Matching Items (41)
Description
N. fowleri has been coined the "brain-eating" amoeba, receiving increased attention from both the media and scientific research since its discovery in 1961. While infection is extremely rare, it infects humans through the nasal passage after exposure to contaminated, warm freshwater, causing the brain destroying reaction primary amoebic meningoencephalitis (PAM). Those infected with PAM present with symptoms such as severe headache and loss of the sense of smell and will typically die within a week thereafter. This fulminant pathogenicity has led to increased awareness of N. fowleri through the news and public health centers. This thesis aims to comprehensively review N. fowleri, the epidemiology and pathology of PAM, interventions against the disease, and how the news has portrayed N. fowleri and PAM. This thesis also strives to raise ethical and thought-provoking questions about how much media coverage and research funding N. fowleri receives given its rarity, as well as explore its value and novel contributions to understanding disease as a whole.
ContributorsFerrell, Chantell Isabell (Author) / Buetow, Kenneth (Thesis director) / Neisewander, Janet (Committee member) / McGlynn, Katherine (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / School of Life Sciences (Contributor)
Created2014-05
Description
Pathway analysis helps researchers gain insight into the biology behind gene expression-based data. By applying this data to known biological pathways, we can learn about mutations or other changes in cellular function, such as those seen in cancer. There are many tools that can be used to analyze pathways; however, it can be difficult to find and learn about the which tool is optimal for use in a certain experiment. This thesis aims to comprehensively review four tools, Cytoscape, PaxtoolsR, PathOlogist, and Reactome, and their role in pathway analysis. This is done by applying a known microarray data set to each tool and testing their different functions. The functions of these programs will then be analyzed to determine their roles in learning about biology and assisting new researchers with their experiments. It was found that each tools holds a very unique and important role in pathway analysis. Visualization pathways have the role of exploring individual pathways and interpreting genomic results. Quantification pathways use statistical tests to determine pathway significance. Together one can find pathways of interest and then explore areas of interest.
ContributorsRehling, Thomas Evan (Author) / Buetow, Kenneth (Thesis director) / Wilson, Melissa (Committee member) / School of Life Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Hepatitis C virus (HCV) is endemic in Pakistan, with 5% of the population suffering from the disease. A unique aspect about HCV in Pakistan is the major role that healthcare workers play in its transmission, by reusing needles and giving therapeutic injections when they are not needed. This issue is furthered by patients’ misconceptions that invasive treatments, like injections, are more effective than oral medicines. The purpose of this project was to create a short video that addressed this inaccurate and dangerous perception, by educating Pakistanis about HCV and how to prevent infection and reinfection. In addition to disease transmission, accessibility to treatment options in Pakistan were also discussed. The video featured Pakistani physicians and some young adults. There were several limitations that delimited the project, including time, budget, the sudden death of a project participant, and the current COVID-19 epidemic as well as cultural, language, and physical barriers that come from filming a video about Pakistan as Americans. In the future, this video can serve as a framework for future efforts.
ContributorsKisana, Soofia (Co-author) / Ahmed, Kinza (Co-author) / Compton, Carolyn (Thesis director) / Buetow, Kenneth (Committee member) / Nadir, Abdul (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Hepatocellular carcinoma (HCC) is a type of liver cancer common in Sub-Saharan Africa and South East Asian countries. Each year more than 700,000 new cases and more than 600,000 deaths are recorded worldwide due to HCC. According to the American Cancer Society HCC is ranked the 5th most common cancer worldwide with a male:female susceptibility ratio ranging between 2:1 and 8:1. HCC risk factors include lifestyle behaviors, such as persistent alcohol abuse and smoking, prolonged exposure to aflatoxins, chronic viral hepatitis infections, inherited metabolic diseases and non-alcoholic fatty liver diseases. To understand the genetic effects underlying sex-bias in HCC, it is necessary to include the sex chromosomes in genomics analyses. X and Y chromosomes are often discluded in genomics studies because of the technical and analytical challenges: sequence homology. The purpose of this thesis is to analyze the effects of sex chromosome complement aware read mapping to germline variant calling. 10 male and 10 female tumor adjacent samples from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA LIHC) cohort were processed using sex-aware and default reference and the concordance of the two approaches was examined. We detected a higher disconcordance of 0.69% on variants called on the X chromosome and a disconcordance of 0.51% on variants called on the Y chromosomes for the reference and alternative alleles respectively compared to autosomes. Variants called on the REF/ALT genotypes had a disconcordances of 1.00%, 1.05%, 1.35% and 12.34% for the autosomes, chromosome 7, the X, and the Y chromosome, respectively. At the end of the project we concluded that the generated datasets showed the effect of sex-aware read mapping on variant calling. Though the data did not show the sites that can be called as variants in one dataset but not in the other, rather the concordance looked at sites that were called as variants in both data sets.
