Title： Biomedical Label-Free Imaging and Spectroscopy with Scattered Light

Time： Thursday 16:00pm, October 24, 2019

Location：Room A-424, West Building 5, Qujiang Campus

Lecturer：

Lev T. Perelman, PhD

Professor and Director

Center for Advanced Biomedical Imaging and Photonics

Beth Israel Deaconess Medical Center

Biological and Biomedical Sciences Program

Harvard University

Inviter: Professor Yulong ZHAO

Lecture Introduction：

Optical spectroscopy emerged as a valuable tool to study live biological tissue at various scales and detect early disease in the human body. While fluorescence and Raman spectra are sensitive to molecular properties of tissue, light scattering spectra, originating from the extracellular matrix, subcellular structures, and other tissue inhomogeneities, carry information about tissue microscopic and macroscopic organization. In this talk we will discuss how scattered light can be used for noninvasive detection of invisible pre-cancer in such diverse organs as the esophagus or pancreas that seem to have little in common. We will show, however, that since pre-cancer in many organs is characterized by certain microscopic changes in epithelial cells, such as increase in nuclear size and nuclear density, light scattering signatures of those precancers are quite similar, allowing early cancer imaging and detection without the need for external markers.

Light scattering signatures could also be used for sensing subnuclear and subcelluar structure of live cells, e.g. chromatin packing, organelle organization, and characterization of cell-derived exosomes. Nanoscale changes in the nuclear structure have been shown to play a critical role in genetic and transcriptional alterations and are a hallmark of neoplasia. However, due to the lack of technologies for label-free nanoscale-sensitive measurements in live cells, many aspects of these phenomena have remained an open problem. We will discuss how the approach based on the combination of confocal microscopy and spectroscopy of scattered light could help to solve this problem, providing several critical advantages over the existing methods.