Effect of grape polyphenols on selected inflammatory mediators

Grapes contain different polyphenols and might prevent inflammation by reducing Nitric Oxide (NO) inactivation through antioxidative enzymes. The aim of this article was to demonstrate the effects of grape polyphenols on the selected inflammatory mediators, such as interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-a), and high-sensitivity C-reactive protein (hs-CRP). To find papers assessing the effects of grape polyphenols on inflammatory mediators, electronic data bases, including ISI web of science, PubMed/Medline, SCOPUS, and Google scholar, were searched up to March 2019. Delphi checklist was used for evaluating the qualities of the included articles. The protocol was registered in PROSPERO (No. CRD42019116695). The mean changes in the intervention and control groups were calculated by subtracting the end values from the baselines. Then, the difference between the two changes was measured and utilized as the effect size in meta-analysis. 9 and 8 articles were included in the systematic review and meta-analysis, respectively. Our results indicated that grape polyphenols did not reduce hs-CRP levels, but omission of one article could lead to a significant reduction in hs-CRP (Weight Mean Difference (WMD): −0.54 mg/L, 95 % CI: −1.02, -0.06; P=0.026, I2=0.0 %). Regarding IL-6 and TNF-α, no significant changes were observed in the intervention compared to the control group (WMD: 0.04 pg/mL, 95 % CI: −0.02, 0.28; P=0.744, I2=0.0 %, WMD: -0.10 pg/mL, 95 % CI: −0.25, 0.05; P=0.183, I2=0.0 %, respectively). We found no beneficial effects of grape polyphenols on the selected inflammatory mediators. Still, more studies with higher doses of polyphenols, longer treatment durations, different sources of grape polyphenols, and larger numbers of participants are required

A General Approach for Minimizing the Maximum Interference of a Wireless Ad-Hoc Network in Plane

The interference reduction is one of the most important problems in the field of wireless sensor networks. Wireless sensor network elements are small mobile receiver and transmitters. The energy of processor and other components of each device is supplied by a small battery with restricted energy. One of the meanings that play an important role in energy consumption is the interference of signals. The interference of messages through a wireless network, results in message failing and transmitter should resend its message, thus the interference directly affect on the energy consumption of transmitter. This paper presents an algorithm which suggests the best subgraph for the input distribution of the nodes in the plane how the maximum interference of the proposed graph has the minimum value. The input of the application is the complete network graph, which means we know the cost of each link in the network graph. Without any lose of generality the Euclidean distance could be used as the weight of each link. The links are arranged and ranked according to their weights, in an iterative process the link which imposition minimum increase on the network interference with some extra conditions which is proposed in future sections, is added to resulting topology and is eliminated from list until all nodes are connected together. Experimental results show the efficiency of proposed algorithm not only for one dimensional known distribution like exponential node chain, but also for two dimensional distributions like two Exponential node chains and alpha-Spiral node chains