Two latent variable risk assessment approaches for mixed continuous and discrete outcomes from developmental toxicity data

Measurements of both continuous and discrete outcomes are encountered in many statistical problems. Here we consider the particular context of teratology studies, where quantitative risk asessment is aimed at determining the effect of dose on the probability that an individual fetus is malformed or of low birth weight, both being important measures of teratogenicity. We will introduce two different joint marginal mean models for outcomes of a mixed nature. First, we propose the Plackett-Dale approach, where for each binary outcome it is assumed that there exists an underlying glatent variable. The latent malformation outcomes are then assumed to follow a Plackett distribution. The second approach we consider is a probit approach. Here it is assumed that there exists an underlying continuous variable for each binary outcome, so the joint distribution for weight and malformation can be assumed to follow a multivariate normal distribution. In both cases, specification of the full distribution will be avoided using pseudolikelihood and generalized estimating equations methodology, respectively. Quantitative risk assessment is illustrated using data from two developmental toxicology experiments.     

Gaussian Copula Mixed Models for Clustered Mixed Outcomes,With Application in Developmental Toxicology

This paper is concerned with the analysis of clustered data from developmental toxicity studies with mixed responses, i.e., where each member of the cluster has binary and continuous outcomes. A copula-based random effects model is proposed that accounts for associations between binary and/or continuous outcomes within clusters, including the intrinsic association between the mixed outcomes for the same subject. The approach allows the adoption of flexible distributions for the mixed outcomes as well as for the random effects. The model includes the correlated probit model of Gueorguieva and Agresti (2001) and the generalized linear mixed models of Faes et al. (2008), and Faes, Geys, and Catalano (2009) as special cases. Maximum likelihood estimation of our model parameters is implemented using standard software such as PROC NLMIXED in SAS. The proposed methodology is motivated by and illustrated using a developmental toxicity study of ethylene glycol in mice. This article has supplementary material online.     

Risk Assessment for Toxicity Experiments with Discrete and Continuous Outcomes: A Bayesian Nonparametric Approach

We present a Bayesian nonparametric modeling approach to inference and risk assessment for developmental toxicity studies. The primary objective of these studies is to determine the relationship between the level of exposure to a toxic chemical and the probability of a physiological or biochemical response. We consider a general data setting involving clustered categorical responses on the number of prenatal deaths, the number of live pups, and the number of live malformed pups from each laboratory animal, as well as continuous outcomes (e.g., body weight) on each of the live pups. We utilize mixture modeling to provide flexibility in the functional form of both the multivariate response distribution and the various dose–response curves of interest. The nonparametric model is built from a structured mixture kernel and a dose-dependent Dirichlet process prior for the mixing distribution. The modeling framework enables general inference for the implied dose–response relationships and for dose-dependent correlations between the different endpoints, features which provide practical advances relative to traditional parametric models for developmental toxicology. We use data from a toxicity experiment that investigated the toxic effects of an organic solvent (diethylene glycol dimethyl ether) to demonstrate the range of inferences obtained from the nonparametric mixture model, including comparison with a parametric hierarchical model.Supplementary materials accompanying this paper appear on-line.     

When is a measured soil organic matter fraction equivalent to a model pool?

Dynamic simulation models are important tools for rationalizing complex changes in soil organic matter. Most such models for organic matter can be described as having either a pool structure or a continuous one. A pool structure can offer advantages in ease of use and transferability. Some pools are easily measured, whereas others cannot be measured directly. New methods of fractionation are being developed in an attempt to base models on measurable fractions. A requirement for such models is a demonstration that the measured fraction and model pool are equivalent. A measured fraction is equivalent to a model pool only if, within acceptable limits, it is unique as well as non‐composite. If the measured fraction is not unique, describing it as a separate pool adds no extra information, while the added complexity can increase propagation of errors. If it is composite then the characteristics of the fraction will change with changing environment as a result of changing proportions of subpools. This will produce a model that cannot be applied without deriving parameters afresh: such a model is of greatly reduced value. Here we develop methods to examine if a fraction is both unique and non‐composite. The tests for unique and composite pools were applied to the SUNDIAL (s imu lation of n itrogen d ynamics i n a rable l and) model of organic matter and nitrogen turnover in soil. Results suggest that the debris, biomass and humus pools are unique, but biomass and humus are composed of two or more subpools. This worked example illustrates how, given suitable data, any pool‐based model can be tested by these methods.     

