Barrett

Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.

Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.

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Multimarker Sensor Development for Intermediate Glycemic Index, A Novel Approach for a Glycated Albumin Sensor

Description
Diabetes mellitus is a disease characterized by many chronic and acute conditions. With the prevalence and cost quickly increasing, we seek to improve on the current standard of care and create a rapid, label free sensor for glycated albumin (GA) index using electrochemical impedance spectroscopy (EIS). The antibody, anti-HA, was…

Diabetes mellitus is a disease characterized by many chronic and acute conditions. With the prevalence and cost quickly increasing, we seek to improve on the current standard of care and create a rapid, label free sensor for glycated albumin (GA) index using electrochemical impedance spectroscopy (EIS). The antibody, anti-HA, was fixed to gold electrodes and a sine wave of sweeping frequencies was induced with a range of HA, GA, and GA with HA concentrations. Each frequency in the impedance sweep was analyzed for highest response and R-squared value. The frequency with both factors optimized is specific for both the antibody-antigen binding interactions with HA and GA and was determined to be 1476 Hz and 1.18 Hz respectively in purified solutions. The correlation slope between the impedance response and concentration for albumin (0 \u2014 5400 mg/dL of albumin) was determined to be 72.28 ohm/ln(mg/dL) with an R-square value of 0.89 with a 2.27 lower limit of detection. The correlation slope between the impedance response and concentration for glycated albumin (0 \u2014 108 mg/dL) was determined to be -876.96 ohm/ln(mg/dL) with an R-squared value of 0.70 with a 0.92 mg/dL lower limit of detection (LLD). The above data confirms that EIS offers a new method of GA detection by providing unique correlation with albumin as well as glycated albumin. The unique frequency response of GA and HA allows for modulation of alternating current signals so that several other markers important in the management of diabetes could be measured with a single sensor. Future work will be necessary to establish multimarker sensing on one electrode.
ContributorsEusebio, Francis Ang (Author) / LaBelle, Jeffrey (Thesis director) / Pizziconi, Vincent (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
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Pyridoxine Wound Healing Trial

Description

The purpose of this study, which was done in conjunction with the Arizona Heart Foundation, was to evaluate whether pyridoxine accelerates ulcer wound healing in diabetic patients with ulcers in the lower extremities. In this study, 100 mg of pyridoxine per day was given to patients in the experimental grou…

The purpose of this study, which was done in conjunction with the Arizona Heart Foundation, was to evaluate whether pyridoxine accelerates ulcer wound healing in diabetic patients with ulcers in the lower extremities. In this study, 100 mg of pyridoxine per day was given to patients in the experimental group (while they receive normal wound treatment) while patients in the control group received normal treatment of wounds without the pyridoxine. Over time, wound healing was evaluated by photographing and then measuring the size of patients' ulcer wounds on the photographs. Results from the experimental group were compared with those of the control group to evaluate the efficacy of the pyridoxine treatment. In addition, comparisons of the healing rates were made with respect to whether the patients smoked, had hypertension or hypotension, and the patients' body mass indexes. It has been found that there was no statistically significant difference in the mean healing rates between the control groups and experimental groups. In addition, it has been found that smoking, BMI and blood pressure did not have a statistically appreciable effect on the difference in mean healing rates between the control and experimental groups. This is evidence that pyridoxine did not have a statistically significant effect on wound healing rates.
ContributorsHaupt, Shawn Anthony (Author) / Caplan, Michael (Thesis director) / Pauken, Christine (Committee member) / Pagan, Pedro (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05
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Developing an Electrochemical Impedance Spectroscopy-Based Insulin Sensor

Description
Currently, the management of diabetes mellitus (DM) involves the monitoring of only blood glucose using self-monitoring blood glucose devices (SMBGs) followed by taking interventional steps, if needed. To increase the amount of information that diabetics can have to base DM care decisions off of, the development of an insulin biosensor…

Currently, the management of diabetes mellitus (DM) involves the monitoring of only blood glucose using self-monitoring blood glucose devices (SMBGs) followed by taking interventional steps, if needed. To increase the amount of information that diabetics can have to base DM care decisions off of, the development of an insulin biosensor is explored. Such a biosensor incorporates electrochemical impedance spectroscopy (EIS) to ensure an extremely sensitive platform. Additionally, anti-insulin antibody was immobilized onto the surface of a gold disk working electrode to ensure a highly specific sensing platform as well. EIS measurements were completed with a 5mV sine wave that was swept through the frequency spectrum of 100 kHz to 1 Hz on concentrations of insulin ranging from 0 pM to 100 μM. The frequency at which the interaction between insulin and its antibody was optimized was determined by finding out at which frequency the R2 and slope of the impedance-concentration plot were best. This frequency, otherwise known as the optimal binding frequency, was determined to be 459 Hz. Three separate electrodes were developed and the impedance data for each concentration measured at 459 Hz was averaged and plotted against the LOG (pM insulin) to construct the calibration curve. The response was calculated to be 263.64 ohms/LOG(pM insulin) with an R2 value of 0.89. Additionally, the average RSD was determined to be 19.24% and the LLD was calculated to be 8.47 pM, which is well below the physiological normal range. These results highlight the potential success of developing commercial point-of-care insulin biosensors or multi-marker devices operating with integrated insulin detection.
ContributorsDecke, Zachary William (Author) / LaBelle, Jeffrey (Thesis director) / Pizziconi, Vincent (Committee member) / Cook, Curtiss (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05
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A Diabetes Education Initiative for Citizens of Rural Kenya

