Assessment of the SRC Inhibition Role in the Efficacy of Breast Cancer Radiotherapy

Introduction: Exposure to the artificial light at night (LAN) effect human health and causes several functional modification in body. Obesity, diabetes, and hormonal changes are reported after LAN in humans. Aim of this study is highlighting critical features of gene expression changes in liver of rats which are received autonomic nervous system.Methods: Up-regulated proteins of irradiated MDA-MB-231 breast cancer cells by a single and fractioned 10 Gray (Gy) 137Cs γ-radiation were analyzed by ptotein-protein interaction (PPI) network analysis by Cytoscape software via STRING database. The network were analyzed by using Network analyzer to characterized the central genes. Action map was mapped for the queried genes and the added neighbors. via CluePedia-STRING ACTIONS-v10.5- 20.11.2017.Results: The 14 differentially expressed proteins (DEPs) plus 10 neighbors were interacted to construct a network. Among the 14 queried DEPs FN1, CSPG4, LRP1, GSN, RTN4, and CTSD were highlighted as a complex set in analysis.  Analysis revealed that SRC as an added neighbor were activated by the critical DEPs. Activation of the other oncogene as like AKT1 also were determined.Conclusion: The results indicate that the inhibition of SRC activity or the inhibition of its activators is a useful function of breast cancer RT.

Game-Theoretic Spectrum Trading in RF Relay-Assisted Free-Space Optical Communications

This work proposes a novel hybrid RF/FSO system based on a game theoretic spectrum trading process. It is assumed that no RF spectrum is preallocated to the FSO link and only when the link availability is severely impaired by the infrequent adverse weather conditions, i.e. fog, etc., the source can borrow a portion of licensed RF spectrum from one of the surrounding RF nodes. Using the leased spectrum, the source establishes a dual-hop RF/FSO hybrid link to maintain its throughout to the destination. The proposed system is considered to be both spectrum- and power-efficient. A market-equilibrium-based pricing process is proposed for the spectrum trading between the source and RF nodes. Through extensive performance analysis, it is demonstrated that the proposed scheme can significantly improve the average capacity of the system, especially when the surrounding RF nodes are with low traffic loads. In addition, the system benefits from involving more RF nodes into the spectrum trading process by means of diversity, particularly when the surrounding RF nodes have high probability of being in heavy traffic loads. Furthermore, the application of the proposed system in a realistic scenario is presented based on the weather statistics in the city of Edinburgh, UK. It is demonstrated that the proposed system can substantially enhance the link availability towards the carrier-class requirement

Renewable Energy Distribution in Cooperative Cellular Networks with Energy Harvesting

In this paper, we propose a novel online centralized algorithm for energy cooperation among energy harvesting capable base stations (BSs) in multi-tier cellular networks. BSs are connected to the non-renewable source used by a BS when it cannot harvest sufficient energy to serve its connected users. BSs with the extra harvested energy operate cooperatively and share their surplus energy with BSs that have not harvested sufficient energy. To stimulate BSs with energy deficit to use the shared energy of other BSs, an energy pricing framework is established which results in reducing of the non-renewable energy consumption. We formulate the problem of maximizing the fairness of the renewable energy distribution. The closed-form of energy share given to each BS with energy deficit is found, by which the renewable energy distribution fairness is maximized. Energy is shared by the smart grid. The problem of minimizing the smart grid usage cost for distributing energy is formulated and an online algorithm is proposed to approximate its solution. Simulation results show that the approximate algorithm reduces the non-renewable energy consumption significantly and reduces the cost of smart grid usage near to the optimal solution

A Matching-Game-Based Energy Trading for Small Cell Networks with Energy Harvesting

Deploying small cells in cellular networks, as a technique for capacity and coverage enhancement, is an indispensable characteristic of future cellular networks. In this paper, a novel online decentralized algorithm for enabling energy trading in multitier cellular networks with selfish energy harvesting capable base stations (BSs) is proposed. A BS uses the non-renewable energy when it cannot harvest sufficient energy to serve its connected users. To minimize the non-renewable energy consumption, we establish a framework for trading energy such that BSs with energy deficit are stimulated to compensate their energy shortage with the extra harvested energy of other BSs. BSs with energy deficit are assigned to BSs with extra harvested energy by using matching theory. The extra harvested energy is distributed by the smart grid. Along with energy trades, BSs gain more profit and their utility functions enhance. Simulation results show that the waste of energy due to limited batteries and the non-renewable energy consumption decreases considerably when the proposed algorithm is applie