The simultaneous analysis of mixed discrete and continuous outcomes using nonlinear threshold models

Mixed discrete and continuous outcomes are commonly measured on each experimental unit in dose-response studies in toxicology. The dose-response relationships for these outcomes often have dose thresholds and nonlinear patterns. In addition, the endpoints are typically correlated, and a statistical analysis that incorporates the association may result in improved precision. We propose an extension of the generalized estimating equation (GEE) methodology to simultaneously analyze binary, count, and continuous outcomes with nonlinear threshold models that incorporates the intra-subject correlation. The methodology uses a quasi-likelihood framework and a working correlation matrix, and is appropriate when the marginal expectation of each outcome is of primary interest and the correlation between endpoints is a nuisance parameter. Because the derivatives of threshold models are not continuous at each point of the parameter space, we describe the necessary modifications that result in asymptotically normal and consistent estimators. Using dose-response data from a neurotoxicity experiment, the methodology is illustrated by analyzing five outcomes of mixed type with nonlinear threshold models. In this example, the incorporation of the intra-subject correlation resulted in decreased standard errors for the threshold parameters.     

T-2 toxin, a trichothecene mycotoxin: review of toxicity, metabolism, and analytical methods

This review focuses on the toxicity and metabolism of T-2 toxin and analytical methods used for the determination of T-2 toxin. Among the naturally occurring trichothecenes in food and feed, T-2 toxin is a cytotoxic fungal secondary metabolite produced by various species of Fusarium. Following ingestion, T-2 toxin causes acute and chronic toxicity and induces apoptosis in the immune system and fetal tissues. T-2 toxin is usually metabolized and eliminated after ingestion, yielding more than 20 metabolites. Consequently, there is a possibility of human consumption of animal products contaminated with T-2 toxin and its metabolites. Several methods for the determination of T-2 toxin based on traditional chromatographic, immunoassay, or mass spectroscopy techniques are described. This review will contribute to a better understanding of T-2 toxin exposure in animals and humans and T-2 toxin metabolism, toxicity, and analytical methods, which may be useful in risk assessment and control of T-2 toxin exposure.     

Analysis of toxicology data with covariates specific to each observation

The standard approach for analysis of teratology studiesis to use a population-averaged model with primary interest on evaluating dose-response effects. For example, generalized estimating equations (GEEs) have become popular for analysis of both developmental toxicity and reproducti vestudies (Ryan 1992). Such an approach is typically appropriate since the covariate of interest—exposure level—is constant for each litter of animals. Recently, however, there has been growing interest in evaluating effects of covariates that can vary between individuals within a cluster. This article explores several opportunities generated by teratology studies with individual-level covariates both in terms of modeling approaches and in decomposition of litter effects into genetic and environmental components.     

Expanding and tracking the capabilities of pesticide multiresidue methodology used in the Food and Drug Administration's pesticide monitoring programs

Foods analyzed for pesticide residues in the monitoring programs of the U.S. Food and Drug Administration (FDA) are most often examined by using one or more of the multiresidue methods developed for this purpose over the years. Because no single method can be used for all potential residues, each commodity is examined by a method or methods which will identify and/or determine the chemicals most likely to have been used. FDA conducts research to develop new multiresidue methods, which are included in monitoring programs as needed to cover additional chemicals. FDA's multiresidue methods have undergone continuous study over a 20 year period to ascertain which compounds can and cannot be recovered by them. FDA continues to perform tests to discover a compound's analytical characteristics. Protocols have been published to direct the testing of additional compounds so that new information can be added to the existing compilations. Methods capable of determining residues of single pesticides are used to analyze selected commodities for residues of high priority that cannot be determined by existing multiresidue methods. Pestrak, a computerized listing of pesticide analytical information, has been developed by FDA to keep track of the capabilities of multiresidue methods and the coverage of residues by the single residue methods used in FDA monitoring.     

