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The Market For Bodies: Investigating the Landscape of Nontransplant Anatomical Donation Organizations

Description

While there is extensive information available about organizations that receive donated organs for transplant, much less is known about those that accept tissue and whole bodies for medical education and research. Throughout the United States, nontransplant anatomical donation organizations exist within an ambiguous sector of the donation industry, unencumbered by…

While there is extensive information available about organizations that receive donated organs for transplant, much less is known about those that accept tissue and whole bodies for medical education and research. Throughout the United States, nontransplant anatomical donation organizations exist within an ambiguous sector of the donation industry, unencumbered by federal regulations. Although these companies adhere to the Uniform Anatomical Gift Act, the lack of a single entity responsible for overseeing their operations has led to public skepticism and animosity among competing businesses. Legislation has the potential to legitimize the industry. For it to be successful, however, the intricacies of a complex market that deals directly with the movement of human remains and intangible issues of human integrity and morality, must be thoroughly understood.

ContributorsGlynn, Emily Sanders (Author) / Brian, Jennifer (Thesis director) / Fisher, Rebecca (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor) / Department of English (Contributor)

Created2015-05

Expansion and Application of Pathways of Topological Rank Analysis (PoTRA) to Various Cancers

Description

Cancer is the second leading cause of death in the United States. Cancer is a serious, complex disease which causes cells to grow uncontrollably, causing millions of deaths per year [1]. Cancer is usually caused by a combination of environmental variables and biological pathways. The pathways have a very robust…

Cancer is the second leading cause of death in the United States. Cancer is a serious, complex disease which causes cells to grow uncontrollably, causing millions of deaths per year [1]. Cancer is usually caused by a combination of environmental variables and biological pathways. The pathways have a very robust structure normally, but are altered because of cancer, resulting in a loss of connectivity between pathways. In order detect these pathways, a PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) was created, which measures the relative rankings of the genes in each pathway. Applying this algorithm will allow us to figure out what pathways differed significantly in areas with cancer and areas without cancer. This would allow scientists to focus on specific pathways in order to learn more about the cancer and find more effective ways to treat it. So far, analysis using PoTRA has been successfully conducted on hepatocellular carcinoma (HCC) and its subtypes, resulting in all significant pathways found being cancer-associated. Now, using the TCGA data stored in Google Cloud's BigQuery, we created a pipeline to apply PoTRA to other cancer data sets and see how well it cross-applies to other cancers. The results show that even though some modification may need to be made to adapt to other datasets, many significant pathways were found for both HCC and breast cancer.

ContributorsMahesh, Sunny Nishant (Author) / Valentin, Dinu (Thesis director) / Liu, Li (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)

Created2018-05

How Summer Camps Can Aid Palliative Care for Cancer Patients

Description

The rate of cancer incidence is a morbid figure. Twenty years ago, 1 in 2 men and 1 in 3 women were predicted to be afflicted by cancer throughout their lifetime (Cancer Facts & Figures- 1998). In 2017, the rate remains the same ("Cancer Statistic Center"). Every year, more people…

The rate of cancer incidence is a morbid figure. Twenty years ago, 1 in 2 men and 1 in 3 women were predicted to be afflicted by cancer throughout their lifetime (Cancer Facts & Figures- 1998). In 2017, the rate remains the same ("Cancer Statistic Center"). Every year, more people are affected by cancer, which is a physiologically, psychologically, emotionally and socially devastating disease. And yet the language and metaphors we use to describe cancer focus our attention on the "fight" of the heroic individual against the brutal disease or on finding a cure. Despite this narrow rhetoric, there are many meaningful, supportive, and palliative measures designed to substantively and holistically care for cancer patients, beyond their medical treatment. Many of these interventions help the patient feel supported (and less alone in this "battle") by building robust communities. In this thesis, I argue the summer camps for children affected by cancer are meaningful interventions that offer palliative care throughout their treatment by creating support networks with peers going through similar medical procedures. Drawing on anecdotal evidence from three cancer camps and a detailed literature review of a subset of palliative interventions designed to promote well-being, this thesis proposes a new model for a summer camp that focuses on emotional processing emotional expression, positive psychology in order to improve palliative care for cancer patients.

