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Description
Modern medical conditions, including cancer, traumatic brain injury, and cardiovascular disease, have elicited the need for cell therapies. The ability to non-invasively track cells in vivo in order to evaluate these therapies and explore cell dynamics is necessary. Magnetic Resonance Imaging provides a platform to track cells as a non-invasive

Modern medical conditions, including cancer, traumatic brain injury, and cardiovascular disease, have elicited the need for cell therapies. The ability to non-invasively track cells in vivo in order to evaluate these therapies and explore cell dynamics is necessary. Magnetic Resonance Imaging provides a platform to track cells as a non-invasive modality with superior resolution and soft tissue contrast. A new methodology for cellular labeling and imaging uses Nile Red doped hexamethyldisiloxane (HMDSO) nanoemulsions as dual modality (Magnetic Resonance Imaging/Fluorescence), dual-functional (oximetry/ detection) nanoprobes. While Gadolinium chelates and super paramagnetic iron oxide-based particles have historically provided contrast enhancement in MRI, newer agents offer additional advantages. A technique using 1H MRI in conjunction with an oxygen reporter molecule is one tool capable of providing these benefits, and can be used in neural progenitor cell and cancer cell studies. Proton Imaging of Siloxanes to Map Tissue Oxygenation Levels (PISTOL) provides the ability to track the polydimethylsiloxane (PDMS) labeled cells utilizing the duality of the nanoemulsions. 1H MRI based labeling of neural stem cells and cancer cells was successfully demonstrated. Additionally, fluorescence labeling of the nanoprobes provided validation of the MRI data and could prove useful for quick in vivo verification and ex vivo validation for future studies.
ContributorsCusick, Alex (Author) / Kodibagkar, Vikram D. (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Kleim, Jeff (Committee member) / Arizona State University (Publisher)
Created2014
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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

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
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Description
Approximately 2.8 million Americans seek medical care for traumatic brain injury (TBI) each year. Of this population, the majority are sufferers of diffuse TBI, or concussion. It is unknown how many more individuals decline to seek medical care following mild TBI. This likely sizeable population of un- or self-treated individuals

Approximately 2.8 million Americans seek medical care for traumatic brain injury (TBI) each year. Of this population, the majority are sufferers of diffuse TBI, or concussion. It is unknown how many more individuals decline to seek medical care following mild TBI. This likely sizeable population of un- or self-treated individuals combined with a lack of definitive biomarkers or objective post-injury diagnostics creates a unique need for practical therapies among diffuse TBI sufferers. Practical therapies stand to decrease the burden of TBI among those who would otherwise not seek treatment or do not meet clinical diagnostic criteria upon examination. For this unique treatment niche, practical therapies for TBI are defined as having one or more of the following qualities: common availability, easy administration, excellent safety profile, and cost-effectiveness. This dissertation identifies and critically examines the efficacy of four classes of practical treatments in improving rodent outcome from experimental diffuse traumatic brain injury.

Over-the-counter (OTC) analgesics, omega-3 fatty acids, specialized pro-resolving mediators (SPMs), and remote ischemic conditioning (RIC) were administered before or following midline fluid percussion injury. Behavioral, histological, and molecular analyses were used to assess treatment effects on functional outcome and secondary injury progression. Acute administration of common OTC analgesics had little effect on post-injury outcome in mice. Dietary supplementation with omega-3 fatty acid docosahexaenoic acid (DHA) prior to or following diffuse TBI significantly reduced injury-induced sensory sensitivity and markers of neuroinflammation with no effect on spatial learning. Intraperitoneal administration of omega-3 fatty acid-derived SPM resolvin E1 significantly increased post-injury sleep and suppressed microglial activation. Aspirin-triggered (AT) resolvin D1 administration improved both motor and cognitive outcome following diffuse TBI. RIC treatment in mice demonstrated little effect on functional outcome from diffuse TBI. Untargeted proteomic analysis of plasma samples from RIC-treated mice was used to identify candidate molecular correlates of RIC. Identification of these candidates represents a vital first step in elucidating the neuroprotective mechanisms underlying RIC. The overall findings suggest that omega-3 fatty acid supplementation, SPM administration, and RIC may serve as effective practical therapies to reduce the somatic, cognitive, and neurological burden of diffuse TBI felt by millions of Americans.
ContributorsHarrison, Jordan L (Author) / Lifshitz, Jonathan (Thesis advisor) / Neisewander, Janet (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Willyerd, Frederick A (Committee member) / Pirrotte, Patrick (Committee member) / Arizona State University (Publisher)
Created2017
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Description
The Hippo signaling pathway is responsible for regulating organ size through cell proliferation, stemness, and apoptosis. Through targeting proteins Yes-associated kinase 1(YAP) and transcriptional co-activator with a PDZ-binding domain(TAZ), YAP/TAZ are unable to enter the nucleus and bind with coactivators to express target genes. To understand YAP/TAZ dynamics and its

