Non-point source nitrogen loss poses a risk to sustainable aquatic ecosystems. However, non-point sources, as well as impaired river segments with high nitrogen concentrations, are difficult to monitor and regulate be...Non-point source nitrogen loss poses a risk to sustainable aquatic ecosystems. However, non-point sources, as well as impaired river segments with high nitrogen concentrations, are difficult to monitor and regulate because of their diffusive nature, budget constraints, and resource deficiencies. For the purpose of catchment management, the Bayesian maximum entropy approach and spatial regression models have been used to explore the spatiotemporal patterns of non-point source nitrogen loss. In this study, a total of 18 sampling sites were selected along the river network in the Hujiashan Catchment. Over the time period of 2008e2012, water samples were collected 116 times at each site and analyzed for non-point source nitrogen loss. The morphometric variables and soil drainage of different land cover types were studied and considered potential factors affecting nitrogen loss. The results revealed that, compared with the approach using the Euclidean distance, the Bayesian maximum entropy approach using the river distance led to an appreciable 10.1% reduction in the estimation error, and more than 53.3% and 44.7% of the river network in the dry and wet seasons, respectively, had a probability of non-point source nitrogen impairment. The proportion of the impaired river segments exhibited an overall decreasing trend in the study catchment from 2008 to 2012, and the reduction in the wet seasons was greater than that in the dry seasons. High nitrogen concentrations were primarily found in the downstream reaches and river segments close to the residential lands. Croplands and residential lands were the dominant factors affecting non-point source nitrogen loss, and explained up to 70.7%of total nitrogen in the dry seasons and 54.7% in the wet seasons. A thorough understanding of the location of impaired river segments and the dominant factors affecting total nitrogen concentration would have considerable importance for catchment management.展开更多
To the Editor:Asialoglycoprotein receptor 1(ASGR1)is the major subunit of ASGR,it is predominantly expressed by liver parenchymal cells and relatively lower expression was found in peripheral blood monocytes.[1]A gene...To the Editor:Asialoglycoprotein receptor 1(ASGR1)is the major subunit of ASGR,it is predominantly expressed by liver parenchymal cells and relatively lower expression was found in peripheral blood monocytes.[1]A genetic study recently revealed that ASGR1 haploinsufficiency resulted from loss-of-function(LOF)variants was strongly associated with the pronounced reductions in serum total cholesterol(TC)and low-density lipoprotein cholesterol(LDL-C)levels,[2,3]suggesting that ASGR1 may play a key role in cholesterol metabolism.However,the function of ASGR1 remains largely unclear.This study was focused on the association of ASGR1 gene expression in monocytes and plasma cholesterol level.展开更多
基金supported by the Special Fund for Agro-Scientific Research in the Public Interest of China(Grant No.201503106)
文摘Non-point source nitrogen loss poses a risk to sustainable aquatic ecosystems. However, non-point sources, as well as impaired river segments with high nitrogen concentrations, are difficult to monitor and regulate because of their diffusive nature, budget constraints, and resource deficiencies. For the purpose of catchment management, the Bayesian maximum entropy approach and spatial regression models have been used to explore the spatiotemporal patterns of non-point source nitrogen loss. In this study, a total of 18 sampling sites were selected along the river network in the Hujiashan Catchment. Over the time period of 2008e2012, water samples were collected 116 times at each site and analyzed for non-point source nitrogen loss. The morphometric variables and soil drainage of different land cover types were studied and considered potential factors affecting nitrogen loss. The results revealed that, compared with the approach using the Euclidean distance, the Bayesian maximum entropy approach using the river distance led to an appreciable 10.1% reduction in the estimation error, and more than 53.3% and 44.7% of the river network in the dry and wet seasons, respectively, had a probability of non-point source nitrogen impairment. The proportion of the impaired river segments exhibited an overall decreasing trend in the study catchment from 2008 to 2012, and the reduction in the wet seasons was greater than that in the dry seasons. High nitrogen concentrations were primarily found in the downstream reaches and river segments close to the residential lands. Croplands and residential lands were the dominant factors affecting non-point source nitrogen loss, and explained up to 70.7%of total nitrogen in the dry seasons and 54.7% in the wet seasons. A thorough understanding of the location of impaired river segments and the dominant factors affecting total nitrogen concentration would have considerable importance for catchment management.
基金This work was supported by grants from the Natural Science Foundation of Hunan Province in China(Nos.2017JJ3250 and 2019JJ40230)the Science and Technology Plan Project of the Health commission of Hunan Province in China(Nos.B2019034 and B2019035).
文摘To the Editor:Asialoglycoprotein receptor 1(ASGR1)is the major subunit of ASGR,it is predominantly expressed by liver parenchymal cells and relatively lower expression was found in peripheral blood monocytes.[1]A genetic study recently revealed that ASGR1 haploinsufficiency resulted from loss-of-function(LOF)variants was strongly associated with the pronounced reductions in serum total cholesterol(TC)and low-density lipoprotein cholesterol(LDL-C)levels,[2,3]suggesting that ASGR1 may play a key role in cholesterol metabolism.However,the function of ASGR1 remains largely unclear.This study was focused on the association of ASGR1 gene expression in monocytes and plasma cholesterol level.