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.
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