The capacity of ad hoc wireless networks can be substantially increased by equipping each network node with multiple radio interfaces that can operate on multiple non-overlapping channels. However, new scheduling, channelassignment, and routing algorithms are required to fully utilize the increased bandwidth in multi-channel multi-radio ad hoc networks. In this paper, we develop a fully distributed algorithm that jointly solves the channel-assignment, scheduling and routing problem. Our algorithm is an online algorithm, i.e., it does not require prior information on the offered load to the network, and can adapt automatically to the changes in the network topology and offered load. We show that our algorithm is provably efficient. That is, even compared with the optimal centralized and offline algorithm, our proposed distributed algorithm can achieve a provable fraction of the maximum system capacity. Further, the achievable fraction that we can guarantee is larger than that of some other comparable algorithms in the literature.

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Abstract-In this paper, we characterize the performance of an important class of scheduling schemes, called Greedy Maximal Scheduling (GMS), for multi-hop wireless networks. While a lower bound on the throughput performance of GMS is relatively well-known in the simple node-exclusive interference model, it has not been thoroughly explored in the more general K-hop interference model. Moreover, empirical observations suggest that the known bounds are quite loose, and that the performance of GMS is often close to optimal. In this paper, we provide a number of new analytic results characterizing the performance limits of GMS. We first provide an equivalent characterization of the efficiency ratio of GMS through a topological property called the local-pooling factor of the network graph. We then develop an iterative procedure to estimate the local-pooling factor under a large class of network topologies and interference models. We use these results to study the worst-case efficiency ratio of GMS on two classes of network topologies. First, we show how these results can be applied to tree networks to prove that GMS achieves the full capacity region in tree networks under the K-hop interference model. Second, we show that the worst-case efficiency ratio of GMS in geometric network graphs is between 1 6 and 1 3 .

In this paper, we characterize the performance of an important class of scheduling schemes, called Greedy Maximal Scheduling (GMS), for multi-hop wireless networks. While a lower bound on the throughput performance of GMS is relatively well-known in the simple node-exclusive interference model, it has not been thoroughly explored in the more general K-hop interference model. Moreover, empirical observations suggest that the known bounds are quite loose, and that the performance of GMS is often close to optimal. In this paper, we provide a number of new analytic results characterizing the performance limits of GMS. We first provide an equivalent characterization of the efficiency ratio of GMS through a topological property called the local-pooling factor of the network graph. We then develop an iterative procedure to estimate the local-pooling factor under a large class of network topologies and interference models. We use these results to study the worst-case efficiency ratio of GMS on two classes of network topologies. First, we show how these results can be applied to tree networks to prove that GMS achieves the full capacity region in tree networks under the K-hop interference model. Second, we show that the worst-case efficiency ratio of GMS in geometric network graphs is between 1 6 and 1 3 .

Type VI secretion systems (T6SSs) which widely distributed in Gram-negative bacteria have been primarily studied in the context of cell interactions with eukaryotic hosts or other bacteria. We have recently identified a thermoregulated T6SS4 in the enteric pathogen Yersinia pseudotuberculosis. Here we report that OmpR directly binds to the promoter of T6SS4 operon and regulates its expression. Further, we observed that the OmpR-regulated T6SS4 is essential for bacterial survival under acidic conditions and that its expression is induced by low pH. Moreover, we showed that T6SS4 plays a role in pumping H(+) out of the cell to maintain intracellular pH homeostasis. The acid tolerance phenotype of T6SS4 is dependent on the ATPase activity of ClpV4, one of the components of T6SS4. These results not only uncover a novel strategy utilized by Y. pseudotuberculosis for acid resistance, but also reveal that T6SS, a bacteria secretion system known to be functional in protein transportation has an unexpected function in H(+) extrusion under acid conditions.

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Background Ferroptosis is an iron-dependent, lipid peroxide-mediated cell death that may be exploited to selective elimination of damaged and malignant cells. Recent studies have identified that small-molecule erastin specifically inhibits transmembrane cystine–glutamate antiporter system xc−, prevents extracellular cystine import and ultimately causes ferroptosis in certain cancer cells. In this study, we aimed to investigate the molecular mechanism underlying erastin-induced ferroptosis resistance in ovarian cancer cells. Methods We treated ovarian cancer cells with erastin and examined cell viability, cellular ROS and metabolites of the transsulfuration pathway. We also depleted cystathionine β-synthase (CBS) and NRF2 to investigate the CBS and NRF2 dependency in erastin-resistant cells. Results We found that prolonged erastin treatment induced ferroptosis resistance. Upon exposure to erastin, cells gradually adapted to cystine deprivation via sustained activation of the reverse transsulfuration pathway, allowing the cells to bypass erastin insult. CBS, the biosynthetic enzyme for cysteine, was constantly upregulated and was critical for the resistance. Knockdown of CBS by RNAi in erastin-resistant cells caused ferroptotic cell death, while CBS overexpression conferred ferroptosis resistance. We determined that the antioxidant transcriptional factor, NRF2 was constitutively activated in erastin-resistant cells and NRF2 transcriptionally upregulated CBS. Genetically repression of NRF2 enhanced ferroptosis susceptibility. Conclusions Based on these results, we concluded that constitutive activation of NRF2/CBS signalling confers erastin-induced ferroptosis resistance. This study demonstrates a new mechanism underlying ferroptosis resistance, and has implications for the therapeutic response to erastin-induced ferroptosis.