Data set of gastroesophageal reflux disease caused by caffeine binding to dopamine receptor protein regulating brain addiction

The research team conducted logistic and Cox regression according to the behavioral data of gastroesophageal reflux disease patients who had long been drinking caffeinated coffee drinks, and determined the sensitivity and mathematical rationality of AI prediction model in behavioral science, which can support the research team to build a deep learning neural network and complete the prediction of gastrointestinal tract involvement. The research team designed a controlled trial to analyze the difference of functional reward and reinforcement in the midbrain limbic between people who have coffee drinking habits and blank people. In terms of molecular dynamics, the research team used molecular docking and molecular dynamics technology to analyze the molecular mechanics of caffeine binding to dopamine receptors, which proved the basis of caffeine induced toxic side reactions activating immune verification pathway in the molecular force field. On the basis of interdisciplinary research, the neuropsychological mechanism of caffeine binding to dopamine receptor protein regulating the activation of inflammatory immune factors by the mesolimbic dopamine pathway was verified, and the AI prediction model of gastrointestinal injury was developed at the application level. This paper solves the difficulty of adjusting caffeine intake to predict gastrointestinal injury, and achieves the goal of drinking coffee and caffeine drinks healthily.