Patterns,origin and possible effects of sediment pollution in a Mediterranean lake

The influence of water permanence and high intra- and inter-annual hydrological variability on macrobenthos (organisms >1 mm) was studied using a taxonomical and a functional approach. The study was carried out in a Mediterranean salt marsh. Monthly samples of macrobenthic fauna were collected during two consecutive hydroperiods from six ponds with different water permanence (temporary, semi-permanent and permanent waters). Organisms were assigned to five functional response groups based on life-strategies according to their capacity to survive desiccation events, their dispersion capability and the necessity of water for their reproduction. Results from both approaches showed that the benthic community was more related to pond type than to intra- and inter-annual variability. The second aim was to analyse to which extent patterns in functional groups were determined by the existence of succession patterns or to environmental variability. In this sense, a clear succession pattern was not observed. In contrast, in most of the functional groups (4 out of 5), species within each functional group showed similar responses to water fluctuations. However, species of the fifth functional group, which comprised species without any particular adaptation to desiccation survival or avoidance, showed different responses to water level fluctuations. Guest editors: R. Céréghino, J. Biggs, B. Oertli & S. Declerck The ecology of European ponds: defining the characteristics of a neglected freshwater habitat     

Analysis of Matched Case–Control Data in Presence of Nonignorable Missing Exposure

Summary.   The present article deals with informative missing (IM) exposure data in matched case–control studies. When the missingness mechanism depends on the unobserved exposure values, modeling the missing data mechanism is inevitable. Therefore, a full likelihood-based approach for handling IM data has been proposed by positing a model for selection probability, and a parametric model for the partially missing exposure variable among the control population along with a disease risk model. We develop an EM algorithm to estimate the model parameters. Three special cases: (a) binary exposure variable, (b) normally distributed exposure variable, and (c) lognormally distributed exposure variable are discussed in detail. The method is illustrated by analyzing a real matched case–control data with missing exposure variable. The performance of the proposed method is evaluated through simulation studies, and the robustness of the proposed method for violation of different types of model assumptions has been considered.     

Asymptotic Distribution of Score Statistics for Spatial Cluster Detection with Censored Data

Summary Cook, Gold, and Li (2007, Biometrics 63, 540–549) extended the Kulldorff (1997, Communications in Statistics 26, 1481–1496) scan statistic for spatial cluster detection to survival‐type observations. Their approach was based on the score statistic and they proposed a permutation distribution for the maximum of score tests. The score statistic makes it possible to apply the scan statistic idea to models including explanatory variables. However, we show that the permutation distribution requires strong assumptions of independence between potential cluster and both censoring and explanatory variables. In contrast, we present an approach using the asymptotic distribution of the maximum of score statistics in a manner not requiring these assumptions.     

Inference methods for the conditional logistic regression model with longitudinal data

This paper considers inference methods for case-control logistic regression in longitudinal setups. The motivation is provided by an analysis of plains bison spatial location as a function of habitat heterogeneity. The sampling is done according to a longitudinal matched case-control design in which, at certain time points, exactly one case, the actual location of an animal, is matched to a number of controls, the alternative locations that could have been reached. We develop inference methods for the conditional logistic regression model in this setup, which can be formulated within a generalized estimating equation (GEE) framework. This permits the use of statistical techniques developed for GEE-based inference, such as robust variance estimators and model selection criteria adapted for non-independent data. The performance of the methods is investigated in a simulation study and illustrated with the bison data analysis.     

Generalized inferences on the overall treatment effect in meta-analysis with normally distributed outcomes

This paper focuses on inferences about the overall treatment effect in meta-analysis with normally distributed responses based on the concepts of generalized inference. A refined generalized pivotal quantity based on t distribution is presented and simulation study shows that it can provide confidence intervals with satisfactory coverage probabilities and perform hypothesis testing with satisfactory type-I error control at very small sample sizes.     

A relative survival model for clustered responses

Relative Survival is the ratio of the overall survival of a group of patients to the expected survival for a demographically similar group. It is commonly used in disease registries to estimate the effect of a particular disease when the true cause of death is not reliably known. Regression models for relative survival have been described and we extend these models to allow for clustered responses by embedding them into the class of Generalized linear mixed models (GLMM). The method is motivated and demonstrated by a data set from the HALLUCA study, an epidemiological study which investigated provision of medical care to lung cancer patients in the region of Halle in the eastern part of Germany.     

