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模拟细胞对电离辐射的反应:从损伤到癌症。

Modeling Cell Reactions to Ionizing Radiation: From a Lesion to a Cancer.

作者信息

Dobrzyński L, Fornalski K W, Reszczyńska J, Janiak M K

机构信息

National Centre for Nuclear Research (NCBJ), Otwock-Świerk, Poland.

Ex-Polon Laboratory, Łazy, Poland.

出版信息

Dose Response. 2019 Apr 7;17(2):1559325819838434. doi: 10.1177/1559325819838434. eCollection 2019 Apr-Jun.

Abstract

This article focuses on the analytic modeling of responses of cells in the body to ionizing radiation. The related mechanisms are consecutively taken into account and discussed. A model of the dose- and time-dependent adaptive response is considered for 2 exposure categories: acute and protracted. In case of the latter exposure, we demonstrate that the response plateaus are expected under the modelling assumptions made. The expected total number of cancer cells as a function of time turns out to be perfectly described by the Gompertz function. The transition from a collection of cancer cells into a tumor is discussed at length. Special emphasis is put on the fact that characterizing the growth of a tumor (ie, the increasing mass and volume), the use of differential equations cannot properly capture the key dynamics-formation of the tumor must exhibit properties of the phase transition, including self-organization and even self-organized criticality. As an example, a manageable percolation-type phase transition approach is used to address this problem. Nevertheless, general theory of tumor emergence is difficult to work out mathematically because experimental observations are limited to the relatively large tumors. Hence, determination of the conditions around the critical point is uncertain.

摘要

本文聚焦于机体细胞对电离辐射反应的分析建模。相关机制被依次考虑并讨论。针对两种暴露类别(急性和持续性),考虑了剂量和时间依赖性适应性反应模型。对于后一种暴露情况,我们证明在所做的建模假设下,反应会达到平稳状态。结果表明,癌细胞总数随时间的变化能很好地用冈珀茨函数来描述。详细讨论了癌细胞集合向肿瘤的转变。特别强调了这样一个事实,即表征肿瘤生长(即质量和体积的增加)时,使用微分方程无法恰当地捕捉关键动态——肿瘤的形成必须表现出相变特性,包括自组织甚至自组织临界性。例如,采用一种易于处理的渗流型相变方法来解决这个问题。然而,肿瘤发生的一般理论在数学上难以推导,因为实验观察仅限于相对较大的肿瘤。因此,临界点周围条件的确定并不确定。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2c69/6454661/f0971451316e/10.1177_1559325819838434-fig1.jpg

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