ContributorsPearce, Spencer Taylor (Author) / Miller, April (Thesis director) / Brian, Jennifer (Committee member) / School of Molecular Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)

Created2017-12

Naïve Bayes Classification for Analyzing Prostate Cancer Treatment Outcomes

Description

Prostate cancer is the second most common kind of cancer in men. Fortunately, it has a 99% survival rate. To achieve such a survival rate, a variety of aggressive therapies are used to treat prostate cancers that are caught early. Androgen deprivation therapy (ADT) is a therapy that is given…

Prostate cancer is the second most common kind of cancer in men. Fortunately, it has a 99% survival rate. To achieve such a survival rate, a variety of aggressive therapies are used to treat prostate cancers that are caught early. Androgen deprivation therapy (ADT) is a therapy that is given in cycles to patients. This study attempted to analyze what factors in a group of 79 patients caused them to stick with or discontinue the treatment. This was done using naïve Bayes classification, a machine-learning algorithm. The usage of this algorithm identified high testosterone as an indicator of a patient persevering with the treatment, but failed to produce statistically significant high rates of prediction.

ContributorsMillea, Timothy Michael (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)

Created2016-12

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…

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

Maturity and the Right to Refuse Treatment for Cancer: Considering the Societal, Biological, and Legal Implications of Allowing a Minor to Make a Complex Medical Decision

Description

Treating a minor diagnosed with cancer is a difficult situation. However, cases in which doctors and the patient's family disagree about the proper course of treatment present complex scenarios when it comes to patient care. The forced treatment of Cassandra Callender came as a result of challenging interactions between the…

Treating a minor diagnosed with cancer is a difficult situation. However, cases in which doctors and the patient's family disagree about the proper course of treatment present complex scenarios when it comes to patient care. The forced treatment of Cassandra Callender came as a result of challenging interactions between the patient, the medical establishment, and the state. While the Connecticut Supreme Court mainly considered Cassandra's maturity and her mother's actions when deciding this case, there were more factors contributing to Cassandra's quality of care than her ability to make decisions. An evaluation of these factors demonstrates important implications for ensuring a minor receives the best care. Cassandra wished to pursue a means of treatment that would have fewer serious side effects than chemotherapy, but her assessment of her prognosis was markedly different than that of her doctors. While it is clear that Cassandra did not fully grasp the likelihood of death without chemotherapy treatment, her perspective should not have been fully ignored. The forced treatment inflicted serious (though short term) harm. To understand the full context of this case, this paper considers relevant legal doctrine, decision-making capabilities of minors, the problems and perils of chemotherapy, the role of the media, and the doctor-patient relationship. Developing a perspective based on these facets of Cassandra's case is important in determining how to facilitate the best interaction between doctor and patient and to make sure that future cases aid the patient and his or her family to make the best decision given the situation. Even when there is no consensus about what is best for a patient, more consideration must be given to the patient's perspective, beyond attempting to solely extend life.

ContributorsStoffer, Sidney Rae (Author) / Brian, Jennifer (Thesis director) / Cook-Deegan, Robert (Committee member) / School of Criminology and Criminal Justice (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)

Created2016-05

Prediction of Binding Affinity of T cell Receptor and Antigens using Deep Neural Networks

Description

Immunotherapy is an effective treatment for cancer which enables the patient's immune system to recognize tumor cells as pathogens. In order to design an individualized treatment, the t cell receptors (TCR) which bind to a tumor's unique antigens need to be determined. We created a convolutional neural network to predict…

Immunotherapy is an effective treatment for cancer which enables the patient's immune system to recognize tumor cells as pathogens. In order to design an individualized treatment, the t cell receptors (TCR) which bind to a tumor's unique antigens need to be determined. We created a convolutional neural network to predict the binding affinity between a given TCR and antigen to enable this.

