Multilamellar Vesicular Clusters of Phosphatidylcholine and Their Sensitivity to Spectrin: A Study by Fractal Analysis

Many length scales surface fractality in monomolecular films of whole myelin lipids and proteins

“…Fractality has been invoked in the Weld of membrane biophysics in connection with a number of phenomena ranging from the geometry of self-aggregated vesicles (Lahiri et al, 1998), the folding of the membrane in 3D space (Paumgartner et al, 1981), the kinetics of channel conductance (Hoop and Peng, 2000), experimentally observed lipid domain topography (Miller et al, 1986) and its simulation (Fogedby et al, 1987), and lateral surface defects or diVusion (Nonnenmacher, 1989;Pink et al, 1991). In connection with lipid domains the focus has traditionally been on the determination of percolation thresholds of bilayer domains at thermotropic phase transition points through Xuorescence recovery after photobleaching (FRAP) experiments (Almeida and Vaz, 1995).…”

Onset of Percolation and Fractal Classification Scheme for Multilamellar Lipid Vesicles

“…For DMPC/cholesterol an additional change in porosity was observed. The retention of porosity of the DMPC/spectrin in spite of perturbation showed the capability of this membrane interactive cytoskeletal protein to confer more stability (31) to the clusters of DMPC vesicles. Its consequence may be understood following Jo and Bogg's work (32) showing K ϩ -ion induced aggregation of acidic lipid vesicles caused by myelin basic protein (MBP).…”

“…For any scale p could be measured from the fraction of nonzero pixels. A log-log plot of the number of occupied pixels versus the scale factor provided the measure of the mass fractal dimension (12). The porosity could be determined by first segmenting the topologically closed image contours and then finding out the average fraction of unoccupied sites.…”

“…First, the gray image (512 ϫ 512 pixels) was subjected to thresholding. The resultant binary image I for which the matrix elements can be either 1 or 0 was resized using a blockwise pixel compression algorithm (12) to a series of binary images each having different scales of compression. For any scale p could be measured from the fraction of nonzero pixels.…”

“…Digitization and processing of microscopically obtained images have provided important information about the structure of different bioorganelles and suborganelles and their fractal properties (8 -11). However, there are only a few reports on the characterization of vesicular clusters using digitized image processing (12,13). Considering the possible randomness that might be associated with both the formation and configuration of such clusters, the present paper makes an attempt to look for a different scheme to find some systematic elements in the pattern formation process.…”