Matching Items (141)
Description
There is an estimated five trillion pieces of plastic in the global ocean, with 4.8 to 12.7 million metric tons entering the ocean annually. Much of the plastic in the ocean is in the form of microplastics, or plastic particles <5mm in size. Microplastics enter the marine environment as primary or secondary microplastics; primary microplastics are pre-manufactured micro-sized particles, such as microbeads used in cosmetics, while secondary microplastics form from the degradation of larger plastic objects, such water bottles. Once in the ocean, plastics are readily colonized by a consortium of prokaryotic and eukaryotic organisms, which form dense biofilms on the plastic; this biofilm is termed the “plastisphere”. Despite growing concerns about the ecological impact of microplastics and their respective plastispheres on the marine environment, there is little consensus about the factors that shape the plastisphere on environmentally relevant secondary microplastics. The goal of my dissertation is to comprehensively analyze the role of plastic polymer type, incubation time, and geographic location on shaping plastisphere communities attached to secondary microplastics. I investigated the plastisphere of six chemically distinct plastic polymer types obtained from common household consumer products that were incubated in the coastal Caribbean (Bocas del Toro, Panama) and coastal Pacific (San Diego, CA) oceans. Genotyping using 16S and 18S rRNA gene amplification and next-generation Illumina sequencing was employed to identify bacterial and eukaryotic communities on the polymer surfaces. Statistical analyses show that there were no polymer-specific assemblages for prokaryotes or eukaryotes, but rather a microbial core community that was shared among plastic types. I also found that rare hydrocarbon degrading bacteria may be specific to certain chemical properties of the microplastics. Statistical comparisons of the communities across both sites showed that prokaryotic plastispheres were shaped primarily by incubation time and geographic location. Finally, I assessed the impact of biofilms on microplastic degradation and deposition and conclude that biofilms enhance microplastic sinking of negatively buoyant particles and reduce microplastic degradation. The results of my dissertation increases understanding of the factors that shape the plastisphere and how these communities ultimately determine the fate of microplastics in the marine environment.
ContributorsDudek, Kassandra Lynn (Author) / Neuer, Susanne (Thesis advisor) / Polidoro, Beth (Committee member) / Garcia-Pichel, Ferran (Committee member) / Cao, Huansheng (Committee member) / Arizona State University (Publisher)
Created2021
Description
With the development and successful landing of the NASA Perseverance rover, there has been growing interest in identifying how evidence of ancient life may be preserved and recognized in the geologic record. Environments that enable fossilization of biological remains are termed, “taphonomic windows”, wherein signatures of past life may be detected. In this dissertation, I have sought to identify taphonomic windows in planetary-analog environments with an eye towards the exploration of Mars. In the first chapter, I describe how evidence of past microbial life may be preserved within serpentinizing systems. Owing to energetic rock-water reactions, these systems are known to host lithotrophic and organotrophic microbial communities. By investigating drill cores from the Samail Ophiolite in Oman, I report morphological and associated chemical biosignatures preserved in these systems as a result of subsurface carbonation. As serpentinites are known to occur on Mars and potentially other planetary bodies, these deposits potentially represent high-priority targets in the exploration for past microbial life. Next, I investigated samples from Atacama Desert, Chile, to understand how evidence of life may be preserved in ancient sediments formed originally in evaporative playa lakes. Here, I describe organic geochemical and morphological evidence of life preserved within sulfate-dominated evaporite rocks from the Jurassic-Cretaceous Tonel Formation and Oligocene San Pedro Formation. Because evaporative lakes are considered to have been potentially widespread on Mars, these deposits may represent additional key targets to search for evidence of past life. In the final chapter, I describe the fossilization potential of surficial carbonates by investigating Crystal Geyser, an active cold spring environment. Here, carbonate minerals precipitate rapidly in the presence of photosynthetic microbial mat communities. I describe how potential biosignatures are initially captured by mineralization, including cell-like structures and microdigitate stromatolites. However, these morphological signatures quickly degrade owing to diagenetic dissolution and recrystallization reactions, as well as textural coarsening that homogenizes the carbonate fabric. Overall, my dissertation underscores the complexity of microbial fossilization and highlights chemically-precipitating environments that may serve as high-priority targets for astrobiological exploration.
