Ningxia University

About: Ningxia University is a education organization based out in Yinchuan, China. It is known for research contribution in the topics: Catalysis & Adsorption. The organization has 5446 authors who have published 4714 publications receiving 42724 citations. The organization is also known as: Níngxià Dàxué.

Prevalence of chronic kidney disease in China: a cross-sectional survey

Abstract: Summary Background The prevalence of chronic kidney disease is high in developing countries. However, no national survey of chronic kidney disease has been done incorporating both estimated glomerular filtration rate (eGFR) and albuminuria in a developing country with the economic diversity of China. We aimed to measure the prevalence of chronic kidney disease in China with such a survey. Methods We did a cross-sectional survey of a nationally representative sample of Chinese adults. Chronic kidney disease was defined as eGFR less than 60 mL/min per 1·73 m 2 or the presence of albuminuria. Participants completed a lifestyle and medical history questionnaire and had their blood pressure measured, and blood and urine samples taken. Serum creatinine was measured and used to estimate glomerular filtration rate. Urinary albumin and creatinine were tested to assess albuminuria. The crude and adjusted prevalence of indicators of kidney damage were calculated and factors associated with the presence of chronic kidney disease analysed by logistic regression. Findings 50 550 people were invited to participate, of whom 47 204 agreed. The adjusted prevalence of eGFR less than 60 mL/min per 1·73 m 2 was 1·7% (95% CI 1·5–1·9) and of albuminuria was 9·4% (8·9–10·0). The overall prevalence of chronic kidney disease was 10·8% (10·2–11·3); therefore the number of patients with chronic kidney disease in China is estimated to be about 119·5 million (112·9–125·0 million). In rural areas, economic development was independently associated with the presence of albuminuria. The prevalence of chronic kidney disease was high in north (16·9% [15·1–18·7]) and southwest (18·3% [16·4–20·4]) regions compared with other regions. Other factors independently associated with kidney damage were age, sex, hypertension, diabetes, history of cardiovascular disease, hyperuricaemia, area of residence, and economic status. Interpretation Chronic kidney disease has become an important public health problem in China. Special attention should be paid to residents in economically improving rural areas and specific geographical regions in China. Funding The Ministry of Science and Technology (China); the Science and Technology Commission of Shanghai; the National Natural Science Foundation of China; the Department of Health, Jiangsu Province; the Sichuan Science and Technology Department; the Ministry of Education (China); the International Society of Nephrology Research Committee; and the China Health and Medical Development Foundation.

Multi-shelled hollow micro-/nanostructures

Abstract: Great progress has been made in the preparation and application of multi-shelled hollow micro-/nanostructures during the past decade. However, the synthetic methodologies and potential applications of these novel and interesting materials have not been reviewed comprehensively in the literature. In the current review we first describe different synthetic methodologies for multi-shelled hollow micro-/nanostructures as well as their compositional and geometric manipulation and then review their applications in energy conversion and storage, sensors, photocatalysis, and drug delivery. The correlation between the geometric properties of multi-shelled hollow micro-/nanostructures and their specific performance in relevant applications are highlighted. These results demonstrate that the geometry has a direct impact on the properties and potential applications of such materials. Finally, the emerging challenges and future development of multi-shelled hollow micro-/nanostructures are further discussed.

Crop pests and predators exhibit inconsistent responses to surrounding landscape composition

Abstract: The idea that noncrop habitat enhances pest control and represents a win-win opportunity to conserve biodiversity and bolster yields has emerged as an agroecological paradigm. However, while noncrop habitat in landscapes surrounding farms sometimes benefits pest predators, natural enemy responses remain heterogeneous across studies and effects on pests are inconclusive. The observed heterogeneity in species responses to noncrop habitat may be biological in origin or could result from variation in how habitat and biocontrol are measured. Here, we use a pest-control database encompassing 132 studies and 6,759 sites worldwide to model natural enemy and pest abundances, predation rates, and crop damage as a function of landscape composition. Our results showed that although landscape composition explained significant variation within studies, pest and enemy abundances, predation rates, crop damage, and yields each exhibited different responses across studies, sometimes increasing and sometimes decreasing in landscapes with more noncrop habitat but overall showing no consistent trend. Thus, models that used landscape-composition variables to predict pest-control dynamics demonstrated little potential to explain variation across studies, though prediction did improve when comparing studies with similar crop and landscape features. Overall, our work shows that surrounding noncrop habitat does not consistently improve pest management, meaning habitat conservation may bolster production in some systems and depress yields in others. Future efforts to develop tools that inform farmers when habitat conservation truly represents a win-win would benefit from increased understanding of how landscape effects are modulated by local farm management and the biology of pests and their enemies.

A comprehensive drought monitoring method integrating MODIS and TRMM data

Abstract: Drought is a complex hazard caused by the breaking of water balance and it has always an impact on agricultural, ecological and socio-economic spheres. Although the drought indices deriving from remote sensing data have been used to monitor meteorological or agricultural drought, there are no indices that can suitably reflect the comprehensive information of drought from meteorological to agricultural aspects. In this paper, the synthesized drought index (SDI) is defined as a principal component of vegetation condition index (VCI), temperature condition index (TCI) and precipitation condition index (PCI). SDI integrates multi-source remote sensing data from moderate resolution imaging spectroradiometer (MODIS) and tropical rainfall measuring mission (TRMM) and it synthesizes precipitation deficits, soil thermal stress and vegetation growth status in drought process. Therefore, this method is favorable to monitor the comprehensive drought. In our research, a heavy drought process was accurately explored using SDI in Shandong province, China from 2010 to 2011. Finally, a validation was implemented and its results show that SDI is not only strongly correlated with 3-month scales standardized precipitation index (SPI3), but also with variation of crop yield and drought-affected crop areas. It was proved that this index is a comprehensive drought monitoring indicator and it can contain not only the meteorological drought information but also it can reflect the drought influence on agriculture.

ParaAT: a parallel tool for constructing multiple protein-coding DNA alignments.

Abstract: Constructing multiple homologous alignments for protein-coding DNA sequences is crucial for a variety of bioinformatic analyses but remains computationally challenging. With the growing amount of sequence data available and the ongoing efforts largely dependent on protein-coding DNA alignments, there is an increasing demand for a tool that can process a large number of homologous groups and generate multiple protein-coding DNA alignments. Here we present a parallel tool – ParaAT that is capable of parallelly constructing multiple protein-coding DNA alignments for a large number of homologs. As testified on empirical datasets, ParaAT is well suited for large-scale data analysis in the high-throughput era, providing good scalability and exhibiting high parallel efficiency for computationally demanding tasks. ParaAT is freely available for academic use only at http://cbb.big.ac.cn/software.