Safarishahrbijari Anahita, Gaffari Ali
Faculty of Mechanical Engineering, K.N. Toosi University of Technology, Teheran, Iran.
Contemp Oncol (Pozn). 2013;17(1):73-7. doi: 10.5114/wo.2013.33778. Epub 2013 Mar 15.
Periodic chronic myelogenous leukemia (PCML) is a dynamic hematopoietic disease which causes oscillations of circulating leukocytes, platelets and reticulocytes. Mathematical modeling is an invaluable tool to help in predicting hematopoiesis behavior. In this paper we modify the existing models based on improving the parameters of the model. Also more parameters are estimated regarding the proposed model. It is our major intention to construct a physiological model which can map major identified mechanisms of leukopoiesis to provide a deeper insight into this complex biological process. In the proposed model the leukocytes line has been modeled more precisely. In fact, precursor cells have been considered as two separate groups: proliferating precursor cells and non-proliferating precursor cells. As a result, more parameters have appeared in the model and identifying the new parameters has resulted in a better fit of clinical data and the data extracted from the model for both platelets and leukocytes. That is, the new model describes the leukocytes and platelets of the system in a way that is closer to clinical data, so the proposed model can be more useful for predicting the behavior of leukocytes and platelets for PCML disease. Compared with the previous works, it is shown that the new model has a better fit of the quantitative data on leukocytes and platelets.
周期性慢性粒细胞白血病(PCML)是一种动态造血疾病,会导致循环白细胞、血小板和网织红细胞的波动。数学建模是帮助预测造血行为的宝贵工具。在本文中,我们通过改进模型参数来修改现有模型。此外,针对所提出的模型估计了更多参数。我们的主要目的是构建一个生理模型,该模型可以映射主要已确定的白细胞生成机制,以便更深入地了解这一复杂的生物学过程。在所提出的模型中,白细胞系得到了更精确的建模。实际上,前体细胞被视为两个独立的组:增殖前体细胞和非增殖前体细胞。结果,模型中出现了更多参数,并且新参数的确定使得临床数据与从模型中提取的血小板和白细胞数据拟合得更好。也就是说,新模型以更接近临床数据的方式描述了系统中的白细胞和血小板,因此所提出的模型对于预测PCML疾病中白细胞和血小板的行为可能更有用。与先前的研究相比,结果表明新模型对白细胞和血小板的定量数据拟合得更好。