ContributorsZaloumis, Jonathan (Author) / Farmer, Jack D (Thesis advisor) / Garcia-Pichel, Ferran (Committee member) / Trembath-Reichert, Elizabeth (Committee member) / Ruff, Steven W (Committee member) / Shock, Everett L (Committee member) / Arizona State University (Publisher)
Created2021
Description
The representation of a patient’s characteristics as the parameters of a model is a key component in many studies of personalized medicine, where the underlying mathematical models are used to describe, explain, and forecast the course of treatment. In this context, clinical observations form the bridge between the mathematical frameworks and applications. However, the formulation and theoretical studies of the models and the clinical studies are often not completely compatible, which is one of the main obstacles in the application of mathematical models in practice. The goal of my study is to extend a mathematical framework to model prostate cancer based mainly on the concept of cell-quota within an evolutionary framework and to study the relevant aspects for the model to gain useful insights in practice. Specifically, the first aim is to construct a mathematical model that can explain and predict the observed clinical data under various treatment combinations. The second aim is to find a fundamental model structure that can capture the dynamics of cancer progression within a realistic set of data. Finally, relevant clinical aspects such as how the patient's parameters change over the course of treatment and how to incorporate treatment optimization within a framework of uncertainty quantification, will be examined to construct a useful framework in practice.
ContributorsPhan, Tin (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric J (Committee member) / Crook, Sharon (Committee member) / Maley, Carlo (Committee member) / Bryce, Alan (Committee member) / Arizona State University (Publisher)
Created2021
Description
Synthetic biology (SB) has become an important field of science focusing on designing and engineering new biological parts and systems, or re-designing existing biological systems for useful purposes. The dramatic growth of SB throughout the past two decades has not only provided us numerous achievements, but also brought us more timely and underexplored problems. In SB's entire history, mathematical modeling has always been an indispensable approach to predict the experimental outcomes, improve experimental design and obtain mechanism-understanding of the biological systems. \textit{Escherichia coli} (\textit{E. coli}) is one of the most important experimental platforms, its growth dynamics is the major research objective in this dissertation. Chapter 2 employs a reaction-diffusion model to predict the \textit{E. coli} colony growth on a semi-solid agar plate under multiple controls. In that chapter, a density-dependent diffusion model with non-monotonic growth to capture the colony's non-linear growth profile is introduced. Findings of the new model to experimental data are compared and contrasted with those from other proposed models. In addition, the cross-sectional profile of the colony are computed and compared with experimental data. \textit{E. coli} colony is also used to perform spatial patterns driven by designed gene circuits. In Chapter 3, a gene circuit (MINPAC) and its corresponding pattern formation results are presented. Specifically, a series of partial differential equation (PDE) models are developed to describe the pattern formation driven by the MINPAC circuit. Model simulations of the patterns based on different experimental conditions and numerical analysis of the models to obtain a deeper understanding of the mechanisms are performed and discussed. Mathematical analysis of the simplified models, including traveling wave analysis and local stability analysis, is also presented and used to explore the control strategies of the pattern formation. The interaction between the gene circuit and the host \textit{E. coli} may be crucial and even greatly affect the experimental outcomes. Chapter 4 focuses on the growth feedback between the circuit and the host cell under different nutrient conditions. Two ordinary differential equation (ODE) models are developed to describe such feedback with nutrient variation. Preliminary results on data fitting using both two models and the model dynamical analysis are included.
