Matching Items (29)
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Mayer-Rokitansky-Küster-Hauser (MRKH) is a rare Disorder of Sexual Development (DSD) that results in the lack of a uterus and vagina in women. Receiving this diagnosis during adolescence can cause various forms of psychological distress in patients and families.<br/>Specifically, this condition could affect a women’s gender identity, body image, romantic relationships,

Mayer-Rokitansky-Küster-Hauser (MRKH) is a rare Disorder of Sexual Development (DSD) that results in the lack of a uterus and vagina in women. Receiving this diagnosis during adolescence can cause various forms of psychological distress in patients and families.<br/>Specifically, this condition could affect a women’s gender identity, body image, romantic relationships, family relationships, and psychological wellbeing. Parents are also put in a stressful<br/>position as they now have to navigate the healthcare system, disclosure, and the relationship with their child. This study aims to expand the knowledge of psychosocial adjustment by studying body<br/>image, gender identity, and mental health in individuals living with MRKH as well as parental disclosure, parental support systems, and parental perceptions of their child’s mental health.

ContributorsLaloudakis, Vasiliki (Author) / Wilson, Melissa (Thesis director) / Fontinha de Alcantara, Christiane (Committee member) / Baimbridge, Erica (Committee member) / Department of Psychology (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Alzheimer’s disease is a disease that can affect cognition, perception and behavior and is currently untreatable. It was discovered in the early 20th century and while significant scientific advancements have occurred, there is ambiguity that remains to be researched and understood. Latinos are the largest ethnic minority in the United

Alzheimer’s disease is a disease that can affect cognition, perception and behavior and is currently untreatable. It was discovered in the early 20th century and while significant scientific advancements have occurred, there is ambiguity that remains to be researched and understood. Latinos are the largest ethnic minority in the United States and while data still needs to be uncovered, possible risk factors for developing Alzheimer’s include heart issues, poverty and obesity, age and education level, to name a few. Poverty is linked to obesity, diabetes and a low education level, which in turn have been found to have an impact on Alzheimer’s and all factors impact cardiovascular and vascular health. Due to the collectivistic culture that is deeply rooted in Latinos, there is a strong sense of family that is upheld when caring for relatives who are afflicted and may be hesitant to receive the care that is needed. Other barriers include financial stability, linguistic and cultural barriers, underutilizing resources and health literacy. There are still research gaps that are yet to be filled like brain health and longitudinal studies for Latinos, but current treatments like diet and culturally competent professionals can help with the prognosis. Alzheimer’s is a complex disease, but with the numerous efforts made thus far, such as creating the LatinosAgainstAlzheimer’s Network, it will soon be able to be understood and hopefully eradicated.

ContributorsJimenez, Brittney (Author) / Wilson, Melissa (Thesis director) / Susan, Holechek (Committee member) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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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,

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
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Description
Glioblastoma (GBM) is the most aggressive adult brain tumor with a devastating median survival time of about fourteen months post-surgery and standard of care therapy with radiation and temozolomide. The low incidence of GBM, cost of developing novel therapeutics, and time cost of clinical trials are dis-incentives to develop novel