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…

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
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ASSESSING VOLUNTEER MOTIVATION AND SATISFACTION: A COLLABORATION BETWEEN SINGLETON MOMS AND THE COMMUNITY ACTION RESEARCH EXPERIENCES (CARE) PROGRAM

Description
The Community Action Research Experiences (CARE) program collaborated with Singleton Moms, a local non-profit organization that provides financial, psychological, and social support services to single parents with cancer. The purpose of this action research project was to assess the volunteer program at Singleton Moms. Both past and present Singleton Moms'…

The Community Action Research Experiences (CARE) program collaborated with Singleton Moms, a local non-profit organization that provides financial, psychological, and social support services to single parents with cancer. The purpose of this action research project was to assess the volunteer program at Singleton Moms. Both past and present Singleton Moms' volunteers (N = 123; 87.0% female) completed an online survey assessing their motivation for volunteering and their satisfaction with the organization. A mixed ANOVA was conducted to identify the most important motivation and satisfaction domains and to see if the findings depended on whether the volunteers were current or past volunteers. For the motivation assessment, results indicated that the volunteers rate the cancer specific and moral/human kindness domains as the strongest reasons for motivating them to volunteer at Singleton Moms. In addition, results revealed that the social connection motivation domain was the only domain with differences between the ratings of the past and present volunteers. For the satisfaction assessment, results indicated that the volunteers rate the organizational climate domain as the most fulfilled area of satisfaction within the Singleton Moms' volunteer program. It was also revealed that there were no significant differences between the ratings of the past and present volunteers among all satisfaction domains. Both the quantitative and qualitative findings suggest that Singleton Moms' implications for action may include: 1) a volunteer database audit, 2) streamlining communications, 3) variability in volunteer times, and 4) bolstering volunteer motivation. Implementing some of these actions may help Singleton Moms increase volunteer motivation and satisfaction and thus create a more effective volunteer program. Ultimately, this may encourage volunteers to continue their services at Singleton Moms and thus help Singleton Moms expand their support programs and assist additional families.
ContributorsDubois, Courtney Michelle (Author) / Miller, Cindy (Thesis director) / Dumka, Larry (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor)
Created2016-05
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Modeling SDF-1α Chemotactic Gradient Formation After Traumatic Brain Injury

Description
Traumatic brain injury (TBI) is a leading cause of injury related death in the United States. The complexity of the injury environment that follows TBI creates an incomplete understanding of all the mechanisms in place to regulate chemotactic responses to TBI. The goal of this project was to develop a…

Traumatic brain injury (TBI) is a leading cause of injury related death in the United States. The complexity of the injury environment that follows TBI creates an incomplete understanding of all the mechanisms in place to regulate chemotactic responses to TBI. The goal of this project was to develop a predictive in silco model using diffusion and autocrine/paracrine signaling specific to stromal cell derived factor-1α (SDF-1α) gradient formation after TBI and compare this model with in vivo experimental data. A COMSOL model using Fickian diffusion and autocrine/paracrine reaction terms was generated to predict the gradient formation observed in vivo at three physiologically relevant time points (1, 3, and 7 days). In vivo data was gathered and analyzed via immunohistochemistry and MATLAB. The spatial distribution of SDF-1α concentration in vivo more consistently demonstrated patterns similar to the in silico model dependent on both diffusion and autocrine/paracrine reaction terms rather than diffusion alone. The temporal distribution of these same results demonstrated degradation of SDF-1α at too rapid a rate, compared to the in vivo results. To account for differences in behavior observed in vivo, reaction terms and constants of 1st-order reaction rates must be modulated to better reflect the results observed in vivo. These results from both the in silico model and in vivo data support the hypothesis that SDF-1α gradient formation after TBI depends on more than diffusion alone. Future work will focus on improving the model with constants that are specific to SDF-1α as well as testing methods to better control the degradation of SDF-1α.
ContributorsFreeman, Sabrina Louise (Author) / Stabenfeldt, Sarah (Thesis director) / Caplan, Michael (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Deep Learning Application to Improve Quality of Life in Diabetes

Description

Carbohydrate counting has been shown to improve HbA1c levels for people with diabetes. However, the learning curve and inconvenience of carbohydrate counting make it difficult for patients to adhere to it. A deep learning model is proposed to identify food from an image, where it can help the user manage…

Carbohydrate counting has been shown to improve HbA1c levels for people with diabetes. However, the learning curve and inconvenience of carbohydrate counting make it difficult for patients to adhere to it. A deep learning model is proposed to identify food from an image, where it can help the user manage their carbohydrate counting. This early model has a 68.3% accuracy of identifying 101 different food classes. A more refined model in future work could be deployed into a mobile application to identify food the user is about to consume and log it for easier carbohydrate counting.
ContributorsCarreto, Cesar (Author) / Pizziconi, Vincent (Thesis director) / Vernon, Brent (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05