We use phenotype-based high-throughput screening to identify natural products that reduce lipid accumulation in hepatic cells. Several bioactive plant extracts and fractions have been identified, and their anti-fatty liver activity has been validated in mouse models. Current efforts focus on identifying the active components and elucidating their molecular mechanisms of action, particularly in relation to lipid droplet metabolism and hepatic metabolic regulation.<\/p>\n
The nuclear factor erythroid 2\u2013related factor 2 (NRF2)\u2013Kelch-like ECH-associated protein 1 (KEAP1) pathway is a master regulator of cellular defense against oxidative stress, electrophilic stress, and xenobiotic exposure. Although NRF2 activation protects normal cells through the induction of cytoprotective genes, aberrant NRF2 activation in cancer cells can promote tumor survival and resistance to chemotherapy. This project aims to identify selective NRF2 regulators that suppress oncogenic NRF2 activity in cancer cells while preserving protective NRF2 functions in normal cells. Such compounds may provide new therapeutic opportunities for cancers driven by dysregulated NRF2 signaling.<\/p>\n
This project aims to construct a comprehensive LC-MS\/MS spectral database of plant crude extracts using standardized extraction protocols and high-resolution mass spectrometry. By integrating advanced data processing, molecular networking, and compound annotation workflows, the platform will enable rapid dereplication, prioritization, and structural characterization of phytochemicals.\u00a0The database will support bioactivity-guided screening, quality control of botanical materials, and machine learning\u2013assisted natural product discovery.<\/p>\n","protected":false},"excerpt":{"rendered":"