scholarly journals Cross Sectional Method with Ar Ion Beam Applied for High Resolution Scanning Electron Microscopy

2019 ◽  
Vol 62 (7) ◽  
pp. 439-442
Author(s):  
Tamae OMOTO ◽  
Shunsuke ASAHINA
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
High Resolution ◽  
Ion Beam ◽  
Cross Sectional ◽  
Scanning Electron

Scanning Electron Microscopy Observation of Interface Between Single Neurons and Conductive Surfaces

2016 ◽  
Vol 16 (4) ◽  
pp. 3383-3387 ◽  
Author(s):  
Toichiro Goto ◽  
Nahoko Kasai ◽  
Rick Lu ◽  
Roxana Filip ◽  
Koji Sumitomo
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Indium Tin Oxide ◽  
Focused Ion Beam ◽  
Ion Beam ◽  
Single Neurons ◽  
Sem Images ◽  
Cross Sectional ◽  
Integrated Devices ◽  
Scanning Electron

Interfaces between single neurons and conductive substrates were investigated using focused ion beam (FIB) milling and subsequent scanning electron microscopy (SEM) observation. The interfaces play an important role in controlling neuronal growth when we fabricate neuron-nanostructure integrated devices. Cross sectional images of cultivated neurons obtained with an FIB/SEM dual system show the clear affinity of the neurons for the substrates. Very few neurons attached themselves to indium tin oxide (ITO) and this repulsion yielded a wide interspace at the neuron-ITO interface. A neuron-gold interface exhibited partial adhesion. On the other hand, a neuron-titanium interface showed good adhesion and small interspaces were observed. These results are consistent with an assessment made using fluorescence microscopy. We expect the much higher spatial resolution of SEM images to provide us with more detailed information. Our study shows that the interface between a single neuron and a substrate offers useful information as regards improving surface properties and establishing neuron-nanostructure integrated devices.

scholarly journals Niwaki Instead of Random Forests: Targeted Serial Sectioning Scanning Electron Microscopy With Reimaging Capabilities for Exploring Central Nervous System Cell Biology and Pathology

2021 ◽  
Vol 15 ◽  
Author(s):  
Martina Schifferer ◽  
Nicolas Snaidero ◽  
Minou Djannatian ◽  
Martin Kerschensteiner ◽  
Thomas Misgeld
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
High Resolution ◽  
Cell Biology ◽  
Ion Beam ◽  
Serial Sectioning ◽  
Actual Structure ◽  
Array Tomography ◽  
Block Face ◽  
Scanning Electron

Ultrastructural analysis of discrete neurobiological structures by volume scanning electron microscopy (SEM) often constitutes a “needle-in-the-haystack” problem and therefore relies on sophisticated search strategies. The appropriate SEM approach for a given relocation task not only depends on the desired final image quality but also on the complexity and required accuracy of the screening process. Block-face SEM techniques like Focused Ion Beam or serial block-face SEM are “one-shot” imaging runs by nature and, thus, require precise relocation prior to acquisition. In contrast, “multi-shot” approaches conserve the sectioned tissue through the collection of serial sections onto solid support and allow reimaging. These tissue libraries generated by Array Tomography or Automated Tape Collecting Ultramicrotomy can be screened at low resolution to target high resolution SEM. This is particularly useful if a structure of interest is rare or has been predetermined by correlated light microscopy, which can assign molecular, dynamic and functional information to an ultrastructure. As such approaches require bridging mm to nm scales, they rely on tissue trimming at different stages of sample processing. Relocation is facilitated by endogenous or exogenous landmarks that are visible by several imaging modalities, combined with appropriate registration strategies that allow overlaying images of various sources. Here, we discuss the opportunities of using multi-shot serial sectioning SEM approaches, as well as suitable trimming and registration techniques, to slim down the high-resolution imaging volume to the actual structure of interest and hence facilitate ambitious targeted volume SEM projects.

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