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

Lang N, Münster S, Metzner C, Krauß P, Schürmann S, Lange J, Aifantis KE, Friedrich O, Fabry B (2013)

Publication Language: English

Publication Status: Published

Publication Type: Journal article, Original article

Publication year: 2013

Journal

Book Volume: 105

Pages Range: 1967-75

Journal Issue: 9

URI: http://www.sciencedirect.com/science/article/pii/S0006349513010862

DOI: 10.1016/j.bpj.2013.09.038

Open Access Link: http://ac.els-cdn.com/S0006349513010862/1-s2.0-S0006349513010862-main.pdf?_tid=d14edbd0-7194-11e5-beb9-00000aab0f6b&acdnat=1444732148_14af0d6c424977dee6f20622fc884990

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 with the square root of the visible network fraction. We experimentally verify the validity of this approach by comparing our estimates with data obtained using confocal fluorescence microscopy, which represents the full structure of the network. As an important application, we investigate the pore size dependence of collagen and fibrin networks on protein concentration. We find that the pore size decreases with the square root of the concentration, consistent with a total fiber length that scales linearly with concentration.

Authors with CRIS profile

Involved external institutions

Aristotle University of Thessaloniki Greece (GR)

How to cite

APA:

Lang, N., Münster, S., Metzner, C., Krauß, P., Schürmann, S., Lange, J.,... Fabry, B. (2013). Estimating the 3D pore size distribution of biopolymer networks from directionally biased data. Biophysical Journal, 105(9), 1967-75. https://dx.doi.org/10.1016/j.bpj.2013.09.038

MLA:

Lang, Nadine, et al. "Estimating the 3D pore size distribution of biopolymer networks from directionally biased data." Biophysical Journal 105.9 (2013): 1967-75.

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