Acarbose degradation mechanism guides design of next-generation antidiabetic drug
Peer-Reviewed Publication
Updates every hour. Last Updated: 19-Oct-2025 00:11 ET (19-Oct-2025 04:11 GMT/UTC)
In a paper published in SCIENCE CHINA Earth Sciences, a team of researchers investigated a fine-scale lightning forecasting approach based on weather foundation models (WFMs) and proposed a dual-source data-driven forecasting framework that integrates the strengths of both WFMs and recent lightning observations to enhance predictive performance. Furthermore, a gated spatiotemporal fusion network (gSTFNet) is designed to address the challenges of cross-temporal and cross-modal fusion inherent in dual-source data integration. Experimental results demonstrate that the dual-source framework significantly improves forecasting performance compared to models trained solely on WFMs and outperforms both the ECMWF HRES lightning product and other deep-learning spatiotemporal forecasting models.
Based on a symmetry-guided synthesis strategy, the research group of Professor Yefeng Tang at Tsinghua University recently achieved the efficient construction of the tricyclic core skeleton of polycyclic aromatic tetralin-type lignans by using as key steps the chiral phosphoric acid-catalyzed photoasymmetric [2+2] cycloaddition and ring strain-driven oxidative ring expansion reactions. They also achieved the efficient enantioselective total synthesis of multiple aromatic tetralin-type lignan natural products through subsequent biomimetic cyclization and local desymmetrization reactions. These results were published as an open access article in CCS Chemistry, the flagship journal of the Chinese Chemical Society.