Matching Items (188)
Description
The phycologist, M. R. Droop, studied vitamin B12 limitation in the flagellate Monochrysis lutheri and concluded that its specific growth rate depended on the concentration of the vitamin within the cell; i.e. the cell quota of the vitamin B12. The Droop model provides a mathematical expression to link growth rate to the intracellular concentration of a limiting nutrient. Although the Droop model has been an important modeling tool in ecology, it has only recently been applied to study cancer biology. Cancer cells live in an ecological setting, interacting and competing with normal and other cancerous cells for nutrients and space, and evolving and adapting to their environment. Here, the Droop equation is used to model three cancers.
First, prostate cancer is modeled, where androgen is considered the limiting nutrient since most tumors depend on androgen for proliferation and survival. The model's accuracy for predicting the biomarker for patients on intermittent androgen deprivation therapy is tested by comparing the simulation results to clinical data as well as to an existing simpler model. The results suggest that a simpler model may be more beneficial for a predictive use, although further research is needed in this field prior to implementing mathematical models as a predictive method in a clinical setting.
Next, two chronic myeloid leukemia models are compared that consider Imatinib treatment, a drug that inhibits the constitutively active tyrosine kinase BCR-ABL. Both models describe the competition of leukemic and normal cells, however the first model also describes intracellular dynamics by considering BCR-ABL as the limiting nutrient. Using clinical data, the differences in estimated parameters between the models and the capacity for each model to predict drug resistance are analyzed.
Last, a simple model is presented that considers ovarian tumor growth and tumor induced angiogenesis, subject to on and off anti-angiogenesis treatment. In this environment, the cell quota represents the intracellular concentration of necessary nutrients provided through blood supply. Mathematical analysis of the model is presented and model simulation results are compared to pre-clinical data. This simple model is able to fit both on- and off-treatment data using the same biologically relevant parameters.
First, prostate cancer is modeled, where androgen is considered the limiting nutrient since most tumors depend on androgen for proliferation and survival. The model's accuracy for predicting the biomarker for patients on intermittent androgen deprivation therapy is tested by comparing the simulation results to clinical data as well as to an existing simpler model. The results suggest that a simpler model may be more beneficial for a predictive use, although further research is needed in this field prior to implementing mathematical models as a predictive method in a clinical setting.
Next, two chronic myeloid leukemia models are compared that consider Imatinib treatment, a drug that inhibits the constitutively active tyrosine kinase BCR-ABL. Both models describe the competition of leukemic and normal cells, however the first model also describes intracellular dynamics by considering BCR-ABL as the limiting nutrient. Using clinical data, the differences in estimated parameters between the models and the capacity for each model to predict drug resistance are analyzed.
Last, a simple model is presented that considers ovarian tumor growth and tumor induced angiogenesis, subject to on and off anti-angiogenesis treatment. In this environment, the cell quota represents the intracellular concentration of necessary nutrients provided through blood supply. Mathematical analysis of the model is presented and model simulation results are compared to pre-clinical data. This simple model is able to fit both on- and off-treatment data using the same biologically relevant parameters.
ContributorsEverett, Rebecca Anne (Author) / Kuang, Yang (Thesis advisor) / Nagy, John (Committee member) / Milner, Fabio (Committee member) / Crook, Sharon (Committee member) / Jackiewicz, Zdzislaw (Committee member) / Arizona State University (Publisher)
Created2015
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
In complex consumer-resource type systems, where diverse individuals are interconnected and interdependent, one can often anticipate what has become known as the tragedy of the commons, i.e., a situation, when overly efficient consumers exhaust the common resource, causing collapse of the entire population. In this dissertation I use mathematical modeling to explore different variations on the consumer-resource type systems, identifying some possible transitional regimes that can precede the tragedy of the commons. I then reformulate it as a game of a multi-player prisoner's dilemma and study two possible approaches for preventing it, namely direct modification of players' payoffs through punishment/reward and modification of the environment in which the interactions occur. I also investigate the questions of whether the strategy of resource allocation for reproduction or competition would yield higher fitness in an evolving consumer-resource type system and demonstrate that the direction in which the system will evolve will depend not only on the state of the environment but largely on the initial composition of the population. I then apply the developed framework to modeling cancer as an evolving ecological system and draw conclusions about some alternative approaches to cancer treatment.
ContributorsKareva, Irina (Author) / Castillo-Chavez, Carlos (Thesis advisor) / Collins, James (Committee member) / Nagy, John (Committee member) / Smith, Hal (Committee member) / Arizona State University (Publisher)
Created2012
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
The role of climate change, as measured in terms of changes in the climatology of geophysical variables (such as temperature and rainfall), on the global distribution and burden of vector-borne diseases (VBDs) remains a subject of considerable debate. This dissertation attempts to contribute to this debate via the use of mathematical (compartmental) modeling and statistical data analysis. In particular, the objective is to find suitable values and/or ranges of the climate variables considered (typically temperature and rainfall) for maximum vector abundance and consequently, maximum transmission intensity of the disease(s) they cause.
