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- All Subjects: Diabetes
- Creators: Harrington Bioengineering Program
- Creators: Muthuswamy, Jitendran
- Resource Type: Text
To better understand the inconsistent effects across rat motor cortex, US modulation of electrically-evoked movements was tested. A stimulation array was implanted on the cortical surface and US (200 kHz, 30-60 W/cm2 peak) was applied while measuring changes in the evoked forelimb and hindlimb movements. Direct US stimulation of the hindlimb was also studied. To test peripheral effects, rat blood glucose levels were measured while applying US near the liver.
No short-term motor modulation was visible (95% confidence interval: -3.5% to +5.1% forelimb, -3.8% to +5.5% hindlimb). There was significant long-term (minutes-order) suppression (95% confidence interval: -3.7% to -10.8% forelimb, -3.8% to -11.9% hindlimb). This suppression may be due to the considerable heating (+1.8°C between US
on-US conditions); effects of heat and US were not separable in this experiment. US directly evoked hindlimb and scrotum movements in some sessions. This required a long interval, at least 3 seconds between US bursts. Movement could be evoked with much shorter pulses than used in literature (3 ms). The EMG latency (10 ms) was compatible with activation of corticospinal neurons. The glucose modulation test showed a strong increase in a few trials, but across all trials found no significant effect.
The single motor response and the long refractory period together suggest that only the beginning of the US burst had a stimulatory effect. This would explain the lack of short-term modulation, and suggests future work with shorter pulses could better explore the missing forelimb response. During the refractory period there was no change in the electrically-evoked response, which suggests the US stimulation mechanism is independent of normal brain activity. These results challenge the literature-standard protocols and provide new insights on the unknown mechanism.
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.
The project was aimed towards middle school and high school students, as this is the estimated level where they learn biology and chemistry—key subject material in biomedical engineering. The high school students were given presentations and activities related to biomedical engineering. Additionally, within classrooms, posters were presented to middle school students. The content of the posters were students of the biomedical engineering program at ASU, coming from different ethnic backgrounds to try and evoke within the middle school students a sense of their own identity as a biomedical engineer. To evaluate the impact these materials had on the students, a survey was distributed before the students’ exposure to the materials and after that assesses the students’ understanding of engineering at two different time points. A statistical analysis was conducted with Microsoft Excel to assess the influence of the activity and/or presentation on the students’ understanding of engineering.
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.