Nanoscale soft x-ray tomography is a powerful new imaging technology for biomedical and translational research. This technique produces high spatial resolution, high-fidelity 3-Dimensional tomographic reconstructions of the specimen, and does so with unprecedented sample throughput. The work of this proposal will further enhance the applicability, usability and fidelity of soft x-ray tomography as a biomedical imaging technique, make it applicable to a greater range of specimen types, significantly increase spatial resolution, and extend the tools and options available for protein localization. We will continue development of our pioneering work on correlated cryogenic fluorescence microscopy. These efforts, and the planned instrumental and technological developments, will allow multi-modal imaging to be carried out on specimens containing endogenous or exogenous fluorescent labels. The end result will be a suite of imaging options that allow protein localization data to be optimally positioned within a 3-Dimensional reconstruction of the specimen. In soft x-ray tomography the image contrast is derived from the biochemical composition of the specimen. Apart from eliminating the need to fix and stain the specimen this results in each organelle having a signature linear x-ray absorption coefficient. This measurement can be used to identify and quantifiably characterize organelles within a specimen and between different specimens. This type of information, together with the location of specific molecules in the specimen is key to understanding the cellular effects of disease, identifying and validating drug targets, and determining modes of action of molecules with therapeutic potential.
Technologies are being developed to visualize the effects of disease on cell structure and organization. This is important information in the identification and validation of targets for drug design, and for determining the mode of action of molecules with therapeutic potential. This technology can be applied to understanding the cellular effects of cancer, or infection, whether it be microbial, viral or parasitic in origin.
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