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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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
A notable feature of advanced eusocial insect groups is a division of labor within the sterile worker caste. However, the physiological aspects underlying the differentiation of behavioral phenotypes are poorly understood in one of the most successful social taxa, the ants. By starting to understand the foundations on which social behaviors are built, it also becomes possible to better evaluate hypothetical explanations regarding the mechanisms behind the evolution of insect eusociality, such as the argument that the reproductive regulatory infrastructure of solitary ancestors was co-opted and modified to produce distinct castes. This dissertation provides new information regarding the internal factors that could underlie the division of labor observed in both founding queens and workers of Pogonomyrmex californicus ants, and shows that changes in task performance are correlated with differences in reproductive physiology in both castes. In queens and workers, foraging behavior is linked to elevated levels of the reproductively-associated juvenile hormone (JH), and, in workers, this behavioral change is accompanied by depressed levels of ecdysteroid hormones. In both castes, the transition to foraging is also associated with reduced ovarian activity. Further investigation shows that queens remain behaviorally plastic, even after worker emergence, but the association between JH and behavioral bias remains the same, suggesting that this hormone is an important component of behavioral development in these ants. In addition to these reproductive factors, treatment with an inhibitor of the nutrient-sensing pathway Target of Rapamycin (TOR) also causes queens to become biased towards foraging, suggesting an additional sensory component that could play an important role in division of labor. Overall, this work provides novel identification of the possible regulators behind ant division of labor, and suggests how reproductive physiology could play an important role in the evolution and regulation of non-reproductive social behaviors.
ContributorsDolezal, Adam G (Author) / Amdam, Gro V (Thesis advisor) / Brent, Colin S. (Committee member) / Gadau, Juergen (Committee member) / Hoelldobler, Bert (Committee member) / Liebig, Juergen (Committee member) / Arizona State University (Publisher)
Created2012
Description
For interspecific mutualisms, the behavior of one partner can influence the fitness of the other, especially in the case of symbiotic mutualisms where partners live in close physical association for much of their lives. Behavioral effects on fitness may be particularly important if either species in these long-term relationships displays personality. Animal personality is defined as repeatable individual differences in behavior, and how correlations among these consistent traits are structured is termed behavioral syndromes. Animal personality has been broadly documented across the animal kingdom but is poorly understood in the context of mutualisms. My dissertation focuses on the structure, causes, and consequences of collective personality in Azteca constructor colonies that live in Cecropia trees, one of the most successful and prominent mutualisms of the neotropics. These pioneer plants provide hollow internodes for nesting and nutrient-rich food bodies; in return, the ants provide protection from herbivores and encroaching vines. I first explored the structure of the behavioral syndrome by testing the consistency and correlation of colony-level behavioral traits under natural conditions in the field. Traits were both consistent within colonies and correlated among colonies revealing a behavioral syndrome along a docile-aggressive axis. Host plants of more active, aggressive colonies had less leaf damage, suggesting a link between a colony personality and host plant health. I then studied how aspects of colony sociometry are intertwined with their host plants by assessing the relationship among plant growth, colony growth, colony structure, ant morphology, and colony personality. Colony personality was independent of host plant measures like tree size, age, volume. Finally, I tested how colony personality influenced by soil nutrients by assessing personality in the field and transferring colonies to plants the greenhouse under different soil nutrient treatments. Personality was correlated with soil nutrients in the field but was not influenced by soil nutrient treatment in the greenhouse. This suggests that soil nutrients interact with other factors in the environment to structure personality. This dissertation demonstrates that colony personality is an ecologically relevant phenomenon and an important consideration for mutualism dynamics.
ContributorsMarting, Peter (Author) / Pratt, Stephen C (Thesis advisor) / Wcislo, William T (Committee member) / Hoelldobler, Bert (Committee member) / Fewell, Jennifer H (Committee member) / Gadau, Juergen (Committee member) / Arizona State University (Publisher)
Created2018
Description
An important component of insect social structure is the number of queens that cohabitate in a colony. Queen number is highly variable between and within species. It can begin at colony initiation when often unrelated queens form cooperative social groups, a strategy known as primary polygyny. The non-kin cooperative groups formed by primary polygyny have profound effects on the social dynamics and inclusive fitness benefits within a colony. Despite this, the evolution of non-kin queen cooperation has been relatively overlooked in considerations of the evolution of cooperative sociality. To date, studies examining the costs and benefits of primary polygyny have focused primarily on the advantages of multiple queens during colony founding and early growth, but the impact of their presence extends to colony maturity and reproduction.
