Oncolytic virotherapy is a promising therapeutic strategy that uses replication-competent viruses to selectively destroy malignancies. However, the therapeutic effect of certain oncolytic viruses (OVs) varies among cancer patients. Thus, it is necessary to overcome resistance to OVs through rationally designed combination strategies. Here, through an anticancer drug screening, we show that DNA-dependent protein kinase (DNA-PK) inhibition sensitizes cancer cells to OV M1 and improves therapeutic effects in refractory cancer models in vivo and in patient tumour samples. Infection of M1 virus triggers the transcription of interferons (IFNs) and the activation of the antiviral response, which can be abolished by pretreatment of DNA-PK inhibitor (DNA-PKI), resulting in selectively enhanced replication of OV M1 within malignancies. Furthermore, DNA-PK inhibition promotes the DNA damage response induced by M1 virus, leading to increased tumour cell apoptosis. Together, our study identifies the combination of DNA-PKI and OV M1 as a potential treatment for cancers.

SUMMARYIn this letter, we propose a Throughput-aimed MAC Protocol with Quality of Service (QoS) provision (T-MAC) for cognitive Ad Hoc networks. This protocol operates based on the Time Division Multiple Access (TDMA) slot assignments and the power control mechanism, which can improve the QoS provision and network throughput. Our simulation results show that the T-MAC protocol can efficiently increase the network throughput and reduce the access delay.

Dynamic spectrum auction is considered as an effective solution to improve spectrum utilization efficiency in dynamic spectrum sharing networks because it can provide an economic incentive to motivate primary users to share their idle spectrum with secondary users. However, the primary users' own quality of services (QoS) cannot be guaranteed in case of demand peak because their spectrum is being used by the winners at auction. To solve this problem, we propose a recall-based dynamic spectrum auction (RBDSA) algorithm with which a primary base station (PBS) can auction its unused channels to some secondary wireless services providers (SWSPs) safely and economically. The PBS' users are granted a higher channel access priority than the SWSPs, then the PBS can recall some channels after auction to satisfy its demand if necessary. To maximize its profit from spectrum auction and self services, the PBS will reduce its excessive or deficient channels reservation, which is enforced with an introduction of punishment item in the PBS' utility. We show analytically that both the PBS and the SWSPs in the RBDSA algorithm are truthful and there is a weakly dominant equilibrium. Moreover, it can be extended to the scenarios with multiple units of channels demand and multiple PBSs. Simulation results show that the RBDSA algorithm can increase the utility of the PBS and improve the channels utilization efficiency while keeping the QoS of the primary users.

Dynamic spectrum auction has been considered as one of potential approaches on spectrum allocation in cognitive radio networks. As an modified version of traditional static or quasi-static spectrum auction, dynamic spectrum auction should not only increase the auction revenue of the owner of spectrum, but also improve spectrum utilization on fine time granularity. We propose a dynamic spectrum auction algorithm with time optimization (DSA-TO) in an 802.22 network. First, the effects of auction period on auction revenue and spectrum utilization are discussed and optimized. Then we give a complete spectrum auction algorithm where an adaptive reserve price is used to balance the revenue and utilization of spectrum auction. Performance analyses show that the DSA-TO algorithm can resist collusion effectively and has low complexity as well as good revenue and utilization. Simulation results show that the DSA-TO algorithm is reasonable in the optimization of auction period and can keep a fine spectrum utilization and bring more revenue for both single unit spectrum auction and multi-unit spectrum auction.

SUMMARYDynamic spectrum auction (DSA) has been considered as one of potential spectrum allocation approaches in cognitive femtocell networks. As a modified version of traditional spectrum auction, DSA should not only increase auction revenue but also improve spectrum utilization on finer time granularity. We propose a DSA algorithm based on a double optimization framework (DOF), which focuses on the optimization of auction revenue and spectrum utilization. The optimization processing consists of two stages. Firstly, a proper auction period is selected to balance the expected spectrum utilization and auction revenue. Then, the cognitive femtocell base station adjusts its reserve price with the repetition of auction to leverage over instant revenue and spectrum utilization. At the same time, the bidders can adjust their bidding price to improve utilities. Performance analysis shows that the DOF‐based DSA algorithm has low complexity and can resist collusion, so it can be carried out frequently with small overhead. On the other hand, it is better than the greedy algorithm and Vickrey–Clarke–Groves auction on revenue. Simulation results show that the DOF‐based DSA algorithm can keep a fine spectrum utilization and bring the cognitive femtocell base station more revenue in both single‐unit award spectrum auction and multi‐unit awards spectrum auction. Copyright © 2012 John Wiley & Sons, Ltd.