Linear Mixed Model Selection for False Discovery Rate Control in Microarray Data Analysis

Summary In a microarray experiment, one experimental design is used to obtain expression measures for all genes. One popular analysis method involves fitting the same linear mixed model for each gene, obtaining gene‐specific p‐values for tests of interest involving fixed effects, and then choosing a threshold for significance that is intended to control false discovery rate (FDR) at a desired level. When one or more random factors have zero variance components for some genes, the standard practice of fitting the same full linear mixed model for all genes can result in failure to control FDR. We propose a new method that combines results from the fit of full and selected linear mixed models to identify differentially expressed genes and provide FDR control at target levels when the true underlying random effects structure varies across genes.     

阳际峰自然保护区地面生苔藓植物分布与环境因子关系研究

在江西阳际峰自然保护区调查的25个样地中,共采集到地面生苔藓植物34科56属106种（包括1变种）。应用CCA排序法,首次定量分析了该区38种主要地面生苔藓植物与环境因子的关系。结果表明,苔藓植物的分布和生物多样性受环境因子的影响较大,湿度、基质是影响地面生苔藓植物分布的主要环境因子,其他影响因子依次为乔木郁闭度、灌木盖度、海拔高度、人为干扰和坡度。     

糖尿病下肢溃疡影响因素分析及治疗方法

目的探讨糖尿病下肢溃疡的原因和治疗方法。方法回顾总结我院近年来急诊科临床收治的糖尿病并发下肢溃疡患者12例,全部病例均使用胰岛素控制血糖、抗生素抗感染、静脉滴注活血化瘀的中药、常规局部换药并结合使用具有去腐、生肌、消炎作用的中药膏剂进行治疗,同时对患者进行糖尿病相关知识的教育和自我护理技能培训。结果全部病人均治愈出院,其中截趾术后伤口愈合出院1例,点状邮票植皮后伤口愈合1例,经换药伤口愈合10例。随访期间全部病例溃疡未复发。结论糖尿病下肢溃疡是由血管、神经、感染等多重因素造成的。对糖尿病并发下肢溃疡患者采用多种方法综合治疗可以取得较好的疗效,同时强调重视糖尿病的管理和教育。     

眼镜王蛇咬伤救治成功临床分析

目的探讨眼镜王蛇咬伤患者的最佳抢救方法。方法对6例眼镜王蛇咬伤患者的抢救过程进行回顾性分析总结。结果通过及时使用抗蛇毒血清、中草药等治疗,6例患者均痊愈出院。结论早期正确局部处理伤口是抢救成功的前提;早期足量应用抗眼镜蛇毒血清和抗银环蛇毒血清治疗是抢救成功的关键;中西医结合治疗是抢救成功和治愈的保证。     

Investigating environmental variation and landscape characteristics of an urban–rural gradient using woodland carabid assemblages

Aim To investigate environmental variation and associated assemblage changes of carabid beetles along an urban–rural gradient. Location ‘Quercus–Acer’ (oak–sycamore) woodlands in the city of Birmingham, UK. Methods We collected carabid data using pitfall traps on 12 sites in the city. The traps were run from April–September in 2000, and we collected environmental data on 24 individual variables associated with the individual sites and their landscape context. Changes in carabid assemblages were analysed using repeat measures anova and the environment–species relationships with a Redundancy Analyses (RDA) and Generalized Linear Modelling (GLM). Results We found that: (1) species richness and diversity were lower in the urban and suburban zone and higher in the rural zone; (2) Berger Parker dominance index was higher in the urban and suburban zones; (3) the number of woodland and woodland associated species was significantly higher at the rural end of the gradient; (4) the number of short‐winged (brachypterous) species was highest in the rural zone and decreased towards the urban woodlands, whereas the long‐winged species were more abundant in suburban woodlands; (5) the median weight length (WML) of the assemblage declined along the gradient from the rural to the urban zone, as did the number of large species; and (6) five of the 24 environmental variables showed a significant relationship with variation in the carabid assemblage. At site level the carabid assemblages were related to the level of site disturbance and soil penetrability, whereas site size and amount of woodland and urban land within 5 km of the site were important at a larger landscape scale. Main conclusions The results suggest that urbanization has a deleterious impact on carabid assemblages, causing a reduction in species richness from the rural fringe to the centre of the city. Changes in assemblage structure were related to woodland fragmentation, which led to variations in woodland size, woodland location and site disturbance due to trampling. Large, flightless and specialist woodland species are more susceptible to changes associated with urbanization, presumably due to their longer life spans, lower reproductive rates, more specialized niches and more limited dispersal potential.     

