Estimating the 3D pore size distribution of biopolymer networks from directionally biased data.

ABSTRACT: The pore size of biopolymer networks governs their mechanical properties and strongly impacts the behavior of embedded cells. Confocal reflection microscopy and second harmonic generation microscopy are widely used to image biopolymer networks; however, both techniques fail to resolve vertically oriented fibers. Here, we describe how such directionally biased data can be used to estimate the network pore size. We first determine the distribution of distances from random points in the fluid phase to the nearest fiber. This distribution follows a Rayleigh distribution, regardless of isotropy and data bias, and is fully described by a single parameter--the characteristic pore size of the network. The bias of the pore size estimate due to the missing fibers can be corrected by multiplication w

SUBMITTER: Lang NR 

PROVIDER: S-EPMC3824714 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature