Structure Characterization and Anti-exercise Fatigue Effect of Selenium Polysaccharide from Morchella esculenta

Objective: To clarify the structural characteristics of selenium polysaccharides from Morchella esculenta, and their ameliorative effects on exercise-fatigued rats. Methods: Polysaccharides from Morchella esculenta were extracted using ultrasound-assisted hot water extraction. Purified polysaccharides (Msp-1) were obtained through DEAE cellulose column chromatography and Sephadex G-100 column chromatography. Nitric acid-sodium selenite method was used to prepare selenized polysaccharide (Se-Msp1) from purified polysaccharides. The structures of Msp-1 and Se-Msp1 were characterized. The swimming time of rats was measured by exhaustive swimming test, and the weighted swimming model was established at the same time. The rats were randomly divided into quiet control group, exercise fatigue control group, positive control group (salidroside, 100 mg/kg), normal polysaccharide group (Msp-1, 100 mg/kg), and selenized polysaccharide low, medium, and high dose groups (Se-Msp1, 50, 100, and 200 mg/kg, respectively). The rats were orally administered with 0.1 mL/(10 g·bw) for 5 weeks. The content of blood lactic acid (BLA), blood urea nitrogen (BUN), hepatic glycogen (HG), and muscular glycogen (MG), as well as malondialdehyde (MDA) content, superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH-Px) activities in skeletal muscle mitochondria, were measured to evaluate the anti-exercise fatigue effect of Se-Msp1. Results: The major component of the purified polysaccharides from Morchella esculenta was Msp-1, which accounted for 85.25%. Infrared spectroscopy showed that the heteromeric carbon of Se-Msp1 was α configuration, and characteristic absorption peaks of selenium were observed, indicating that Se-Msp1 was successfully selenided. The Se content in Se-Msp1 was 9.56 mg/g, the polysaccharide content was 56.34%, with uronic acid content of 36.82%, and the weight average molecular weight was 3.482×105 Da, particle size of 384.71 nm, zeta potential was −45.78 mV, indicating that Se-Msp1 had a high selenium content and good stability. The monosaccharide composition of Se-Msp1 consisted of mannose, glucose, galactose, galacturonic acid, and rhamnose, with molar ratios of 1:0.42:3.57:3.34:1.86. The anti fatigue results of rats showed that compared with the control group (Con), both Msp-1 and Se-Msp1 significantly increased the exhausted swimming time (P<0.01), demonstrating good anti fatigue effects. The weighted swimming model results of rats showed that compared with the exercise fatigue control group, the content of hepatic glycogen and muscular glycogen in the low, middle and high dose groups of Se-Msp1 were significantly increased (P<0.01), while the blood lactic acid and blood urea nitrogen were significantly reduced (P<0.01). Se-Msp1 at low, medium, and high doses significantly increased the HG and MG content (P<0.01), and reduced the levels of BLA and BUN (P<0.01). In addition, The MDA content in skeletal muscle mitochondria were also significantly reduced (P<0.01), and the antioxidant enzyme activities (SOD, CAT, GSH Px) were significantly increased (P<0.01), and Se-Msp1 exhibited higher antioxidant activity than Msp-1. Conclusion: In summary, the prepared selenium rich polysaccharide from Morchella esculenta (Se-Msp1) had a stable structure and high anti-exercise fatigue activity, providing a theoretical basis for the development of selenium rich polysaccharide products from Morchella esculenta

On the Temporal-spatial Analysis of Estimating Urban Traffic Patterns Via GPS Trace Data of Car-hailing Vehicles

Car-hailing services have become a prominent data source for urban traffic studies. Extracting useful information from car-hailing trace data is essential for effective traffic management, while discrepancies between car-hailing vehicles and urban traffic should be considered. This paper proposes a generic framework for estimating and analyzing urban traffic patterns using car-hailing trace data. The framework consists of three layers: the data layer, the interactive software layer, and the processing method layer. By pre-processing car-hailing GPS trace data with operations such as data cutting, map matching, and trace correction, the framework generates tensor matrices that estimate traffic patterns for car-hailing vehicle flow and average road speed. An analysis block based on these matrices examines the relationships and differences between car-hailing vehicles and urban traffic patterns, which have been overlooked in previous research. Experimental results demonstrate the effectiveness of the proposed framework in examining temporal-spatial patterns of car-hailing vehicles and urban traffic. For temporal analysis, urban road traffic displays a bimodal characteristic while car-hailing flow exhibits a 'multi-peak' pattern, fluctuating significantly during holidays and thus generating a hierarchical structure. For spatial analysis, the heat maps generated from the matrices exhibit certain discrepancies, but the spatial distribution of hotspots and vehicle aggregation areas remains similar