Glioblastoma (GBM) is the most aggressive adult brain tumor with a devastating median survival time of about fourteen months post-surgery and standard of care therapy with radiation and temozolomide. The low incidence of GBM, cost of developing novel therapeutics, and time cost of clinical trials are dis-incentives to develop novel therapies. To overcome that obstacle, we investigated the efficacy of repurposing four FDA approved drugs known to cross the blood brain barrier (BBB), minocycline, propranolol, chlorpromazine, and metformin, to inhibit signaling and metabolism in GBM cells.
Minocycline is a tetracycline class broad spectrum antibiotic commonly used to treat severe acne and other skin infections. Propranolol is a beta blocker type heart medication primarily used to treat high blood pressure and irregular heartbeat. Chlorpromazine is a phenothiazine antipsychotic usually used for schizophrenia. Metformin is the most widely used first-line oral treatment for type-2 diabetes. Based on a literature survey, minocycline is expected to prevent the phosphorylation of STAT3, a transcription factor downstream of EGFR; propranolol is expected to disrupt EGFR trafficking; chlorpromazine is expected to target the PI3K/mTOR/Akt signaling pathway; metformin is believed to exploit vulnerabilities in cancer cell metabolism, as well as upregulate AMPK against the PI3K/mTOR/Akt pathway.
Efficacy of minocycline in inhibiting EGFR-driven STAT3 activation was investigated using western blot analysis. Our results demonstrate that Minocycline effectively inhibits activation of EGFR-driven STAT3 in U373 glioma cells at 100μM. The ability of chlorpromazine to inhibit the PI3K/mTOR/Akt pathway was similarly tested via western blot, which showed inhibition of phosphorylated Akt and S6 at 10μM. Efficacy of propranolol in perturbing EGFR trafficking was evaluated using flow cytometry and immunofluorescence, which failed to depict altered membrane-associated EGFR abundance. Finally, concentration-dependent inhibition of colony formation was tested for all four drugs. Propranolol and minocycline showed potential biphasic stimulatory effects at 10μM, but all drugs inhibited cell growth at 50μM and higher. Efficacy of these drugs in the treatment of GBM is being further evaluated using in vitro neurosphere cultures from patients identified as having the cellular vulnerabilities potentially targeted by these drugs. Successful completion of this project will lead to in vivo efficacy testing of these four drugs in orthotopic GBM PDX models.
ContributorsNeal, Tristan Thomas (Co-author) / Neal, Tristan (Co-author) / Byron, Sara (Co-author) / Dhruv, Harshil (Co-author, Committee member) / Berens, Michael (Co-author) / Wilson, Melissa (Thesis director) / Ferdosi, Shayesteh (Committee member) / School of Human Evolution & Social Change (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Malignant Pleural Mesothelioma is a type of lung cancer usually discovered at an advanced stage at which point there is no cure. Six primary MPM cell lines were used to conduct in vitro research to make conclusions about specific gene mutations associated with Mesothelioma. DNA exome sequencing, a time efficient

Malignant Pleural Mesothelioma is a type of lung cancer usually discovered at an advanced stage at which point there is no cure. Six primary MPM cell lines were used to conduct in vitro research to make conclusions about specific gene mutations associated with Mesothelioma. DNA exome sequencing, a time efficient and inexpensive technique, was used for identifying specific DNA mutations. Computational analysis of exome sequencing data was used to make conclusions about copy number variation among common MPM genes. Results show a CDKN2A gene heterozygous deletion in Meso24 cell line. This data is validated by a previous CRISPR-Cas9 outgrowth screen for Meso24 where the knocked-out gene caused increased Meso24 growth.
ContributorsKrdi, Ghena (Author) / Plaisier, Christopher (Thesis director) / Wilson, Melissa (Committee member) / School of Life Sciences (Contributor) / Hugh Downs School of Human Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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Analyzing human DNA sequence data allows researchers to identify variants associated with disease, reconstruct the demographic histories of human populations, and further understand the structure and function of the genome. Identifying variants in whole genome sequences is a crucial bioinformatics step in sequence data processing and can be performed using

Analyzing human DNA sequence data allows researchers to identify variants associated with disease, reconstruct the demographic histories of human populations, and further understand the structure and function of the genome. Identifying variants in whole genome sequences is a crucial bioinformatics step in sequence data processing and can be performed using multiple approaches. To investigate the consistency between different bioinformatics methods, we compared the accuracy and sensitivity of two genotyping strategies, joint variant calling and single-sample variant calling. Autosomal and sex chromosome variant call sets were produced by joint and single-sample calling variants for 10 female individuals. The accuracy of variant calls was assessed using SNP array genotype data collected from each individual. To compare the ability of joint and single-sample calling to capture low-frequency variants, folded site frequency spectra were constructed from variant call sets. To investigate the potential for these different variant calling methods to impact downstream analyses, we estimated nucleotide diversity for call sets produced using each approach. We found that while both methods were equally accurate when validated by SNP array sites, single-sample calling identified a greater number of singletons. However, estimates of nucleotide diversity were robust to these differences in the site frequency spectrum between call sets. Our results suggest that despite single-sample calling’s greater sensitivity for low-frequency variants, the differences between approaches have a minimal effect on downstream analyses. While joint calling may be a more efficient approach for genotyping many samples, in situations that preclude large sample sizes, our study suggests that single-sample calling is a suitable alternative.
ContributorsHowell, Emma (Co-author) / Wilson, Melissa (Thesis director) / Stone, Anne (Committee member) / Phung, Tanya (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
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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

