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Organizer: Maryann Martone |
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Instructor: Robert Zucker |
| The confocal laser scanning microscope (CLSM) has enormous potential in many bioloical fields. The goal of a CLSM is to acquire and in some intruments acquire spectral characterization of the emitted signal. The accuracy of these measurements demands that the system be in alignment, with stable laser power and spectral registration. For many applications, it is useful to confirm the system's spatial resolution, sensitivity and precision prior to acquiring image data. The most common method to check the performance of a CLSM system is to characterize a histological slide to create a Òpretty pictureÓ. We have developed tests to replace this subjective method with objective measurements of field illumination, lens function and clarity, spectral registration, total laser power, laser stability, dichroic reflectance, axial resolution, scanning stability, overall machine stability, and system noise. We developed additional tests to measure spectral performance to serve as guidelines for investigators to assess both the performance of their instruments as well as the quality of their data. |
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Instructor: Neils Volkmann |
| To understand the function of biological macromolecules in their cellular context, it is essential to link highresolution information with cell biology. We will discuss a number of computational tools that assist in bridging the gap between the information coming from atomic structures of individual macromolecules and higherorder structural entities obtained by electron tomography. Examples include detection of macromolecular footprints, autosegmentation approaches, docking of crystallographic structures, and noisereduction algorithms. |
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Instructor: Thomas Deerinck |
| Nanocrystals composed of cadmium selenide coated with zinc sulfide, also referred to as quantum dots, are becoming increasingly attractive as probes for cellular localization of proteins owing to their unique optical properties. Quantum dots exhibit exceptional photostability, high absorbance and fluorescent quantum yields, as well as narrow band fluorescence emission, making them excellent for immunofluorescence. Quantum dots can be synthesized in a variety of distinct shapes and sizes in order to tune their fluorescence emission over the visible spectrum, making them ideal for multiple labeling studies. An additional benefit is that not only can they be visualized in the electron microscope, but that the different shapes and sizes can be easily discriminated from each other, making correlated multiple labeling at the light and EM level possible. This tutorial will cover the application of quantum dot bioconjugates for labeling of proteins in cells and tissues using confocal, 2photon and electron microscopy. |
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Organizer: Peter Crozier |
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Instructor: Eric A. Stach |
| Advances in imaging and diffraction techniques, sample preparation methods and new holder developments have created substantial interest in dynamic electron microscopy. This tutorial will present a general overview of the various categories of insitu electron microscopy studies (both tried and true as well as cutting edge developments), with an emphasis on the classes of materials science problems that can be solved with each approach. As a technique, insitu TEM studies in particular can suffer from unwanted artifacts introduced by the thin foil geometry Ð as a result, I will discuss various sample preparation and experimental strategies that can be used to minimize (but not entirely mitigate) these concerns. Additional emphasis will be placed on such practical concerns as temperature measurement and calibration and rapid data analysis from video captures. |
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| This tutorial will review the principles of Monte Carlo simulations to perform Xray microanalysis in the SEM and in the TEM. Image simulation of BSE images in the SEM will also be covered. Emphasis will be on two free commercial software packages, Casino and Win Xray that can be used to perform quantitative Xray microanalysis as well as to find optimum conditions for analysis and imaging of various types of materials. The utility of Monte Carlo simulations to characterize nonhomogeneous materials in the SEM will be covered. Finally, Monte Carlo simulations for the effect of the skirt on Xray microanalysis in the ESEM or VPSEM will be presented. |
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Instructor: Michael Treacy |
| Fluctuation Electron Microscopy (FEM) has become an effective tool for detecting medium range atomic ordering in glasses and amorphous materials. Success arises from the statistical approach of examining differences in scattering between small volumes. Whereas the mean scattering properties are related to the mean diffracted intensity, the variance of the scattering properties reveals the underlying structural fluctuations. By examining the variance as a function of scattering conditions, structural ÒnoiseÓ (true random fluctuations) can be differentiated from the underlying structural trends. |
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Instructor: Andreas Thust |
| Focal-series reconstruction has proven to be a valuable tool for the investigation of materials on an atomic level by means of HRTEM. By taking a series of typically 1020 highresolution images at different objective lens defocus values, one can retrieve numerically the quantummechanical wavefunction of the electrons at the exit surface of the object. The retrieved wavefunction is ideally free from all imaging artifacts caused by the observation instrument and yields, at least for sufficiently thin samples, a direct insight into the object structure. The technique of focalseries reconstruction can also be used to completely remove the nonlinear contrast contributions to the images and compensate aposteriori for unwanted residual optical aberrations. This makes the technique a powerful tool even when combined with the newest generation of sphericalaberration corrected microscopes. Applications from a variety of very different materials classes are now available demonstrating the impact of the reconstruction technique. |
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Organizers: Peter Crozier and Maryann Martone |
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Instructor: Jose Maria Carazo |
| Information integration is at the basis of almost any data analysis task. Stated simply, the image data sets are either too complex, large or numerous to keep working without tools to automatically extract new knowledge. One of the most basic approaches in this knowledge extraction quest is the use of classification techniques. In essence, the goal is to place an order upon the data such that we group together into ÒbasketsÓ those elements that are similar to one another, in such a way that the differences among the elements from different baskets are larger than that between the elements in any particular basket. The elements to be grouped may be complete images showing, for instance, different structural conformations of a given macromolecular nanomachine or they could be, in a totally different context, similar pixels within one or a series of images of an alloy taken at different energy intervals. In this joint tutorial, we will cover basic data reduction and classification techniques such as principal component analysis, Kmeans, dendrograms and selforganizing neural networks. The motivation for these techniques is to discover order and pattern in our imaging data so that we will be in a much better position to advance in the understanding of complex systems. |
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Organizers: Scott Walck, Mike Marko |
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Environmental Electron Microscopy
Photoshop
3-D Visualization Using Amira |