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.
According to the CDC, obesity has increased from 30.5% to 42.4% over the past 18 years. Western diets (WDs) consist of large portions in high fats, high carbohydrates, excess sugar and high-glycemic foods that can cause metabolic complications and mitochondrial dysfunction. Diet-induced obesity can lead to changes in muscle metabolism and muscle fiber phenotypes, which in turn lead to metabolic complications. Muscle fiber phenotype is determined protein isoform-content of myosin heavy chain (MHC). Regular exercise alters mitochondrial content and fat oxidation and shifts MHC proportions under healthy circumstances. However, diet and exercise-driven fiber type shifts in diet-induced obesity are less understood. We designed our experiment to better understand the impact of diet and/ or exercise on fiber type content of gastrocnemius muscle in diet-induced obese mice. Exercise and genistein may be used as a treatment strategy to restore the MHC proportions in obese subjects to that of the lean subjects. We hypothesized that genistein and exercise would have the greatest MHC I change in muscle fiber phenotype of mouse gastrocnemius muscles. Further, we also hypothesized that a standard diet would reverse the expected increase in fast fiber phenotype (MHC IIb). Lastly, we also hypothesized that exercise would also reduce the abundance of MHC IIb. Gastrocnemius muscles were collected from mice, homogenized, run through gel electrophoresis and stained to give muscle fiber proportions. Paired sample t-tests were conducted for differences between the MHC isoforms compared to the lean (LN) and high-fat diet (HFD) control groups. The results showed that genistein and exercise significantly increased the abundance of MHC I muscle fibers (19%, p<0.05). Additionally, diet and exercise restored the muscle fiber phenotype to that of lean control. As expected, HFD obese mice exhibited elevated fast twitch fibers compared to only 3% slow twitch fibers. These findings show the potential for exercise and supplementation of genistein as a strategy to combat diet induced obesity. Future research should aim to understand the mechanisms that genistein acts on to make these changes, and aim to replicate these data in humans with obesity.
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.
Diabetes affects millions of people globally and can lead to other severe health complications when undiagnosed or not properly managed. The incidence of diabetes has rapidly increased over the past several years, however, not all individuals have access to affordable or convenient healthcare. We hypothesize that wastewater-based epidemiology (WBE) has the potential to assess community health status by analyzing biomarkers indicative of human health and disease, including diabetes. Used in tandem with current methods, monitoring indicators of diabetes in community wastewater could provide a comprehensive assessment tool for disease prevalence in large and small populations. Specifically, the proposed targeted biomarker evaluated in this study to indicate population-wide diabetes prevalence was 8-hydroxy-2’- deoxyguanosine (8-OHdG). This work combines a rigorous literature review and initial laboratory studies to explore the possibility of diabetes monitoring at the community level using WBE. Here, 24-hour composite wastewater samples were collected from within two wastewater sub-catchments of Greater Tempe, AZ. Overall goals of this study were to: i) Determine the feasibility to detect endogenous markers of diabetes in community wastewater; ii) Assess the potential impact of confounding factors, such as smoking, cancer, and atherosclerosis, through a literature analysis; and iii) Evaluate the socioeconomic status and demographics of the study population. Preliminary results of the experiments suggest this methodology to be feasible, as indicated by the observation of detectable signals of 8-OHdG in community wastewater collected from the sewer infrastructure; however, future work and continued experimentation will be required to address low signal intensity and assay precision and accuracy. Thus, the work presented here provides valuable proof-of-concept data, with detailed information on the method employed and identified opportunities to further determine the relationship between 8-OHdG concentrations in municipal wastewater and diabetes prevalence at the community level.
Diabetes affects millions of people globally and can lead to other severe health complications when undiagnosed or not properly managed. The incidence of diabetes has rapidly increased over the past several years, however, not all individuals have access to affordable or convenient healthcare. We hypothesize that wastewater-based epidemiology (WBE) has the potential to assess community health status by analyzing biomarkers indicative of human health and disease, including diabetes. Used in tandem with current methods, monitoring indicators of diabetes in community wastewater could provide a comprehensive assessment tool for disease prevalence in large and small populations. Specifically, the proposed targeted biomarker evaluated in this study to indicate population-wide diabetes prevalence was 8-hydroxy-2’-deoxyguanosine (8-OHdG). This work combines a rigorous literature review and initial laboratory studies to explore the possibility of diabetes monitoring at the community level using WBE. Here, 24-hour composite wastewater samples were collected from within two wastewater sub-catchments of Greater Tempe, AZ. Overall goals of this study were to: i) Determine the feasibility to detect endogenous markers of diabetes in community wastewater; ii) Assess the potential impact of confounding factors, such as smoking, cancer, and atherosclerosis, through a literature analysis; and iii) Evaluate the socioeconomic status and demographics of the study population. Preliminary results of the experiments suggest this methodology to be feasible, as indicated by the observation of detectable signals of 8-OHdG in community wastewater collected from the sewer infrastructure; however, future work and continued experimentation will be required to address low signal intensity and assay precision and accuracy. Thus, the work presented here provides valuable proof-of-concept data, with detailed information on the method employed and identified opportunities to further determine the relationship between 8-OHdG concentrations in municipal wastewater and diabetes prevalence at the community level.