Matching Items (21)
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- All Subjects: Astronomy
- All Subjects: Cancer
- Creators: Mauskopf, Philip
- Creators: School of Mathematical and Statistical Sciences
- Resource Type: Text
- Status: Published
Description
Cancer rates vary between people, between cultures, and between tissue types, driven by clinically relevant distinctions in the risk factors that lead to different cancer types. Despite the importance of cancer location in human health, little is known about tissue-specific cancers in non-human animals. We can gain significant insight into how evolutionary history has shaped mechanisms of cancer suppression by examining how life history traits impact cancer susceptibility across species. Here, we perform multi-level analysis to test how species-level life history strategies are associated with differences in neoplasia prevalence, and apply this to mammary neoplasia within mammals. We propose that the same patterns of cancer prevalence that have been reported across species will be maintained at the tissue-specific level. We used a combination of factor analysis and phylogenetic regression on 13 life history traits across 90 mammalian species to determine the correlation between a life history trait and how it relates to mammary neoplasia prevalence. The factor analysis presented ways to calculate quantifiable underlying factors that contribute to covariance of entangled life history variables. A greater risk of mammary neoplasia was found to be correlated most significantly with shorter gestation length. With this analysis, a framework is provided for how different life history modalities can influence cancer vulnerability. Additionally, statistical methods developed for this project present a framework for future comparative oncology studies and have the potential for many diverse applications.
ContributorsFox, Morgan Shane (Author) / Maley, Carlo C. (Thesis director) / Boddy, Amy (Committee member) / Compton, Zachary (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Molecular Sciences (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This work examines star formation in the debris associated with collisions of dwarf and spiral galaxies. While the spectacular displays of major mergers are famous (e.g., NGC 4038/9, ``The Antennae''), equal mass galaxy mergers are relatively rare compared to minor mergers (mass ratio <0.3) Minor mergers are less energetic than major mergers, but more common in the observable universe and, thus, likely played a pivotal role in the formation of most large galaxies. Centers of mergers host vigorous star formation from high gas density and turbulence and are surveyed over cosmological distances. However, the tidal debris resulting from these mergers have not been well studied. Such regions have large reservoirs of gaseous material that can be used as fuel for subsequent star formation but also have lower gas density. Tracers of star formation at the local and global scale have been examined for three tidal tails in two minor merger systems. These tracers include young star cluster populations, H-alpha, and [CII] emission. The rate of apparent star formation derived from these tracers is compared to the gas available to estimate the star formation efficiency (SFE). The Western tail of NGC 2782 formed isolated star clusters while massive star cluster complexes are found in the UGC 10214 (``The Tadpole'') and Eastern tail of NGC 2782. Due to the lack of both observable CO and [CII] emission, the observed star formation in the Western tail of NGC 2782 may have a low carbon abundance and represent only the first round of local star formation. While the Western tail has a normal SFE, the Eastern tail in the same galaxy has an low observed SFE. In contrast, the Tadpole tidal tail has a high observed star formation rate and a corresponding high SFE. The low SFE observed in the Eastern tail of NGC 2782 may be due to its origin as a splash region where localized gas heating is important. However, the other tails may be tidally formed regions where gravitational compression likely dominates and enhances the local star formation.
ContributorsKnierman, Karen A (Author) / Scowen, Paul (Thesis advisor) / Groppi, Christopher (Thesis advisor) / Mauskopf, Philip (Committee member) / Windhorst, Rogier (Committee member) / Jansen, Rolf (Committee member) / Arizona State University (Publisher)
Created2013
Description
Despite the 40-year war on cancer, very limited progress has been made in developing a cure for the disease. This failure has prompted the reevaluation of the causes and development of cancer. One resulting model, coined the atavistic model of cancer, posits that cancer is a default phenotype of the cells of multicellular organisms which arises when the cell is subjected to an unusual amount of stress. Since this default phenotype is similar across cell types and even organisms, it seems it must be an evolutionarily ancestral phenotype. We take a phylostratigraphical approach, but systematically add species divergence time data to estimate gene ages numerically and use these ages to investigate the ages of genes involved in cancer. We find that ancient disease-recessive cancer genes are significantly enriched for DNA repair and SOS activity, which seems to imply that a core component of cancer development is not the regulation of growth, but the regulation of mutation. Verification of this finding could drastically improve cancer treatment and prevention.
ContributorsOrr, Adam James (Author) / Davies, Paul (Thesis director) / Bussey, Kimberly (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Glioblastoma Multiforme (GBM) is an aggressive and deadly form of brain cancer with a median survival time of about a year with treatment. Due to the aggressive nature of these tumors and the tendency of gliomas to follow white matter tracks in the brain, each tumor mass has a unique growth pattern. Consequently it is difficult for neurosurgeons to anticipate where the tumor will spread in the brain, making treatment planning difficult. Archival patient data including MRI scans depicting the progress of tumors have been helpful in developing a model to predict Glioblastoma proliferation, but limited scans per patient make the tumor growth rate difficult to determine. Furthermore, patient treatment between scan points can significantly compound the challenge of accurately predicting the tumor growth. A partnership with Barrow Neurological Institute has allowed murine studies to be conducted in order to closely observe tumor growth and potentially improve the current model to more closely resemble intermittent stages of GBM growth without treatment effects.
