Matching Items (369)
- Creators: Harrington Bioengineering Program
- Member of: Theses and Dissertations
I spent the first half of my project researching Mexican cuisine, as well as the history of traditional recipes and how various ingredients became incorporated into the food of the Southwest region. The second half of my project was focused on creating a video to document my family's recipe for making tamales. I analyzed the recipe and its larger cultural and social implications which I presented with a PowerPoint.
Smart contrast agents allow for noninvasive study of specific events or tissue conditions inside of a patient's body using Magnetic Resonance Imaging (MRI). This research aims to develop and characterize novel smart contrast agents for MRI that respond to temperature changes in tissue microenvironments. Transmission Electron Microscopy, Nuclear Magnetic Resonance, and cell culture growth assays were used to characterize the physical, magnetic, and cytotoxic properties of candidate nanoprobes. The nanoprobes displayed thermosensitve MR properties with decreasing relaxivity with temperature. Future work will be focused on generating and characterizing photo-active analogues of the nanoprobes that could be used for both treatment of tissues and assessment of therapy.
Student Emergency Medical Services (SEMS): A Summary of Prehospital Emergency Medical Care and its Impact on Arizona State University
Emergency medicine has long been an important part of the medical system in the United States. Those employed in an emergent setting know how to operate under extremely high stakes. Prehospital care in particular is a vital part of emergency response. Student Emergency Medical Services works to bring said prehospital care to ASU in a voluntary, high-quality, and efficient manner. We serve the ASU population while educating our members to be professional individuals for the service of society.
Contrast agents in medical imaging can help visualize structural details, distributions of particular cell types, or local environment characteristics. Multi-modal imaging techniques have become increasingly popular for their improved sensitivity, resolution, and ability to correlate structural and functional information. This study addresses the development of dual-modality (magnetic resonance/fluorescence) and dual-functional (thermometry/detection) nanoprobes for enhanced tissue imaging.
This research investigates the whether dietary and nutritional treatments will improve some of the symptoms of autism. This treatment includes a combination of 6 nutritional and dietary treatments, which are vitamins/minerals, essential fatty acids, Epsom salts, carnitine, digestive enzymes, and healthy gluten-free, casein-free diet. 55 participants were involved in this study; 28 participants are in the Treatment Group and 27 participants in the Delayed Group. Data from the PDD-BI form, the ADOS form, the CARS form and the professional SAS form will be used in this thesis project for analyses. Factors analyzed are age, gender and severity [initial professional SAS data] and then correlating these factors with data from PDD-BI (autism composite score and each subscale), ADOS and CARS. The data analyses show that changing the dietary and nutritional needs of children/adults with autism improves the symptoms of autism (as rated by the PDD-BI) by approximately 22% in the treatment group vs. 3% in the non-treatment group, p<0.001. Overall, these results also suggest that the treatment is equally beneficial for males and females of varying age (young children to adult) and of all severity levels.
Development of a rapid and label-free Electrochemical Impedance Spectroscopy (EIS) biosensor for Cardiovascular Disease (CVD) detection based on Inerluekin-18 (IL-18) sensitivity was proposed to fill the technology gap between rapid and portable CVD point-of-care diagnosis. IL-18 was chosen for this CVD biosensor due to its ability to detect plaque vulnerability of the heart. Custom (hand) made sensors, which utilized a three electrode configuration with a gold disk working electrode, were created to run EIS using both IL-18 and anti-IL-18 molecules in both purified and blood solutions. The EIS results for IL-18 indicated the optimal detection frequency to be 371Hz. Blood interaction on the working electrode increased the dynamic range of impedance values for the biosensor. Future work includes Developing and testing prototypes of the biosensor along with determining if a Nafion based coating on the working electrode will reduce the dynamic range of impedance values caused by blood interference.
The Making of a COVID Testing Laboratory: Deconstructing the Saliva Sample Collection Process and Preanalytical Standardization
This thesis project is the result of close collaboration with the Arizona State University Biodesign Clinical Testing Laboratory (ABCTL) to document the characteristics of saliva as a test sample, preanalytical considerations, and how the ABCTL utilized saliva testing to develop swift COVID-19 diagnostic tests for the Arizona community. As of April 2021, there have been over 130 million recorded cases of COVID-19 globally, with the United States taking the lead with approximately 31.5 million cases. Developing highly accurate and timely diagnostics has been an important need of our country that the ABCTL has had tremendous success in delivering. Near the start of the pandemic, the ABCTL utilized saliva as a testing sample rather than nasopharyngeal (NP) swabs that were limited in supply, required highly trained medical personnel, and were generally uncomfortable for participants. Results from literature across the globe showed how saliva performed just as well as the NP swabs (the golden standard) while being an easier test to collect and analyze. Going forward, the ABCTL will continue to develop high quality diagnostic tools and adapt to the ever-evolving needs our communities face regarding the COVID-19 pandemic.
The COVID-19 pandemic has resulted in preventative measures and has led to extensive changes in lifestyle for the vast majority of the American population. As the pandemic progresses, a growing amount of evidence shows that minority groups, such as the Deaf community, are often disproportionately and uniquely affected. Deaf people are directly affected in their ability to personally socialize and continue with daily routines. More specifically, this can constitute their ability to meet new people, connect with friends/family, and to perform in their work or learning environment. It also may result in further mental health changes and an increased reliance on technology. The impact of COVID-19 on the Deaf community in clinical settings must also be considered. This includes changes in policies for in-person interpreters and a rise in telehealth. Often, these effects can be representative of the pre-existing low health literacy, frequency of miscommunication, poor treatment, and the inconvenience felt by Deaf people when trying to access healthcare. Ultimately, these effects on the Deaf community must be taken into account when attempting to create a full picture of the societal shift caused by COVID-19.
Using Machine Learning to Objectively Determine Colorimetric Assay Results from Cell Phone Photos Taken Under Ambient Lighting
Colorimetric assays are an important tool in point-of-care testing that offers several advantages to traditional testing methods such as rapid response times and inexpensive costs. A factor that currently limits the portability and accessibility of these assays are methods that can objectively determine the results of these assays. Current solutions consist of creating a test reader that standardizes the conditions the strip is under before being measured in some way. However, this increases the cost and decreases the portability of these assays. The focus of this study is to create a machine learning algorithm that can objectively determine results of colorimetric assays under varying conditions. To ensure the flexibility of a model to several types of colorimetric assays, three models were trained on the same convolutional neural network with different datasets. The images these models are trained on consist of positive and negative images of ETG, fentanyl, and HPV Antibodies test strips taken under different lighting and background conditions. A fourth model is trained on an image set composed of all three strip types. The results from these models show it is able to predict positive and negative results to a high level of accuracy.
The Founders lab is a year-long program that gives its students an opportunity to participate in a unique team-based, experiential Barrett honors thesis project to design and apply marketing and sales strategies, as well as business and financial models to start up and launch a new business. This honors thesis project focuses on increasing the rate of vaccination outcomes in a country where people are increasingly busy (less time) and unwilling to get a needle through a new business venture that provides a service that brings vaccinations straight to businesses, making them available for their employees. Through our work with the Founders Lab, our team was able to create this pitch deck.