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

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.

2021 ◽  
Author(s):  
Katya Giannios ◽  
Abhishek Chaurasia ◽  
Guillaume Thibault ◽  
Jessica L. Riesterer ◽  
Erin Stempinski ◽  
...  

Recent advances in Focused Ion Beam-Scanning Electron Microscopy (FIB- SEM) allows the imaging and analysis of cellular ultrastructure at nanoscale resolution, but the collection of labels and/or noise-free data sets has several challenges, often immutable. Reasons range from time consuming manual annotations, requiring highly trained specialists, to introducing imaging artifacts from the prolonged scanning during acquisition. We propose a fully unsupervised Noise Reconstruction and Removal Network for denoising scanning electron microscopy images. The architecture, inspired by gated recurrent units, reconstructs and removes the noise by synthesizing the sequential data. At the same time the fully un- supervised training guides the network in distinguishing true signal from noise and gives comparable results to supervised architectures. We demonstrate that this new network specialized on 3D electron microscopy data sets, achieves comparable and even better results than supervised networks.


Biology ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 51
Author(s):  
Michela Relucenti ◽  
Giuseppe Familiari ◽  
Orlando Donfrancesco ◽  
Maurizio Taurino ◽  
Xiaobo Li ◽  
...  

Several imaging methodologies have been used in biofilm studies, contributing to deepening the knowledge on their structure. This review illustrates the most widely used microscopy techniques in biofilm investigations, focusing on traditional and innovative scanning electron microscopy techniques such as scanning electron microscopy (SEM), variable pressure SEM (VP-SEM), environmental SEM (ESEM), and the more recent ambiental SEM (ASEM), ending with the cutting edge Cryo-SEM and focused ion beam SEM (FIB SEM), highlighting the pros and cons of several methods with particular emphasis on conventional SEM and VP-SEM. As each technique has its own advantages and disadvantages, the choice of the most appropriate method must be done carefully, based on the specific aim of the study. The evaluation of the drug effects on biofilm requires imaging methods that show the most detailed ultrastructural features of the biofilm. In this kind of research, the use of scanning electron microscopy with customized protocols such as osmium tetroxide (OsO4), ruthenium red (RR), tannic acid (TA) staining, and ionic liquid (IL) treatment is unrivalled for its image quality, magnification, resolution, minimal sample loss, and actual sample structure preservation. The combined use of innovative SEM protocols and 3-D image analysis software will allow for quantitative data from SEM images to be extracted; in this way, data from images of samples that have undergone different antibiofilm treatments can be compared.


Langmuir ◽  
2020 ◽  
Vol 36 (11) ◽  
pp. 2816-2822 ◽  
Author(s):  
Takashi Kakubo ◽  
Katsunori Shimizu ◽  
Akemi Kumagai ◽  
Hiroaki Matsumoto ◽  
Miki Tsuchiya ◽  
...  

2014 ◽  
Vol 254 (3) ◽  
pp. 109-114 ◽  
Author(s):  
C. KIZILYAPRAK ◽  
J. DARASPE ◽  
B.M. HUMBEL

PLoS ONE ◽  
2013 ◽  
Vol 8 (2) ◽  
pp. e57405 ◽  
Author(s):  
Bohumil Maco ◽  
Anthony Holtmaat ◽  
Marco Cantoni ◽  
Anna Kreshuk ◽  
Christoph N. Straehle ◽  
...  

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