ContributorsSnyder, Lena Haley (Author) / Kostelich, Eric (Thesis director) / Frakes, David (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
Using data from the Arizona Radio Observatory Submillimeter Telescope, we have studied the active, star-forming region of the R Coronae Australis molecular cloud in 12CO (2-1), 13CO (2-1), and HCO+ (3-2). We baselined and mapped the data using CLASS. It was then used to create integrated intensity, outflow, and centroid velocity maps in IDL. These clearly showed the main large outflow, and then we identified a few other possible outflows.
ContributorsBlumm, Margaret Elizabeth (Author) / Groppi, Christopher (Thesis director) / Bowman, Judd (Committee member) / Mauskopf, Philip (Committee member) / Barrett, The Honors College (Contributor) / School of Earth and Space Exploration (Contributor)
Created2014-05
Description
An automated test system was developed to characterize detectors for the Kilopixel Array Pathfinder Project (KAPPa). KAPPa is an astronomy instrument that detects light at terahertz wavelengths using a 16-pixel heterodyne focal plane array. Although primarily designed for the KAPPa receiver, the test system can be used with other instruments to automate tests that might be tedious and time-consuming by hand. Mechanical components of the test setup include an adjustable structure of aluminum t-slot framing that supports a rotating chopper. Driven by a stepper motor, the chopper alternates between blackbodies at room temperature and 77 K. The cold load consists of absorbing material submerged in liquid nitrogen in an open Styrofoam cooler. Scripts written in Matlab and Python control the mechanical system, interface with receiver components, and process data. To calculate the equivalent noise temperature of a receiver, the y-factor method is used. Test system operation was verified by sweeping the local oscillator frequency and power level for two room temperature Schottky diode receivers from Virginia Diodes, Inc. The test system was then integrated with the KAPPa receiver, providing a low cost, simple, adaptable means to measure noise with minimal user intervention.
ContributorsKuenzi, Linda Christine (Author) / Groppi, Christopher (Thesis director) / Mauskopf, Philip (Committee member) / Kulesa, Craig (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2014-05
Description
Over time, tumor treatment resistance inadvertently develops when androgen de-privation therapy (ADT) is applied to metastasized prostate cancer (PCa). To combat tumor resistance, while reducing the harsh side effects of hormone therapy, the clinician may opt to cyclically alternates the patient’s treatment on and off. This method,known as intermittent ADT, is an alternative to continuous ADT that improves the patient’s quality of life while testosterone levels recover between cycles. In this paper,we explore the response of intermittent ADT to metastasized prostate cancer by employing a previously clinical data validated mathematical model to new clinical data from patients undergoing Abiraterone therapy. This cell quota model, a system of ordinary differential equations constructed using Droop’s nutrient limiting theory, assumes the tumor comprises of castration-sensitive (CS) and castration-resistant (CR)cancer sub-populations. The two sub-populations rely on varying levels of intracellular androgen for growth, death and transformation. Due to the complexity of the model,we carry out sensitivity analyses to study the effect of certain parameters on their outputs, and to increase the identifiability of each patient’s unique parameter set. The model’s forecasting results show consistent accuracy for patients with sufficient data,which means the model could give useful information in practice, especially to decide whether an additional round of treatment would be effective.
ContributorsBennett, Justin Klark (Author) / Kuang, Yang (Thesis director) / Kostelich, Eric (Committee member) / Phan, Tin (Committee member) / School of Mathematical and Statistical Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Magnetic resonance imaging (MRI) data of metastatic brain cancer patients at the Barrow Neurological Institute sparked interest in the radiology department due to the possibility that tumor size distributions might mimic a power law or an exponential distribution. In order to consider the question regarding the growth trends of metastatic brain tumors, this thesis analyzes the volume measurements of the tumor sizes from the BNI data and attempts to explain such size distributions through mathematical models. More specifically, a basic stochastic cellular automaton model is used and has three-dimensional results that show similar size distributions of those of the BNI data. Results of the models are investigated using the likelihood ratio test suggesting that, when the tumor volumes are measured based on assuming tumor sphericity, the tumor size distributions significantly mimic the power law over an exponential distribution.
ContributorsFreed, Rebecca (Co-author) / Snopko, Morgan (Co-author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
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 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
Description
Balloon-borne telescopes are an economic alternative to scientists seeking to study light compared to other ground- and space-based alternatives, such as the Keck Observatory and the Hubble Space Telescope. One such balloon-borne telescope is the Balloon-borne Large Aperture Submillimeter Telescope, or simply BLAST. Arizona State University was tasked with assembling one of the primary optics plates for the telescope's next mission. This plate, detailed in the following paragraphs, is designed to detect and capture submillimeter wavelength light. This will help scientists understand the formation and early life of stars. Due to its highly sensitive nature detecting light, the optics plate had to be carefully assembled following a strict assembly and testing procedure. Initially, error tolerances for the mirrors and plate were developed using a computer model, later to be compared to measured values. The engineering decisions made throughout the process pertained to every aspect of the plate, from ensuring the compliance of the engineering drawings to the polishing of the mirrors for testing. The assembly procedure itself was verified at the conclusion using a coordinate measuring machine (CMM) to analyze whether or not the plate was within defined error tolerances mentioned above. This data was further visualized within the document to show that the assembly procedure of the BLAST optics plate was successful. The largest error margins seen were approximately one order of magnitude lower than their tolerated limits, reflecting good engineering judgement and care applied to the manufacturing process. The plate has since been shipped offsite to continue testing and the assembly team is confident it will perform well within expected parameters.
ContributorsDombrowski, Shane Matthew (Author) / Groppi, Christopher (Thesis director) / Mauskopf, Philip (Committee member) / Underhill, Matthew (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05