肿瘤诱导血管生成的三维CA模型

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摘要翻译：
肿瘤诱导的血管生成是指从附近已存在的亲本血管中形成新芽。在计算上，肿瘤诱导的血管生成可以用细胞自动机(CA)和偏微分方程等方法来模拟。本研究利用三维细胞自动机模型来模拟血管生成过程是一种现实的生理学方法。CA技术使用各种邻域，如Von-Neumann邻域、Moore邻域和Margolus邻域。在我们的模型中，Von-Neumann邻域被用来描述一些重要的化学和非化学肿瘤血管生成因子，如血管内皮生长因子、内皮细胞、O2、细胞外基质、纤维连接蛋白等的分布，Moore邻域被用来描述基质金属蛋白酶的分布。在体内肿瘤环境中，各因子在细胞外基质中分布不均。这些化学和非化学因子的分布取决于它们的来源、性质和功能。为了保持与生物肿瘤环境的相似性，我们相应地制定了化学和非化学因素的初始分布。我们已经用这个初始分布在MATLAB中开始了仿真。发芽的数量在一次运行到另一次运行中随机变化。我们观察到，在每个模拟中，芽不是来自相同的位置。芽苗对VEGF和纤维连接蛋白浓度有较高的敏感性。sVEGFR-1总是试图倒退萌芽。当两个或更多的芽靠近时，它们相互融合导致吻合。足够数量的尖端细胞可引起向肿瘤的萌发。
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英文标题：
《3D CA model of tumor-induced angiogenesis》
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作者：
Monjoy Saha, Amit Kumar Ray, Swapan Kumar Basu
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最新提交年份：
2020
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分类信息：

一级分类：Quantitative Biology        数量生物学
二级分类：Other Quantitative Biology        其他定量生物学
分类描述：Work in quantitative biology that does not fit into the other q-bio classifications
不适合其他q-bio分类的定量生物学工作
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一级分类：Computer Science        计算机科学
二级分类：Computational Engineering, Finance, and Science        计算工程、金融和科学
分类描述：Covers applications of computer science to the mathematical modeling of complex systems in the fields of science, engineering, and finance. Papers here are interdisciplinary and applications-oriented, focusing on techniques and tools that enable challenging computational simulations to be performed, for which the use of supercomputers or distributed computing platforms is often required. Includes material in ACM Subject Classes J.2, J.3, and J.4 (economics).
涵盖了计算机科学在科学、工程和金融领域复杂系统的数学建模中的应用。这里的论文是跨学科和面向应用的，集中在技术和工具，使挑战性的计算模拟能够执行，其中往往需要使用超级计算机或分布式计算平台。包括ACM学科课程J.2、J.3和J.4（经济学）中的材料。
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英文摘要：
  Tumor-induced angiogenesis is the formation of new sprouts from preexisting nearby parent blood vessels. Computationally, tumor-induced angiogenesis can be modeled using cellular automata (CA), partial differential equations, etc. In this present study, a realistic physiological approach has been made to model the process of angiogenesis by using 3D CA model. CA technique uses various neighborhoods like Von-Neumann neighborhood, Moore neighborhood, and Margolus neighborhood. In our model Von-Neumann neighborhood has used for distribution of some significant chemical and non-chemical tumor angiogenic factors like vascular endothelial growth factor, endothelial cells, O2, extracellular matrix, fibronectin, etc., and Moore neighborhood is used for distribution of matrix metalloproteinase. In vivo tumor environment all the factors are not distributed equally in the extracellular matrix. Distributions of those chemical and nonchemical factors depend on their source, nature and function. To keep similarity with the biological tumor environment, we have formulated initial distributions of the chemical and non-chemical factors accordingly. We have started the simulation in MATLAB with this initial distribution. Number of sprouts randomly varies from one run to another. We observed that sprouts are not originating from the same locations in each simulation. A sprout has high sensitivity of VEGF and fibronectin concentrations. sVEGFR-1 always tries to regress the sprout. When two or more sprouts come closer, they merge with each other leading to anastomosis. Sufficient number of tip cells may cause sprout towards tumor.
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PDF链接：
https://arxiv.org/pdf/2005.12852

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关键词：neighborhood distribution Quantitative Applications Mathematical 诱导 生成 chemical induced neighborhood