This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.Describe basic parameters needed to create a quadri-dimmensional model forautonomously growing virtual tissue array constructs. These guidelines andvariables would simulate biological process and structure while remainingflexible and extensible to a broad range of potential researchapplications. The constructs would model quadri-dimensional growth kinetics at the tissuerather than cellular level taking advantage of basic principles of cyclekinetics. The model should conform to our basic concept of both normal andabnormal growth kinetics including the presence or absence ofbiophyisologic modifiers. This kinetic model could model neoplastic and non-neoplastic tissue forexample Intraductal and Invasive breast cancer as well as the immuneresponse to cancer. The choice of programming language would be either JAVA and/or PYTHON whichare both extensible object oriented platform independent high levelprogramming languages which could support the eventual development of aninternet accessible user interface to the interactive model. The dataset would be dynamically written to a PYTHON enabled renderingprogram (trueSapce V6.6) which could create a three dimensional model ofthe construct as it evolves.An outline of the program flow follows: An instance of a cell class would be instantiated through an objectoriented language. The first cell would be assigned to spatial coordinates0,0,0. The time of instantiation would be logged as an instance variable. After a given period of time (checked against the computer clock) the cellis given an opportunity to enter the proliferative phase of the cell cycle. The relative timing of this process would simulate actual cell cyclekinetic data referenced in the medical literature. If, for example, thecell does enter the next phase of the cell cycle and ultimately completesits transit time through the cycle then a second cell object would beinstantiated and assigned to an adjacent unoccupied coordinate. Thecoordinate system could be pre-configured (to simulate no growth areas ortissue structures), and could also use a polar coordinate system. The likelihood of entering, the duration of transit and the ultimate exitfrom the individual cell cycle phases would be guided by the presence orabsence of instance variables. For example the presence of estrogen orprogesterone receptor on a breast cancer cell could be represented by avariable with a real number from 0.0-1.0 with higher values representingincreased density of receptor. Not only could biological parameters be setin this way but calls to cell cycle specific functions to regulate transitthrough the cell cycle based on the presence or absence of markers couldgovern individual cell-objects though the cell cycle phases based on abalance of variables representing both positive and negative cell cyclemodifiers. Subclasses of the cell object could be instantiated to represent normalcells possibly modeling an immune response to cell subclasses whichrepresent tumorous cells. In this way it might be possible to simulatecell interactions (both normal and abnormal) with virtual chemotherapeuticcompounds (with known cell cycle effects), radiation therapy or evenmicrogravity environments. The same approach could be applied to cell differentiation where timedependent variables or instance variables would trigger calls to celldifferentiation functions.
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