A Group Decision Making Approach Considering Self-Confidence Behaviors and Its Application in Environmental Pollution Emergency Management

Self-confidence as one of the human psychological behaviors has important influence on emergency management decision making, which has been ignored in existing methods. To fill this gap, we dedicate to design a group decision making approach considering self-confidence behaviors and apply it to the environmental pollution emergency management. In the proposed method, the self-confident fuzzy preference relations are utilized to express experts’ evaluations. This new type of preference relations allow experts to express multiple self-confidence levels when providing their evaluations, which can deal with the self-confidence of them well. To apply the proposed group decision making method to environmental pollution emergency management, a novel determination of the decision weights of experts is given combining the subjective and objective weights. The subjective weight can be directly assigned by organizer, while the objective weight is determined by the self-confidence degree of experts on their evaluations. Afterwards, by utilizing the weighted averaging operator, the individuals’ evaluations can be aggregated into a collective one. To do that, some operational laws for self-confident fuzzy preference relations are introduced. And then, a self-confidence score function is designed to get the best solution for environmental pollution emergency management. Finally, some analyses and discussions show that the proposed method is feasible and effective.The work was supported by National Key R&D Program of China (Grant No. 2017YFC0404600), National Natural Science Foundation of China (NSFC) under Grants (71871085, 71471056), Qing Lan Project of Jiangsu Province. Additionally, Xia Liu andWeike Zhang gratefully acknowledge the financial support of the China Scholarship Council (Nos. 201706710084, 201806240231)

Size Effect on the Magnetic Phase in Sr\u3csub\u3e4\u3c/sub\u3eRu\u3csub\u3e3\u3c/sub\u3eO\u3csub\u3e10\u3c/sub\u3e

High quality Sr4Ru3O10 nanoflakes are obtained by the scotch tape-based micro-mechanical exfoliation method. The metamagnetic transition temperature Tmflake is found to decrease in line with the decrease of thickness, while the ferromagnetic (FM) phase, the ordinary, and anomalous Hall effects (OHE and AHE) are independent on the thickness of the flake. Analysis of the data demonstrates that the AHE reflects the FM nature of Sr4Ru3O10, and the decrease of thickness favors the Ru moments aligned in the ab-plane, which induces a decrease of the metamagnetic transition temperature compared with the bulk

PrivateRec: Differentially Private Training and Serving for Federated News Recommendation

Privacy protection is an essential issue in personalized news recommendation, and federated learning can potentially mitigate the privacy concern by training personalized news recommendation models over decentralized user data.For a theoretical privacy guarantee, differential privacy is necessary. However, applying differential privacy to federated recommendation training and serving conventionally suffers from the unsatisfactory trade-off between privacy and utility due to the high-dimensional characteristics of model gradients and hidden representations. In addition, there is no formal privacy guarantee for both training and serving in federated recommendation. In this paper, we propose a unified federated news recommendation method for effective and privacy-preserving model training and online serving with differential privacy guarantees. We first clarify the notion of differential privacy over users' behavior data for both model training and online serving in the federated recommendation scenario. Next, we propose a privacy-preserving online serving mechanism under this definition with differentially private user interest decomposition. More specifically, it decomposes the high-dimensional and privacy-sensitive user embedding into a combination of public basic vectors and adds noise to the combination coefficients. In this way, it can avoid the dimension curse and improve the utility by reducing the required noise intensity for differential privacy. Besides, we design a federated recommendation model training method with differential privacy, which can avoid the dimension-dependent noise for large models via label permutation and differentially private attention modules. Experiments on real-world news recommendation datasets validate the effectiveness of our method in achieving a good trade-off between privacy protection and utility for federated news recommendations

Comprehensive analysis of SSRs and database construction using all complete gene-coding sequences in major horticultural and representative plants

