Department of Mathematics, The University of Auckland, 38 Princes Street, Auckland 1010, New Zealand.
University of Rochester Medical Center, School of Medicine and Dentistry, 601 Elmwood Ave, Box 711, Rochester NY, United States of America.
Bull Math Biol. 2019 May;81(5):1394-1426. doi: 10.1007/s11538-018-00563-z. Epub 2019 Jan 14.
We have constructed a spatiotemporal model of [Formula: see text] dynamics in parotid acinar cells, based on new data about the distribution of inositol trisphophate receptors (IPR). The model is solved numerically on a mesh reconstructed from images of a cluster of parotid acinar cells. In contrast to our earlier model (Sneyd et al. in J Theor Biol 419:383-393. https://doi.org/10.1016/j.jtbi.2016.04.030 , 2017b), which cannot generate realistic [Formula: see text] oscillations with the new data on IPR distribution, our new model reproduces the [Formula: see text] dynamics observed in parotid acinar cells. This model is then coupled with a fluid secretion model described in detail in a companion paper: A mathematical model of fluid transport in an accurate reconstruction of a parotid acinar cell (Vera-Sigüenza et al. in Bull Math Biol. https://doi.org/10.1007/s11538-018-0534-z , 2018b). Based on the new measurements of IPR distribution, we show that Class I models (where [Formula: see text] oscillations can occur at constant [[Formula: see text]]) can produce [Formula: see text] oscillations in parotid acinar cells, whereas Class II models (where [[Formula: see text]] needs to oscillate in order to produce [Formula: see text] oscillations) are unlikely to do so. In addition, we demonstrate that coupling fluid flow secretion with the [Formula: see text] signalling model changes the dynamics of the [Formula: see text] oscillations significantly, which indicates that [Formula: see text] dynamics and fluid flow cannot be accurately modelled independently. Further, we determine that an active propagation mechanism based on calcium-induced calcium release channels is needed to propagate the [Formula: see text] wave from the apical region to the basal region of the acinar cell.
我们根据关于肌醇三磷酸受体(IPR)分布的新数据,构建了腮腺腺泡细胞中[Formula: see text]动力学的时空模型。该模型在根据一组腮腺腺泡细胞图像重建的网格上进行数值求解。与我们早期的模型(Sneyd 等人,在 J Theor Biol 419:383-393。https://doi.org/10.1016/j.jtbi.2016.04.030 ,2017b)不同,该模型无法使用新的 IPR 分布数据生成真实的[Formula: see text]振荡,我们的新模型再现了在腮腺腺泡细胞中观察到的[Formula: see text]动力学。然后,该模型与在一篇配套论文中详细描述的流体分泌模型耦合:一个在准确重建的腮腺腺泡细胞中流体传输的数学模型(Vera-Sigüenza 等人,在 Bull Math Biol。https://doi.org/10.1007/s11538-018-0534-z ,2018b)。基于新的 IPR 分布测量结果,我们表明,I 类模型(其中[Formula: see text]振荡可以在常数[[Formula: see text]]下发生)可以在腮腺腺泡细胞中产生[Formula: see text]振荡,而 II 类模型(其中[[Formula: see text]]需要振荡才能产生[Formula: see text]振荡)不太可能这样做。此外,我们证明,将流体流动分泌与[Formula: see text]信号模型耦合会显著改变[Formula: see text]振荡的动力学,这表明[Formula: see text]动力学和流体流动不能独立地进行准确建模。此外,我们确定需要基于钙诱导钙释放通道的主动传播机制将[Formula: see text]波从腺泡细胞的顶端区域传播到底部区域。