Sandwich freezing (freezing the specimen rapidly with liquid propane by placing it between two copper disks) and freeze-substitution of living yeast cells has been used for observing exquisite close-to-native ultrastructure of cells. Glutaraldehyde fixation, sandwich freezing, and freeze substitution of bacteria and other microorganisms also yield close-to-native ultrastructure. Here, we have used glutaraldehyde fixation, sandwich freezing, and freeze substitution to observe human cells and tissues. We obtained clear and natural cell images of tissues sliced to 0.2 mm thickness. This is a remarkable result because, in the past, tissues as thick as 0.2 mm could only be frozen by high-pressure freezing. The present study has shown that it is possible to observe clear and natural cell structures in animal and human tissues anytime because glutaraldehyde-fixed tissues can be stored at 4 C for several months before freezing, and a sandwich-freezing device will soon become commercially available. Also, natural ultrastructure of cultured cells in suspension was found to be observed more clearly by glutaraldehyde-fixation, sandwich freezing, and freeze-substitution than sandwich freezing and freeze substitution of living cells. The present method should be used as a standard method to observe the close-to-native ultrastructure of animal and human tissues.

This study focused on the problem of projection parameter search in 3D reconstruction using single-particle analysis. We treated the sampling distribution for the parameter search as a prior distribution and designed a probabilistic model for efficient parameter estimation. Using our method, we showed that it is possible to perform 3D reconstruction from synthetic and actual electron microscope images using an initial model, and to generate the initial model itself. We also examined whether the optimization function used in the stochastic gradient descent method can be applied with loose constraints to improve the convergence of initial model generation and confirmed the effect. In order to investigate the advantage of generating a smooth sampling distribution from the stochastic model, we compared the distribution of estimated projection directions with the conventional method of performing a global search using spherical gridding. As a result, our method, which is simple in both mathematical model and implementation, showed no algorithmic artifacts.

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