Time：4:00-5:30 PM, Thursday, Sept. 22, 2022
Venue: E10-201, Yungu Campus
Host: Dr. Yongdeng Zhang, PI, School of Life Sciences
Liangyi ChenLiangyi Chen is Boya Professor of Peking University. He obtained his undergraduate degrees Biomedical engineering in Xi’an JiaoTong University, then majored in Biomedical engineering in pursuing PhD degree in Huazhong University of Science and Technology. His lab focused on two interweaved aspects: the development of new imaging and quantitative image analysis algorithms, and the application of these technology to study how glucose-stimulated insulin secretion is regulated in the health and disease at multiple levels (single cells, islets and in vivo) in the health and disease animal models. The techniques developed included ultrasensitive Hessian structured illumination microscopy (Hessian SIM) for live cell super-resolution imaging, the Sparse deconvolution algorithm for extending spatial resolution of fluorescence microscopes limited by the optics, Super-resolution fluorescence-assisted diffraction computational tomography (SR-FACT) for revealing the three-dimensional landscape of the cellular organelle interactome, two-photon three-axis digital scanned lightsheet microscopy (2P3A-DSLM) for tissue and small organism imaging, and fast High-resolution Miniature Two-photon Microscopy (FHIRM-TPM) for Brain Imaging in Freely-behaving Mice. He is recipient of the National Distinguish Scholar Fund project from National Natural Science Foundation of China, and also a guest professor at Université PSL and École Normale Supérieure.
报告题目/Title:The Next-generation of Live Cell Super-resolution Microscopy: New Mechanisms and Applications
讲座摘要/Abstract:Here we will present three pieces of high-resolution fluorescence microscopy methods we invented for live sample imaging. The first one is for live-cell long-term super-resolution (SR) imaging. We have developed a deconvolution algorithm for structured illumination microscopy based on Hessian matrixes (Hessian-SIM). After the first work, we realized that the spatial resolutions of live-cell super-resolution microscopes are limited by the maximum collected photon flux. Taking advantage of a priori knowledge of the sparsity and continuity of biological structures, we develop a deconvolution algorithm that further extends the resolution of super-resolution microscopes under the same photon budgets by nearly twofold. The third technology is a dual-mode SR microscopy for highlighting molecules as well as a holistic view of related interacting organelles in live cells. It is a combination of two-dimensional Hessian-SIM with label-free three-dimensional optical diffraction tomography (ODT), term SR fluorescence-assisted diffraction computational tomography (SR-FACT).