Researchers developed a chromatographic method using an immobilized ATR to identify bioactive compounds in Tibetan medicine. Naringenin, pinocembrin, and chrysin were found to specifically bind to ATR, showing potential for drug development.
Scientists isolated 18 compounds from south wild jujube fruits, including new and known derivatives. These compounds showed significant inhibitory activity on α-glucosidase, suggesting potential as hypoglycemic bioactive components for functional foods.
Study developed a framework to extract and represent non-pharmaceutical interventions (NPI) information from biomedical literature in a knowledge graph, using various models to repurpose NPIs for Alzheimer's Disease prevention. Identified novel NPI candidates and mechanistic pathways for potential AD prevention.
A study used a knowledge graph, ADInt, to predict new non-pharmaceutical interventions (NPI) for Alzheimer's Disease (AD) using computational drug repurposing. The graph included AD concepts and potential interventions, integrating dietary supplement domain knowledge graph and semantic relations. Machine learning models were compared to learn representation, and the R-GCN model outperformed others. Discovery patterns were used to generate mechanism pathways for high scoring predictions. The study discovered plausible mechanisms for photodynamic therapy and Choerospondias axillaris preventing AD. This study presents a novel methodology for discovering NPIs for AD and potentially other clinical problems.