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- Creators: Harrington Bioengineering Program
- Creators: College of Health Solutions
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Resource Type: Text
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.
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.
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.