The Effect of Design Imbalance on the Power of the F‐test of a Variance Component in the One‐Way Random Model

The ANOVA‐based F‐test used for testing the significance of the random effect variance component is a valid test for an unbalanced one‐way random model. However, it does not have an uniform optimum property. For example, this test is not uniformly most powerful invariant (UMPI). In fact, there is no UMPI test in the unbalanced case (see Khuri , Mathew , and Sinha , 1998). The power of the F‐test depends not only on the design used, but also on the true values of the variance components. As Khuri (1996) noted, we can gain a better insight into the effect of data imbalance on the power of the F‐test using a method for modelling the power in terms of the design parameters and the variance components. In this study, generalized linear modelling (GLM) techniques are used for this purpose. It is shown that GLM, in combination with a method of generating designs with a specified degree of imbalance, is an effective way of studying the behavior of the power of the F‐test in a one‐way random model.     

Biophysical stratification of the Amazon basin

In field measurement programmes, stratified sampling can optimize sampling efficiency, but stratification is often undertaken subjectively, and is frequently based on a priori classification schemes such as those used for vegetation maps. In order to avoid the problems associated with a priori subjective schemes, we explore here an objective procedure, Regression Tree Analysis (RTA). RTA has previously been used in local-scale studies, but here we apply it to a very large study domain, namely the entire humid tropical zone of South America. The aim of the study was to develop an optimal sampling design in preparation for the Large Scale Biosphere-Atmosphere Experiment in Amazonia (LBA). Co-registered spatially continuous fields of rainfall, temperature, photosynthetically active radiation (PAR), the normalized difference index (NDVI), an index of surface moisture, and other independent variables were used to predict three dependent variables, annual net radiation (Rn), latent heat (LE) and net primary production (NPP). Rather than simply dividing the study area based on differing levels of the three dependent variables, empirical models were developed using RTA to indicate how the relationships between these and possible forcing variables vary across the study area. For each variable long-term seasonal indices such as annual average, monthly minimum and amplitude were used to exclude effects of temporal phase differences between the hemispheres. The resulting hierarchical models revealed variations in the interdependence of the forcing variables throughout the study area and therefore provided a basis for a stratified sampling and identifying the most important variables to be collected in LBA for the Amazon basin as a whole as well as optimizing the sampling scheme for scaling up findings from the field scale to larger areas.     

Determination of drugs in biological fluids by direct injection of samples for liquid-chromatographic analysis

The analysis of drugs in various biological fluids is an important criterion for the determination of the physiological performance of a drug. After sampling of the biological fluid, the next step in the analytical process is sample preparation. The complexity of biological fluids adds to the challenge of direct determination of the drug by chromatographic analysis, therefore demanding a sample preparation step that is often time-consuming, tedious, and frequently overlooked. However, direct on-line injection methods offer the advantage of reducing sample preparation steps and enabling effective pre-concentration and clean-up of biological fluids. These procedures can be automated and therefore reduce the requirements for handling potentially infectious biomaterial, improve reproducibility, and minimize sample manipulations and potential contamination. The objective of this review is to present an overview of the existing literature with emphasis on advances in automated sample preparation methods for liquid-chromatographic methods. More specifically, this review concentrates on the use of direct injection techniques, such as restricted-access materials, turbulent-flow chromatography and other automated on-line solid-phase extraction (SPE) procedures. It also includes short overviews of emerging automated extraction-phase technologies, such as molecularly imprinted polymers, in-tube solid-phase micro-extraction, and micro-extraction in a packed syringe for a more selective extraction of analytes from complex samples, providing further improvements in the analysis of biological materials. Lastly, the outlook for these methods and potential new applications for these technologies are briefly discussed.