Water-Insoluble Polysaccharide Extracted from Poria cocos Alleviates Antibiotic-Associated Diarrhea Based on Regulating the Gut Microbiota in Mice.

Antibiotics are very effective in treating a variety of bacterial infections, while clinical overuse of antibiotics can lead to diseases such as antibiotic-associated diarrhea. Numerous studies have shown that natural polysaccharides can be used as prebiotics to alleviate antibiotic-associated diarrhea (AAD). Poria cocos is a medicinal and edible mushroom widely used for thousands of years in China, and our former study demonstrated that water-insoluble polysaccharide (PCY) has the potential prebiotic function. Therefore, we simulated the digestion and fermentation of PCY using feces from volunteers, and then administered it to C57BL/6 mice with AAD to study its effects on the gut microbiota and metabolites. The results indicated that PCY effectively alleviated the symptoms of AAD in mice, restored the intestinal barrier function, improved the content of short-chain fatty acids (SCFAs), decreased the level of inflammatory cytokines, and changed the structure of gut microbiota by increasing the relative abundance of norank_f__Muribaculaceae and unclassified_f__Lachnospiraceae, and decreasing that of Escherichia-Shigella, Staphylococcus and Acinetobacter. This study further demonstrated that PCY is an effective functional prebiotic for improving AAD disease, and provided a new avenue and insight for developing PCY as a functional food or prebiotic for alleviating gastrointestinal diseases.

A GIS-based method for modeling methane emissions from paddy fields by fusing multiple sources of data.

Quantification of regional methane (CH4) gas emission in the paddy fields is critical under climate warming. Mechanism models generally require numerous parameters while empirical models are too coarse. Based on the mechanism and structure of the widely used model CH4MOD, a GIS-based Regional CH4 Emission Calculation (GRMC) method was put forward by introducing multiple sources of remote sensing images, including MOD09A1, MOD11A2, MOD15A2H as well as local water management standards. The stress of soil moisture condition (f(water)) on CH4 emissions was quantified by calculating the redox potential (Eh) from days after flooding or falling dry. The f(water)-t curve was calculated under different exogenous organic matter addition. Combining the f(water)-t curve with local water management standards, the seasonal variation of f(water) was obtained. It was proven that f(water) was effective in reflecting the regulation role of soil moisture condition. The GRMC was tested at four Eddy Covariance (EC) sites: Nanchang (NC) in China, Twitchell (TWT) in the USA, Castellaro (CAS) in Italy and Cheorwon (CRK) in Korea and has been proven to well track the seasonal dynamics of CH4 emissions with R2 ranges of 0.738-0.848, RMSE ranges of 31.94-149.22 mg C/m2d and MBE ranges of -66.42- -14.79 mg C/m2d. The parameters obtained in Nanchang (NC) site in China were then applied to the Ganfu Plain Irrigation System (GFPIS), a typical rice planting area of China, to analyse the spatial-temporal variations of CH4 emissions. The total CH4 emissions of late rice in the GFPIS from 2001 to 2013 was in the range of 14.47-20.48 (103 t CH4-C). Ts caused spatial variation of CH4 production capacity, resulting in the spatial variability of CH4 emissions. Overall, the GRMC is effective in obtaining CH4 emissions from rice fields on a regional scale.

Fuzzy Logic-Based Geographic Routing Protocol for Dynamic Wireless Sensor Networks.

The geographic routing protocol only requires the location information of local nodes for routing decisions, and is considered very efficient in multi-hop wireless sensor networks. However, in dynamic wireless sensor networks, it increases the routing overhead while obtaining the location information of destination nodes by using a location server algorithm. In addition, the routing void problem and location inaccuracy problem also occur in geographic routing. To solve these problems, a novel fuzzy logic-based geographic routing protocol (FLGR) is proposed. The selection criteria and parameters for the assessment of the next forwarding node are also proposed. In FLGR protocol, the next forward node can be selected based on the fuzzy location region of the destination node. Finally, the feasibility of the FLGR forwarding mode is verified and the performance of FLGR protocol is analyzed via simulation. Simulation results show that the proposed FLGR forwarding mode can effectively avoid the routing void problem. Compared with existing protocols, the FLGR protocol has lower routing overhead, and a higher packet delivery rate in a sparse network.