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血管形态的动态适应。

Dynamic adaption of vascular morphology.

机构信息

Department of Micro- and Nanotechnology, Technical University of Denmark Lyngby, Denmark.

出版信息

Front Physiol. 2012 Oct 2;3:390. doi: 10.3389/fphys.2012.00390. eCollection 2012.

Abstract

The structure of vascular networks adapts continuously to meet changes in demand of the surrounding tissue. Most of the known vascular adaptation mechanisms are based on local reactions to local stimuli such as pressure and flow, which in turn reflects influence from the surrounding tissue. Here we present a simple two-dimensional model in which, as an alternative approach, the tissue is modeled as a porous medium with intervening sharply defined flow channels. Based on simple, physiologically realistic assumptions, flow-channel structure adapts so as to reach a configuration in which all parts of the tissue are supplied. A set of model parameters uniquely determine the model dynamics, and we have identified the region of the best-performing model parameters (a global optimum). This region is surrounded in parameter space by less optimal model parameter values, and this separation is characterized by steep gradients in the related fitness landscape. Hence it appears that the optimal set of parameters tends to localize close to critical transition zones. Consequently, while the optimal solution is stable for modest parameter perturbations, larger perturbations may cause a profound and permanent shift in systems characteristics. We suggest that the system is driven toward a critical state as a consequence of the ongoing parameter optimization, mimicking an evolutionary pressure on the system.

摘要

血管网络的结构不断适应以满足周围组织需求的变化。大多数已知的血管适应机制基于对局部刺激(如压力和流量)的局部反应,而这反过来又反映了周围组织的影响。在这里,我们提出了一个简单的二维模型,作为一种替代方法,将组织建模为具有间隔分明的流动通道的多孔介质。基于简单的、生理上合理的假设,流动通道结构会进行调整,以达到为组织的所有部分提供供应的配置。一组模型参数唯一地确定模型动态,我们已经确定了性能最佳模型参数的区域(全局最优)。该区域在参数空间中被参数值较差的模型包围,并且这种分离的特征是相关适应度景观中的陡峭梯度。因此,似乎最优参数集倾向于接近临界转变区域。因此,尽管对于适度的参数扰动,最优解是稳定的,但较大的扰动可能会导致系统特征发生深刻和永久的转变。我们认为,由于正在进行的参数优化,系统被推向临界状态,模拟了对系统的进化压力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c77/3462325/430ea9dcb246/fphys-03-00390-g001.jpg

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