ContributorsHe, Changhan (Author) / Kuang, Yang (Thesis advisor) / Wang, Xiao (Committee member) / Kostelich, Eric (Committee member) / Tian, Xiaojun (Committee member) / Gumel, Abba (Committee member) / Arizona State University (Publisher)
Created2021
Description
Since the 20th century, Arizona has undergone shifts in agricultural practices, driven by urban expansion and crop irrigation regulations. These changes present environmental challenges, altering atmospheric processes and influencing climate dynamics. Given the potential threats of climate change and drought on water availability for agriculture, further modifications in the agricultural landscape are expected. To understand these land use changes and their impact on carbon dynamics, our study quantified aboveground carbon storage in both cultivated and
abandoned agricultural fields. To accomplish this, we employed Python and various geospatial libraries in Jupyter Notebook files, for thorough dataset assembly and visual, quantitative analysis. We focused on nine counties known for high cultivation levels, primarily located in the lower latitudes of Arizona. Our analysis investigated carbon dynamics across not only abandoned and actively cultivated croplands but also neighboring uncultivated land, for which we estimated the extent. Additionally, we compared these trends with those observed in developed land areas.
The findings revealed a hierarchy in aboveground carbon storage, with currently cultivated lands having the lowest levels, followed by abandoned croplands and uncultivated wilderness. However, wilderness areas exhibited significant variation in carbon storage by county compared to cultivated and abandoned lands. Developed lands ranked highest in aboveground carbon storage, with the median value being the highest. Despite county-wide variations, abandoned croplands generally contained more carbon than currently cultivated areas, with adjacent wilderness lands containing even more than both. This trend suggests that cultivating croplands in the region reduces aboveground carbon stores, while abandonment allows for some replenishment, though only to a limited extent. Enhancing carbon stores in Arizona can be achieved through active restoration efforts on abandoned cropland. By promoting native plant regeneration and boosting aboveground carbon levels, these measures are crucial for improving carbon sequestration. We strongly advocate for implementing this step to facilitate the regrowth of native plants and enhance overall carbon storage in the region.
ContributorsGoodwin, Emily (Author) / Eikenberry, Steffen (Thesis director) / Kuang, Yang (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2024-05
Description
Glioblastoma Multiforme is a prevalent and aggressive brain tumor. It has an average 5-year survival rate of 6% and average survival time of 14 months. Using patient-specific MRI data from the Barrow Neurological Institute, this thesis investigates the impact of parameter manipulation on reaction-diffusion models for predicting and simulating glioblastoma growth. The study aims to explore key factors influencing tumor morphology and to contribute to enhancing prediction techniques for treatment.
ContributorsShayegan, Tara (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution & Social Change (Contributor)
Created2024-05
Description
Food insecurity is an economic and social condition involving limited or uncertain access to food. The problem of food insecurity in communities is influenced by economic conditions, food deserts, and barriers to accessing healthy food. Individuals experiencing food insecurity often endure concurrent problems of financial instability, hunger, and poor mental and physical health. Public and non-profit services in the U.S., such as the federally supported Supplemental Nutrition Assistance Program (SNAP) and community food banks, provide food-related assistance to individuals who are at a high risk of experiencing food insecurity. Unfortunately, many individuals who qualify for these services still experience food insecurity due to barriers preventing them from accessing food, which may include inadequate finances, transportation, skills, and information. Effective approaches for removing barriers that prevent individuals from accessing food are needed to mitigate the increased risk of hunger, nutritional deficiencies, and chronic disease among vulnerable populations. This dissertation tested a novel food insecurity intervention using informational nudges to promote food security through the elimination of information barriers to accessing food. The intervention used in this mixed-methods feasibility study consisted of informational nudges in the form of weekly text messages that were sent to food pantry clients experiencing food insecurity. The study aims were to test the efficacy and acceptability of the intervention by examining whether the informational nudges could enhance food pantry utilization, increase SNAP registration, and promote food security. Quantitative study results showed a lower prevalence of food insecurity in the intervention group than the control group. Qualitative findings revealed how the intervention group found the text messages to be helpful and informative. These study findings can enhance future food insecurity interventions aiming to eliminate barriers that prevent individuals who are food insecure from accessing healthy food.
