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Indoleamine 2,3-dioxygenase (IDO) and tryptophan 2,3-dioxygenase (TDO2) are the key enzymes of tryptophan (TRP) metabolism in the kynurenine pathway (KP). Both enzymes function as indicators of immunosuppression and poor survival in cancer patients. Direct or indirect targeting of either of these substances seems thus reasonable to improve therapy options for patients. In this study, glioblastoma multiforme (GBM) as well as head and neck squamous cell carcinomas (HNSCC) were examined because of their different mechanisms of spontaneous and treatment-induced immune escape. Effects on gene expression and protein levels were examined. Accompanying assessment of TRP metabolites from treated GBM cell culture supernatants was conducted. Our results show a heterogeneous and inversely correlated expression profile of TRP-metabolizing genes among GBM and HNSCC cells, with low, but inducible IDO1 expression upon IFNγ treatment. TDO2 expression was higher in GBM cells, while genes encoding kynurenine aminotransferases were mainly confined to HNSCC cells. These data indicate that the KP is active in both entities, with however different enzymes involved in TRP catabolism. Upon treatment with Temozolomide, the standard of care for GBM patients, IDO1 was upregulated. Comparable, although less pronounced effects were seen in HNSCC upon Cetuximab and conventional drugs (i.e., 5-fluorouracil, Gemcitabine). Here, IDO1 and additional genes of the KP (KYAT1, KYAT2, and KMO) were induced. Vice versa, the novel yet experimental cyclin-dependent kinase inhibitor Dinaciclib suppressed KP in both entities. Our comprehensive data imply inhibition of the TRP catabolism by Dinaciclib, while conventional chemotherapeutics tend to activate this pathway. These data point to limitations of conventional therapy and highlight the potential of targeted therapies to interfere with the cells' metabolism more than anticipated.
To suit a wide variety of space mission profiles, different designs of ion thrusters were developed, such as the High‐Efficiency‐Multistage‐Plasma thrusters (HEMP‐T). In the past, the optimization of ion thrusters was a difficult and time‐consuming process and evolved experimentally. Because the construction of new designs is expensive, cheaper methods for optimization were sought‐after. Computer‐based simulations are a cheap and useful method towards predictive modelling. The physics in HEMP‐T requires a kinetic model. The Particle‐in‐Cell (PIC) method delivers self‐consistent solutions for the plasmas of ion thrusters, but it is limited by the high amount of computing time required to study a specific system. Therefore, it is not suited to explore a wide operational and design space. An approach to decrease computing time is self‐similarity scaling schemes, which can be derived from the kinetic equations. One specific self‐similarity scheme is investigated quantitatively in this work for selected HEMP‐Ts, using PIC simulations. The possible application of the scaling is explained and the limits of this approach are derived.
In recent years, the colon has become a hot topic in biopharmaceutical research as several in vitro models of the human colon have been presented. A major focus is on the characterization of the microbiota and its capabilities. The aim of the present study was to further develop the MimiCol, preserving its properties and accelerating data acquisition. Emphasis was placed on the simplicity of its design and easy scalability. To prove the viability of the concept, degradation of sulfasalazine was investigated, and the bacterial composition during the experiment was assessed by 16S rRNA sequencing. The transfer of the experimental conditions to the new model was successful. Commercially available components were implemented in the setup. The model MimiCol3 represented the colon ascendens satisfactorily in its properties regarding volume, pH value, and redox potential. 16S rRNA sequencing led to further insights into the bacterial composition in the vessels. Degradation of sulfasalazine was in good agreement with in vivo data. The new model of the colon ascendens MimiCol3 enabled us to collect more reliable data, as three experiments were conducted simultaneously under the same conditions.