ContributorsCai, Michael Ray (Author) / Lee, Heewook (Thesis director) / Meuth, Ryan (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)

Created2020-12

Nanomedical Treatments for Cancer: Breakthroughs and Challenges

Description

The purpose of this project is to analyze the current state of cancer nanomedicine and its challenges. Cancer is the second most deadly illness in the United States after heart disease. Nanomedicine, the use of materials between 1 and 100 nm to for the purpose of addressing healthcare-related problems, is…

The purpose of this project is to analyze the current state of cancer nanomedicine and its challenges. Cancer is the second most deadly illness in the United States after heart disease. Nanomedicine, the use of materials between 1 and 100 nm to for the purpose of addressing healthcare-related problems, is particularly suited for treating it since nanoparticles have properties such as high surface area-to-volume ratios and favorable drug release profiles that make them more suitable for tasks such as consistent drug delivery to tumor tissue. The questions posed are: What are the current nanomedical treatments for cancer? What are the technical, social, and legal challenges related to nanomedical treatments and how can they be overcome? To answer the questions mentioned above, information from several scientific papers on nanomedical treatments for cancer as well as from social science journals was synthesized. Based on the findings, nanomedicine has a wide range of applications for cancer drug delivery, detection, and immunotherapy. The main technical challenge related to nanomedical treatments is navigating through biological barriers such as the mononuclear phagocyte system, the kidney, the blood-brain barrier, and the tumor microenvironment. Current approaches to meeting this challenge include altering the size, shape, and charge of nanoparticles for easier passage. The main social and legal challenge related to nanomedical treatments is the difficulty of regulating them due to factors such as the near impossibility of detecting nanowaste. Current approaches to meeting this challenge include the use of techniques such as scanning tunneling microscopy and atomic force microscopy to help distinguish nanowaste from the surroundings. More research will have to be done in these and other areas to enhance a major cancer-fighting tool.

ContributorsAbraham, Alfred Francy (Author) / Brian, Jennifer (Thesis director) / Liu, Yan (Committee member) / Materials Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)

Created2021-05

Machine Learning Approaches to Tumor Estimation of Whole Slide Images

Description

Molecular pathology makes use of estimates of tumor content (tumor percentage) for pre-analytic and analytic purposes, such as molecular oncology testing, massive parallel sequencing, or next-generation sequencing (NGS), assessment of sample acceptability, accurate quantitation of variants, assessment of copy number changes (among other applications), determination of specimen viability for testing…

Molecular pathology makes use of estimates of tumor content (tumor percentage) for pre-analytic and analytic purposes, such as molecular oncology testing, massive parallel sequencing, or next-generation sequencing (NGS), assessment of sample acceptability, accurate quantitation of variants, assessment of copy number changes (among other applications), determination of specimen viability for testing (since many assays require a minimum tumor content to report variants at the limit of detection) may all be improved with more accurate and reproducible estimates of tumor content. Currently, tumor percentages of samples submitted for molecular testing are estimated by visual examination of Hematoxylin and Eosin (H&E) stained tissue slides under the microscope by pathologists. These estimations can be automated, expedited, and rendered more accurate by applying machine learning methods on digital whole slide images (WSI).

ContributorsCirelli, Claire (Author) / Yang, Yezhou (Thesis director) / Yalim, Jason (Committee member) / Velu, Priya (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)

Created2022-05

panCanSYGNAL

Description

panCanSYGNAL is a web-application designed to allow cancer researchers to search the relationships between somatic mutations, regulators, and biclusters corresponding to many cancers using a Google-like searchable database.

ContributorsWatson, Jacob (Author) / Plaisier, Christopher (Thesis director) / Clough, Michael (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)

Created2022-05

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