Tumor treating fields (TTFields) represent a novel FDA-approved treatment modality for patients with newly diagnosed or recurrent glioblastoma multiforme. This therapy applies intermediate frequency alternating electric fields with low intensity to the tumor volume by the use of non-invasive transducer electrode arrays. Mechanistically, TTFields have been proposed to impair formation of the mitotic spindle apparatus and cytokinesis. In order to identify further potential molecular targets, here the effects of TTFields on Ca2+-signaling, ion channel activity in the plasma membrane, cell cycle, cell death, and clonogenic survival were tested in two human glioblastoma cell lines in vitro by fura-2 Ca2+ imaging, patch-clamp cell-attached recordings, flow cytometry and pre-plated colony formation assay. In addition, the expression of voltage-gated Ca2+ (Cav) channels was determined by real-time RT-PCR and their significance for the cellular TTFields response defined by knock-down and pharmacological blockade. As a result, TTFields stimulated in a cell line-dependent manner a Cav1.2-mediated Ca2+ entry, G1 or S phase cell cycle arrest, breakdown of the inner mitochondrial membrane potential and DNA degradation, and/or decline of clonogenic survival suggesting a tumoricidal action of TTFields. Moreover, inhibition of Cav1.2 by benidipine aggravated in one glioblastoma line the TTFields effects suggesting that Cav1.2-triggered signaling contributes to cellular TTFields stress response. In conclusion, the present study identified Cav1.2 channels as TTFields target in the plasma membrane and provides the rationale to combine TTFields therapy with Ca2+ antagonists that are already in clinical use.

A novel hybrid simulation approach is developed, which combines the advantages of deterministic and stochastic modeling of complex polymerization networks. The fast deterministic simulation solves the heat and pressure balances and generates positiondependent event frequency profiles. The detailed stochastic simulation is used as add-on and offers a deep insight into the polymeric microstructure of each macromolecule. Our hybrid simulation approach is applied to high-pressure ethylene polymerization in industrial tubular and continuous autoclave reactors with peroxide initiation. But in general, the presented approach can be used for all types of polymerization reactions in ideal and non-ideal reactors of any kind.

Cover: A novel hybrid simulation approach combines the deterministic and stochastic modeling of complex polymerization networks, for all types of polymerization reactions in ideal and non‐ideal reactors. The fast deterministic simulation solves the heat and pressure balances and generates position‐dependent event frequency profiles. The detailed stochastic simulation offers insight into the polymeric microstructure of each macromolecule. Further details can be found in the article by E. Neuhaus, T. Herrmann, I. Vittorias, D. Lilge, G. Mannebach, A. Gonioukh, and M. Busch* http://doi.wiley.com/10.1002/mats.201400014.

Summary: Simulation based process development of new LDPE grades often requires a deep insight into the exact microstructure of individual macromolecules. Therefore, we developed an approach, which combines the advantages of the deterministic (low computational time and high accuracy) and stochastic simulation (individual macromolecules with distinct microstructure). The approach can be used for the modeling of continuously driven autoclave and tubular reactors. First results visualize the random conformation of a distinct macromolecule as well as the resulting contraction factor.

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