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- All Subjects: Cancer
- All Subjects: Education
- Creators: Harrington Bioengineering Program
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Member of: Theses and Dissertations
- Resource Type: Text
Description
This creative project created and implemented a seven-day STEM curriculum that ultimately encouraged engagement in STEM subjects in students ages 5 through 11. The activities were incorporated into Arizona State University's Kids' Camp over the summer of 2017, every Tuesday afternoon from 4 to 6 p.m. with each activity running for roughly 40 minutes. The lesson plans were created to cover a myriad of scientific topics to account for varied student interest. The topics covered were plant biology, aerodynamics, zoology, geology, chemistry, physics, and astronomy. Each lesson was scaffolded to match the learning needs of the three age groups (5-6 year olds, 7-8 year olds, 9-11 year olds) and to encourage engagement. "Engagement" was measured by pre- and post-activity surveys approved by IRB. The surveys were in the form of statements where the children would totally agree, agree, be undecided, disagree, or totally disagree with it. To more accurately test engagement, the smiley face Likert scale was incorporated with the answer choices. After implementation of the intervention, two-tailed paired t-tests showed that student engagement significantly increased for the two lesson plans of Aerodynamics and Chemistry.
ContributorsHunt, Allison Rene (Co-author) / Belko, Sara (Co-author) / Merritt, Eileen (Thesis director) / Ankeny, Casey (Committee member) / Division of Teacher Preparation (Contributor) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
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 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
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
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
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 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
Description
To supplement lectures, various resources are available to students; however, little research has been done to look systematically at which resources studies find most useful and the frequency at which they are used. We have conducted a preliminary study looking at various resources available in an introductory material science course over four semesters using a custom survey called the Student Resource Value Survey (SRVS). More specifically, the SRVS was administered before each test to determine which resources students use to do well on exams. Additionally, over the course of the semester, which resources students used changed. For instance, study resources for exams including the use of homework problems decreased from 81% to 50%, the utilization of teaching assistant for exam studying increased from 25% to 80%, the use of in class Muddiest Points for exam study increased form 28% to 70%, old exams and quizzes only slightly increased for exam study ranging from 78% to 87%, and the use of drop-in tutoring services provided to students at no charge decreased from 25% to 17%. The data suggest that students thought highly of peer interactions by using those resources more than tutoring centers. To date, no research has been completed looking at courses at the department level or a different discipline. To this end, we adapted the SRVS administered in material science to investigate resource use in thirteen biomedical engineering (BME) courses. Here, we assess the following research question: "From a variety of resources, which do biomedical engineering students feel addresses difficult concept areas, prepares them for examinations, and helps in computer-aided design (CAD) and programming the most and with what frequency?" The resources considered include teaching assistants, classroom notes, prior exams, homework problems, Muddiest Points, office hours, tutoring centers, group study, and the course textbook. Results varied across the four topical areas: exam study, difficult concept areas, CAD software, and math-based programming. When preparing for exams and struggling with a learning concept, the most used and useful resources were: 1) homework problems, 2) class notes and 3) group studying. When working on math-based programming (Matlab and Mathcad) as well as computer-aided design, the most used and useful resources were: 1) group studying, 2) engineering tutoring center, and 3) undergraduate teaching assistants. Concerning learning concepts and exams in the BME department, homework problems and class notes were considered some of the highest-ranking resources for both frequency and usefulness. When comparing to the pilot study in MSE, both BME and MSE students tend to highly favor peer mentors and old exams as a means of studying for exams at the end of the semester1. Because the MSE course only considered exams, we cannot make any comparisons to BME data concerning programming and CAD. This analysis has highlighted potential resources that are universally beneficial, such as the use of peer work, i.e. group studying, engineering tutoring center, and teaching assistants; however, we see differences by both discipline and topical area thereby highlighting the need to determine important resources on a class-by-class basis as well.
