Gold nanoparticles have been used as effective surface-enhanced Raman spectroscopy (SERS) substrates for decades. However, the origin of the enhancement and the effect of the size of nanoparticles still need clarification. Here, gold nanoparticles with different sizes from 17 to 80 nm were synthesized and characterized, and their SERS enhancement toward both 4-aminothiophenol and 4-nitrothiophenol was examined. For the same number of nanoparticles, the enhancement factor generated from the gold nanoparticles increases as the size of nanoparticles increases. Interestingly, when the concentration of gold or the total surface area of gold nanoparticles was kept the same, the optimal size of gold nanoparticles was found out to be around 50 nm when the enhancement factor reached a maximum. The same size effect was observed for both 4-aminothiophenol and 4-nitrothiophenol, which suggests that the conclusions drawn in this study might also be applicable to other adsorbates during SERS measurements.

Background and AimIncreasing evidence has indicated a close association of host-gut flora metabolic interaction with obesity. Flos Lonicera, a traditional herbal medicine, is used widely in eastern Asia for the treatment of various disorders. The aim of this study was to evaluate whether unfermented or fermented formulations of Flos Lonicera could exert a beneficial impact to combat obesity and related metabolic endotoxemia.MethodsObesity and metabolic endotoxemia were induced separately or together in rats through feeding a eight-week high fat diet either alone (HFD control group) or in combination with a single LPS stimulation (intraperitoneal injection, 0.75 mg/kg) (LPS control group). While, the mechanism of action of the Lonicera formulations was explored in vitro using RAW 264.7 and HCT 116 cell lines as models.ResultsIn cell-based studies, treatment with both unfermented Flos Lonicera (UFL) and fermented Flos Lonicera (FFL) formulations resulted in suppression of LPS-induced NO production and gene expression of vital proinflammatory cytokines (TNF-α, COX-2, and IL-6) in RAW 264.7 cells, reduced the gene expression of zonula occludens (ZO)-1 and claudin-1, and normalized trans epithelial electric resistance (TEER) and horseradish peroxidase (HRP) flux in LPS-treated HCT-116 cells. In an animal study, treatment of HFD as well as HFD+LPS groups with UFL or FFL resulted in a notable decrease in body and adipose tissue weights, ameliorated total cholesterol, HDL, triglyceride, aspartate transaminase and endotoxin levels in serum, reduced the urinary lactulose/mannitol ratio, and markedly alleviated lipid accumulation in liver. In addition, exposure of HFD as well as HFD+LPS groups with UFL or FFL resulted in significant alteration of the distribution of intestinal flora, especially affecting the population of Akkermansia spp. and ratio of Bacteroidetes and Firmicutes.ConclusionThis evidence collectively demonstrates that Flos Lonicera ameliorates obesity and related metabolic endotoxemia via regulating distribution of gut flora and gut permeability.

For better performance over a noisy channel, mobile wireless networks transmit packets with forward error correction (FEC) code to recover corrupt bits without retransmission. The static determination of the FEC code size, however, degrades their performance since the evaluation of the underlying channel state is hardly accurate and even widely varied. Our measurements over a wireless sensor network, for example, show that the average bit error rate (BER) per second or per minute continuously changes from 0 up to 10 −3 . Under this environment, wireless networks waste their bandwidth since they can't deterministically select the appropriate size of FEC code matching to the fluctuating channel BER.This paper proposes an adaptive FEC technique called adaptive FEC code control (AFECCC), which dynamically tunes the amount of FEC code per packet based on the arrival of acknowledgement packets without any specific information such as signal to noise ratio (SNR) or BER from receivers. Our simulation experiments indicate that AFECCC performs better than any static FEC algorithm and some conventional dynamic hybrid FEC/ARQ algorithms when wireless channels are modeled with two-state Markov chain, chaotic map, and traces collected from real sensor networks. Finally, AFECCC implemented in sensor motes achieves better performance than any static FEC algorithm.Index Terms: Adaptive forward error correction (FEC) algorithm, wireless mobile sensor networks.

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