A research team from the Hong Kong University of Science and Technology (HKUST) has identified a key protein that may shed light on how to reverse the aging process using the adult stem cell of skeletal muscle (or muscle stem cells, MuSCs) as a model system. The discovery paves the way for the possible future development of therapeutic interventions for aging-related diseases and various mitochondrial diseases. Read More...
Prof. Tom CHEUNG, the S H Ho Associate Professor of Life Science in the Division of Life Science at HKUST (right), and his research group member Zhang Wenxin (Mphil student) (left).
An international research team led by the Hong Kong University of Science and Technology (HKUST) has developed an artificial intelligence (AI)-based model that uses genetic information to predict an individual’s risk of developing Alzheimer’s disease (AD) well before symptoms occur. This groundbreaking study paves the way for using deep learning methods to predict the risks of diseases and uncover their molecular mechanisms; this could revolutionize the diagnosis of, interventions for, and clinical research on AD and other common diseases such as cardiovascular diseases.
To discover and thoroughly demonstrate the newly identified noncanonical cleavage mechanism, the Hong Kong University of Science and Technology (HKUST) research team, led by Prof. Tuan Anh Nguyen, Assistant Professor of the Division of Life Science, used several sophisticated techniques, such as miRNA sequencing, pri-miRNA structure analysis, and high-throughput pri-miRNA cleavage assays for approximately 260,000 pri-miRNA sequences. In contrast to the canonical mechanism, the noncanonical mechanism does not rely on several essential protein and RNA elements required for the canonical mechanism.