Simple sequence repeats (SSRs) are one of the most important genetic markers and widely exist in most species. Here, we identified 249,822 SSRs from 3,951,919 genes in 112 plants. Then, we conducted a comprehensive analysis of these SSRs and constructed a plant SSR database (PSSRD). Interestingly, more SSRs were found in lower plants than in higher plants, showing that lower plants needed to adapt to early extreme environments. Four specific enriched functional terms in the lower plant Chlamydomonas reinhardtii were detected when it was compared with seven other higher plants. In addition, Guanylate_cyc existed in more genes of lower plants than of higher plants. In our PSSRD, we constructed an interactive plotting function in the chart interface, and users can easily view the detailed information of SSRs. All SSR information, including sequences, primers, and annotations, can be downloaded from our database. Moreover, we developed Web SSR Finder and Batch SSR Finder tools, which can be easily used for identifying SSRs. Our database was developed using PHP, HTML, JavaScript, and MySQL, which are freely available at http://www.pssrd.info/. We conducted an analysis of the Myb gene families and flowering genes as two applications of the PSSRD. Further analysis indicated that whole-genome duplication and whole-genome triplication played a major role in the expansion of the Myb gene families. These SSR markers in our database will greatly facilitate comparative genomics and functional genomics studies in the future

Effect of symbiotic fungi-Armillaria gallica on the yield of Gastrodia elata Bl. and insight into the response of soil microbial community

Armillaria members play important roles in the nutrient supply and growth modulation of Gastrodia elata Bl., and they will undergo severe competition with native soil organisms before colonization and become symbiotic with G. elata. Unraveling the response of soil microbial organisms to symbiotic fungi will open up new avenues to illustrate the biological mechanisms driving G. elata’s benefit from Armillaria. For this purpose, Armillaria strains from four main G. elata production areas in China were collected, identified, and co-planted with G. elata in Guizhou Province. The result of the phylogenetic tree indicated that the four Armillaria strains shared the shortest clade with Armillaria gallica. The yields of G. elata were compared to uncover the potential role of these A. gallica strains. Soil microbial DNA was extracted and sequenced using Illumina sequencing of 16S and ITS rRNA gene amplicons to decipher the changes of soil bacterial and fungal communities arising from A. gallica strains. The yield of G. elata symbiosis with the YN strain (A. gallica collected from Yunnan) was four times higher than that of the GZ strain (A. gallica collected from Guizhou) and nearly two times higher than that of the AH and SX strains (A. gallica collected from Shanxi and Anhui). We found that the GZ strain induced changes in the bacterial community, while the YN strain mainly caused changes in the fungal community. Similar patterns were identified in non-metric multidimensional scaling analysis, in which the GZ strain greatly separated from others in bacterial structure, while the YN strain caused significant separation from other strains in fungal structure. This current study revealed the assembly and response of the soil microbial community to A. gallica strains and suggested that exotic strains of A. gallica might be helpful in improving the yield of G. elata by inducing changes in the soil fungal community

Knowledge, attitudes and practices (KAP) relating to avian influenza in urban and rural areas of China

<p>Abstract</p> <p>Background</p> <p>Studies have revealed that visiting poultry markets and direct contact with sick or dead poultry are significant risk factors for H5N1 infection, the practices of which could possibly be influenced by people's knowledge, attitudes and practices (KAPs) associated with avian influenza (AI). To determine the KAPs associated with AI among the Chinese general population, a cross-sectional survey was conducted in China.</p> <p>Methods</p> <p>We used standardized, structured questionnaires distributed in both an urban area (Shenzhen, Guangdong Province; n = 1,826) and a rural area (Xiuning, Anhui Province; n = 2,572) using the probability proportional to size (PPS) sampling technique.</p> <p>Results</p> <p>Approximately three-quarters of participants in both groups requested more information about AI. The preferred source of information for both groups was television. Almost three-quarters of all participants were aware of AI as an infectious disease; the urban group was more aware that it could be transmitted through poultry, that it could be prevented, and was more familiar with the relationship between AI and human infection. The villagers in Xiuning were more concerned than Shenzhen residents about human AI viral infection. Regarding preventative measures, a higher percentage of the urban group used soap for hand washing whereas the rural group preferred water only. Almost half of the participants in both groups had continued to eat poultry after being informed about the disease.</p> <p>Conclusions</p> <p>Our study shows a high degree of awareness of human AI in both urban and rural populations, and could provide scientific support to assist the Chinese government in developing strategies and health-education campaigns to prevent AI infection among the general population.</p