Biomedical Engineering Reference
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(second panel from the top). We now have a choice. Are the B cells initially TdT
and
then negative or is it the other way around? Perhaps, it is even more complicated.
Perhaps, the progression begins with TdT
þ
, becomes negative, and then becomes
TdT
þ
again. Since our data sets no longer contain the string of time, we must resort to
using other information outside this data set to infer this sequence. The best that we can
do is to assume that the data from the literature is relevant to our data set. Most of this
work was done in the late 1980s by Loken and Terstappen [2, 3]. Using a number of
techniques, Loken and Terstappen showed that TdTand CD34 were lost early in B-cell
differentiation. We now need to use some of that information to create our B-cell
progression model.
We choose a step-down type of parameter profile and then let themodel optimize so
that the frequency is as uniform as possible (Figure 14.9d). As soon as the system
shows the final solution, we can see something very interesting. Notice that CD19 is
no longer constant. Very early B cells have less CD19. Also notice that there is some
SSC structure during this phase as well. The fact that CD19 is lower for early B cells
also happens to be a well-published observation and thus serves as confirmation that
we are on the right track.
þ
14.7 TRADITIONAL GATING STRATEGIES AND
METAINFORMATION
Before continuing on, it is important to discuss the relevance of this metainformation
that we are using in our model definition. You might be tempted to say that traditional
gating techniques do not make this assumption and therefore are not as dependent on
these initial assumptions. The truth is, however, that when an experienced cytome-
trists looks at a histogram that has TdTas a parameter, theywill impose this relation on
the data to understand what is going on with the sample. If they did not, all that they
would see would be dots. Those of you who are new to cytometry know exactly what I
mean. Experienced cytometerists see patterns in the data that are not really there. They
can do this because they have been taught all these important relations and their minds
automatically connect all the dots with arrows.
14.7.1 CD10 Three-Level Parameter Profile
Let us now examine CD10 (Figure 14.10a). As soon as we examine the dot patterns for
CD10, we observe that CD10 is positive early in B-cell differentiation. The crossword
puzzle is still a great analogy for what is happening.With a crossword puzzle, when you
put down a word, you are providing additional information that is important in finding
the answers to the other, more complicated clues. TdT is providing us with information
about early CD10. Even with this information, however, we are faced with another
decision. After the early B-cell state, CD10 forms two clusters with intermediate and
negative intensities. Again, we are faced with a lack of information in the data set and
must resort to the literature to help us decide what would be the correct parameter
profile to use. Loken and Terstappen showed that CD10 has high intensity early in the
lineage, drops to an intermediate intensity, and then becomes negative.
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