ContributorsMalkoc, Aldin (Author) / Ankeny, Casey (Thesis director) / Krause, Stephen (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Glioblastoma multiforme (GBM) is an aggressive malignant brain tumor with a median prognosis of 14 months. Human hairless protein (HR) is a 130 kDa nuclear transcription factor that plays a critical role in skin and hair function but was found to be highly expressed in neural tissue as well. The expression of HR in GBM tumor cells is significantly decreased compared to the normal brain tissue and low levels of HR expression is associated with shortened patient survival. We have recently reported that HR is a DNA binding phosphoprotein, which binds to p53 protein and p53 responsive element (p53RE) in vitro and in intact cells. We hypothesized that HR can regulate p53 downstream target genes, and consequently affects cellular function and activity. To test the hypothesis, we overexpressed HR in normal human embryonic kidney HEK293 and GBM U87MG cell lines and characterized these cells by analyzing p53 target gene expression, viability, cell-cycle arrest, and apoptosis. The results revealed that the overexpressed HR not only regulates p53-mediated target gene expression, but also significantly inhibit cell viability, induced early apoptosis, and G2/M cell cycle arrest in U87MG cells, compared to mock groups. Translating the knowledge gained from this research on the connections between HR and GBM could aid in identifying novel therapies to circumvent GBM progression or improve clinical outcome.
ContributorsBrook, Lemlem Addis (Author) / Blattman, Joseph (Thesis director) / Hsieh, Jui-Cheng (Committee member) / Goldstein, Elliott (Committee member) / Harrington Bioengineering Program (Contributor) / School of Social Transformation (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Diabetes is a growing epidemic in developing countries, specifically in rural Kenya. In addition to the high cost of glucose testing, many diabetics in Kenya do not understand the importance of testing their blood glucose, let alone the nature of the disease. This project addresses the insufficiency of educational materials regarding diabetes in rural Kenya. The resulting documents can easily be adjusted for use in other developing countries.
ContributorsBuchak, Jacqueline (Author) / Caplan, Michael (Thesis director) / Snyder, Jan (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
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
Engineers have a strong influence on everyday lives, ranging from electronics and trains to chemicals and organs [1]. However, in the United States, there is a large knowledge gap in the roles of engineers, especially in K-12 students [2] [3]. The National Academy of Engineering (NAE) recognizes the current problems in engineering, such as the dominance of white males in the field and the amount of education needed to become a successful engineer [4]. Therefore, the NAE encourages that the current engineering community begin to expose the younger generations to the real foundation of engineering: problem-solving [4]. The objective of this thesis is to minimize the knowledge gap by assessing the current perception of engineering amongst middle school and high school students and improving it through engaging and interactive presentations and activities that build upon the students’ problem-solving abilities.
The project was aimed towards middle school and high school students, as this is the estimated level where they learn biology and chemistry—key subject material in biomedical engineering. The high school students were given presentations and activities related to biomedical engineering. Additionally, within classrooms, posters were presented to middle school students. The content of the posters were students of the biomedical engineering program at ASU, coming from different ethnic backgrounds to try and evoke within the middle school students a sense of their own identity as a biomedical engineer. To evaluate the impact these materials had on the students, a survey was distributed before the students’ exposure to the materials and after that assesses the students’ understanding of engineering at two different time points. A statistical analysis was conducted with Microsoft Excel to assess the influence of the activity and/or presentation on the students’ understanding of engineering.
The project was aimed towards middle school and high school students, as this is the estimated level where they learn biology and chemistry—key subject material in biomedical engineering. The high school students were given presentations and activities related to biomedical engineering. Additionally, within classrooms, posters were presented to middle school students. The content of the posters were students of the biomedical engineering program at ASU, coming from different ethnic backgrounds to try and evoke within the middle school students a sense of their own identity as a biomedical engineer. To evaluate the impact these materials had on the students, a survey was distributed before the students’ exposure to the materials and after that assesses the students’ understanding of engineering at two different time points. A statistical analysis was conducted with Microsoft Excel to assess the influence of the activity and/or presentation on the students’ understanding of engineering.
ContributorsLlave, Alison Rose (Author) / Ganesh, Tirupalavanam (Thesis director) / Parker, Hope (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05