DataMedAssist, HTW Dresden, Dresden, Germany.
Faculty of Informatics/Mathematics, HTW Dresden - University of Applied Sciences, Dresden, Germany.
PLoS Comput Biol. 2022 Sep 19;18(9):e1010460. doi: 10.1371/journal.pcbi.1010460. eCollection 2022 Sep.
Understanding the segregation of cells is crucial to answer questions about tissue formation in embryos or tumor progression. Steinberg proposed that separation of cells can be compared to the separation of two liquids. Such a separation is well described by the Cahn-Hilliard (CH) equations and the segregation indices exhibit an algebraic decay with exponent 1/3 with respect to time. Similar exponents are also observed in cell-based models. However, the scaling behavior in these numerical models is usually only examined in the asymptotic regime and these models have not been directly applied to actual cell segregation data. In contrast, experimental data also reveals other scaling exponents and even slow logarithmic scaling laws. These discrepancies are commonly attributed to the effects of collective motion or velocity-dependent interactions. By calibrating a 2D cellular automaton (CA) model which efficiently implements a dynamic variant of the differential adhesion hypothesis to 2D experimental data from Méhes et al., we reproduce the biological cell segregation experiments with just adhesive forces. The segregation in the cellular automaton model follows a logarithmic scaling initially, which is in contrast to the proposed algebraic scaling with exponent 1/3. However, within the less than two orders of magnitudes in time which are observable in the experiments, a logarithmic scaling may appear as a pseudo-algebraic scaling. In particular, we demonstrate that the cellular automaton model can exhibit a range of exponents ≤1/3 for such a pseudo-algebraic scaling. Moreover, the time span of the experiment falls into the transitory regime of the cellular automaton rather than the asymptotic one. We additionally develop a method for the calibration of the 2D Cahn-Hilliard model and find a match with experimental data within the transitory regime of the Cahn-Hilliard model with exponent 1/4. On the one hand this demonstrates that the transitory behavior is relevant for the experiment rather than the asymptotic one. On the other hand this corroborates the ambiguity of the scaling behavior, when segregation processes can be only observed on short time spans.
理解细胞的分离对于回答胚胎组织形成或肿瘤进展等问题至关重要。斯坦伯格提出,细胞的分离可以与两种液体的分离进行比较。这种分离可以很好地用 Cahn-Hilliard(CH)方程来描述,并且分离指数随时间呈 1/3 的代数衰减。在基于细胞的模型中也观察到类似的指数。然而,这些数值模型中的标度行为通常仅在渐近状态下进行检查,并且这些模型尚未直接应用于实际的细胞分离数据。相比之下,实验数据还揭示了其他标度指数,甚至是缓慢的对数标度律。这些差异通常归因于集体运动或速度相关相互作用的影响。通过对一个 2D 元胞自动机(CA)模型进行校准,该模型有效地实现了微分粘附假说的动态变体,可以重现来自 Méhes 等人的 2D 实验数据中的生物细胞分离实验,而仅使用粘附力。在元胞自动机模型中的分离最初遵循对数标度,这与提议的 1/3 指数的代数标度形成对比。然而,在实验中可观察到的不到两个数量级的时间内,对数标度可能呈现出伪代数标度。特别是,我们证明了元胞自动机模型可以表现出这种伪代数标度的范围为 1/3 的指数。此外,实验的时间跨度属于元胞自动机的过渡状态,而不是渐近状态。我们还开发了一种校准 2D Cahn-Hilliard 模型的方法,并在 Cahn-Hilliard 模型的过渡状态下找到了与实验数据的匹配,其指数为 1/4。一方面,这表明过渡行为对于实验是相关的,而不是渐近的。另一方面,这证实了在只能观察到短时间跨度的情况下,标度行为的模糊性。