Wind and sand control by an oasis protective system: a case from the southeastern edge of the Tengger Desert, China - Yun-hu Xie; Xiao-hong Dang; Zhong-ju Meng; Hong-tao Jiang; Xiao-jia Li; Rui-ping Zhou; Dan-dan Zhou; Xiao-xi Liu; Jing Ding; Xue-qin Wu; Yu-hao Wang; Chun-xing Hai; et al. (Journal of Mountain Science, 2019)

Carbon Monoxide Attenuates High Salt-Induced Hypertension While Reducing Pro-inflammatory Cytokines and Oxidative Stress in the Paraventricular Nucleus - Dong-Dong Zhang; Yan-Feng Liang; Jie Qi; Kai B. Kang; Xiao-Jing Yu; Hong-Li Gao; Kai-Li Liu; Yan-Mei Chen; Xiao-Lian Shi; Guo-Rui Xin; Li-Yan Fu; Yu-Ming Kang; et al. (Cardiovascular Toxicology, 2019)

Comprehensive assessment of Coupled Model Intercomparison Project Phase 5 global climate models using observed temperature and precipitation over mainland Southeast Asia - Jing Li; Zhaofei Liu; Zhijun Yao; Rui Wang (International Journal of Climatology, 2019)
In this study, the performances of 31 global climate models (GCMs) from Coupled Model Intercomparison Project Phase 5 (CMIP5) were evaluated using observed temperature and precipitation data sets for mainland Southeast Asia (MSA). In addition, the technique for order preference by similarity to ideal solution model (TOPSIS), which is an effective multi‐objective decision method and has been widely applied in systems engineering, was used to comprehensively evaluate the GCMs on a regional scale. The meteorological variables employed included monthly mean, maximum, and minimum air temperature series and annual/seasonal precipitation during the period 1961–2004. Results showed the overall C i values ranged from 0.56 to 0.80. Overall, ACCESS1.0, HadGEM2‐A, HadGEM2‐CC, and CESM1 (BGC) performed better than the other models with respect to air temperature and precipitation over MSA. For meteorological variables, the C i of extreme temperature by GCMs was 0.65 and higher than mean temperature at 0.61. The performance of GCMs in simulating precipitation during wet season was superior to that for annual and dry season precipitation. With respect to evaluation indicators, most of the GCMs assessed in this study failed to capture observed mean annual air temperature and annual precipitation (they underestimated annual air temperature and overestimated mean annual precipitation). When evaluating the performance of the GCMs with respect to reproducing individual climatic variables, the use of various statistical evaluation criteria provided inconsistent results. These results demonstrate the need to consider the influence of different statistical eigenvalues and to employ multiple indicators when possible to enable a comprehensive evaluation of GCMs. The results of this study provide useful information for climate change, water resource, and agricultural management research in MSA.

The relief effects of organic acids on Scirpus triqueter L. under pyrene–lead stress - Xinying Zhang; Jing Chen; Xiaoyan Liu; Xueping Chen; Lu Liu; Yinghu Niu; Rui Wang (Environmental Science and Pollution Research, 2019)

Spatial distribution, source identification, and potential risk assessment of toxic contaminants in surface waters from Yulin, China - Jing Liu; Yongjun Liu; Aining Zhang; Yu Liu; Ying Zhu; Ming Guo; Rui Zhang (Environmental Monitoring and Assessment, 2019)

Transcriptome sequencing to reveal the genetic regulation of leaf margin variation at early stage in birch - Xiuyan Bian; Chang Qu; Manman Zhang; Yidi Li; Rui Han; Jing Jiang; Guifeng Liu (Tree Genetics & Genomes, 2019)

Gut microbiota in patients after surgical treatment for colorectal cancer - Ye Jin; Yang Liu; Lei Zhao; Fuya Zhao; Jing Feng; Shengda Li; Huinan Chen; Jiayu Sun; Biqiang Zhu; Rui Geng; Yunwei Wei (Environmental Microbiology, 2019)
Summary Colorectal cancer (CRC) is a common disease worldwide that is strongly associated with the gut microbiota. However, little is known regarding the gut microbiota after surgical treatment. 16S rRNA gene sequencing was used to evaluate differences in gut microbiota among colorectal adenoma patients, CRC patients, CRC postoperative patients and healthy controls by comparing gut microbiota diversity, overall composition and taxonomic signature abundance. The gut microbiota of CRC patients, adenoma patients and healthy controls developed in accordance with the adenoma‐carcinoma sequence, with impressive shifts in the gut microbiota before or during the development of CRC. The gut microbiota of postoperative patients and CRC patients differed significantly. Subdividing CRC postoperative patients according to the presence or absence of newly developed adenoma which based on the colonoscopy findings revealed that the gut microbiota of newly developed adenoma patients differed significantly from that of clean intestine patients and was more similar to the gut microbiota of carcinoma patients than to the gut microbiota of healthy controls. The alterations of the gut microbiota between the two groups of postoperative patients corresponded to CRC prognosis. More importantly, we used the different gut microbiota as biomarkers to distinguish postoperative patients with or without newly developed adenoma, achieving an AUC value of 0.72. These insights on the changes in the gut microbiota of CRC patients after surgical treatment may allow the use of the microbiota as non‐invasive biomarkers for the diagnosis of newly developed adenomas and to help prevent cancer recurrence in postoperative patients.

Postprandial change in glucose metabolism at the molecular level in the adipose tissue of omnivorous GIFT Oreochromis niloticus - Jing-Yun Feng; Qin-Qin Liu; Hang-Zhong Xu; Rui-Hong Chen; Li Luo; Shi-Mei Lin; Yong-Jun Chen; De-Shou Wang (Fisheries Science, 2019)