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Electron Microscope Tomography and Single-particle Reconstruction01:07

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Transmission electron microscopy (TEM) can be used to determine the 3D structure of biological samples with the help of techniques such as electron microscope tomography and single-particle reconstruction. While single-particle reconstruction can examine macromolecules and macromolecular complexes in vitro conditions only, tomography permits the study of cell components or small cells in vivo.
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In 1931, physicist Ernst Ruska—building on the idea that magnetic fields can direct an electron beam just as lenses can direct a beam of light in an optical microscope—developed the first prototype of the electron microscope. This development led to the development of the field of electron microscopy. In the transmission electron microscope (TEM), electrons are produced by a hot tungsten element and accelerated by a potential difference in an electron gun, which gives them up to 400 keV in...

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SynapticDB, effective web-based management and sharing of data from serial section electron microscopy.

Bitao Shi1, Jennifer Bourne, Kristen M Harris

  • 1Center for Learning and Memory, The University of Texas at Austin, University Station C7000, Austin, TX 78712-0805, USA.

Neuroinformatics
|December 25, 2010
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Summary

Serial section electron microscopy (ssEM) generates vast ultrastructural data. SynapticDB is a web-based system for managing, analyzing, and sharing this crucial neuroscience data to advance brain circuitry research.

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Area of Science:

  • Neuroscience
  • Cell Biology
  • Bioinformatics

Background:

  • Serial section electron microscopy (ssEM) is a powerful tool for studying synaptic structure and plasticity.
  • The large volume of data generated by ssEM exceeds individual laboratory capacity, necessitating data sharing.
  • Understanding neural circuitry and function relies on comprehensive analysis of ultrastructural data.

Purpose of the Study:

  • To introduce SynapticDB, a web-based system for managing ssEM data.
  • To facilitate the cataloging, analysis, and sharing of experimental data from ssEM.
  • To support future meta-analyses and discoveries in neuroscience.

Main Methods:

  • Development of SynapticDB, a web-based management system.
  • Implementation of a library with check-in, check-out, and experimental tracking.
  • Creation of flexible spreadsheet templates for data collection and analysis.
  • Integration of experimental note management and dynamic PDF forms for progress tracking.

Main Results:

  • SynapticDB provides a centralized platform for ssEM data.
  • Templates guide consistent data collection and quantitative analysis.
  • Tracking mechanisms ensure data integrity and association with images/analyses.
  • Flexible template options cater to various user needs.

Conclusions:

  • SynapticDB enables efficient management and sharing of critical ssEM data.
  • The system supports standardized protocols and collaborative research.
  • Facilitates future meta-analyses for new discoveries in neural circuitry and plasticity.
  • Aids understanding of brain development, behavior, learning, memory, and neuropathology.