ContributorsRoyer, Michael F. (Author) / Wharton, Christopher (Thesis advisor) / Buman, Matthew (Committee member) / Der Ananian, Cheryl (Committee member) / MacKinnon, David (Committee member) / Ohri-Vachaspati, Punam (Committee member) / Arizona State University (Publisher)
Created2023
Description
The study of organismal adaptations oftentimes focuses on specific, constant conditions, but environmental parameters are characterized by more or less marked levels of variability, rather than constancy. This is important in environments like soils where microbial activity follows pulses of water availability driven by precipitation. Nowhere are these pulses more variable and unpredictable than in arid soils. Pulses constitute stressful conditions for bacteria because they cause direct cellular damage that must be repaired and they force cells to toggle between dormancy and active physiological states, which is energetically taxing. I hypothesize that arid soil microorganisms are adapted to the variability in wet/dry cycles itself, as determined by the frequency and duration of hydration pulses. To test this, I subjected soil microbiomes from the Chihuahuan Desert to controlled incubations for a total common growth period of 60 hours, but separated into treatments in which the total active time was reached with hydration pulses of different length with intervening periods of desiccation, so as to isolate pulse length and frequency as the varying factors in the experiment. Using 16S rRNA amplicon data, I characterized changes in microbiome growth, diversity, and species composition, and tracked the individual responses to treatment intensity in the 447 most common bacterial species (phylotypes) in the soil. Considering knowledge of extremophile microbiology, I hypothesized that growth yield and diversity would decline with shorter pulses. I found that microbial diversity was indeed a direct function of pulse length, but surprisingly, total yield was an inverse function of it. Pulse regime treatments resulted in progressively more significant differences in community composition with increasing pulse length, as differently adapted phylotypes became more prominent. In fact, more than 30% of the most common bacterial phylotypes demonstrated statistically significant population growth responses to pulse length. Most responsive phylotypes were apparently best adapted to short pulse regimes (known in the literature as Nimble Responders or NIRs), while fewer did better under long pulse regimes (known as TORs or Torpid Responders). Examples of extreme NIRs and TORs could be found among bacteria from different phyla, indicating that these adaptations have occurred multiple times during evolution.
ContributorsKut, Patrick John (Author) / Garcia-Pichel, Ferran (Thesis advisor) / Sala, Osvaldo (Committee member) / Zhu, Qiyun (Committee member) / Arizona State University (Publisher)
Created2023
Description
A description of numerical and analytical work pertaining to models that describe the growth and progression of glioblastoma multiforme (GBM), an aggressive form of primary brain cancer. Two reaction-diffusion models are used: the Fisher-Kolmogorov-Petrovsky-Piskunov equation and a 2-population model that divides the tumor into actively proliferating and quiescent (or necrotic) cells. The numerical portion of this work (chapter 2) focuses on simulating GBM expansion in patients undergoing treatment for recurrence of tumor following initial surgery. The models are simulated on 3-dimensional brain geometries derived from magnetic resonance imaging (MRI) scans provided by the Barrow Neurological Institute. The study consists of 17 clinical time intervals across 10 patients that have been followed in detail, each of whom shows significant progression of tumor over a period of 1 to 3 months on sequential follow up scans. A Taguchi sampling design is implemented to estimate the variability of the predicted tumors to using 144 different choices of model parameters. In 9 cases, model parameters can be identified such that the simulated tumor contains at least 40 percent of the volume of the observed tumor. In the analytical portion of the paper (chapters 3 and 4), a positively invariant region for our 2-population model is identified. Then, a rigorous derivation of the critical patch size associated with the model is performed. The critical patch (KISS) size is the minimum habitat size needed for a population to survive in a region. Habitats larger than the critical patch size allow a population to persist, while smaller habitats lead to extinction. The critical patch size of the 2-population model is consistent with that of the Fisher-Kolmogorov-Petrovsky-Piskunov equation, one of the first reaction-diffusion models proposed for GBM. The critical patch size may indicate that GBM tumors have a minimum size depending on the location in the brain. A theoretical relationship between the size of a GBM tumor at steady-state and its maximum cell density is also derived, which has potential applications for patient-specific parameter estimation based on magnetic resonance imaging data.
ContributorsHarris, Duane C. (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric J. (Thesis advisor) / Preul, Mark C. (Committee member) / Crook, Sharon (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2023
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