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- All Subjects: Diabetes
- Creators: College of Health Solutions
- Status: Published
As the return to normality in the wake of the COVID-19 pandemic enters its early stages, the necessity for accurate, quick, and community-wide surveillance of SARS-CoV-2 has been emphasized. Wastewater-based epidemiology (WBE) has been used across the world as a tool for monitoring the pandemic, but studies of its efficacy in comparison to the best-known method for surveillance, randomly selected COVID-19 testing, has limited research. This study evaluated the trends and correlations present between SARS-CoV-2 in the effluent wastewater of a large university campus and random COVID-19 testing results published by the university. A moderately strong positive correlation was found between the random testing and WBE surveillance methods (r = 0.63), and this correlation was strengthened when accommodating for lost samples during the experiment (r = 0.74).
Chronic diseases place a financial burden on the United States and claim the lives of nearly 2 million Americans every year. Among the chronic diseases that plague American people, type 2 diabetes is particularly prevalent and injurious. Thus, action is warranted to improve prevention and management of this disease. Nutrition plays a significant role in prevention and management of type 2 diabetes and other chronic diseases. Registered dietitians, as nutrition experts, are qualified to use medical nutrition therapy as a method of prevention and treatment for chronic diseases using a nutritional approach. However, there is no consensus as to which eating pattern is the most efficacious. The aim of this review of research was to examine how plant-based eating patterns impact chronic disease conditions, with an emphasis on type 2 diabetes mellitus, as compared to omnivorous eating patterns. A literature search was conducted through the ASU Library, PubMed, and CINAHL using terms related to plant-based diets and chronic diseases, such as type 2 diabetes. The results revealed that a plant-based eating pattern may be beneficial in the prevention and treatment of certain chronic diseases, such as type 2 diabetes. Specifically, adults who have type 2 diabetes and consume a plant-based diet may exhibit enhanced glycemic control as evidenced by less insulin resistance, increased incretin and insulin secretion, greater insulin sensitivity, and improved HbA1c levels. There is sufficient evidence for registered dietitians to recommend a plant-based approach to patients with type 2 diabetes who would like to achieve enhanced glycemic control.
Objective: There were three main objectives of the study. One objective was to elucidate potential new relationships via linear regression. Another objective was to determine which factors were indicative of Type 2 DM in the population. Finally, the last objective was to compare the incidence of Type 2 DM in the dataset to trends seen elsewhere.
Methods: The dataset was uploaded from an open source site with citation onto Python. The dataset, created in 1990, was composed of 768 female patients across 9 different attributes (Number of Pregnancies, Plasma Glucose Levels, Systolic Blood Pressure, Triceps Skin Thickness, Insulin Levels, BMI, Diabetes Pedigree Function, Age and Diabetes Presence (0 or 1)). The dataset was then cleaned using mean or median imputation. Post cleaning, linear regression was done to assess the relationships between certain factors in the population and assessed via the probability statistic for significance, with the exclusion of the Diabetes Pedigree Function and Diabetes Presence. Reverse stepwise logistic regression was used to determine the most pertinent factors for Type 2 DM via the Akaike Information Criterion and through the statistical significance in the model. Finally, data from the Center of Disease Control (CDC) Diabetes Surveillance was assessed for relationships with Female DM Percenatge in Pinal County through Obesity or through Physical Inactivity via simple logistic regression for statistical significance.
Results: The majority of the relationships found were statistically significant with each other. The most pertinent factors of Type 2 DM in the dataset were the number of pregnancies, the plasma glucose levels as well as the Blood Pressure. Via the USDS Data from the CDC, the relationships between Female DM Percentage and the obesity and inactivity percentages were statistically significant.
Conclusion: The trends found in the study matched the trends found in the literature. Per the results, recommendations for better diabetes control include more medical education as well as better blood sugar monitoring.With more analysis, there can be more done for checking other factors such as genetic factors and epidemiological analysis. In conclusion, the study accomplished its main objectives.
A total of 26 human subjects were used in this study. Each subject was classified as either lean or obese, according to their BMI measurement. First, the subjects underwent an oral glucose tolerance test. Blood samples were taken to measure glucose levels in the blood. After the test subject characteristics for each subject was obtained. These included age, BMI, body fat percentage, fat free mass (FFM), height, total mass, waist circumference, hip circumference, and waist to hip ratio. After the subject characteristics and blood glucose were measured the blood samples taken previously were then centrifuged, and the blood plasma was extracted. The blood plasma was then used to undergo an Insulin ELISA test. After extensive analysis, the Matsuda Index of each subject was obtained. Subjects with a Matsuda value of 6.0 or under were considered insulin resistant while subjects with a Matsuda value higher than 6.0 were considered insulin sensitive. Subjects were also required to submit a dietary record over the course of three days. The food intake was then put into a food processing software which gave a daily average of the macro and micro nutrients for each subject. Both the subject and dietary values were put into a multiple regression with a significance factor of p < 0.5 to see which factors contributed most to the Matsuda value.
It was found that BMI, height, total mass, insulin and fat free mass, all of which were subject characteristics, were considered to be significant. Some of these factors an individual has no control over, such as height and insulin. However other factors such as BMI, total mass and fat free mass can be affected by both a healthy diet and frequent exercise. This study validated that diet and physical activity can greatly influence an individual’s susceptibility to insulin resistance and ultimately T2DM.
An exploration into the history of the 1918 Influenza Pandemic and the societal impacts associated with it, as well as an analysis of the developing SARS-CoV-2 pandemic today. Based upon these analyses, similarities were drawn between the two pandemics which suggested a lack of innovation in preventative measures over the last century. Given this conclusion a series of proposals were made that should be further explored to give not only the United States, but the world at large, a better chance in the face of the next emerging disease.
This thesis creative project involved the planning, preparation, and facilitation of a community-wide event targeting Diabetes Awareness. The event was hosted March 16, 2022, on ASU west campus and includes a PowerPoint presentation of the overall process. It also includes a reflection of successes, challenges, and experience gained from planning and facilitation. At the end, there is information analyzing how the event could be improved upon for the future, and a summary of key ideas discussed throughout the project. There is also a paper with the description of the presentation and an embedded link to the recorded presentation of the project during the defense.
Virus-like particles (VLPs) are optimum candidates for creating vaccines, as they are highly flexible, adaptable, safe, and similar to the structural proteins of the target cells. The COVID 19 pandemic has increased the need to create effective and safe vaccines that can be mass produced to stop the spread of COVID-19. Till now, various types of vaccine platforms have been utilized to create COVID-19 vaccines, each with unique characteristics and techniques. It is essential to use robust vaccine platforms that can deliver optimum results in a short period of time, with minimal risks. The structural proteins found in SARS-CoV-2, such as Spike (S) protein have been widely targeted to induce antibody response, also called a humoral response, which is a part of acquired immunity. The other structural proteins such as M (membrane) and E (envelope) can also be used as targets for antibodies. The S2 and glycoprotein (S full) can be used to induce an efficient IgG response. Therefore, the incorporation of structural proteins into VLPs can prove to be useful. Furthermore, double mosaic VLPs employs double epitopes, which can effectively cover the distances between the S proteins, thus optimizing the B cell activation process. This review describes the various developments that have taken place in the field of VLPs and more specifically, with regards to developing VLP vaccines against the SARS-CoV-2 virus.