ContributorsPhiri, Lovender Teresa (Co-author) / Phiri, Lovender (Co-author) / Wilson Sayres, Melissa (Thesis director) / Buetow, Kenneth (Committee member) / Natri, Heini (Committee member) / School of Life Sciences (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Schizophrenia is a disease that affects 15.2/100,000 US citizens, with about 0.6-1.9% of the total population being afflicted with some range of severity of the disease. A lot of research has been done on the progression of the disease and its differences between males and females; however, the true underlying cause of the disease remains unknown. In the literature, however, there is a lot of indication that a genetic cause for schizophrenia is the primary origin for the disorder. In order to establish a foundation in differential gene expression and isoform expression between males and females, we utilized the Genotype-Tissue Expression Project data set (which contains samples from healthy individuals at their time of death) for the amygdala, anterior cingulate cortex, and frontal cortex. We performed quality control on the data with Trimmomatic and visualized it with FastQC and MultiQC. We then aligned to a sex-specific reference genome with Hisat2. Finally, we performed a differential expression analysis dthrough the limma/voom package with inputs from featureCounts. An isoform level analysis was run on the anterior cingulate cortex with the IsoformSwitchAnalyzeR package. We were able to identify a few differentially expressed genes in the three tissue sites, which included XIST and other highly conserved, Y-linked genes. As for the isoform level analysis, we were able to identify 13 genes with significant levels of differential isoform usage and expression, two of which have clinical relevance (DAB1 and PACRG). These findings will allow for a comparison to be made by future studies on gene expression in brain tissue samples from patients that had been diagnosed with schizophrenia in their life. By identifying any unique genes in these patients, gene therapies can be developed to target and correct any misexpression that may be occurring.
ContributorsEvanovich, Austin Phillip (Author) / Wilson, Melissa (Thesis director) / Buetow, Kenneth (Committee member) / Natri, Heini Maaret (Committee member) / School of Life Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Learning student names has been promoted as an inclusive classroom practice, but it is unknown whether students value having their names known by an instructor. We explored this question in the context of a high-enrollment active-learning undergraduate biology course. Using surveys and semistructured interviews, we investigated whether students perceived that instructors know their names, the importance of instructors knowing their names, and how instructors learned their names. We found that, while only 20% of students perceived their names were known in previous high-enrollment biology classes, 78% of students perceived that an instructor of this course knew their names. However, instructors only knew 53% of names, indicating that instructors do not have to know student names in order for students to perceive that their names are known. Using grounded theory, we identified nine reasons why students feel that having their names known is important. When we asked students how they perceived instructors learned their names, the most common response was instructor use of name tents during in-class discussion. These findings suggest that students can benefit from perceiving that instructors know their names and name tents could be a relatively easy way for students to think that instructors know their names. Academic self-concept is one's perception of his or her ability in an academic domain compared to other students. As college biology classrooms transition from lecturing to active learning, students interact more with each other and are likely comparing themselves more to students in the class. Student characteristics, such as gender and race/ethnicity, can impact the level of academic self-concept, however this has been unexplored in the context of undergraduate biology. In this study, we explored whether student characteristics can affect academic self-concept in the context of a college physiology course. Using a survey, students self-reported how smart they perceived themselves in the context of physiology compared to the whole class and compared to the student they worked most closely with in class. Using logistic regression, we found that males and native English speakers had significantly higher academic self-concept compared to the whole class compared with females and non-native English speakers, respectively. We also found that males and non-transfer students had significantly higher academic self-concept compared to the student they worked most closely with in class compared with females and transfer students, respectively. Using grounded theory, we identified ten distinct factors that influenced how students determined whether they are more or less smart than their groupmate. Finally, we found that students were more likely to report participating less than their groupmate if they had a lower academic self-concept. These findings suggest that student characteristics can influence students' academic self-concept, which in turn may influence their participation in small group discussion.