A Baseline Category Logit Model for Assessing Competing Strains of <Emphasis Type="Italic">Rhizobium</Emphasis> Bacteria

In this paper we describe novel methodology for evaluating competition among strains of Rhizobium bacteria which can be found naturally occurring in or can be introduced into soil. Rhizobia can occupy nodules on the roots of legume plants allowing the plant to ‘fix’ atmospheric nitrogen. Our model defines competitive outcomes for a community (the multinomial count of nodules occupied by each strain at the end of a time period) relative to the past state of the community (the proportion of each strain present at the beginning of the time period) and incorporates this prior information in the analysis. Our approach for assessing competition provides an analogy to multivariate methods for continuous responses in competition studies and an alternative to univariate methods for discrete responses that respects the multivariate nature of the data. It can also handle zero values in the multinomial response providing an alternative to compositional data analysis methods, which traditionally have not been able to facilitate zero values. The proposed experimental design is based on the simplex design and the model is an extension of multinomial baseline category logit models that includes multiple offsets and random terms to allow for correlation among clustered responses. Supplemental materials for this article are available from the journal website.     

Dietary toxicity of decomposed arborescent leaf litter against larval mosquito: involvement of a lignin-polypeptidic complex

To characterize the toxic compounds involved in the dietary toxicity of decomposed arborescent leaf litter against larval mosquito, a toxic fraction was extracted from crude leaf litter by using hot water. Preliminary characterization of this fraction, called the insoluble fraction (IF) because it progressively precipitates after extraction, has suggested the involvement of lignin-like compounds in the toxicity. Further analyzes are currently being performed by using additional phytotoxicity-based methods. The involvement of lignin-like compounds in the toxicity was indicated by both the comparative effects of different enzymatic oxidative treatments and reversed-phase high-performance liquid chromatography analysis of the phenolic aldehydes and acids obtained after alkaline nitrobenzene oxidation. However, these lignin-like compounds may not be involved alone in the toxicity, as no specific feature of those components was associated with the toxicity. Among the possible compounds associated with lignin-like compounds in the toxicity, peptidic compounds were suggested by comparative determination of the C/N ratio and then revealed by denaturation experiments, use of specific binding protein molecules, and thin-layer chromatography analysis. A possible role of these peptidic compounds associated with lignin-like compounds in the dietary toxicity of the leaf litter against the larval mosquito midgut is discussed.     

Literature review on higher plants for toxicity testing

Phytotoxicity tests using higher plants in general are infrequently used as a part of ecotoxicology. Many reports assess herbicide toxicity merely on the basis of faunal species tests. This is inadequate because the herbicide impact is much greater on flora than on fauna. Environmental pollution by herbicides was likely to have been quite wide-spread during the past years (1964–1984) when the use of herbicides grew five-fold. When herbicides reach non-target areas, they can cause unacceptable harm to non-target species, plants in particular. The toxicity of herbicides to algal species is not likely to be identical to that of higher plants, so that algal species may not serve as a surrogate species for the toxicity evaluation. Currently there are two promising phytotoxicity tests. Common duckweed is an aquatic species and sensitive to toxicity. Duckweek test can be used with static, renewal, or flow-through methods. The latter two are especially useful for unstable compounds or samples. Seed germination and root elongation tests are versatile and can be tested in water, wastewater, sediment, and slurry. Many recent activities in these areas suggest that phytotoxicity tests are a valuable part of ecotoxicology.     

Hierarchical Rank Aggregation with Applications to Nanotoxicology

The development of high throughput screening (HTS) assays in the field of nanotoxicology provide new opportunities for the hazard assessment and ranking of engineered nanomaterials (ENMs). It is often necessary to rank lists of materials based on multiple risk assessment parameters, often aggregated across several measures of toxicity and possibly spanning an array of experimental platforms. Bayesian models coupled with the optimization of loss functions have been shown to provide an effective framework for conducting inference on ranks. In this article we present various loss-function-based ranking approaches for comparing ENM within experiments and toxicity parameters. Additionally, we propose a framework for the aggregation of ranks across different sources of evidence while allowing for differential weighting of this evidence based on its reliability and importance in risk ranking. We apply these methods to high throughput toxicity data on two human cell-lines, exposed to eight different nanomaterials, and measured in relation to four cytotoxicity outcomes. This article has supplementary material online.     

