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- Creators: Harrington Bioengineering Program
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Polymer drug delivery system offers a key to a glaring issue in modern administration routes of drugs and biologics. Poly(lactic-co-glycolic acid) (PLGA) can be used to encapsulate drugs and biologics and deliver them into the patient, which allows high local concentration (compared to current treatment methods), protection of the cargo from the bodily environment, and reduction in systemic side effects. This experiment used a single emulsion technique to encapsulate L-tyrosine in PLGA microparticles and UV spectrophotometry to analyze the drug release over a period of one week. The release assay found that for the tested samples, the released amount is distinct initially, but is about the same after 4 days, and they generally follow the same normalized percent released pattern. The experiment could continue with testing more samples, test the same samples for a longer duration, and look into higher w/w concentrations such as 20% or 50%.
Introduction. Human papillomavirus (HPV) is the most common sexually transmitted infections globally. HPV is responsible for several health concerns including genital warts, cancer of the cervix, vulva, penis, anus, and oropharynx. In China, HPV infection accounts for 69.1% of invasive cervical cancer. Currently, there is no treatment for HPV infection, but HPV vaccination has been proven to be effective against HPV-related diseases. Given the highest rate of contracting HPV and suboptimal vaccination rate in college students including international students in the U.S., it is important to investigate key factors associated with vaccine uptake among Chinese international students. Purpose. This study aimed to investigate knowledge and awareness of HPV and the vaccine, attitudes, and vaccination intention in this population. We conducted a cross-sectional online survey via REDCap. Methods. Participants who were (1) Chinese international student at Arizona State University; (2) 18 and older; (3) able to read, speak and write in Chinese or English were recruited from Arizona State University. Descriptive statistics (mean, standard deviation, frequency) and inferential statistics (Chi-square test, independent t-test) were conducted using SPSS 26.0. Results. One hundred and ten participants were included in this study (56.4% female, mean age = 24, SD = 3.7). Female students had significantly higher HPV vaccination rate than males (p = 0.000). The mean knowledge score was 8.09 (SD = 1.35); female students were more likely to receive HPV education than males (p = 0.001). The most common source of education was friends (50.7%). Three most common perceived risks were not being sexually active, being male, and not having any physical signs and symptoms. The three most common facilitators were infection prevention, access to vaccination, and ability to afford vaccination. The three most common barriers were the cost, safety, and efficacy of HPV vaccine. In conclusion, gender disparities exist among Chinese<br/>international students’ HPV vaccine uptake and HPV related education. Implication. Although Chinese international students possess moderate to high level of knowledge about HPV and HPV vaccines, they lack education from credible sources. Culturally and gender appropriate education is needed in order to address barriers of getting HPV vaccination.
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.
Traumatic brain injury (TBI) is a widespread health issue that affects approximately 1.7 million lives per year. The effects of TBI go past the incident of primary injury, as chronic damage can follow for years and cause irreversible neurodegeneration. A potential strategy for repair that has been studied is cell transplantation, as neural stem cells improve neurological function. While promising, neural stem cell transplantation presents challenges due to a relatively low survival rate post-implantation and issues with determining the optimal method of transplantation. Shear-thinning hydrogels are a type of hydrogel whose linkages break when under shear stress, exhibiting viscous flow, but reform and recover upon relaxation. Such properties allow them to be easily injected for minimally invasive delivery, while also shielding encapsulated cells from high shear forces, which would normally degrade the function and viability of such cells. As such, it is salient to research whether shear-thinning hydrogels are feasible candidates in neural cell transplantation applications for neuroregenerative medicine. In this honors thesis, shear-thinning hydrogels were formed through guest-host interactions of adamantane modified HA (guest ad-HA) and beta-cyclodextrin modified HA (host CD-HA). The purpose of the study was to characterize the injection force profile of different weight percentages of the HA shear-thinning hydrogel. The break force and average glide force were also compared between the differing weight percentages. By understanding the force exerted on the hydrogel when being injected, we could characterize how neural cells may respond to encapsulation and injection within HA shear-thinning hydrogels. We identified that 5% weight HA hydrogel required greater injection force than 4% weight HA hydrogel to be fully delivered. Such contexts are valuable, as this implies that higher weight percentage gels impart higher shear forces on encapsulated cells than lower weight gels. Further study is required to optimize our injection force system’s sensitivity and to investigate if cell encapsulation increases the force required for injection.
There are many challenges in designing neuroprostheses and one of them is to maintain proper axon selectivity in all situations. This project is based on an electrode that is implanted into a fascicle in a peripheral nerve and used to provide tactile sensory feedback of a prosthetic arm. This fascicle can undergo mechanical deformation during every day motion. This work aims to characterize the effect of fascicle deformation on axon selectivity and recruitment when electrically stimulated using hybrid modeling. The main framework consists of combining finite element modeling (FEM) and simulation environment NEURON. A suite of programs was developed to first populate a fascicle with axons followed by deforming the fascicle and rearranging axons accordingly. A model of the fascicle with an implanted electrode is simulated to find the electrical potential profile through FEM. The potential profile is then used to compare which axons are activated in the two conformations of the fascicle using NERUON.
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.