ContributorsKrieg, Anna Florence (Author) / Brownell, Sara (Thesis director) / Stout, Valerie (Committee member) / Cooper, Katelyn (Committee member) / School of Life Sciences (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Big Data Network Analysis of Genetic Variation and Gene Expression in Individuals with Breast Cancer
Description
The advent of big data analytics tools and frameworks has allowed for a plethora of new approaches to research and analysis, making data sets that were previously too large or complex more accessible and providing methods to collect, store, and investigate non-traditional data. These tools are starting to be applied in more creative ways, and are being used to improve upon traditional computation methods through distributed computing. Statistical analysis of expression quantitative trait loci (eQTL) data has classically been performed using the open source tool PLINK - which runs on high performance computing (HPC) systems. However, progress has been made in running the statistical analysis in the ecosystem of the big data framework Hadoop, resulting in decreased run time, reduced storage footprint, reduced job micromanagement and increased data accessibility. Now that the data can be more readily manipulated, analyzed and accessed, there are opportunities to use the modularity and power of Hadoop to further process the data. This project focuses on adding a component to the data pipeline that will perform graph analysis on the data. This will provide more insight into the relation between various genetic differences in individuals with breast cancer, and the resulting variation - if any - in gene expression. Further, the investigation will look to see if there is anything to be garnered from a perspective shift; applying tools used in classical networking contexts (such as the Internet) to genetically derived networks.
ContributorsRandall, Jacob Christopher (Author) / Buetow, Kenneth (Thesis director) / Meuth, Ryan (Committee member) / Almalih, Sara (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Course-Based Undergraduate Research Experiences, or CUREs have become an increasingly popular way to integrate research opportunities into the undergraduate biology curriculum. Unlike traditional cookbook labs which provide students with a set experimental design and known outcome, CUREs offer students the opportunity to participate in novel and interesting research that is of interest to the greater biology community. While CUREs have been championed as a way to provide more students with the opportunity to experience, it is unclear whether students benefit differently from participating in different CURE with different structural elements. In this study we focused in on one proposed element of a CURE, collaboration, to determine whether student's perception of this concept change over the course of a CURE and whether it differs among students enrolled in different CUREs. We analyzed pre and post open-ended surveys asking the question "Why might collaboration be important in science?" in two CUREs with different structures of collaboration. We also compared CURE student responses to the responses of senior honors thesis students who had been conducting authentic research. Five themes emerged in response to students' conceptions of collaboration. Comparing two CURE courses, we found that students' conceptions of collaboration were varied within each individual CURE, as well as what students were leaving with compared to the other CURE course. Looking at how student responses compared between 5 different themes, including "Different Perspectives", "Validate/Verify Results", "Compare Results", "Requires Different Expertise", and "Compare results", students appeared to be thinking about collaboration in distinct different ways by lack of continuity in the amount of students discussing each of these among the classes. In addition, we found that student responses in each of the CURE courses were not significantly different for any of the themes except "Different Expertise" compared to the graduating seniors. However, due to the small (n) that the graduating seniors group had, 22, compared to each of the CURE classes composing of 155 and 98 students, this comparison must be taken in a preliminary manner. Overall, students thought differently about collaboration between different CUREs. Still, a gap filling what it means to "collaborate", and whether the structures of CUREs are effective to portray collaboration are still necessary to fully elaborate on this paper's findings.
