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Unplanned exposure to radiation can cause side effects on high-risk individuals; meanwhile, radiotherapies can also cause injury on normal cells and tissues surrounding the tumor. Besides the direct radiation damage, most of the ionizing radiation- (IR-) induced injuries were caused by generation of reactive oxygen species (ROS). Human mesenchymal stem cells (hMSCs), which possess self-renew and multilineage differentiation capabilities, are a critical population of cells to participate in the regeneration of IR-damaged tissues. Therefore, it is imperative to search effective radioprotectors for hMSCs. This study was to demonstrate whether natural source ginger oleoresin would mitigate IR-induced injuries in human mesenchymal stem cells (hMSCs). We demonstrated that ginger oleoresin could significantly reduce IR-induced cytotoxicity, ROS generation, and DNA strand breaks. In addition, the ROS-scavenging mechanism of ginger oleoresin was also investigated. The results showed that ginger oleoresin could induce the translocation of Nrf2 to cell nucleus and activate the expression of cytoprotective genes encoding for HO-1 and NQO-1. It suggests that ginger oleoresin has a potential role of being an effective antioxidant and radioprotective agent.

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Climate change significantly affects geographic distribution of plants pests and diseases worldwide. Understanding the influence of future climate change on the suitable areas of Diaphorina citri (Kuwayama) in our country and taking timely countermeasures are crucial for improving the effectiveness of control of pest. Based on the occurrence points of D. citri and the selected environmental variables, the potential suitable areas of this pest under climate change scenarios in China were predicted by using MaxEnt and GIS tools. Our results showed that the higly suitable area were mainly located in Guangxi, Guangdong, Fujian, Southern Zhejiang, Southern Jiangxi, Eastern Hunan, Southwestern Guizhou, and the area was 43.7 × 104 km2. Areas of moderate and low suitability were centered on areas of high suitability and radiate to the North successively, with an area of 59.28 × 104 km2 and 93.46 × 104 km2 respectively. From current to 2070 s, the areas of the highly suitable areas will increase, and the geometric center of the highly and total suitable areas will move to north under three climate change scenarios.

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Soil is an important environment for crop growth. Quick and accurately access to soil nutrient content information is a prerequisite for scientific fertilization. In this work, hyperspectral imaging (HSI) technology was applied for the classification of soil types and the measurement of soil total nitrogen (TN) content. A total of 183 soil samples collected from Shangyu City (People’s Republic of China), were scanned by a near-infrared hyperspectral imaging system with a wavelength range of 874–1734 nm. The soil samples belonged to three major soil types typical of this area, including paddy soil, red soil and seashore saline soil. The successive projections algorithm (SPA) method was utilized to select effective wavelengths from the full spectrum. Pattern texture features (energy, contrast, homogeneity and entropy) were extracted from the gray-scale images at the effective wavelengths. The support vector machines (SVM) and partial least squares regression (PLSR) methods were used to establish classification and prediction models, respectively. The results showed that by using the combined data sets of effective wavelengths and texture features for modelling an optimal correct classification rate of 91.8%. could be achieved. The soil samples were first classified, then the local models were established for soil TN according to soil types, which achieved better prediction results than the general models. The overall results indicated that hyperspectral imaging technology could be used for soil type classification and soil TN determination, and data fusion combining spectral and image texture information showed advantages for the classification of soil types.