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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Prediction of diabetes using supervised classification
The authors develop and test a machine learning algorithm for predicting diabetes diagnoses.
Read More...Entropy-based subset selection principal component analysis for diabetes risk factor identification
In this article, the authors looked at developing a strategy that would allow for earlier diagnosis of Diabetes as that improves long-term outcomes. They were able to find that BMI, tricep skin fold thickness, and blood pressure are the risk factors with the highest accuracy in predicting diabetes risk.
Read More...Combating Insulin Resistance Using Medicinal Plants as a Supplementary Therapy to Metformin in 3T3-L1 Adipocytes: Improving Early Intervention-Based Diabetes Treatment
A primary cause of diabetes is insulin resistance, which is caused by disruption of insulin signal transduction. The objective of this study was to maximize insulin sensitivity by creating a more effective, early intervention-based treatment to avert severe T2D. This treatment combined metformin, “the insulin sensitizer”, and medicinal plants, curcumin, fenugreek, and nettle.
Read More...Investigating the inhibition of catabolic enzymes for implications in cardiovascular diseases and diabetes
Enzymes that metabolize carbohydrates and lipids play a key role in our health, including global health challenges like cardiovascular diseases and diabetes. To learn more about these important enzymes, Gandhi and Gandhi test whether various natural substances (ginger, Aloe vera, lemon, and mint leaves) affect the activity of α-amylase and lipase enzymes.
Read More...Evaluation of the causality between testosterone, obesity, and diabetes
The study explored the role of testosterone beyond its well-established effects on male sex characteristics, focusing on its association with non-communicable diseases (NCDs) like obesity and type 2 diabetes (T2D), using Mendelian randomization (MR) analysis on genomic data.
Read More...Indole-3 carbinol on lipid accumulation in Caenorhabditis elegans as a novel therapeutic for Type II Diabetes
In this study the authors look at the use of Indole 3 Carbinol as a treatment for Type II Diabetes finding that it may be an effective treatment.
Read More...Observing effects of resolving leaky gut on sugar, fat, and insulin levels during type 1 diabetes in fruit flies
This study uses a fruit fly model of type 1 diabetes (T1D) to determine whether strengthening intestinal tight junctions to reduce intestinal permeability would improve T1D symptoms.
Read More...Public Perception of the Effects of Artificial Sweeteners on Diabetes Based on YouTube Comments
Artificial sweeteners are rising in popularity, in part due to the influence of social media platforms like YouTube. However, YouTube commenters often repeat information about artificial sweeteners that is not supported by scientific research. To investigate how misinformation about sweeteners spreads through social media, Kim and Yoo conduct a content analysis of YouTube comments to reveal how many comments repeat misinformation about artificial sweeteners' effects.
Read More...Potential Multifunctional Agents for Dual Therapy of Age-Related and Associated Diseases: Alzheimer’s Disease and Type 2 Diabetes Mellitus
Studies show an age-related link between Alzheimer’s Disease and Type 2 Diabetes Mellitus with oxidative stress a characteristic of both. Here, methanolic fractionations and extracts of four Ayurvedic plants were assessed for their protective abilities using a number of in vitro assays. Extracts inhibited oxidative stress and reduced activity of key enzymes involved in the pathogenesis of both diseases in neuroblastoma cells.
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