1. Integrated coherent Raman scattering and two-photon fluorescence microscopy for biological imaging
- Author
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Li, Xuesong ECE and Li, Xuesong ECE
- Abstract
The nonlinear optical (NLO) technology has become a powerful tool in the biological research. It has many unique advantages over traditional optical technology. First, the NLO technology includes a wide variety of NLO effects such as two-photon excited fluorescence (TPEF) and coherent Raman scattering (CRS). These NLO phenomena have different properties from linear optical processes, indicating that they could provide new opportunities to explore a variety of endogenous molecules in biological specimens. Second, the NLO microscopies have advantages over traditional microscopies on many aspects, such as inherent three-dimensional (3D) imaging with < 0.5 μm lateral resolution, reduced out-of-focus photo-damage, decreased photobleaching to fluorescent molecule and deep penetration depth with the usage of near-infrared ultrafast lasers. These unique properties make NLO microscopy a superior choice for in vivo biological imaging. Since the NLO technology has such advantages, my PhD thesis work focuses on utilizing integrated CRS and TPEF techniques to study biological tissues and processes. Specifically, we develop a femtosecond (fs) multimodal NLO microscopy to study the morphological and biomedical features of lipid droplets (LDs) in C. elegans in vivo. By cross-filtering signals from multiple imaging modalities, our fs NLO microscope system is capable of highly specific assignment of LDs. This enables us to achieve high spectral-resolution image based on single fs laser source. To go one step further, we investigate the lipid dynamics using a powerful picosecond (ps) hyperspectral stimulated Raman scattering (hsSRS) microscope in vibrational cell-silent region. Specifically, we image, monitor and quantify the alkyne-tagged fatty acid 17-ODYA, deuterium-labeled saturated and unsaturated fatty acids PA-D31 & OA-D34 in live C. elegans. The fat accumulation, basal fat turnover and consumption during starvation are quantitatively imaged and analyze
- Published
- 2018