ContributorsWassef, Cyril Alexander (Author) / Brownell, Sara (Thesis director) / Stout, Valerie (Committee member) / Cooper, Katelyn (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Evolution is a key feature of undergraduate biology education: the AmericanAssociation for the Advancement of Science (AAAS) has identified evolution as one of
the five core concepts of biology, and it is relevant to a wide array of biology-related
careers. If biology instructors want students to use evolution to address scientific
challenges post-graduation, students need to be able to apply evolutionary principles to
real-life situations, and accept that the theory of evolution is the best scientific
explanation for the unity and diversity of life on Earth. In order to help students progress
on both fronts, biology education researchers need surveys that measure evolution
acceptance and assessments that measure students’ ability to apply evolutionary concepts.
This dissertation improves the measurement of student understanding and acceptance of
evolution by (1) developing a novel Evolutionary Medicine Assessment that measures
students’ ability to apply the core principles of Evolutionary Medicine to a variety of
health-related scenarios, (2) reevaluating existing measures of student evolution
acceptance by using student interviews to assess response process validity, and (3)
correcting the validity issues identified on the most widely-used measure of evolution
acceptance - the Measure of Acceptance of the Theory of Evolution (MATE) - by
developing and validating a revised version of this survey: the MATE 2.0.
ContributorsMisheva, Anastasia Taya (Author) / Brownell, Sara (Thesis advisor) / Barnes, Elizabeth (Committee member) / Collins, James (Committee member) / Cooper, Katelyn (Committee member) / Sterner, Beckett (Committee member) / Arizona State University (Publisher)
Created2023
Description
While only the sixth most common cancer globally, liver cancer is the third most deadly. Despite the importance of accurate diagnosis and effective treatment, standard diagnostic tests for most solid organ neoplasms are not required for the most common type of liver cancer, Hepatocellular Carcinoma (HCC). In addition, major discrepancies in the practices currently in place limits the ability to develop more precise oncological treatment and prognosis. This study aimed to identify biomarkers, with potential to more accurately diagnose how far cancer has advanced within a patient and determine prognosis. It is the hope that pathways provided by this study form the basis for future research into more standardized practices and potential treatment based on specific affected biological processes. The PathOlogist tool was utilized to calculate activity metrics for 1,324 biological pathways in 374 The Cancer Genome Atlas (TCGA) hepatocellular carcinoma donors. Further statistical analysis was done on two datasets, formed to identify grade or stage at time of diagnosis for the activity levels calculated by PathOlogist. The datasets were evaluated individually. Based on the variance and normality of each pathway’s activity levels in the respective data sets analysis of variance, Tukey-Kramer, Kruskal-Wallis, and Mann-Whitney-Wilcox tests were performed, when appropriate, to determine any statistically significant differences in pathway activity levels. Pathways were identified in both stage and grade data analyses that show significant differences in activity levels across designation. While some overlap is seen, there was a significant number of pathways unique to either stage or grade. These pathways are known to affect the cell cycle, cellular transport, disease, immune system, and metabolism regulation.
The biological pathways named by this research depict prospective biomarkers for progression of hepatocellular carcinoma per subdivision within both stage and grade. These findings may be instrumental to new methods of early and more accurate diagnosis. The distinct differences in identified pathways in grade and stage illustrate the need for these new methods to not only look at stage but also grade when determining prognosis. Furthermore, the pathways identified herein have potential to aid in the development of targeted treatment based on the affected biological processes.
ContributorsGarrison, Alyssa Cameron (Author) / Buetow, Kenneth (Thesis advisor) / Hinde, Katie (Committee member) / Wilson, Melissa (Committee member) / Arizona State University (Publisher)
Created2022