我国农牧交错区土地退化研究——以宁夏盐池县为例

 从荒漠化发展历史角度出发,通过收集历史资料和固定样地观测,采用数学分析方法,利用马尔可夫链(Markov)模型和模糊模式识别方法对盐池荒漠化现状、动态变化以及荒漠化治理措施效益进行分析。结果表明:1)盐池县近半个世纪以来土地荒漠化呈急剧扩大趋势,荒漠化土地面积平均年增长率4.03％。2)盐池县荒漠化主要原因是在脆弱生态环境基础上,人为不合理经济活动所致。3)如果能做到严格执法,全面落实禁牧政策并加强防沙治沙工程管理,盐池县荒漠化土地将得到全面治理,否则盐池县荒漠化形势将继续恶化。认为能否全面落实禁牧和退耕还林政策,将直接影响盐池县荒漠化防治。     

The use of Folsomia candida (Collembola,Isotomidae) in bioassays of waste

There is a high probability that urban compost, sewage sludge and ash will come in contact with natural terrestrial ecosystems. The present paper investigates the extent to which the Folsomia candida population development test (now a standardised ecotoxicological test, ISO 11267, for testing the impact of pure chemicals on soil fauna) can be applied to the detection of the toxicity of these wastes, the goal being to evaluate ecotoxicity of wastes before they are spread on land. We show that some potentially useful information on waste toxicity can be obtained with this test, but the results must be interpreting with caution, indeed, problems can arise from differences in pH, humidity and organic matter content of the waste relative to the characteristics of the dilution soil. On the basis of the results of these assays, we propose a classification of the toxicity of seven wastes.     

Framework for intake simulation of functional ingredients

OBJECTIVE: To create a general framework for the simulation of intakes from mandatory or voluntary fortification, which will make outcomes of simulation studies more comparable and give insight on uncertainties. DESIGN: A general framework was developed based on methods used in already published case studies of mandatory fortification. The framework was extended to be suitable for the simulation of voluntary fortification. Case studies of folic acid fortification were used to illustrate the general framework. RESULTS: The developed framework consists of six steps. First, the definition of the fortification strategy (step 1), followed by the identification of potential carrier products (step 2), and the definition of fortification levels or ranges (step 3). Thereafter, virtual food/supplement composition data are created (step 4) and food/supplement consumption data are required (step 5). Finally, the intake of the functional ingredient from functional foods, other foods and dietary supplements is calculated during the simulation resulting in total habitual intake distributions (step 6). CONCLUSIONS: Simulation of both mandatory and voluntary folic acid fortification in The Netherlands showed that the general framework is applicable. Also with incomplete data or data from different sources, the (habitual) intake distributions can be estimated using assumptions, statistical procedures or probabilistic modelling approaches. It is important that the simulation procedure is described well, so that an insight on uncertainties and knowledge gaps to be filled is given.     

Ozone sensitivity of Phaseolus vulgaris in relation to cultivar differences,growth stage and growing conditions

Exposure of Phaseolus vulgaris cv. Lit to ambient ozone caused a 14% pod yield reduction in 1994. This yield loss was assessed by comparing plants that were protected against ozone by treatment with EDU (ethylenediurea) with unprotected plants, both cultivated in pots with a continuous water supply. The plants had experienced an AOT40 of 8135 ppb.h during their growth. However, plant response to ozone depends on a large number of environmental and plant-specific conditions. Visible injury increased mainly after flowering and was much less severe on soil-grown bean cultivars (Lit, Stella and Groffy) not receiving additional water. Ozone fumigations in closed chambers before or after flowering proved that the growth stage during which the plants are exposed also plays a very important role with regard to injury development. Plants seem to be more susceptible during the generative growth stage and the relative cultivar sensitivity was related to the developmental stage during fumigation. However with regard to yield effects the timing of the ozone exposure seems to be less important.     

Molecular mechanisms of plant adaptation to acid soils: A review

Acid soils are widespread and limit global plant production. Aluminum(Al)/manganese(Mn) toxicity and phosphorus(P) deficiency are the major limiting factors affecting plant growth and productivity on acid soils. Plants, however, have evolved various strategies to adapt to these stresses. These strategies include using both external and internal mechanisms to adapt to Al toxicity, regulating Mn uptake, translocation, and distribution to avoid Mn toxicity, and orchestrating a set of P transport me...     