Motivated by the fact that understanding the dynamics of disease vector is crucial to understanding the transmission and control of the VBDs they cause, a novel weather-driven deterministic model for the population biology of the mosquito is formulated and rigorously analyzed. Numerical simulations, using relevant weather and entomological data for Anopheles mosquito (the vector for malaria), show that maximum mosquito abundance occurs when temperature and rainfall values lie in the range [20-25]C and [105-115] mm, respectively.
The Anopheles mosquito ecology model is extended to incorporate human dynamics. The resulting weather-driven malaria transmission model, which includes many of the key aspects of malaria (such as disease transmission by asymptomatically-infectious humans, and enhanced malaria immunity due to repeated exposure), was rigorously analyzed. The model which also incorporates the effect of diurnal temperature range (DTR) on malaria transmission dynamics shows that increasing DTR shifts the peak temperature value for malaria transmission from 29C (when DTR is 0C) to about 25C (when DTR is 15C).
Finally, the malaria model is adapted and used to study the transmission dynamics of chikungunya, dengue and Zika, three diseases co-circulating in the Americas caused by the same vector (Aedes aegypti). The resulting model, which is fitted using data from Mexico, is used to assess a few hypotheses (such as those associated with the possible impact the newly-released dengue vaccine will have on Zika) and the impact of variability in climate variables on the dynamics of the three diseases. Suitable temperature and rainfall ranges for the maximum transmission intensity of the three diseases are obtained.
Motivated by the fact that understanding the dynamics of disease vector is crucial to understanding the transmission and control of the VBDs they cause, a novel weather-driven deterministic model for the population biology of the mosquito is formulated and rigorously analyzed. Numerical simulations, using relevant weather and entomological data for Anopheles mosquito (the vector for malaria), show that maximum mosquito abundance occurs when temperature and rainfall values lie in the range [20-25]C and [105-115] mm, respectively.
The Anopheles mosquito ecology model is extended to incorporate human dynamics. The resulting weather-driven malaria transmission model, which includes many of the key aspects of malaria (such as disease transmission by asymptomatically-infectious humans, and enhanced malaria immunity due to repeated exposure), was rigorously analyzed. The model which also incorporates the effect of diurnal temperature range (DTR) on malaria transmission dynamics shows that increasing DTR shifts the peak temperature value for malaria transmission from 29C (when DTR is 0C) to about 25C (when DTR is 15C).
Finally, the malaria model is adapted and used to study the transmission dynamics of chikungunya, dengue and Zika, three diseases co-circulating in the Americas caused by the same vector (Aedes aegypti). The resulting model, which is fitted using data from Mexico, is used to assess a few hypotheses (such as those associated with the possible impact the newly-released dengue vaccine will have on Zika) and the impact of variability in climate variables on the dynamics of the three diseases. Suitable temperature and rainfall ranges for the maximum transmission intensity of the three diseases are obtained.
ContributorsOkuneye, Kamaldeen O (Author) / Gumel, Abba B (Thesis advisor) / Kuang, Yang (Committee member) / Smith, Hal (Committee member) / Thieme, Horst (Committee member) / Nagy, John (Committee member) / Arizona State University (Publisher)
Created2018
Description
A series of mitochondria targeting probes was synthesized for the purpose of exploring the feasibility of a mitochondria targeting fluorescent sensor. Of the probes, the probe with a two carbon spacer showed the best co-localization from staining with the established MitoTracker Red® FM, indicating a potential development of the probe into mitochondria targeting sensor. However, cytotoxicity was observed for the probe with a six carbon spacer. Three additional mitochondria targeting fluorescent probes of longer spacer groups were synthesized, but the cytotoxicity was not observed to be as high as that of the probe with a two carbon spacer. The cytotoxicity was characterized to be that of caspase dependent cell death. To screen for a possible effect on apoptosis due to the mitochondrial probe, three fluorescent fusion proteins binding the anti-apoptotic proteins were designed and expressed. Each purified fusion protein was then incubated with the cytotoxic mitochondrial probe, and the mixture was isolated by running an affinity column. The fluorescence analysis of eluted fractions showed preliminary data of possible interaction between the protein and the mitochondrial probe.
ContributorsLee, Fred (Author) / Meldrum, Deirdre R. (Thesis director) / Tian, Yanqing (Committee member) / Zhang, Liqiang (Committee member) / Barrett, The Honors College (Contributor) / Chemical Engineering Program (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2014-12
Description
An in-depth analysis of Homeview Realty and Homeview Financial was conducted. A marketing plan for both companies was prepared for this project. Homeview Realty and Homeview Financial are in the midst of dynamic industries. The landscape of doing business in the real estate and mortgage industries are constantly changing and evolving. Thus, it is vital for Homeview Realty and Homeview Financial to constantly be knowledgeable in these fields. With this dynamic aspect, the landscape for marketing has also changed; it became digital in nature. Thus, it is important to analyze Homeview Realty and Homeview Financial currently and create a live marketing plan that can be updated when needed. With a marketing plan in hand, Homeview will be able understand its business model, mission, goals, and objectives and in turn be able to create marketing campaigns compatible with the companies objectives and strategic directions.