Resampling-based empirical Bayes multiple testing procedures for controlling generalized tail probability and expected value error rates: focus on the false discovery rate and simulation study

This article proposes resampling-based empirical Bayes multiple testing procedures for controlling a broad class of Type I error rates, defined as generalized tail probability (gTP) error rates, gTP (q,g) = Pr(g (V(n),S(n)) > q), and generalized expected value (gEV) error rates, gEV (g) = E [g (V(n),S(n))], for arbitrary functions g (V(n),S(n)) of the numbers of false positives V(n) and true positives S(n). Of particular interest are error rates based on the proportion g (V(n),S(n)) = V(n) /(V(n) + S(n)) of Type I errors among the rejected hypotheses, such as the false discovery rate (FDR), FDR = E [V(n) /(V(n) + S(n))]. The proposed procedures offer several advantages over existing methods. They provide Type I error control for general data generating distributions, with arbitrary dependence structures among variables. Gains in power are achieved by deriving rejection regions based on guessed sets of true null hypotheses and null test statistics randomly sampled from joint distributions that account for the dependence structure of the data. The Type I error and power properties of an FDR-controlling version of the resampling-based empirical Bayes approach are investigated and compared to those of widely-used FDR-controlling linear step-up procedures in a simulation study. The Type I error and power trade-off achieved by the empirical Bayes procedures under a variety of testing scenarios allows this approach to be competitive with or outperform the Storey and Tibshirani (2003) linear step-up procedure, as an alternative to the classical Benjamini and Hochberg (1995) procedure.     

The stay/switch model describes choice among magnitudes of reinforcers

The stay/switch model is an alternative to the generalized matching law for describing choice in concurrent procedures. The purpose of the present experiment was to extend this model to choice among magnitudes of reinforcers. Rats were exposed to conditions in which the magnitude of reinforcers (number of food pellets) varied for staying at alternative 1, switching from alternative 1, staying at alternative 2 and switching from alternative 2. A changeover delay was not used. The results showed that the stay/switch model provided a good account of the data overall, and deviations from fits of the generalized matching law to response allocation data were in the direction predicted by the stay/switch model. In addition, comparisons among specific conditions suggested that varying the ratio of obtained reinforcers, as in the generalized matching law, was not necessary to change the response and time allocations. Other comparisons suggested that varying the ratio of obtained reinforcers was not sufficient to change response allocation. Taken together these results provide additional support for the stay/switch model of concurrent choice.     

Ⅱ型糖尿病大鼠海马Alzheimer病样Tau蛋白过度磷酸化修饰及机制探讨

Tau蛋白过度磷酸化是Alzheimer病 (Alzheimer′s disease, AD) 的一个重要特征.本研究检测了Ⅱ型糖尿病大鼠海马tau蛋白磷酸化水平,对其形成机制进行探讨. 以同龄正常Wistar大鼠作为对照,高脂高蛋白高糖饮食加小剂量链脲佐菌素（streptozotocin,STZ）注射诱导造Ⅱ型糖尿病模型（T2DM组）.放免法检测血浆胰岛素;葡萄糖氧化酶法检测血浆葡萄糖;蛋白质印迹技术检测各组大鼠海马内总tau蛋白、tau蛋白上部分位点磷酸化、神经细胞膜上胰岛素受体及葡萄糖转运子3（glucose transport 3,GLUT3）水平;表面等离子共振技术（surface plasmon resonance, SPR）检测细胞膜上胰岛素受体与血浆胰岛素结合力;γ32-P标记的ATP和特异性底物肽检测海马内胰岛素信号传导系统中的关键酶糖原合酶激酶-3β（glycogen synthase kinase-3β, GSK-3β）活性.结果显示,T2DM组血浆血糖、血浆胰岛素及运用HOMA-IR公式计算的胰岛素抵抗指数显著高于对照组.蛋白质印迹结果显示两组大鼠海马回总tau蛋白水平无差异;T2DM组中tau蛋白在Ser199、Thr212、Ser214、Thr217、Ser396及Ser422位点上的磷酸化水平均显著高于对照组;T2DM组海马神经细胞膜上胰岛素受体水平及与胰岛素结合的功能均显著低于对照组;GSK-3β活性检测结果显示,T2DM组大鼠模型海马回中GSK-3β活性明显增高.研究结果表明,Ⅱ型糖尿病中由于胰岛素抵抗导致GSK-3β激活从而出现AD样tau蛋白的过度磷酸化,葡萄糖代谢紊乱也可能在tau蛋白的过度磷酸化起一定作用.     

Cope's rule in cryptodiran turtles: do the body sizes of extant species reflect a trend of phyletic size increase?

Cope's rule of phyletic size increase is questioned as a general pattern of body size evolution. Most studies of Cope's rule have examined trends in the paleontological record. However, neontological approaches are now possible due to the development of model-based comparative methods, as well as the availability of an abundance of phylogenetic data. I examined whether the phylogenetic distribution of body sizes in extant cryptodiran turtles is consistent with Cope's rule. To do this, I examined body size evolution in each of six major clades of cryptodiran turtles and also across the whole tree of cryptodirans (n = 201 taxa). Extant cryptodiran turtles do not appear to follow Cope's rule, as no clade showed a significant phyletic body size trend. Previous analyses in other extant vertebrates have also found no evidence for phyletic size increase, which is in contrast to the paleontological data that support the rule in a number of extinct vertebrate taxa.