Physical Science in Oncology Center, Princeton Institute for the Science and Technology of Materials, Princeton University, Princeton, NJ 08544, USA.
Phys Biol. 2012 Jun;9(3):036009. doi: 10.1088/1478-3975/9/3/036009. Epub 2012 Jun 8.
Biopolymer networks are of fundamental importance to many biological processes in normal and tumorous tissues. In this paper, we employ the panoply of theoretical and simulation techniques developed for characterizing heterogeneous materials to quantify the microstructure and effective diffusive transport properties (diffusion coefficient D(e) and mean survival time τ) of collagen type I networks at various collagen concentrations. In particular, we compute the pore-size probability density function P(δ) for the networks and present a variety of analytical estimates of the effective diffusion coefficient D(e) for finite-sized diffusing particles, including the low-density approximation, the Ogston approximation and the Torquato approximation. The Hashin-Strikman upper bound on the effective diffusion coefficient D(e) and the pore-size lower bound on the mean survival time τ are used as benchmarks to test our analytical approximations and numerical results. Moreover, we generalize the efficient first-passage-time techniques for Brownian-motion simulations in suspensions of spheres to the case of fiber networks and compute the associated effective diffusion coefficient D(e) as well as the mean survival time τ, which is related to nuclear magnetic resonance relaxation times. Our numerical results for D(e) are in excellent agreement with analytical results for simple network microstructures, such as periodic arrays of parallel cylinders. Specifically, the Torquato approximation provides the most accurate estimates of D(e) for all collagen concentrations among all of the analytical approximations we consider. We formulate a universal curve for τ for the networks at different collagen concentrations, extending the work of Torquato and Yeong (1997 J. Chem. Phys. 106 8814). We apply rigorous cross-property relations to estimate the effective bulk modulus of collagen networks from a knowledge of the effective diffusion coefficient computed here. The use of cross-property relations to link other physical properties to the transport properties of collagen networks is also discussed.
生物聚合物网络对于正常组织和肿瘤组织中的许多生物学过程都具有重要意义。在本文中,我们利用为描述非均匀材料而开发的各种理论和模拟技术,定量研究了不同胶原浓度下 I 型胶原网络的微观结构和有效扩散输运性质(扩散系数 D(e)和平均生存时间 τ)。特别是,我们计算了网络的孔径概率密度函数 P(δ),并提出了各种有限尺寸扩散粒子有效扩散系数 D(e)的分析估计,包括低密度近似、Ogston 近似和 Torquato 近似。有效扩散系数 D(e)的 Hashin-Strikman 上限和平均生存时间 τ 的孔径下限被用作测试我们的分析近似和数值结果的基准。此外,我们将球体悬浮液中布朗运动模拟的有效首次通过时间技术推广到纤维网络的情况,并计算了相关的有效扩散系数 D(e)和平均生存时间 τ,后者与磁共振弛豫时间有关。我们对 D(e)的数值结果与简单网络微观结构的分析结果非常吻合,例如平行圆柱的周期性阵列。具体而言,在我们考虑的所有分析近似中,Torquato 近似为所有胶原浓度提供了 D(e)最准确的估计。我们为不同胶原浓度下的网络制定了 τ 的通用曲线,扩展了 Torquato 和 Yeong(1997 J. Chem. Phys. 106 8814)的工作。我们利用严格的交叉性质关系,从这里计算的有效扩散系数来估计胶原网络的有效体模量。还讨论了利用交叉性质关系将其他物理性质与胶原网络的输运性质联系起来的问题。