The Hippo signaling pathway is responsible for regulating organ size through cell proliferation, stemness, and apoptosis. Through targeting proteins Yes-associated kinase 1(YAP) and transcriptional co-activator with a PDZ-binding domain(TAZ), YAP/TAZ are unable to enter the nucleus and bind with coactivators to express target genes. To understand YAP/TAZ dynamics and its role in tumorigenesis, tissue regeneration, and tissue degeneration, a regulatory network was modeled by ordinary differential equations. Using MATLAB, the deterministic behavior of the network was observed to determine YAP/TAZ activity in different states. Performing the bifurcation analysis of the system through Oscill8, three states were identified: tumorigenic/regenerative, degenerative, and homeostatic states. Further analysis through parameter modification allowed a better understanding of which proteins can be targeted for cancer and degenerative disease.
ContributorsBarra Avila, Diego Rodrigo (Author) / Tian, Xiaojun (Thesis director) / Wang, Xiao (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Description
Traumatic brain injury (TBI) may result in numerous pathologies that cannot currently be mitigated by clinical interventions. Stem cell therapies are widely researched to address TBI-related pathologies with limited success in pre-clinical models due to limitations in transplant survival rates. To address this issue, the use of tissue engineered scaffolds

Traumatic brain injury (TBI) may result in numerous pathologies that cannot currently be mitigated by clinical interventions. Stem cell therapies are widely researched to address TBI-related pathologies with limited success in pre-clinical models due to limitations in transplant survival rates. To address this issue, the use of tissue engineered scaffolds as a delivery mechanism has been explored to improve survival and engraftment rates. Previous work with hyaluronic acid \u2014 laminin (HA-Lm) gels found high viability and engraftment rates of mouse fetal derived neural progenitor/stem cells (NPSCs) cultured on the gel. Furthermore, NPSCs exposed to the HA-Lm gels exhibit increased expression of CXCR4, a critical surface receptor that promotes cell migration. We hypothesized that culturing hNPCs on the HA-Lm gel would increase CXCR4 expression, and thus enhance their ability to migrate into sites of tissue damage. In order to test this hypothesis, we designed gel scaffolds with mechanical properties that were optimized to match that of the natural extracellular matrix. A live/dead assay showed that hNPCs preferred the gel with this optimized formulation, compared to a stiffer gel that was used in the CXCR4 expression experiment. We found that there may be increased CXCR4 expression of hNPCs plated on the HA-Lm gel after 24 hours, indicating that HA-Lm gels may provide a valuable scaffold to support viability and migration of hNPCs to the injury site. Future studies aimed at verifying increased CXCR4 expression of hNPCs cultured on HA-Lm gels are necessary to determine if HA-Lm gels can provide a beneficial scaffold for stem cell engraftment therapy for treating TBI.
ContributorsHemphill, Kathryn Elizabeth (Author) / Stabenfeldt, Sarah (Thesis director) / Brafman, David (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
Cancer is one of the leading causes of death globally according to the World Health Organization. Although improved treatments and early diagnoses have reduced cancer related mortalities, metastatic disease remains a major clinical challenge. The local tumor microenvironment plays a significant role in cancer metastasis, where tumor cells respond and

