3D Analysis of Helium-3 Nanobubbles in Palladium Aged under Tritium by Electron Tomography

Author(s):  
Bérengère Evin ◽  
Éric Leroy ◽  
Walid Baaziz ◽  
Mathieu Segard ◽  
Valérie Paul-Boncour ◽  
...  
2011 ◽  
Vol 193 (2) ◽  
pp. 333-346 ◽  
Author(s):  
Matt West ◽  
Nesia Zurek ◽  
Andreas Hoenger ◽  
Gia K. Voeltz

We analyzed the structure of yeast endoplasmic reticulum (ER) during six sequential stages of budding by electron tomography to reveal a three-dimensional portrait of ER organization during inheritance at a nanometer resolution. We have determined the distribution, dimensions, and ribosome densities of structurally distinct but continuous ER domains during multiple stages of budding with and without the tubule-shaping proteins, reticulons (Rtns) and Yop1. In wild-type cells, the peripheral ER contains cytoplasmic cisternae, many tubules, and a large plasma membrane (PM)–associated ER domain that consists of both tubules and fenestrated cisternae. In the absence of Rtn/Yop1, all three domains lose membrane curvature, ER ribosome density changes, and the amount of PM-associated ER increases dramatically. Deletion of Rtns/Yop1 does not, however, prevent bloated ER tubules from being pulled from the mother cisterna into the bud and strongly suggests that Rtns/Yop1 stabilize/maintain rather than generate membrane curvature at all peripheral ER domains in yeast.


2010 ◽  
Vol 638-642 ◽  
pp. 2517-2522 ◽  
Author(s):  
Christian Kübel ◽  
Dirk Niemeyer ◽  
Robert Cieslinski ◽  
Steve Rozeveld

Electron tomography has developed into a powerful technique to image the 3D structure of complex materials with nanometer resolution. Both, TEM and HAADF-STEM tomography exhibit tremendous possibilities to visualize nanostructured materials for a wide range of applications. Electron tomography is not only a qualitative tool to visualize nano¬structures, but recently electron tomographic results are also exploited to obtain quantitative measurements in 3D. We evaluated the reconstruction and segmentation process for a heterogeneous catalyst and, in particular, tried to assess the reliability and accuracy of the quantification process. Furthermore, a quantitative analysis of electron tomographic results was compared to macroscopic measurements.


2007 ◽  
Vol 84 (11) ◽  
pp. 2707-2713 ◽  
Author(s):  
H. Bender ◽  
O. Richard ◽  
A. Kalio ◽  
E. Sourty

2019 ◽  
Vol 25 (S2) ◽  
pp. 392-393 ◽  
Author(s):  
Silvan Englisch ◽  
Janis Wirth ◽  
Thomas Przybilla ◽  
Benjamin Apeleo Zubiri ◽  
Junwei Wang ◽  
...  

2019 ◽  
Vol 25 (S2) ◽  
pp. 396-397 ◽  
Author(s):  
Benjamin Apeleo Zubiri ◽  
Tobias Weissenberger ◽  
Thomas Przybilla ◽  
Janis Wirth ◽  
Silvan Englisch ◽  
...  

2020 ◽  
Author(s):  
Norbert Lindow ◽  
Florian N. Brünig ◽  
Vincent J. Dercksen ◽  
Gunar Fabig ◽  
Robert Kiewisz ◽  
...  

AbstractWe present a software-assisted workflow for the alignment and matching of filamentous structures across a 3D stack of serial images. This is achieved by combining automatic methods, visual validation, and interactive correction. After an initial alignment, the user can continuously improve the result by interactively correcting landmarks or matches of filaments. Supported by a visual quality assessment of regions that have been already inspected, this allows a trade-off between quality and manual labor. The software tool was developed to investigate cell division by quantitative 3D analysis of microtubules (MTs) in both mitotic and meiotic spindles. For this, each spindle is cut into a series of semi-thick physical sections, of which electron tomograms are acquired. The serial tomograms are then stitched and non-rigidly aligned to allow tracing and connecting of MTs across tomogram boundaries. In practice, automatic stitching alone provides only an incomplete solution, because large physical distortions and a low signal-to-noise ratio often cause experimental difficulties. To derive 3D models of spindles despite the problems related to sample preparation and subsequent data collection, semi-automatic validation and correction is required to remove stitching mistakes. However, due to the large number of MTs in spindles (up to 30k) and their resulting dense spatial arrangement, a naive inspection of each MT is too time consuming. Furthermore, an interactive visualization of the full image stack is hampered by the size of the data (up to 100 GB). Here, we present a specialized, interactive, semi-automatic solution that considers all requirements for large-scale stitching of filamentous structures in serial-section image stacks. The key to our solution is a careful design of the visualization and interaction tools for each processing step to guarantee real-time response, and an optimized workflow that efficiently guides the user through datasets.Author summaryElectron tomography of biological samples is used for a 3D reconstruction of filamentous structures, such as microtubules (MTs) in mitotic and meiotic spindles. Large-scale electron tomography can be applied to increase the reconstructed volume for the visualization of full spindles. For this, each spindle is cut into a series of semi-thick physical sections, of which electron tomograms are acquired. The serial tomograms are then stitched and non-rigidly aligned to allow tracing and connecting of MTs across tomogram boundaries. Previously, we presented fully automatic approaches for this 3D reconstruction pipeline. However, large volumes often suffer from imperfections (i.e. physical distortions) caused during sectioning and imaging, making it difficult to apply fully automatic approaches for matching and stitching of numerous tomograms. Therefore, we developed an interactive, semi-automatic solution that considers all requirements for large-scale stitching of microtubules in serial-section image stacks. We achieved this by combining automatic methods, visual validation and interactive error correction, thus allowing the user to continuously improve the result by interactively correcting landmarks or matches of filaments. We present large-scale reconstructions of spindles in which the automatic workflow failed and where different steps of manual corrections were needed. Our approach is also applicable to other biological samples showing 3D distributions of MTs in a number of different cellular contexts.


2019 ◽  
Vol 9 (Suppl_1) ◽  
pp. S35-S35
Author(s):  
Alexey Mikhutkin ◽  
Roman Kamyshinsky ◽  
Nikita Kuznetsov ◽  
Sergey Chvalun ◽  
Alexander Vasiliev

Small Methods ◽  
2018 ◽  
Vol 2 (1) ◽  
pp. 1870011
Author(s):  
Thomas Przybilla ◽  
Benjamin Apeleo Zubiri ◽  
Ana M. Beltrán ◽  
Benjamin Butz ◽  
Albert G. F. Machoke ◽  
...  

Small Methods ◽  
2017 ◽  
Vol 2 (1) ◽  
pp. 1700276 ◽  
Author(s):  
Thomas Przybilla ◽  
Benjamin Apeleo Zubiri ◽  
Ana M. Beltrán ◽  
Benjamin Butz ◽  
Albert G. F. Machoke ◽  
...  

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