The role of chemokines in cancer immune surveillance by the adaptive immune system.

Chemokines are key molecules involved in the migration and homeostasis of immune cells. However, also tumor cells use chemokine signals for different processes such as tumor progression and metastasis. It is thus unclear whether chemokines, through their immunostimulatory roles, contribute to the repression of tumor cells by tumor immunosurveillance or whether chemokines act primarily as growth factors and chemoattractants for primary and metastatizing tumors, respectively. Research of recent years, using gene knockout mice, recombinant chemokines, and agents able to block chemokine actions, has provided further insight into the diverse functions of chemokines. Here, we review the current knowledge on the complex actions of chemokines at the interface of the immune system and the tumor.

Local-global splitting for spatiotemporal-adaptive multiscale methods

We present a novel spatiotemporal-adaptive Multiscale Finite Volume (MsFV) method, which is based on the natural idea that the global coarse-scale problem has longer characteristic time than the local fine-scale problems. As a consequence, the global problem can be solved with larger time steps than the local problems. In contrast to the pressure-transport splitting usually employed in the standard MsFV approach, we propose to start directly with a local-global splitting that allows to locally retain the original degree of coupling. This is crucial for highly non-linear systems or in the presence of physical instabilities. To obtain an accurate and efficient algorithm, we devise new adaptive criteria for global update that are based on changes of coarse-scale quantities rather than on fine-scale quantities, as it is routinely done before in the adaptive MsFV method. By means of a complexity analysis we show that the adaptive approach gives a noticeable speed-up with respect to the standard MsFV algorithm. In particular, it is efficient in case of large upscaling factors, which is important for multiphysics problems. Based on the observation that local time stepping acts as a smoother, we devise a self-correcting algorithm which incorporates the information from previous times to improve the quality of the multiscale approximation. We present results of multiphase flow simulations both for Darcy-scale and multiphysics (hybrid) problems, in which a local pore-scale description is combined with a global Darcy-like description. The novel spatiotemporal-adaptive multiscale method based on the local-global splitting is not limited to porous media flow problems, but it can be extended to any system described by a set of conservation equations.