### 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.

Original language | English (US) |
---|---|

Pages (from-to) | 1967-1975 |

Number of pages | 9 |

Journal | Biophysical Journal |

Volume | 105 |

Issue number | 9 |

DOIs | |

State | Published - Nov 5 2013 |

Externally published | Yes |

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### ASJC Scopus subject areas

- Biophysics

### Cite this

*Biophysical Journal*,

*105*(9), 1967-1975. https://doi.org/10.1016/j.bpj.2013.09.038

**Estimating the 3D pore size distribution of biopolymer networks from directionally biased data.** / Lang, Nadine R.; Münster, Stefan; Metzner, Claus; Krauss, Patrick; Schürmann, Sebastian; Lange, Janina; Aifantis, Katerina E; Friedrich, Oliver; Fabry, Ben.

Research output: Contribution to journal › Article

*Biophysical Journal*, vol. 105, no. 9, pp. 1967-1975. https://doi.org/10.1016/j.bpj.2013.09.038

}

TY - JOUR

T1 - Estimating the 3D pore size distribution of biopolymer networks from directionally biased data

AU - Lang, Nadine R.

AU - Münster, Stefan

AU - Metzner, Claus

AU - Krauss, Patrick

AU - Schürmann, Sebastian

AU - Lange, Janina

AU - Aifantis, Katerina E

AU - Friedrich, Oliver

AU - Fabry, Ben

PY - 2013/11/5

Y1 - 2013/11/5

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84887374919&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84887374919&partnerID=8YFLogxK

U2 - 10.1016/j.bpj.2013.09.038

DO - 10.1016/j.bpj.2013.09.038

M3 - Article

C2 - 24209841

AN - SCOPUS:84887374919

VL - 105

SP - 1967

EP - 1975

JO - Biophysical Journal

JF - Biophysical Journal

SN - 0006-3495

IS - 9

ER -