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肺纤维化中组织硬化相关生长的网络模型。

A network model of correlated growth of tissue stiffening in pulmonary fibrosis.

作者信息

Oliveira Cláudio L N, Bates Jason H T, Suki Béla

机构信息

Department of Biomedical Engineering, Boston University, Boston, MA 02215.

Department of Medicine, University of Vermont, Burlington, VT 05405.

出版信息

New J Phys. 2014 Jun 26;16(6):065022. doi: 10.1088/1367-2630/16/6/065022.

Abstract

During the progression of pulmonary fibrosis, initially isolated regions of high stiffness form and grow in the lung tissue due to collagen deposition by fibroblast cells. We have previously shown that ongoing collagen deposition may not lead to significant increases in the bulk modulus of the lung until these local remodeled regions have become sufficiently numerous and extensive to percolate in a continuous path across the entire tissue [Bates . 2007 . 617]. This model, however, did not include the possibility of spatially correlated deposition of collagen. In the present study, we investigate whether spatial correlations influence the bulk modulus in a two-dimensional elastic network model of lung tissue. Random collagen deposition at a single site is modeled by increasing the elastic constant of the spring at that site by a factor of 100. By contrast, correlated collagen deposition is represented by stiffening the springs encountered along a random walk starting from some initial spring, the rationale being that excess collagen deposition is more likely in the vicinity of an already stiff region. A combination of random and correlated deposition is modeled by performing random walks of length from randomly selected initial sites, the balance between the two processes being determined by . We found that the dependence of bulk modulus, (), on both and the fraction of stiff springs, , can be described by a strikingly simple set of empirical equations. For < 0.3, () exhibits exponential growth from its initial value according to () ≈ (2)[1 + ln()], where = 0.994 ± 0.024 and = 0.54 ± 0.026. For intermediate concentrations of stiffening, 0.3 ≤ ≤ 0.8, another exponential rule describes the bulk modulus as () = 4[ ( - )], where and are parameters that depend on . For > 0.8, () is linear in and independent of , such that () = 100 - 100 (1 - ), where = 2.857. For small concentrations, the physiologically most relevant regime, the forces in the network springs are distributed according to a power law. When = 0.3, the exponent of this power law increases from -4.5, when = 1, and saturates to about -2, as increases above 40. These results suggest that the spatial correlation of collagen deposition in the fibrotic lung has a strong effect on the rate of lung function decline and on the mechanical environment in which the cells responsible for remodeling find themselves.

摘要

在肺纤维化进展过程中,由于成纤维细胞沉积胶原蛋白,肺组织中最初会形成孤立的高硬度区域并不断扩大。我们之前已经表明,持续的胶原蛋白沉积可能不会导致肺的体积模量显著增加,直到这些局部重塑区域变得足够多且广泛,能够在整个组织中形成连续路径渗透 [贝茨,2007,617]。然而,该模型并未考虑胶原蛋白空间相关沉积的可能性。在本研究中,我们在肺组织的二维弹性网络模型中研究空间相关性是否会影响体积模量。通过将单个位点处弹簧的弹性常数提高100倍来模拟单个位点的随机胶原蛋白沉积。相比之下,相关胶原蛋白沉积通过从某个初始弹簧开始沿着随机游走使遇到的弹簧变硬来表示,其基本原理是在已经变硬的区域附近更有可能发生过量胶原蛋白沉积。通过从随机选择的初始位点进行长度为 的随机游走对随机和相关沉积的组合进行建模,这两个过程之间的平衡由 决定。我们发现,体积模量 () 对 和硬弹簧比例 的依赖性可以用一组非常简单的经验方程来描述。对于 < 0.3,() 根据 () ≈ (2)[1 + ln()] 从其初始值呈现指数增长,其中 = 0.994 ± 0.024 且 = 0.54 ± 0.026。对于中等程度的硬化浓度,0.3 ≤ ≤ 0.8,另一个指数规则将体积模量描述为 () = 4[ ( - )],其中 和 是依赖于 的参数。对于 > 0.8,() 与 呈线性关系且与 无关,使得 () = 100 - 100 (1 - ),其中 = 2.857。对于低浓度,即生理上最相关的值域,网络弹簧中的力根据幂律分布。当 = 0.3 时,该幂律的指数从 = 1 时的 -4.5 增加,并在 增加到 40 以上时饱和到约 -2。这些结果表明,纤维化肺中胶原蛋白沉积的空间相关性对肺功能下降速率以及负责重塑的细胞所处的力学环境有强烈影响。

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