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Number, Spatial distribution |
Nearest Neighbor investigates the 3D spatial arrangement of objects such as cells within thick sections of a region of interest. |
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Thick |
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Any |
Stereo Investigator records the (X,Y,Z) coordinates of "parent cells" and of neighboring "offspring cells." From this coordinate data, Stereo Investigator calculates the nearest neighbor distance for each parent cell and the nearest neighbor distributions for the region of interest.
The Nearest Neighbor analysis is performed within the context of a systematic random sampling of the tissue; this means that a counting frame size and XY grid spacing between counting frames must be defined for each specimen.
Once the Nearest Neighbor probe is started,Stereo Investigator drives the stage to each counting frame location and displays a standard counting frame.
See Optical Fractionator prerequisites.
Place a representative slide under the microscope, navigate to the region of interest using a low magnification lens, place a reference point.
The magnification should be high enough to clearly distinguish individual cells, but low enough to display each cell’s nearest neighbor in the same field of view.
Displaying the nearest neighbor be in the same field of view is not a requirement, but it will save significant time in the survey.
Click Probes>Define Counting Frame and set the size and location of the counting frame.
If the total number of counting frames is too large, use larger values for the X and Y SURS Grid Size.
(Guard Zone height * 2) + Optical Disector Height <= minimum Mounted Thickness.
If a new offspring cell is further away from the parent cell than a previously marked offspring cell, the radius of the circle does not change.
The radius of the circle changes as you focus up and down because it represents a sphere around the parent cell.
The offspring cells do not need to be located within the counting frame, which is why the counting frame is not displayed.
To see the number of markers counted:
OR
Do not change these values for a new section in the same specimen.
The counting parameters can vary across specimens, but they must remain the same for every section in a given specimen in order to extract valid CE data.
Typically each marker is used to represent one cell type. If an optical fractionator is being used to count multiple types of cells, a different marker type should be used to identify each cell type.
Displays the file name associated with this data set if the data has been saved to or read from a file.
Displays the data and time when the probe was completed.
Displays the name of the contour type that defines the region of interest over which the probe was implemented.
If a composite of several runs is being examined, Stereo Investigator displays the contour name used for the first run.
Number of sampling sites visited on all selected sections.
Area of the contour bounding the regions of interest or sum of areas (for composite of multiple optical fractionator runs).
Stereo Investigator calculates this area from the geometry of the bounding contour(s). This area can be compared to the area determined using the Cavalieri Probe.
Area of a single counting frame.
Thickness of the counting frames along the Z-axis.
Volume of a single counting frame.
X-axis width of each counting frame (in microns).
Y-axis height of each counting frame (in microns).
Represents the distance between counting frames (sampling sites) along the X-axis.
Represents the distance between counting frames (sampling sites) along the Y-axis.
Area of the region that is associated with each sampling step.
Value used for section thickness across all sections that were sampled.
Should be the minimum actual section thickness as measured by Stereo Investigator.
Number weighted mean of all sections measured by focusing at the top and bottom of the section.
This value should be relatively close to the Section Thickness.
Estimated population count determined by the selected series of optical fractionator runs.
Estimated population count determined by the selected series of optical fractionator runs, using for the section thickness value the number weighted section thickness.
Actual number of markers of this type counted during the optical fractionator survey.
These markers also represent the cells designated as parent cells during the Nearest Neighbor survey.
Raw data of the number of counts for each counting frame visited in each of the runs of the optical fractionator.
Raw data of the nearest neighbor distance for each designated parent cell. The X,Y,Z distance from each parent cell to all designated offspring cells is calculated, and the shortest of these distances reported for each cell.
CRF (cumulative relative frequency) is created from the raw data for the nearest neighbor distances (nnd). For each nnd on the X-axis, the graph shows a Y-value that indicates the probability that any particle would be that distance or less from another particle.
Example CRF Graph and Explanation
In this example of a CRF graph, the nearest neighbor distances are given on the x-axis. For this discussion, ignore the area delineated by the dotted lines. If you look at a given nnd, you can tell the probability that any particle would be that distance, or less (since it’s a cumulative frequency graph), from another particle. You can use the CRF graph to interpret the 3D arrangement of your particles. For instance, in this graph, there is a scarcity of short distances that indicates a relatively dispersed situation. If we compared this data set to another group of cells that were more clustered, the CRF would rise more rapidly because there are many short distances.
For examples with comparisons of CRF graphs of nnds, see Fig. 2 in Altered Spatial Arrangements (Schmitz et al.) or Fig. 4 in Spatial distribution and density... (Segal et al.). Apply caution when comparing CRF graphs that come from systems with different number of cells and/or different densities.
Shows the probability that a cell anywhere in the tissue will be located within a given distance of another cell (i.e., will have a particular nearest neighbor distance).
The maximum distance shows a probability of 1, since all cells will be within that distance or less of their nearest neighbor.
Diggle (1983). Statistical analysis of spatial point patterns. London, Academic Press.
Schmitz C, G. N., Hof PR, Boehringer R, Glaser J, Korr H. (2002). Altered spatial arrangement of layer V pyramidal cells in the mouse brain following prenatal low-dose X-irradiation. A stereological study using a novel three-dimensional analysis method to estimate the nearest neighbor distance distributions of cells in thick sections." Cereb Cortex 12(9): 954-960.
Segal D, S. C., Hof PR. (2008). Spatial distribution and density of oligodendrocytes in the cingulum bundle are unaltered in schizophrenia. Acta Neuropathol 117(4): 385-394.
Stereo Investigator 11 | MBF Bioscience Support Center | Downloads