Zeiss LSM 880, Руководство по эксплуатации

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3
rd
dimension
In addition to the possibility to observe a single plane (or
slice) of a thick specimen in good contrast, optical section-
ing allows a great number of slices to be cut and recorded at
different Z-planes of the specimen, with the specimen being
moved along the optical axis by controlled increments. The
result is a 3D data set, which provides information about
the spatial structure of the object. The quality and accuracy
of this information depend on the thickness of the slice
and on the spacing between successive slices (optimum
scanning rate in Z direction = 0.5x the slice thickness). By
computation, various aspects of the object can be gener-
ated from the 3D data set (3D reconstruction, sections of
any spatial orientation, stereo pairs etc.). Figure 4 shows a
3D reconstruction computed from a 3D data set.
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Fig. 4 3D projection reconstructed from 108 optical slices of a
three-dimensional data set of epithelium cells of a lacrimal gland.
Actin filaments of myoepithelial cells marked with BODIPY-FL
phallacidin (green), cytoplasm and nuclei of acinar cells with
ethidium homodimer-1 (red).
Fig. 5 Gallery of a time series experiment with Kaede-transfected
cells. By repeated activation of the Kaede marker (green-to-red
color change) in a small cell region, the entire green fluorescence is
converted step by step into the red fluorescence.
Timeseries
A further field of importance is the investigation of living
specimens that show dynamic changes even in the range of
microseconds. Here, the acquisition of time-resolved confo-
cal image series (known as time series) provides a possibility
of visualizing and quantifying the changes (figure 5).
SpectralImaging
The detection of spectral information becomes necessary
when overlapping emission signals of multiple marked spec-
imen are to be separated. By means of a special Multichan-
nel PMT it is possible to record the spectral information of
the fluorescent signal. Together with advanced computation
methods one can separate signals which almost overlap
completely and only differ in their spectral signature. The
method behind is called ‘’linear unmixing’’ and allows, for
example, several fluorescent proteins to be distinguished.
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