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Figure 7.6 Identification of fiber type and extracellular matrix proteins. Left, a section of
a monkey muscle is shown labeled for laminin (green) and slow myosin (red). Right,
masks developed by the Skeletal Muscle Algorithm include the thick membrane mask
(blue), which encompasses the extracellular matrix. Fiber ID#s are also shown.
automated method using CyteSeer ® (researchers using the different methods
were blinded to the results from the other method during sample
processing). Virtually identical results were obtained between the manual
and automated procedures for the two species (as
20% of the monkey fibers
were positive for slow-type myosin and 10% of the swine fibers were pos-
itive for myosin IIA). Examples of the fiber identification by CyteSeer ® for
several monkey samples are shown in Fig. 7.7 , which illustrate that the auto-
mated method is relatively accurate for muscle sections that vary in labeling,
background intensity, and structural complexity.
6.1.3 Analysis of the effects of denervation
In another experiment, the automated procedure was used to quantify the
effect of denervation on skeletal muscle size. Denervation leads to inactivity
and atrophy of muscle fibers, with a concomitant reduction in CSA, and
occurs with aging and in the context of neuronal damage, particularly spinal
cord injury ( Kostrominova et al., 2005 ). To test the ability of automated
methods for quantifying effects of denervation, muscle sections from control
and 2-month experimentally denervated rat EDL muscle were labeled with
laminin, photographed, and the images analyzed via the automated algo-
rithm. Note that the algorithm reported an overall decrease in fiber size
of approximately 60% for the sample set ( Fig. 7.8 ), which is consistent with
expectations for this intervention.
In a related experiment, a muscle section was obtained from SOD1-null
mice that show significantly accelerated age-related denervation of skeletal
muscle. Muscle was labeled for laminin, and for NCAM, a protein that is
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