Interference-aware coordinated power allocation in autonomous Wi-Fi environment

Self-managed access points (APs) with growing intelligence can optimize their own performances but pose potential negative impacts on others without energy ef ciency. In this paper, we focus on modeling the coordinated interaction among interest-independent and self-con gured APs, and conduct the power allocation case study in the autonomous Wi-Fi scenario. Speci cally, we build a `coordination Wi-Fi platform (CWP), a public platform for APs interacting with each other. OpenWrt-based APs in the physical world are mapped to virtual agents (VAs) in CWP, which communicate with each other through a standard request-reply process de ned as AP talk protocol (ATP).With ATP, an active interference measurement methodology is proposed re ecting both in-range interference and hidden terminal interference, and the Nash bargaining-based power control is further formulated for interference reductions. CWP is deployed in a real of ce environment, where coordination interactions between VAs can bring a maximum 40-Mb/s throughput improvement with the Nash bargaining-based power control in the multi-AP experiments

Network association strategies for an energy harvesting aided super-wifi network relying on measured solar activity

The super-WiFi network concept has been proposed for nationwide Internet access in the United States. However, the traditional mains power supply is not necessarily ubiquitous in this large-scale wireless network. Furthermore, the non-uniform geographic distribution of both the based-stations and the tele-traffic requires carefully considered user association. Relying on the rapidly developing energy harvesting techniques, we focus our attention on the sophisticated access point (AP) selection strategies conceived for the energy harvesting aided super-WiFi network. Explicitly, we propose a solar radiation model relying on the historical solar activity observation data provided by the University of Queensland, followed by a beneficial radiation parameter estimation method. Furthermore, we formulate both a Markov decision process (MDP) as well as a partially observable MDP (POMDP) for supporting the users’ decisions on beneficially selecting APs. Moreover, we conceive iterative algorithms for implementing our MDP and POMDP-based AP-selection, respectively. Finally, our performance results are benchmarked against a range of traditional decision-making algorithms

Information-sharing outage-probability analysis of vehicular networks

In vehicular networks, information dissemination/sharing among vehicles is of salient importance. Although diverse mechanisms have been proposed in the existing literature, the related information credibility issues have not been investigated. Against this background, in this paper, we propose a credible information-sharing mechanism capable of ensuring that the vehicles do share genuine road traffic information (RTI). We commence with the outage-probability analysis of information sharing in vehicular networks under both a general scenario and a specific highway scenario. Closed-form expressions are derived for both scenarios, given the specific channel settings. Based on the outage-probability expressions, we formulate the utility of RTI sharing and design an algorithm for promoting the sharing of genuine RTI. To verify our theoretical analysis and the proposed mechanism, we invoke a real-world dataset containing the locations of Beijing taxis to conduct our simulations. Explicitly, our simulation results show that the spatial distribution of the vehicles obeys a Poisson point process (PPP), and our proposed credible RTI sharing mechanism is capable of ensuring that all vehicles indeed do share genuine RTI with each other

The effect of celecoxib on tumor growth in ovarian cancer cells and a genetically engineered mouse model of serous ovarian cancer

Our objective was to evaluate the effect of the COX-2 inhibitor, celecoxib, on (1) proliferation and apoptosis in human ovarian cancer cell lines and primary cultures of ovarian cancer cells, and (2) inhibition of tumor growth in a genetically engineered mouse model of serous ovarian cancer under obese and non-obese conditions. Celecoxib inhibited cell proliferation in three ovarian cancer cell lines and five primary cultures of human ovarian cancer after 72 hours of exposure. Treatment with celecoxib resulted in G1 cell cycle arrest, induction of apoptosis, inhibition of cellular adhesion and invasion and reduction of expression of hTERT mRNA and COX-2 protein in all of the ovarian cancer cell lines. In the KpB mice fed a high fat diet (obese) and treated with celecoxib, tumor weight decreased by 66% when compared with control animals. Among KpB mice fed a low fat diet (non-obese), tumor weight decreased by 46% after treatment with celecoxib. In the ovarian tumors from obese and non-obese KpB mice, treatment with celecoxib as compared to control resulted in decreased proliferation, increased apoptosis and reduced COX-2 and MMP9 protein expression, as assessed by immunohistochemistry. Celecoxib strongly decreased the serum level of VEGF and blood vessel density in the tumors from the KpB ovarian cancer mouse model under obese and non-obese conditions. This work suggests that celecoxib may be a novel chemotherapeutic agent for ovarian cancer prevention and treatment and be potentially beneficial in both obese and non-obese women

The HMG-CoA reductase inhibitor, simvastatin, exhibits anti-metastatic and anti-tumorigenic effects in ovarian cancer

