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Soft-shelled turtle (Trionyx sinensis) is one of the most important aquacultural species in China. In recent years, an infectious disease frequently occurred in soft-shelled turtle, which exhibited similar symptoms, including craned necks, ulcerated pores on shells, hemorrhagic intestinal mucosa and heart, intumescent liver and spleen. In this study, a Gram-positive rod bacterial strain BC12 with vigorous hemolytic and lipolytic activity isolated from the sick soft-shelled turtles. Strain BC12 was identified as Bacillus cereus via 16S rRNA phylogenetic analysis and species-specific gene amplification. The juvenile soft-shelled turtles challenged with B. cereus BC12 exhibited similar symptoms as those natural infections, and the 50% lethal dose (LD 50) is 3.89 × 105 colony-forming unit (CFU). Pure B. cereus re-isolated from the heart and liver of turtles infected with BC12. Noticeable pathological changes, including necrosis in the heart and liver and damage in the germinal center of the spleen, were observed in the B. cereus BC12 infected turtles for the first time. Antibiotics susceptibility assay showed that B. cereus BC12 is sensitive to the aminoglycosides, polypeptides, most of the cephalosporins and quinolones, which might be chosen as candidates to prevent and treat B. cereus infection. • An infectious disease frequently occurred in soft-shelled turtles in recent years. • Bacillus cereus strain BC12 was identified as the pathogenic agent of the outbreak in a turtle farm in Hubei province. • Turtles infected with B. cereus strain BC12 exhibited significant pathological changes in the heart, liver and spleen. • B. cereus strain BC12 is sensitive to the aminoglycosides, polypeptides, most of the cephalosporins and quinolones. [ABSTRACT FROM AUTHOR]

Landslide susceptibility assessment has become the focus of geological disaster research to strengthen disaster prevention and mitigation. Landslide disasters frequently occur in the Hubei section of the Three Gorges Reservoir Area (TGRA), with some potential landslides located along the highway, which brings risks to highway engineering, maintenance and transportation. In this paper, a comprehensive landslide susceptibility evaluation indicator framework with three dimensions and 12 factors was established, and an integrated approach was applied to evaluate the landslide susceptibility level, which combined weights-of-evidence model, seven clustering algorithms, three quality evaluation indices and the elbow method. To validate the effectiveness of the methods, five objective measures were employed for evaluation. The 69 samples along the highway were used for training, and another 30 samples were collected for validation. The results showed that the landslide susceptibility level of potential landslides can be effectively predicted by K-means algorithm. It was found that the landslide susceptibility for each cluster had significant differences, which were mainly reflected in natural induced factors, followed by human induced factors, while the slope structure showed little differences; the areas with low landslide susceptibility appeared sheet distribution, while the areas with high landslide susceptibility showed zonal distribution along the Yangtze River and its tributaries. This study developed a comprehensive indicator system and method for landslide susceptibility assessment along highways and provided a reference for the risk evaluation and prevention management. • The landslide susceptibility evaluation indicators along the highways are provided. • The methods based on GIS and machine learning are proposed. • The landslide susceptibility in the study area has obvious regional characteristics. • Specific landslide prevention suggestions are put forward. [ABSTRACT FROM AUTHOR]