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
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Description

Vaccines are one of the most effective ways of combating infectious diseases and developing vaccine platforms that can be used to produce vaccines can greatly assist in combating global public health threats. This dissertation focuses on the development and pre-clinical testing of vaccine platforms that are highly immunogenic, easily modifiable,

Vaccines are one of the most effective ways of combating infectious diseases and developing vaccine platforms that can be used to produce vaccines can greatly assist in combating global public health threats. This dissertation focuses on the development and pre-clinical testing of vaccine platforms that are highly immunogenic, easily modifiable, economically viable to produce, and stable. These criteria are met by the recombinant immune complex (RIC) universal vaccine platform when produced in plants. The RIC platform is modeled after naturally occurring immune complexes that form when an antibody, a component of the immune system that recognizes protein structures or sequences, binds to its specific antigen, a molecule that causes an immune response. In the RIC platform, a well-characterized antibody is linked via its heavy chain, to an antigen tagged with the antibody-specific epitope. The RIC antibody binds to the epitope tags on other RIC molecules and forms highly immunogenic complexes. My research has primarily focused on the optimization of the RIC platform. First, I altered the RIC platform to enable an N-terminal antigenic fusion instead of the previous C-terminal fusion strategy. This allowed the platform to be used with antigens that require an accessible N-terminus. A mouse immunization study with a model antigen showed that the fusion location, either N-terminal or C-terminal, did not impact the immune response. Next, I studied a synergistic response that was seen upon co-delivery of RIC with virus-like particles (VLP) and showed that the synergistic response could be produced with either N-terminal or C-terminal RIC co-delivered with VLP. Since RICs are inherently insoluble due to their ability to form complexes, I also examined ways to increase RIC solubility by characterizing a panel of modified RICs and antibody-fusions. The outcome was the identification of a modified RIC that had increased solubility while retaining high immunogenicity. Finally, I modified the RIC platform to contain multiple antigenic insertion sites and explored the use of bioinformatic tools to guide the design of a broadly protective vaccine.

ContributorsPardhe, Mary (Author) / Mason, Hugh S (Thesis advisor) / Chen, Qiang (Committee member) / Mor, Tsafrir (Committee member) / Wilson, Melissa (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Mutation is the source of heritable variation of genotype and phenotype, on which selection may act. Mutation rates describe a fundamental parameter of living things, which influence the rate at which evolution may occur, from viral pathogens to human crops and even to aging cells and the emergence of cancer.

Mutation is the source of heritable variation of genotype and phenotype, on which selection may act. Mutation rates describe a fundamental parameter of living things, which influence the rate at which evolution may occur, from viral pathogens to human crops and even to aging cells and the emergence of cancer. An understanding of the variables which impact mutation rates and their estimation is necessary to place mutation rate estimates in their proper contexts. To better understand mutation rate estimates, this research investigates the impact of temperature upon transcription rate error estimates; the impact of growing cells in liquid culture vs. on agar plates; the impact of many in vitro variables upon the estimation of deoxyribonucleic acid (DNA) mutation rates from a single sample; and the mutational hazard induced by expressing clustered regularly interspaced short palindromic repeat (CRISPR) proteins in yeast. This research finds that many of the variables tested did not significantly alter the estimation of mutation rates, strengthening the claims of previous mutation rate estimates across the tree of life by diverse experimental approaches. However, it is clear that sonication is a mutagen of DNA, part of an effort which has reduced the sequencing error rate of circle-seq by over 1,000-fold. This research also demonstrates that growth in liquid culture modestly skews the mutation spectrum of MMR- Escherichia coli, though it does not significantly impact the overall mutation rate. Finally, this research demonstrates a modest mutational hazard of expressing Cas9 and similar CRISPR proteins in yeast cells at an un-targeted genomic locus, though it is possible the indel rate has been increased by an order of magnitude.
ContributorsBaehr, Stephan (Author) / Lynch, Michael (Thesis advisor) / Geiler-Samerotte, Kerry (Committee member) / Mangone, Marco (Committee member) / Wilson, Melissa (Committee member) / Arizona State University (Publisher)
Created2023
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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

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