Development of a novel drug information provision system for Kampo medicine using natural language processing technology.

Background: Kampo medicine is widely used in Japan; however, most physicians and pharmacists have insufficient knowledge and experience in it. Although a chatbot-style system using machine learning and natural language processing has been used in some clinical settings and proven useful, the system developed specifically for the Japanese language using this method has not been validated by research. The purpose of this study is to develop a novel drug information provision system for Kampo medicines using a natural language classifier® (NLC®) based on IBM Watson.

COL8A1 facilitates the growth of triple-negative breast cancer via FAK/Src activation.

Purpose: Triple-negative breast cancer (TNBC) is one of the most aggressive breast cancer subtypes, and treatment options are limited because of the lack of signature molecules and heterogeneous properties of cancer. COL8A1 expression is higher in breast cancer than in normal tissues and is strongly correlated with worse overall survival in patients with breast cancer. However, the biological function of COL8A1 on cancer progression is not fully understood.