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Metastasis significantly reduces the survival rate of osteosarcoma (OS) patients. Therefore, identification of novel targets remains extremely important to prevent metastasis and treat OS. In this report, we show that SPARCL1 is downregulated in OS by epigenetic methylation of promoter DNA. In vitro and in vivo experiments revealed that SPARCL1 inhibits OS metastasis. We further demonstrated that SPARCL1-activated WNT/β-catenin signaling by physical interaction with various frizzled receptors and lipoprotein receptor-related protein 5/6, leading to WNT–receptor complex stabilization. Activation of WNT/β-catenin signaling contributes to the SPARCL1-mediated inhibitory effects on OS metastasis. Furthermore, we uncovered a paracrine effect of SPARCL1 on macrophage recruitment through activated WNT/β-catenin signaling-mediated secretion of chemokine ligand5 from OS cells. These findings suggest that the targeting of SPARCL1 as a new anti-metastatic strategy for OS patients.

Cooperative communication has the potential of providing better throughput and reliability to wireless systems when compared with direct communication. To realise the potential gain, it is important to design cooperative strategies for some representative scenarios. This survey deals with three basic wireless relay channels, namely, the parallel relay channel, the multiple‐access relay channel and the broadcast relay channel. For the first channel, which models a single unicast connection, various forwarding strategies are studied. For the second and third channels, which model, respectively, the uplink and downlink scenarios with multiple unicast connections; network codes that exploit the possibility of coding among the connections are studied. The common aim pertaining to the studies of all these three channels is to use the limited radio resource in the most efficient way. Beside the aforementioned conventional works, studies that have state‐of‐the‐art assumptions for relay networks, including outdated channel state information at the transmitter, full duplex relay and practical rateless‐coded cooperation, are also extensively reviewed. Copyright © 2014 John Wiley & Sons, Ltd.

In the original index coding problem, each user has a set of uncoded packets as side information, and wants to decode some other packets from the source node. The source node aims at satisfying the demands of all users as quickly as possible. With linear network coding, this is accomplished by broadcasting linear combinations of the source packets over some finite field. Since the broadcast is performed over a wireless channel, a user may overhear some coded packets that are not intended to him/her. This motivates a generalization of the index coding problem to the case where linearly coded packets are used as side information. We show that this generalized linear index coding problem is equivalent to solving a system of multi-variable polynomial equations. A heuristic solution is constructed and is applied to the broadcast relay channel.Index Terms-Index coding, broadcast relay channel, network coding. I. BACKGROUND AND MOTIVATIONSIn the index coding problem [1], [2], there is a transmitting node and a group of M users. The transmitting node has N source packets, P 1 , P 2 , . . . , P N . Each user requests one specific data packet from the transmitting node. Each user has some side information, which is known to the transmitter through a feedback channel. The side information consists of some packets which is not wanted by that particular user. An index coding problem is specified by M "want sets" and M "has sets". The "want set" of user i is a singleton containing the data packet required by user i, and the "has set" of user i is a set containing the packets in user i's cache. The objective of index coding is to satisfy the demands of all users with minimum number of packet transmission. The index coding problem is shown to be NP-hard, and evening finding an approximation solution is hard, under certain complexity assumption [3], [4]. Studies of index coding can be found in [5], [6] and the references therein.Suppose that the content of a packet is regarded as an element of a finite field, say the finite field with 2 n elements, denoted by GF (2 n ). A packet then carries n bits of information. The transmitting node can send linear combination of the source packets, with coefficients taken from GF (2 n ). In this case, we say that the index coding is (scalar) linear. A linear combination of source packets is called a coded packet. (For slot sent by user 1? by user 2? by user 3? 1 P 1 no yes no 2 P 2 yes no no 3 P 3 yes yes no 4 P 1 + P 2 no no yes 5 P 1 + P 2 + P 3 yes yes yes Fig. 1. Illustration of utilizing coded packets as side information. vector linear index coding, we refer the readers to [7], [8]. In this paper, we focus on the scalar linear case.)In some application of index coding in wireless broadcast channel, the "has set" of a user may contain coded packets as well. We give a simple example for motivation. The source node has three packets P 1 , P 2 and P 3 , which are elements in GF (2 n ). There are three users. For i = 1, 2, 3, user i wants packet P i . The transmitted packet is subject to inde...