Evaluating sample quality requires access to cryo-electron microscopes and a strong expertise in EM. To facilitate and accelerate the selection procedure of probes suitable for high-resolution cryo-EM, we devised a method to assess the vitreous ice layer thickness of sample coated grids. The ...
et al. Automated cryoEM data acquisition and analysis of 284 742 particles of GroEL. J. Struct. Biol. 155, 470–481 (2006). Article CAS PubMed Google Scholar Rice, W. J. et al. Routine determination of ice thickness for cryo-EM grids. J. Struct. Biol. 204, 38–44 (2018). ...
cryo-ultramicrotome, to a suitable thickness and view the resulting “cryosections” in the cryo-EM. Cryo-ultramicrotomy is a difficult technique that is not free of its own inherent artifacts. A number of laboratories around the world have worked hard to improve the technique and develop ...
Super flat[1] –especially at the hole edges where the ice is vitrified For even and low ice thickness For better particle dispersion No cleaning required – C-flat™ holey carbon film is clean out of the box Fast delivery – most standard types of C-flat™ grids are in stock and re...
Au-flat™ is an ultrastable, biocompatible holey gold alloy film (80% Au and 20% Pd) with a thickness of ca. 45 nm supported by a TEM gold grid. Significant improvements have made Au-flats™ the new gold standard for Cryo-EM sample supports:...
This tutorial demonstrates how to use three new capabilities in Smart EPU: Plasmon Peak Imaging , Smart Ice Thickness Prediction, and Tilted Acquisition. Open Application Programming Interface (API) The Smart EPU ecosystem, through its open API, allows you to develop plugins that interact wi...
This tutorial demonstrates how to use three new capabilities in Smart EPU: Plasmon Peak Imaging , Smart Ice Thickness Prediction, and Tilted Acquisition. Open Application Programming Interface (API) The Smart EPU ecosystem, through its open API, allows you to develop plugins that interact wi...
Smart Ice Thickness Prediction— for automated classification of foil holes depending on predicted ice thickness based on trained neural networks. Smart Filter— for auto selection of the best quality holes: A pretrained neural network that automatically exclude contaminated or broken holes on a grid ...
Because of the particle's large size, different blot pad positions and blotting times were tested with offset number −2 and 3 s blotting giving satisfactory results in terms of ice thickness relative to the particle's size and rupture. Two data sets were acquired for the virion sample. ...
holes with suitable ice thickness were selected with the hole finder and combined to produce multishot–multihole targets, which enabled the acquisition of six movies per hole in each of the neighbouring nine holes. These movies were captured with a K3 direct electron detector. A total dose of...