People with Type One diabetes often rely on Continuous Blood Glucose Monitors (CGMs) to track their blood glucose and manage their condition. Researchers are now working to help people with Type One diabetes more easily monitor their health by developing models that will future blood glucose levels based on CGM readings. Jalla and Ghanta tackle this issue by exploring the use of AI models to forecast blood glucose levels with CGM data.
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Correlates of Sugar Consumption Among High School Students and Faculty
The availability, portion sizes, and consumption of highly palatable food has been linked adverse health outcomes. McBurnett and O’Donnell sought to assess the relationship between reward-based eating drive, consumption, cravings, and knowledge of the effects of sugary foods. In this study population, reward-based eating drive was related to both consumption and cravings. Further, for females, the knowledge of sugar’s effects was significantly and inversely associated with its consumption.
Read More...Developing “Off the Shelf” Pancreases for Diabetic Patients Using Bacterial and Kombucha Tea Waste
In this study, the authors investigate the suitability of using bacterial cellulose as a scaffold for cell transplants. Interestingly, this cellulose is a can be found in the discard from a symbiotic culture of bacteria and yeast (SCOBY) used to make kombucha.
Read More...The Clinical Accuracy of Non-Invasive Glucose Monitoring for ex vivo Artificial Pancreas
Diabetes is a serious worldwide epidemic that affects a growing portion of the population. While the most common method for testing blood glucose levels involves finger pricking, it is painful and inconvenient for patients. The authors test a non-invasive method to measure glucose levels from diabetic patients, and investigate whether the method is clinically accurate and universally applicable.
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