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The poor prognosis of HNSCC is partly due to treatment resistance. The SMAC mimetic Xevinapant is a promising new approach to targeted cancer therapy. Xevinapant inhibits cIAP1/2 and XIAP, leading to apoptosis, necroptosis and inhibition of prosurvival signaling. Combining Xevinapant with IR could improve therapeutic potential. The effect of Xevinapant in combination with IR on HNSCC and healthy tissue cells was investigated. Cell growth, cell death, clonogenic survival and DNA double-strand breaks (DSBs) were studied, and intracellular cIAP1 and XIAP levels were evaluated. Xevinapant had cytostatic and cytotoxic, as well as radiosensitizing, effects on the malignant cells, while healthy tissue cells were less affected. Apoptotic and necrotic cell death was particularly affected, but the increase in residual DSBs and the reduced survival implied an additional effect of Xevinapant on DNA damage repair and other cell inactivation mechanisms. cIAP1 and XIAP levels varied for each cell line and were affected by Xevinapant and IR treatment. There was an association between higher IAP levels and increased cell death. Xevinapant appears to be a potent new drug for HNSCC therapy, especially in combination with IR. IAP levels could be an indicator for impaired DNA damage repair and increased susceptibility to cellular stress.

We present a decentralized sequencing algorithm applicable to modular high(est)-density conveyor systems that enables items to enter the system randomly from multiple input points. They are rearranged within the system to be retrieved at an assigned output point observing a predefined sequence. A variety of applications benefits from this, such as storing and retrieving, order picking, packing and shipping operations as well as Just-in-Sequence (JiS) applications of production systems. We prove that our decentralized algorithm – based on the concept of logical time – is able to prevent deadlocks, livelocks, and starvation. It guarantees a complexity of order $\mathcal{O}(n^2)$ at module level depending on system size $n$ . Using throughput evaluations, we show how to parameterize the decentralized sequencing algorithm to optimize its performance. Furthermore, we deduce that small batch sizes, high conveying speeds, a high number of output points, or non-perforated network structures increase system throughput. A simulative demonstration of the developed algorithm can be found at our institute channel. Note to Practitioners —The need for flexibility, scalability, and robustness has led to decentralized control concepts becoming more and more popular in practice. In the field of material handling systems, transportation, storage, sortation, and picking functionality is already being realized based on decentralized control. In this paper, we present a decentralized control algorithm which dispatches randomly introduced items to match a specified sequence at their assigned destination. It applies to systems including multiple input and output points ( $(m:n)$ setting) and thus allows for parallel order processing and customizable system configurations of various application scenarios. As sequencing combines routing, buffering and relocation functionality, additionally, an overall logic for implementing transport, storage and retrieval, sortation and picking systems is provided as well.