Ovarian cancer is the 5th leading cause of cancer death among women in the United States. The mevalonate pathway is thought to be a potential oncogenic pathway in the pathogenesis of ovarian cancer. Simvastatin, a 3-hydroxy-3-methyl-glutaryl-CoA reductase (HMGCR) inhibitor, is a widely used drug for inhibiting the synthesis of cholesterol and may also have anti-tumorigenic activity. Our goal was to evaluate the effects of simvastatin on ovarian cancer cell lines, primary cultures of ovarian cancer cells and in an orthotopic ovarian cancer mouse model. Simvastatin significantly inhibited cellular proliferation, induced cell cycle G1 arrest and apoptosis, and caused cellular stress via reduction in the enzymatic activity of HMGCR and inhibition of the MAPK and mTOR pathways in ovarian cancer cells. Furthermore, simvastatin induced DNA damage and reduced cell adhesion and invasion. Simvastatin also exerted anti-proliferative effects on primary cell cultures of ovarian cancer. Treatment with simvastatin in an orthotopic mouse model reduced ovarian tumor growth, coincident with decreased Ki-67, HMGCR, phosphorylated-Akt and phosphorylated-p42/44 protein expression. Our findings demonstrate that simvastatin may have therapeutic benefit for ovarian cancer treatment and be worthy of further exploration in clinical trials

Everolimus exhibits anti-tumorigenic activity in obesity-induced ovarian cancer

Everolimus inhibits mTOR kinase activity and its downstream targets by acting on mTORC1 and has anti-tumorigenic activity in ovarian cancer. Clinical and epidemiologic data find that obesity is associated with worse outcomes in ovarian cancer. In addition, obesity leads to hyperactivation of the mTOR pathway in epithelial tissues, suggesting that mTOR inhibitors may be a logical choice for treatment in obesity-driven cancers. However, it remains unclear if obesity impacts the effect of everolimus on tumor growth in ovarian cancer. The present study was aimed at evaluating the effects of everolimus on cytotoxicity, cell metabolism, apoptosis, cell cycle, cell stress and invasion in human ovarian cancer cells. A genetically engineered mouse model of serous ovarian cancer fed a high fat diet or low fat diet allowed further investigation into the inter-relationship between everolimus and obesity in vivo. Everolimus significantly inhibited cellular proliferation, induced cell cycle G1 arrest and apoptosis, reduced invasion and caused cellular stress via inhibition of mTOR pathways in vitro. Hypoglycemic conditions enhanced the sensitivity of cells to everolimus through the disruption of glycolysis. Moreover, everolimus was found to inhibit ovarian tumor growth in both obese and lean mice. This reduction coincided with a decrease in expression of Ki-67 and phosphorylated-S6, as well as an increase in cleaved caspase 3 and phosphorylated-AKT. Metabolite profiling revealed that everolimus was able to alter tumor metabolism through different metabolic pathways in the obese and lean mice. Our findings support that everolimus may be a promising therapeutic agent for obesity-driven ovarian cancers

Dual inhibition of glycolysis and glutaminolysis as a therapeutic strategy in the treatment of ovarian cancer

Cancer cell metabolism is required to support the biosynthetic demands of cell growth and cell division, and to maintain reduction oxidaton (redox) homeostasis. This study was designed to test the effects of glucose and glutamine on ovarian cancer cell growth and explore the inter-relationship between glycolysis and glutaminolysis. The SKOV3, IGROV-1 and Hey ovarian cancer cell lines were assayed for glucose, pyruvate and glutamine dependence by analyzing cytotoxicity, cell cycle progression, apoptosis and ATP production. As determined by MTT assay, glucose stimulated cell growth while the combination of glucose, glutamine and pyruvate resulted in the greatest stimulation of cell proliferation. Furthermore, 2-deoxy-glucose (2-DG) and 3-bromopyruvate (3-BP) induced apoptosis, caused G1 phase cell cycle arrest and reduced glycolytic activity. Moreover, 2-DG in combination with a low dose of aminooxyacetate (AOA) synergistically increased the sensitivity to 2-DG in the inhibition of cell growth in the ovarian cancer cell lines. These studies suggest that dual inhibition of glycolysis and glutaminolysis may be a promising therapeutic strategy for the treatment of ovarian cancer

Evaluation of the anti-tumor effects of lactate dehydrogenase inhibitor galloflavin in endometrial cancer cells

High rates of aerobic glycolysis represent a key mechanism by which endometrial cancer cells consume glucose as its primary energy source. The up-regulated glycolytic pathway is a common therapeutic target whose inhibition has implications for anti-tumor activity in cancer cells. The present study was aimed at evaluating the potential of a novel lactate dehydrogenase (LDH) inhibitor, Galloflavin, as a therapeutic agent for endometrial cancer. Our results revealed that Galloflavin effectively inhibited cell growth in endometrial cancer cell lines and primary cultures of human endometrial cancer through its involvement in multiple signaling pathways that regulate metabolism, cell cycle, apoptosis, cell stress and metastasis.Electronic supplementary materialThe online version of this article (doi:10.1186/s13045-014-0097-x) contains supplementary material, which is available to authorized users