Cancer is one of the leading causes of death globally according to the World Health Organization. Although improved treatments and early diagnoses have reduced cancer related mortalities, metastatic disease remains a major clinical challenge. The local tumor microenvironment plays a significant role in cancer metastasis, where tumor cells respond and adapt to a plethora of biochemical and biophysical signals from stromal cells and extracellular matrix (ECM) proteins. Due to these complexities, there is a critical need to understand molecular mechanisms underlying cancer metastasis to facilitate the discovery of more effective therapies. In the past few years, the integration of advanced biomaterials and microengineering approaches has initiated the development of innovative platform technologies for cancer research. These technologies enable the creation of biomimetic in vitro models with physiologically relevant (i.e. in vivo-like) characteristics to conduct studies ranging from fundamental cancer biology to high-throughput drug screening. In this review article, we discuss the biological significance of each step of the metastatic cascade and provide a broad overview on recent progress to recapitulate these stages using advanced biomaterials and microengineered technologies. In each section, we will highlight the advantages and shortcomings of each approach and provide our perspectives on future directions.
ContributorsPeela, Nitish (Author) / Nikkhah, Mehdi (Thesis director) / LaBaer, Joshua (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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Description
Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and

Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.
ContributorsAnderies, Barrett James (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Stepien, Tracy (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
Breast and other solid tumors exhibit high and varying degrees of intra-tumor heterogeneity resulting in targeted therapy resistance and other challenges that make the management and treatment of these diseases rather difficult. Due to the presence of admixtures of non-neoplastic cells with polyclonal cell populations, it is difficult to define

Breast and other solid tumors exhibit high and varying degrees of intra-tumor heterogeneity resulting in targeted therapy resistance and other challenges that make the management and treatment of these diseases rather difficult. Due to the presence of admixtures of non-neoplastic cells with polyclonal cell populations, it is difficult to define cancer genomes in patient samples. By isolating tumor cells from normal cells, and enriching distinct clonal populations, clinically relevant genomic aberrations that drive disease can be identified in patients in vivo. An in-depth analysis of clonal architecture and tumor heterogeneity was performed in a stage II chemoradiation-naïve breast cancer from a sixty-five year old patient. DAPI-based DNA content measurements and DNA content-based flow sorting was used to to isolate nuclei from distinct clonal populations of diploid and aneuploid tumor cells in surgical tumor samples. We combined DNA content-based flow cytometry and ploidy analysis with high-definition array comparative genomic hybridization (aCGH) and next-generation sequencing technologies to interrogate the genomes of multiple biopsies from the breast cancer. The detailed profiles of ploidy, copy number aberrations and mutations were used to recreate and map the lineages present within the tumor. The clonal analysis revealed driver events for tumor progression (a heterozygous germline BRCA2 mutation converted to homozygosity within the tumor by a copy number event and the constitutive activation of Notch and Akt signaling pathways. The highlighted approach has broad implications in the study of tumor heterogeneity by providing a unique ultra-high resolution of polyclonal tumors that can advance effective therapies and clinical management of patients with this disease.
ContributorsLaughlin, Brady Scott (Author) / Ankeny, Casey (Thesis director) / Barrett, Michael (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / School for the Science of Health Care Delivery (Contributor)
Created2015-05
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DescriptionMy main goal for my thesis is in conjunction with the research I started in the summer of 2010 regarding the creation of a TBI continuous-time sensor. Such goals include: characterizing the proteins in sensing targets while immobilized, while free in solution, and while in free solution in the blood.
ContributorsHaselwood, Brittney (Author) / LaBelle, Jeffrey (Thesis director) / Pizziconi, Vincent (Committee member) / Cook, Curtiss (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2011-12
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Description
The purpose of this project was to examine the viability of protein biomarkers in pre-symptomatic detection of lung cancer. Regular screening has been shown to vastly improve patient survival outcome. Lung cancer currently has the highest occurrence and mortality of all cancers and so a means of screening would be

The purpose of this project was to examine the viability of protein biomarkers in pre-symptomatic detection of lung cancer. Regular screening has been shown to vastly improve patient survival outcome. Lung cancer currently has the highest occurrence and mortality of all cancers and so a means of screening would be highly beneficial. In this research, the biomarker neuron-specific enolase (Enolase-2, eno2), a marker of small-cell lung cancer, was detected at varying concentrations using electrochemical impedance spectroscopy in order to develop a mathematical model of predicting protein expression based on a measured impedance value at a determined optimum frequency. The extent of protein expression would indicate the possibility of the patient having small-cell lung cancer. The optimum frequency was found to be 459 Hz, and the mathematical model to determine eno2 concentration based on impedance was found to be y = 40.246x + 719.5 with an R2 value of 0.82237. These results suggest that this approach could provide an option for the development of small-cell lung cancer screening utilizing electrochemical technology.
ContributorsEvans, William Ian (Author) / LaBelle, Jeffrey (Thesis director) / Spano, Mark (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05