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Bacillus velezensis LPL061, which shows strong exopolysaccharide (EPS) producing capacity, was isolated from carnations in Beijing, China. The complete genome of LPL061 comprised a single circular chromosome (3,907,268 bp; G+C content of 46.7%) with 3,737 coding DNA sequences, 26 rRNA, and 89 tRNA. According to genome analysis, 12 protein-coding genes which related to polysaccharide biosynthesis in LPL061 were identified. Comparative genome analysis revealed that the EPS biosynthetic gene cluster was relatively conserved among Bacillus species. EPS showed approximately 60% inhibitory activity on the α-glucosidase at 100 μg/mL. The results of quantitative reverse transcription PCR further demonstrated that compared to insulin-resistant model with insulin (500 μg/mL) (without EPS treatment), the insulin-resistant HepG2 cells treated with EPS decreased the expression of phosphoenolpyruvate carboxykinase (PEPCK) from 4.425 to 0.1587, glucose-6-phosphatase (G6Pase) decreased from 4.272 to 0.1929, and glycogen synthase kinase3β (GSK(3)β) decreased from 2.451 to 0.993, respectively. Meanwhile, EPS treatment increased GS expression and resulted in intracellular glycogen concentration increased from 28.30% to 86.48%, which further supported that EPS form LPL061 could reduce the concentration of blood glucose effectively. These results could be beneficial for better understanding of the hypoglycemic mechanism of B. velezensis LPL061 EPS and developing an EPS-based anti-diabetic agent in the future. [ABSTRACT FROM AUTHOR]

Urban black and odorous water (BOW) is a serious global environmental problem. Since these waters are often narrow rivers or small ponds, the detection of BOW waters using traditional satellite data and algorithms is limited both by a lack of spatial resolution and by imperfect retrieval algorithms. In this paper, we used the Chinese high-resolution remote sensing satellite Gaofen-2 (GF-2, 0.8 m). The atmospheric correction showed that the mean absolute percentage error of the derived remote sensing reflectance ($R_{\mathrm {rs}}$) in visible bands is 25.19%. We first measured $R_{\mathrm {rs}}$ spectra of two classes of BOW [BOW with high concentrations of iron (II) sulfide, i.e., BOW1 and BOW with high concentrations of total suspended matter, i.e., BOW2] and ordinary water in Shenyang. Then, in situ $R_{\mathrm {rs}}$ data were converted into $R_{\mathrm {rs}}$ corresponding to the wide GF-2 bands using the spectral response functions. We used the converted $R_{\mathrm {rs}}$ data to calculate several band combinations, including the baseline height, [ $R_{\mathrm {rs}}$ (green) $- R_{\mathrm {rs}}$ (red))/($R_{\mathrm {rs}}$ (green) $+ R_{\mathrm {rs}}$ (red)], and the color purity on a Commission Internationale de L’Eclairage (CIE) chromaticity diagram. The color purity was found to be the best index to extract BOW from ordinary water. Then, $R_{\mathrm {rs}}$ (645) was applied to categorize BOW into BOW1 and BOW2. We applied the algorithm to two synchronous GF-2 images. The recognition accuracy of BOW2 and ordinary water are both 100%. The extracted river water type near Weishanhu Road was BOW1, which agreed well with ground truth. The algorithm was further applied to other GF-2 data for Shenyang and Beijing. [ABSTRACT FROM AUTHOR]