In this project I explored the relationship between Qigong and Tai Chi Easy meditative practices and cardiometabolic risk factors, specifically looking at obesity and stress. The meditative focus of Qigong and Tai Chi Easy was expected to improve cardiac vagal tone which should lead to decreases in the inflammatory effects of stress. Additionally, due to the decreases in the harmful effects of stress, we expect to see a decrease in obesity through decreases in BMI and in waist circumference.
The field of biomedical research relies on the knowledge of binding interactions between various proteins of interest to create novel molecular targets for therapeutic purposes. While many of these interactions remain a mystery, knowledge of these properties and interactions could have significant medical applications in terms of understanding cell signaling and immunological defenses. Furthermore, there is evidence that machine learning and peptide microarrays can be used to make reliable predictions of where proteins could interact with each other without the definitive knowledge of the interactions. In this case, a neural network was used to predict the unknown binding interactions of TNFR2 onto LT-ɑ and TRAF2, and PD-L1 onto CD80, based off of the binding data from a sampling of protein-peptide interactions on a microarray. The accuracy and reliability of these predictions would rely on future research to confirm the interactions of these proteins, but the knowledge from these methods and predictions could have a future impact with regards to rational and structure-based drug design.