In this dissertation, I evaluate the ecological drivers and fitness consequences of non-kin queen cooperation, by comparing the reproduction of mature single-queen versus polygynous harvester ant (Pogonomyrmex californicus) colonies in the field. I captured and quantified the total number and biomass of reproductives across multiple mating seasons, comparing between populations that vary in the proportion of single queen versus polygynous colonies, to assess the fitness outcomes of queen cooperation. Colonies in a mainly polygynous site had lower reproductive investment than those in sites with predominantly single-queen colonies. The site dominated by polygyny had higher colony density and displayed evidence of resource limitation, pressures that may drive the evolution of queen cooperation.
I also used microsatellite markers to examine how polygynous queens share worker and reproductive production with nest-mate queens. The majority of queens fairly contribute to worker production and equally share reproductive output. However, there is a low frequency of queens that under-produce workers and over-produce reproductive offspring. This suggests that cheating by reproducing queens is possible, but uncommon. Competitive pressure from neighboring colonies could reduce the success of colonies that contain cheaters and maintain a low frequency of this phenotype in the population.
In this dissertation, I evaluate the ecological drivers and fitness consequences of non-kin queen cooperation, by comparing the reproduction of mature single-queen versus polygynous harvester ant (Pogonomyrmex californicus) colonies in the field. I captured and quantified the total number and biomass of reproductives across multiple mating seasons, comparing between populations that vary in the proportion of single queen versus polygynous colonies, to assess the fitness outcomes of queen cooperation. Colonies in a mainly polygynous site had lower reproductive investment than those in sites with predominantly single-queen colonies. The site dominated by polygyny had higher colony density and displayed evidence of resource limitation, pressures that may drive the evolution of queen cooperation.
I also used microsatellite markers to examine how polygynous queens share worker and reproductive production with nest-mate queens. The majority of queens fairly contribute to worker production and equally share reproductive output. However, there is a low frequency of queens that under-produce workers and over-produce reproductive offspring. This suggests that cheating by reproducing queens is possible, but uncommon. Competitive pressure from neighboring colonies could reduce the success of colonies that contain cheaters and maintain a low frequency of this phenotype in the population.
ContributorsHaney, Brian R (Author) / Fewell, Jennifer H (Thesis advisor) / Cole, Blaine J. (Committee member) / Gadau, Juergen (Committee member) / Hoelldobler, Bert (Committee member) / Rutowski, Ron L (Committee member) / Arizona State University (Publisher)
Created2017
Description
Predicting resistant prostate cancer is critical for lowering medical costs and improving the quality of life of advanced prostate cancer patients. I formulate, compare, and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). I accomplish these tasks by employing clinical data of locally advanced prostate cancer patients undergoing androgen deprivation therapy (ADT). I demonstrate that the inverse problem of parameter estimation might be too complicated and simply relying on data fitting can give incorrect conclusions, since there is a large error in parameter values estimated and parameters might be unidentifiable. I provide confidence intervals to give estimate forecasts using data assimilation via an ensemble Kalman Filter. Using the ensemble Kalman Filter, I perform dual estimation of parameters and state variables to test the prediction accuracy of the models. Finally, I present a novel model with time delay and a delay-dependent parameter. I provide a geometric stability result to study the behavior of this model and show that the inclusion of time delay may improve the accuracy of predictions. Also, I demonstrate with clinical data that the inclusion of the delay-dependent parameter facilitates the identification and estimation of parameters.
ContributorsBaez, Javier (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric (Committee member) / Crook, Sharon (Committee member) / Gardner, Carl (Committee member) / Nagy, John (Committee member) / Arizona State University (Publisher)
Created2017
Description
Understanding how and why animals choose what to eat is one of the fundamental goals of nutritional and behavioral biology. This question can be scaled to animals that live in social groups, including eusocial insects. One of the factors that plays an important role in foraging decisions is the prevalence of specific nutrients and their relative balance. This dissertation explores the role of relative nutrient content in the food selection decisions of a species that is eusocial and also agricultural, the desert leafcutter ant Acromyrmex versicolor. A dietary choice assay, in which the relative amount of protein and carbohydrates in the available diets was varied, demonstrated that A. versicolor colonies regulate relative collection of protein and carbohydrates. Tracking the foraging behavior of individual workers revelaed that foragers vary in their relative collection of experimental diets and in their foraging frequency, but that there is no relationship between these key factors of foraging behavior. The high proportion of carbohydrates preferred by lab colonies suggests that they forage to nutritionally support the fungus rather than brood and workers. To test this, the relative amounts of 1) fungus, and 2) brood (larvae) was manipulated and foraging response was measured. Changing the amount of brood had no effect on foraging. Although decreasing the size of fungus gardens did not change relative P:C collection, it produced significant increases in caloric intake, supporting the assertion that the fungus is the main driver of colony nutrient regulation. The nutritional content of naturally harvested forage material collected from field colonies was measured, as was recruitment to experimental diets with varying relative macronutrient content. Field results confirmed a strong colony preference for high carbohydrate diets. They also indicated that this species may, at times, be limited in its ability to collect sufficiently high levels of carbohydrates to meet optimal intake. This dissertation provides important insights about fundamental aspects of leafcutter ant biology and extends our understanding of the role of relative nutrient content in foraging decisions to systems that span multiple trophic levels.
