Estimation of pyrethroid pesticide intake using regression modeling of food groups based on composite dietary samples

Population-based estimates of pesticide intake are needed to characterize exposure for particular demographic groups based on their dietary behaviors. Regression modeling performed on measurements of selected pesticides in composited duplicate diet samples allowed (1) estimation of pesticide intakes for a defined demographic community, and (2) comparison of dietary pesticide intakes between the composite and individual samples. Extant databases were useful for assigning individual samples to composites, but they could not provide the breadth of information needed to facilitate measurable levels in every composite. Composite sample measurements were found to be good predictors of pyrethroid pesticide levels in their individual sample constituents where sufficient measurements are available above the method detection limit. Statistical inference shows little evidence of differences between individual and composite measurements and suggests that regression modeling of food groups based on composite dietary samples may provide an effective tool for estimating dietary pesticide intake for a defined population.     

Sample size requirements for multiple regression interval estimation

Sample size planning is one of the most important issues in the design of a study. Simple and accurate sample size formulas for a desired confidence interval width have been developed for many statistical procedures, but a simple and accurate sample size formula for the squared multiple correlation has been a notable exception. Several rule‐of‐thumb sample size recommendations for a multiple regression analysis have been proposed over the years but none are satisfactory. Other approaches have focused on the construction of elaborate tables of sample size requirements, but these tables are both unwieldy and inadequate. We present a simple, accurate, and general method of approximating the sample size requirement for obtaining a squared multiple correlation confidence interval with desired precision. We also present a simple method for approximating the sample size needed to estimate unstandardized regression coefficients with desired precision. Copyright © 2010 John Wiley & Sons, Ltd.     

大型吹砂吹尘综合环境试验系统工程实现及应用

本文介绍了大型吹砂吹尘综合试验系统的设备构成和系统设计应考虑的关键技术。阐述了主要功能和技术指标,论述了砂尘浓度、试验段风速、试验段温度和相对湿度等主要试验参数的调节技术,并给出了应用结果。能够为大型吹砂环境试验设备的设计和试验应用提供参考借鉴。     

有机污染物应急监测的样品前处理技术

样品前处理是有机污染物应急监测中的重要环节。介绍了热分离进样杆、分散液液微萃取、搅拌棒吸附萃取、固相微萃取等适合于有机污染物应急监测的样品前处理技术,并概述了它们在环境分析领域的应用进展。如何将这些前处理技术与自身拥有的应急监测设备有效结合是环境监测技术人员亟待解决的问题。     

Importance of health assessments for conservation in noncaptive wildlife

Wildlife health assessments help identify populations at risk of starvation, disease, and decline from anthropogenic impacts on natural habitats. We conducted an overview of available health assessment studies in noncaptive vertebrates and devised a framework to strategically integrate health assessments in population monitoring. Using a systematic approach, we performed a thorough assessment of studies examining multiple health parameters of noncaptive vertebrate species from 1982 to 2020 (n = 261 studies). We quantified trends in study design and diagnostic methods across taxa with generalized linear models, bibliometric analyses, and visual representations of study location versus biodiversity hotspots. Only 35% of studies involved international or cross-border collaboration. Countries with both high and threatened biodiversity were greatly underrepresented. Species that were not listed as threatened on the International Union for Conservation of Nature Red List represented 49% of assessed species, a trend likely associated with the regional focus of most studies. We strongly suggest following wildlife health assessment protocols when planning a study and using statistically adequate sample sizes for studies establishing reference ranges. Across all taxa blood analysis (89%), body composition assessments (81%), physical examination (72%), and fecal analyses (24% of studies) were the most common methods. A conceptual framework to improve design and standardize wildlife health assessments includes guidelines on the experimental design, data acquisition and analysis, and species conservation planning and management implications. Integrating a physiological and ecological understanding of species resilience toward threatening processes will enable informed decision making regarding the conservation of threatened species.     

环境监测站如何通过盲样和加标回收考核

探讨了盲样和加标回收两种实验室考核中应注意的细节,介绍了通过考核的一些经验技巧,为实验人员提供了值得借鉴的信息。     

Bootstrap方法在小样本随机振动环境测量数据归纳中的应用研究

针对传统正态容差上限方法在确定平台振动环境条件时,不适合处理小样本实测数据统计归纳的问题,提出了利用Bootstrap法对测量样本重采样,进而统计归纳振动环境条件的计算方法。首先利用Bootstrap法对来自正态分布的试验数据进行容差上限估计,通过与真值的对比分析,验证各种自助置信区间估计方法的适用性,而后提出使用纠偏百分位法和Bootstrap-t法对小样本振动测量数据进行归纳。最后,分别对某型飞机实测数据进行了统计归纳,并与传统容差上限估计方法进行了对比分析。     

环境样品免疫检测基质效应分析与控制

免疫检测技术以其特异性强、灵敏度高、分析容量大、反应速度快、检测费用低廉等优点,逐渐成为环境样品大规模快速筛查和预警监测的首选技术.由于免疫检测无需样品预处理、能实现对样品的在线检测,因此环境样品中复杂的基质可能对免疫检测产生非常大的干扰和影响.以水环境中微囊藻毒素-LR的酶联免疫吸附试验（ELISA）检测为基础,系统地考察了环境样品中各种背景基质对ELISA检测的影响,评价了各个基质的影响规律和程度,并研究提出了相应的控制和消除各不利影响的方法,最后统一提出水环境样品免疫检测抗基质效应干扰的控制方案,即采用10×PBS＋1%BSA＋0.5%EDTA作为免疫检测反应的缓冲体系,能有效消除各基质效应对免疫检测的干扰.该方案同样适应于其它不需要对环境样品进行预处理的免疫检测技术.     

恩诺沙星完全抗原的合成及间接竞争ELISA方法的建立

为了建立环境新型抗生素类污染物恩诺沙星的免疫检测方法,采用间接竞争ELISA方法,用酶标仪测定酶标二抗与底物反应生成的有色产物量来确定恩诺沙星含量.研究了恩诺沙星完全抗原的合成方法,以及间接竞争ELISA的优化条件和实际水样的检测效果.结果表明,通过碳二亚胺法(EDC+NHS)成功合成了恩诺沙星的理想完全抗原,采用BCA法测定完全抗原浓度,紫外吸收法和MADLI-TOF MS法测得完全抗原的偶联比为14~16.建立的恩诺沙星间接竞争ELISA检测方法,检测限为1.92μg·L~(-1),定量检测区间为7.33~238.24μg·L~(-1).采用优化后的实验条件测定了清华大学地下水和饮用水配制的恩诺沙星加标样品,发现所有样品的变异系数和回收率分别为3%~11%和82%~122%,表明建立的间接竞争ELISA方法适用于实际水样中恩诺沙星的快速简便检测.