The association between co-exposure to multiple metals and renal function is poorly understood. We aimed to evaluate the individual and joint effects of metal exposure on renal function in this study. We performed a cross-sectional study including 5828 participants in Guangxi, China, in 2019. Urine concentrations of 17 metals were detected by inductively coupled plasma mass spectrometry (ICP-MS). Logistic regression model and restricted cubic spline (RCS) were applied to investigate the association of individual metal exposure with renal dysfunction. Weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were used to assess the co-exposure effects of the metals. Participants with the highest quartile of urinary Cu were at 1.84-fold (95% confidence interval (CI): 1.20–2.87) increased risk of renal dysfunction compared with the lowest quartile. The highest quartiles of urinary Sr, Cs, V, Ba, and Se were associated with 0.27-fold (95% CI: 0.17–0.43), 0.33 (95% CI: 0.19–0.53), 0.41 (95% CI: 0.25–0.65), 0.58 (95% CI: 0.36–0.90), and 0.33 (95% CI: 0.19–0.56) decreased risk of renal dysfunction compared with their lowest quartile, respectively. Furthermore, urinary Ba and Cu were non-linearly correlated with renal dysfunction. The WQS analysis showed that mixed metal exposure was inversely associated with renal dysfunction (OR = 0.47, 95% CI: 0.35–0.62), and Sr accounted for the largest weight (52.2%), followed by Cs (32.3%) in the association. Moreover, we observed a potential interaction between Cu, Cs, and Ba for renal dysfunction in BKMR model. Exposure to Se, Sr, Cs, V, and Ba is associated with decreased risk of renal dysfunction, whereas an increased risk is associated with Cu exposure. Co-exposure to these metals is negatively associated with renal dysfunction, and Sr and Cs are the main contributors to the associations.
Field surveys were carried out from January 2007 to December 2008 to investigate seasonal variations of dissolved inorganic nitrogen (DIN) and phosphorus (DIP) transported to the Linjiang Bay of the Three Gorges Reservoir, China. The results revealed that both DIN and DIP exhibited large seasonal variability. DIN (dominated by NH4?CN) concentrations were drastically higher in the dry season than those in the rainy season, and the same seasonal patterns of DIP concentrations and DIN and DIP fluxes were observed but inverse to that of DIN concentrations. The interannual variation in DIN fluxes descended by 28.2% from 2007 to 2008, while DIP fluxes increased by 40.9%, which were closely constant with interannual changes in DIN and DIP concentrations, respectively. The study indicated that nutrient fluxes (DIN and DIP) were strongly correlated with both nutrient concentrations and river discharge, and the Linjiang Bay received approximately 3,416 × 103 kg DIN and 324 × 103 kg DIP every year. In addition, DIN mainly originated from point sources, but DIP originated from non-point sources. It is shown that to control point source pollution is the most effective step for water quality improvement and reducing nutrient loading inputs in the Linjiang Bay. 相似文献
We compare the performance of a number of estimators of the cumulative distribution function (CDF) for the following scenario: imperfect measurements are taken on an initial sample from afinite population and perfect measurements are obtained on a small calibration subset of the initial sample. The estimators we considered include two naive estimators using perfect and imperfect measurements; the ratio, difference and regression estimators for a two-phasesample; a minimum MSE estimator; Stefanski and Bay's SIMEX estimator (1996); and two proposed estimators. The proposed estimators take the form of a weighted average of perfect and imperfect measurements. They are constructed by minimizing variance among the class of weighted averages subject to an unbiasedness constraint. They differ in the manner of estimating the weight parameters. The first one uses direct sample estimates. The second one tunes the unknown parameters to an underlying normal distribution. We compare the root mean square error (RMSE) of the proposed estimator against other potential competitors through computer simulations. Our simulations show that our second estimator has the smallest RMSE among thenine compared and that the reduction in RMSE is substantial when the calibration sample is small and the error is medium or large. 相似文献
2004年5月10日云南怒江州福贡县石月亮乡发生泥石流等地质灾害,造成人员、经济重大损失。分析了此次泥石流形成的条件,并着重探讨了天气学成因,结果表明:脆弱的地质环境、陡峻的迎风坡、便于集水、集物的地形地貌和丰富的松散物质是怒江贡山泥石流易发生的有利地质地貌条件;连续性累积降水及短时间暴雨的产生为泥石流提供了较好的水源条件;高原短波槽与孟加拉湾南支槽东移合并,中、低层槽前西偏南暖湿气流500 h Pa偏西北气流是形成怒江暴雨过程的大尺度天气环流背景;地面辐合线、干线、低层显著湿区、湿舌等是导致降水的中尺度系统;高能高湿的潜在不稳定及近地层的水汽辐合是暴雨发生的有利条件;多普勒雷达图10~20 d Bz分散的絮状回波、部分35 d Bz块絮状回波、卫星云图多絮状对流云、无强对流云团活动反映此次暴雨过程为非对流性暴雨。 相似文献
To better understand the diversity of metal resistance genetic determinant from microbes that survived atmetal tailings in northwest of China, a highly elevated level of heavymetal containing region, genomic analyses was conducted using genome sequence of three native metal-resistant plant growth promoting bacteria (PGPB). It shows that: Mesorhizobium amorphae CCNWGS0123 contains metal transporters from P-type ATPase, CDF (Cation Diffusion Facilitator), HupE/UreJ and CHR (chromate ion transporter) family involved in copper, zinc, nickel as well as chromate resistance and homeostasis. Meanwhile, the putative CopA/CueO system is expected to mediate copper resistance in Sinorhizobium meliloti CCNWSX0020 while ZntA transporter, assisted with putative CzcD, determines zinc tolerance in Agrobacterium tumefaciens CCNWGS0286. The greenhouse experiment provides the consistent evidence of the plant growth promoting effects of these microbes on their hosts by nitrogen fixation and/or indoleacetic acid (IAA) secretion, indicating a potential in-site phytoremediation usage in themining tailing regions of China. 相似文献