ContributorsSmith, Nathan Edward (Author) / Fewell, Jennifer H (Thesis advisor) / Harrison, Jon F (Committee member) / Pavlic, Ted (Committee member) / Cease, Arianne (Committee member) / Hoelldobler, Bert (Committee member) / Arizona State University (Publisher)
Created2023
Description
Cancer is a disease involving abnormal growth of cells. Its growth dynamics is perplexing. Mathematical modeling is a way to shed light on this progress and its medical treatments. This dissertation is to study cancer invasion in time and space using a mathematical approach. Chapter 1 presents a detailed review of literature on cancer modeling.
Chapter 2 focuses sorely on time where the escape of a generic cancer out of immune control is described by stochastic delayed differential equations (SDDEs). Without time delay and noise, this system demonstrates bistability. The effects of response time of the immune system and stochasticity in the tumor proliferation rate are studied by including delay and noise in the model. Stability, persistence and extinction of the tumor are analyzed. The result shows that both time delay and noise can induce the transition from low tumor burden equilibrium to high tumor equilibrium. The aforementioned work has been published (Han et al., 2019b).
In Chapter 3, Glioblastoma multiforme (GBM) is studied using a partial differential equation (PDE) model. GBM is an aggressive brain cancer with a grim prognosis. A mathematical model of GBM growth with explicit motility, birth, and death processes is proposed. A novel method is developed to approximate key characteristics of the wave profile, which can be compared with MRI data. Several test cases of MRI data of GBM patients are used to yield personalized parameterizations of the model. The aforementioned work has been published (Han et al., 2019a).
Chapter 4 presents an innovative way of forecasting spatial cancer invasion. Most mathematical models, including the ones described in previous chapters, are formulated based on strong assumptions, which are hard, if not impossible, to verify due to complexity of biological processes and lack of quality data. Instead, a nonparametric forecasting method using Gaussian processes is proposed. By exploiting the local nature of the spatio-temporal process, sparse (in terms of time) data is sufficient for forecasting. Desirable properties of Gaussian processes facilitate selection of the size of the local neighborhood and computationally efficient propagation of uncertainty. The method is tested on synthetic data and demonstrates promising results.
Chapter 2 focuses sorely on time where the escape of a generic cancer out of immune control is described by stochastic delayed differential equations (SDDEs). Without time delay and noise, this system demonstrates bistability. The effects of response time of the immune system and stochasticity in the tumor proliferation rate are studied by including delay and noise in the model. Stability, persistence and extinction of the tumor are analyzed. The result shows that both time delay and noise can induce the transition from low tumor burden equilibrium to high tumor equilibrium. The aforementioned work has been published (Han et al., 2019b).
In Chapter 3, Glioblastoma multiforme (GBM) is studied using a partial differential equation (PDE) model. GBM is an aggressive brain cancer with a grim prognosis. A mathematical model of GBM growth with explicit motility, birth, and death processes is proposed. A novel method is developed to approximate key characteristics of the wave profile, which can be compared with MRI data. Several test cases of MRI data of GBM patients are used to yield personalized parameterizations of the model. The aforementioned work has been published (Han et al., 2019a).
Chapter 4 presents an innovative way of forecasting spatial cancer invasion. Most mathematical models, including the ones described in previous chapters, are formulated based on strong assumptions, which are hard, if not impossible, to verify due to complexity of biological processes and lack of quality data. Instead, a nonparametric forecasting method using Gaussian processes is proposed. By exploiting the local nature of the spatio-temporal process, sparse (in terms of time) data is sufficient for forecasting. Desirable properties of Gaussian processes facilitate selection of the size of the local neighborhood and computationally efficient propagation of uncertainty. The method is tested on synthetic data and demonstrates promising results.
ContributorsHan, Lifeng (Author) / Kuang, Yang (Thesis advisor) / Fricks, John (Thesis advisor) / Kostelich, Eric (Committee member) / Baer, Steve (Committee member) / Gumel, Abba (Committee member) / Arizona State University (Publisher)
Created2020