This work elucidates how variation in collective properties emerges from nonlinear interactions between varying components in eusocial insects, but it can be generalized to other biological systems with similar fundamental characteristics but less empirical tractability. Moreover, it has the potential of inspiring algorithms that capitalize on heterogeneity in engineered systems where simple components with limited information and no central control must solve complex tasks.
ContributorsNavas Zuloaga, Maria Gabriela (Author) / Kang, Yun (Thesis advisor) / Smith, Brian H (Thesis advisor) / Pavlic, Theodore P (Committee member) / Arizona State University (Publisher)
Created2022
Description
Male reproductive dysfunction accounts for almost half of male infertility cases, yet the signaling mechanisms involved in the male reproductive system remain unclear. Although the exact cause of male reproductive dysfunction varies, obtaining a better understanding of the modulators of smooth muscle contractions may provide new targets for the treatment of male reproductive conditions. The male reproductive tract, consisting of the testes, epididymis, vas deferens, and penis, is lined with innervated smooth muscle fibers that transport spermatozoa through the system. Contractions of these smooth muscle fibers can be modulated by neurotransmitters and hormones, like dopamine and norepinephrine, as well as biogenic amines. The focus of this study is on the biogenic amine tyramine, which is produced by the breakdown of tyrosine via decarboxylation. Tyramine has been shown to modulate vasoconstriction and increase blood pressure due to its effect on smooth muscle contractions. This study has found that tyramine localizes in male reproductive tissues and modulates smooth muscle contractions. Age and environment were also found to play a significant role in the expression of tyramine and its associated receptor, TAAR1.
ContributorsSteadman, Solange (Author) / Baluch, Debra (Thesis advisor) / Roberson, Robert (Committee member) / Sweazea, Karen (Committee member) / Arizona State University (Publisher)
Created2023
Description
Human preterm labor is the single most significant issue in modern obstetrics andgynecology, affecting ten percent of pregnancies, constituting the leading cause of infant death, and contributing significantly to chronic childhood disease. Obstetricians and reproductive scientists are faced with the major challenge of trying to increase the understanding of the complex molecular and cellular signals that regulate uterine activity during human pregnancy and labor. Even though preterm labor accounts for a large portion of perinatal mortality and morbidity, there still is not an effective therapeutic strategy for the treatment or prevention of preterm labor. This dissertation presents tyramine as an alternative modulator of uterine activity. In this dissertation the aims were as follows: 1) to investigate the localization of tyramine and trace amine associated receptor 1 (TAAR1) in the mouse uterine horn using immunohistochemistry as well as confirm the presence of tyramine in the uterine tissue using high performance liquid chromatography, 2) identify which TAAR 1-9 subtypes were present in the mouse uterine horn using RT-qPCR, 3) investigate ultrastructural differences in the mouse uterine horn following tyramine and dopamine treatment using transmission electron microscopy and 4) investigate pinopod ultrastructure as well as pinopod ultrastructural differences following tyramine and dopamine treatment. The research presented in this dissertation showed: 1) tyramine has very specific localization in the mouse endometrium, mainly in the uterine glands, TAAR1 is localized all throughout the perimetrium, myometrium and endometrium, and that tyramine was confirmed and quantified using HPLC, 2) TAAR 1- 9 genes are expressed in trace levels in the mouse uterine horn, 3) tyramine influences changes in endometrial ultrastructure, and 4) tyramine influences changes in pinopod ultrastructure. Ultimately these findings can help with identifying novel treatment options not only for spontaneous preterm labor contractions but also for other uterine related disorders.
ContributorsObayomi, SM Bukola (Author) / Baluch, Debra P (Thesis advisor) / Roberson, Robert (Thesis advisor) / Sweazea, Karen (Committee member) / Brent, Colin (Committee member) / Arizona State University (Publisher)
Created2023
Description
Dominance behavior can regulate a division of labor in a group, such as that between reproductive and non-reproductive individuals. Manipulations of insect societies in a controlled environment can reveal how dominance behavior is regulated. Here, I examined how morphological caste, fecundity, group size, and age influence the expression of dominance behavior using the ponerine ant Harpegnathos saltator. All H. saltator females have the ability to reproduce. Only those with a queen morphology that enables dispersal, however, show putative sex pheromones. In contrast, those with a worker morphology normally express dominance behavior. To evaluate how worker-like dominance behavior and associated traits could be expressed in queens, I removed the wings from alate gynes, those with a queen morphology who had not yet mated or left the nest, making them dealate. Compared to gynes with attached wings, dealates frequently performed dominance behavior. In addition, only the dealates demonstrated worker-like ovarian activity in the presence of reproductive individuals, whereas gynes with wings produced sex pheromones exclusively. Therefore, the attachment of wings determines a gyne’s expression of worker-like dominance behavior and physiology. When the queen dies, workers establish a reproductive hierarchy among themselves by performing a combination of dominance behaviors. To understand how reproductive status depends on these interactions as well as a worker’s age, I measured the frequency of dominance behaviors in groups of different size composed of young and old workers. The number of workers who expressed dominance scaled with the size of the group, but younger ones were more likely to express dominance behavior and eventually become reproductive. Therefore, the predisposition of age integrates with a self-organized process to form this reproductive hierarchy. A social insect’s fecundity and fertility signal depends on social context because fecundity increases with colony size. To evaluate how a socially dependent signal regulates dominance behavior, I manipulated a reproductive worker’s social context. Reproductive workers with reduced fecundity and a less prominent fertility signal expressed more dominance behavior than those with a stronger fertility signal and higher fecundity. Therefore, dominance behavior reinforces rank to compensate for a weak signal, indicating how social context can feed back to influence the maintenance of dominance. Mechanisms that regulate H. saltator’s reproductive hierarchy can inform how the reproductive division of labor is regulated in other groups of animals.
ContributorsPyenson, Benjamin (Author) / Liebig, Jürgen (Thesis advisor) / Hölldobler, Bert (Committee member) / Fewell, Jennifer (Committee member) / Pratt, Stephen (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2022