ContributorsCrowley, Rachel Victoria (Author) / Ostrom, Lonnie (Thesis director) / Montoya, Detra (Committee member) / Mirshak, Paul (Committee member) / Barrett, The Honors College (Contributor) / Department of Marketing (Contributor) / Department of Supply Chain Management (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Department of Finance (Contributor) / School of Accountancy (Contributor)
Created2014-05
Description
Repeating tiles made of DNA were used to try to form an indefinitely large structure. Both the tiles and structure were 2D. Two different patterns were tested, one corrugated and one not. Corrugation means that the tiles alternated between facing up and facing down, canceling out any curvature to the tile and creating a slightly corrugated but largely 2D pattern. Annealing methods were also experimented with. Annealing the structure in two, separate steps as opposed to one was tested. Another experiment was comparing cyclic versus linear annealing. A linear decrease in temperatures defines the linear annealing, and a cyclic method involved a linear drop to a certain temperature, followed by a slight increase in temperature and cooling back down again. This cycle is done several times before it continues linear cool down. It was seen that both corrugated and non-corrugated structures could be made. In both cases tiles that make up a larger section of the overall pattern were more successful. This is especially important for the non-corrugated pattern. Linear and 2step annealing methods seem to yield the best results.
ContributorsHunt, Ashley Elizabeth (Author) / Yan, Liu (Thesis director) / Yan, Hao (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
Description
Lung cancer is the leading cause of cancer-related deaths in the US. Low-dose computed tomography (LDCT) scans are speculated to reduce lung cancer mortality. However LDCT scans impose multiple risks including false-negative results, false- positive results, overdiagnosis, and cancer due to repeated exposure to radiation. Immunosignaturing is a new method proposed to screen and detect lung cancer, eliminating the risks associated with LDCT scans. Known and blinded primary blood sera from participants with lung cancer and no cancer were run on peptide microarrays and analyzed. Immunosignatures for each known sample collectively indicated 120 peptides unique to lung cancer and non-cancer participants. These 120 peptides were used to determine the status of the blinded samples. Verification of the results from Vanderbilt is pending.
ContributorsNguyen, Geneva Trieu (Author) / Woodbury, Neal (Thesis director) / Zhao, Zhan-Gong (Committee member) / Stafford, Phillip (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Department of Psychology (Contributor)
Created2015-05
Description
The purpose of this project was to identify proteins associated with the migration and invasion of non-transformed MCF10A mammary epithelial cells with ectopically expressed missense mutations in p53. Because of the prevalence of TP53 missense mutations in basal-like and triple-negative breast cancer tumors, understanding the effect of TP53 mutations on the phenotypic expression of human mammary epithelial cells may offer new therapeutic targets for those currently lacking in treatment options. As such, MCF10A mammary epithelial cells ectopically overexpressing structural mutations (G245S, H179R, R175H, Y163C, Y220C, and Y234C) and DNA-binding mutations (R248Q, R248W, R273C, and R273H) in the DNA-binding domain were selected for use in this project. Overexpression of p53 in the mutant cell lines was confirmed by western blot and q-PCR analysis targeting the V5 epitope tag present in the pLenti4 vector used to transduce TP53 into the mutant cell lines. Characterization of the invasion and migration phenotypes resulting from the overexpression of p53 in the mutant cell lines was achieved using transwell invasion and migration assays with Boyden chambers. Statistical analysis showed that three cell lines—DNA-contact mutants R248W and R273C and structural mutant Y220C—were consistently more migratory and invasive and demonstrated a relationship between the migration and invasion properties of the mutant cell lines. Two families of proteins were then explored: those involved in the Epithelial-Mesenchymal Transition (EMT) and matrix metalloproteinases (MMPs). Results of q-PCR and immunofluorescence analysis of epithelial marker E-cadherin and mesenchymal proteins Slug and Vimentin did not show a clear relationship between mRNA and protein expression levels with the migration and invasiveness phenotypes observed in the transwell studies. Results of western blotting, q-PCR, and zymography of MMP-2 and MMP-9 also did not show any consistent results indicating a definite relationship between MMPs and the overall invasiveness of the cells. Finally, two drugs were tested as possible treatments inhibiting invasiveness: ebselen and SBI-183. These drugs were tested on only the most invasive of the MCF10A p53 mutant cell lines (R248W, R273C, and Y220C). Results of invasion assay following 30 μM treatment with ebselen and SBI-183 showed that ebselen does not inhibit invasiveness; SBI-183, however, did inhibit invasiveness in all three cell lines tested. As such, SBI-183 will be an important compound to study in the future as a treatment that could potentially serve to benefit triple-negative or basal-like breast cancer patients who currently lack therapeutic treatment options.
ContributorsZhang, Kathie Q (Author) / LaBaer, Joshua (Thesis director) / Anderson, Karen (Committee member) / Gonzalez, Laura (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05