Simultaneous Biodegradation and Detoxification of the Herbicides 2,4-Dichlorophenoxyacetic Acid and 4-Chloro-2-Methylphenoxyacetic Acid in a Continuous Biofilm Reactor

The herbicides 2,4-diclorophenoxiacetic and 4-chloro-2-methylphenoxyacetic acids (2,4-D and MCPA) are widely used in agricultural practices worldwide. Not only are these practices responsible of surface waters contamination, but also agrochemical industries through the discharge of their liquid effluents. In this investigation, the ability of a 2,4-D degrading Delftia sp. strain to degrade the related compound MCPA and a mixture of both herbicides was assessed in batch reactors. The strain was also employed to remove and detoxify both herbicides from a synthetic effluent in a continuous reactor. Batch experiments were conducted in a 2-L aerobic microfermentor, at 28 °C. Continuous experiments were carried out in an aerobic downflow fixed-bed reactor. Bacterial growth was evaluated by the plate count method. Degradation of the compounds was evaluated by UV spectrophotometry, gas chromatography (GC), and chemical oxygen demand (COD). Toxicity was assessed before and after the continuous process by using Lactuca sativa seeds as test organisms. Delftia sp. was able to degrade 100 mg L^?1 of MCPA in 52 h. When the biodegradation assay was carried out with a mixture of 100 mg L^?1 of each herbicide, the process was accomplished in 56 h. In the continuous reactor, the strain showed high efficiency in the simultaneous removal of 100 mg L^?1 of each herbicide. Removals of 99.7, 99.5, and 95.0% were achieved for 2,4-D, MCPA, and COD, respectively. Samples from the influent of the continuous reactor showed high toxicity levels for Lactuca sativa seeds, while toxicity was not detected after the continuous process.     

水稻叶面积指数和产量的空间变异性及关系研究

该文运用地质统计学方法分析了水稻叶面积指数与产量的空间分布及关系,结果表明：叶面积指数和产量均近似正态分布;在所研究的条件下,产量和大部分生育阶段(除拔节期)的叶面积指数都具有空间结构;孕穗期、抽穗期和乳熟期叶面积指数与产量在一定范围内具有显著空间相关关系。借鉴指示克立格的思想,提出了指示值分布法,分析了以上3个生育阶段的综合叶面积指数分布与产量的关系,该方法不仅对于水稻的遥感估产和精确农业的实施具有借鉴意义,且对于其它领域研究某一变量与某几个变量的空间分布关系,或某一变量随时间的动态变化与另一个变量的关系具有一定的参考价值。     

Fuzzy classification methods for determining land suitability from soil profile observations and topography

Because conventional Boolean retrieval of soil survey data and logical models for assessing land suitability treat both spatial units and attribute value ranges as exactly specifiable quantities, they ignore the continuous nature of soil and landscape variation and uncertainties in measurement which can result in the misclassification of sites that just fail to match strictly defined requirements. This paper uses fuzzy classification to determine land suitability from (i) multivariate point observations of soil attributes, (ii) topographically controlled site drainage conditions, and (iii) minimum contiguous areas, and compares the results obtained with conventional Boolean methods. The methods are illustrated using data from the Alberta Agricultural Department experimental farm at Lacombe in Alberta, Canada. Data on site elevation and soil chemical and physical properties measured at 154 soil profiles were interpolated by ordinary block kriging to 15 m × 15 m cells on a 50 × 50 grid. The soil property data for each cell were classified by Boolean and fuzzy methods. The digital elevation model created by interpolating the elevation data was used to determine the surface drainage network and map it in terms of the numbers of cells draining through each cell on the grid. This map was reclassified to yield Boolean and fuzzy maps of surface wetness which were then intersected with the soil profile classes. The resulting classification maps were examined for contiguity to locate areas where a block of minimum size (45m × 45m) could be located successfully. In this study Boolean methods reject larger numbers of cells than fuzzy classification, and select cells that are insufficiently contiguous to meet the aims of the land classification. Fuzzy methods produce contiguous areas and reject less information at all stages of the analyses than Boolean methods. They are much better than Boolean methods for classification of continuous variation, such as the results of the drainage analysis.