TISSUE KINETICS MODEL FOR ARTIFICIAL CELL/TISSUE ARRAY CONSTRUCTS

人工细胞/组织阵列构建的组织动力学模型

• 批准号: 7723129
• 负责人: RICHARD H. SIDERITS
• 金额: $ 0.05万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7723129
• 关键词: Area; Biological; Biological Process; Breast Cancer Cell; Cell Communication; Cell Cycle; Cell Cycle Kinetics; Cell Differentiation process; Cells; Class; Computer Retrieval of Information on Scientific Projects Database; Computers; Data; Data Set; Development; Environment; Equilibrium; Estrogens; Funding; Grant; Growth; Guidelines; Immune response; Individual; Institution; Internet; Invasive; Java; Kinetics; Language; Literature; Malignant Neoplasms; Medical; Microgravity; Modeling; Normal Cell; Numbers; Phase; Process; Progesterone Receptors; Programming Languages; Pythons; Radiation therapy; Range; Relative (related person); Research; Research Personnel; Resources; Simulate; Source; Structure; System; Time; Tissue Microarray; Tissues; United States National Institutes of Health; Writing; base; concept; malignant breast neoplasm; neoplastic; platform-independent; programs; radiation effect; receptor density; three-dimensional modeling; virtual

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Describe basic parameters needed to create a quadri-dimmensional model for autonomously growing virtual tissue array constructs. These guidelines and variables would simulate biological process and structure while remaining flexible and extensible to a broad range of potential research applications. The constructs would model quadri-dimensional growth kinetics at the tissue rather than cellular level taking advantage of basic principles of cycle kinetics. The model should conform to our basic concept of both normal and abnormal growth kinetics including the presence or absence of biophyisologic modifiers. This kinetic model could model neoplastic and non-neoplastic tissue for example Intraductal and Invasive breast cancer as well as the immune response to cancer. The choice of programming language would be either JAVA and/or PYTHON which are both extensible object oriented platform independent high level programming languages which could support the eventual development of an internet accessible user interface to the interactive model. The dataset would be dynamically written to a PYTHON enabled rendering program (trueSapce V6.6) which could create a three dimensional model of the construct as it evolves. An outline of the program flow follows: An instance of a cell class would be instantiated through an object oriented language. The first cell would be assigned to spatial coordinates 0,0,0. The time of instantiation would be logged as an instance variable. After a given period of time (checked against the computer clock) the cell is given an opportunity to enter the proliferative phase of the cell cycle. The relative timing of this process would simulate actual cell cycle kinetic data referenced in the medical literature. If, for example, the cell does enter the next phase of the cell cycle and ultimately completes its transit time through the cycle then a second cell object would be instantiated and assigned to an adjacent unoccupied coordinate. The coordinate system could be pre-configured (to simulate no growth areas or tissue structures), and could also use a polar coordinate system. The likelihood of entering, the duration of transit and the ultimate exit from the individual cell cycle phases would be guided by the presence or absence of instance variables. For example the presence of estrogen or progesterone receptor on a breast cancer cell could be represented by a variable with a real number from 0.0-1.0 with higher values representing increased density of receptor. Not only could biological parameters be set in this way but calls to cell cycle specific functions to regulate transit through the cell cycle based on the presence or absence of markers could govern individual cell-objects though the cell cycle phases based on a balance of variables representing both positive and negative cell cycle modifiers. Subclasses of the cell object could be instantiated to represent normal cells possibly modeling an immune response to cell subclasses which represent tumorous cells. In this way it might be possible to simulate cell interactions (both normal and abnormal) with virtual chemotherapeutic compounds (with known cell cycle effects), radiation therapy or even microgravity environments. The same approach could be applied to cell differentiation where time dependent variables or instance variables would trigger calls to cell differentiation functions.

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 描述创建四维模型所需的基本参数 自主生长的虚拟组织阵列结构。这些指南和 变量将模拟生物过程和结构，而不是 灵活且可扩展到广泛的潜在研究 申请。 这些构造将模拟组织中的四维生长动力学 而不是在细胞水平上利用循环的基本原理 运动学。模型应该符合我们的基本概念，即正常和 异常生长动力学包括存在或不存在 生物生理改良剂。 该动力学模型可以模拟肿瘤组织和非肿瘤组织 导管内和浸润性乳腺癌以及免疫 对癌症的反应。 编程语言的选择将是Java和/或Python语言 两者都是可扩展的面向对象的独立于平台的高层 可以支持最终开发的 可通过互联网访问的交互模型的用户界面。 数据集将被动态写入启用了Python的渲染 程序(trueSapce V6.6)，该程序可以创建 随着它的发展，这个结构。 以下是计划流程的概要： 单元格类的实例将通过对象实例化 定向语言。第一个像元将被分配到空间坐标 0，0，0。实例化的时间将被记录为实例变量。 在给定的时间段(对照计算机时钟)之后，细胞 有机会进入细胞周期的增殖期。 这个过程的相对时序将模拟实际的细胞周期 医学文献中引用的动力学数据。例如，如果 细胞确实进入细胞周期的下一个阶段，并最终完成 其通过周期的传输时间，则第二个单元格对象将是 实例化并分配给相邻的未占用坐标。这个 可以预先配置坐标系(以模拟无增长区域或 组织结构)，并且还可以使用极坐标系统。 进入的可能性、过境的持续时间和最终的离开 来自各个细胞周期阶段的信号将由存在或 没有实例变量。例如，雌激素或 乳腺癌细胞上的孕激素受体可以由一个 变量，实数介于0.0-1.0之间，较大的值表示 受体密度增加。不仅可以设置生物参数 通过这种方式，但调用细胞周期特定的功能来调节转运 通过细胞周期的标记的存在或不存在可以 通过细胞周期阶段控制单个细胞对象 代表正、负细胞周期的变量平衡 修饰符。 单元格对象的子类可以实例化以表示正常 细胞可能模拟对细胞亚类的免疫反应 代表肿瘤细胞。这样，就有可能模拟出 细胞与虚拟化疗药物的相互作用(包括正常和异常) 化合物(已知对细胞周期的影响)、放射治疗，甚至 微重力环境。 同样的方法也可以应用于细胞分化，因为时间 依赖变量或实例变量将触发对单元格的调用 分化功能。