An overall strategy for the testing of chemicals for human hazard and risk assessment under the EU REACH system

In its White Paper, "Strategy for a Future Chemicals Policy," published in 2001, the European Commission (EC) proposed the REACH (Registration, Evaluation and Authorisation of CHemicals) system to deal with both existing and new chemical substances. This system is based on a top-down approach to toxicity testing, in which the degree of toxicity information required is dictated primarily by production volume (tonnage). If testing is to be based on traditional methods, very large numbers of laboratory animals could be needed in response to the REACH system, causing ethical, scientific and logistical problems that would be incompatible with the time-schedule envisaged for testing. The EC has emphasised the need to minimise animal use, but has failed to produce a comprehensive strategy for doing so. The present document provides an overall scheme for predictive toxicity testing, whereby the non-animal methods identified and discussed in a recent and comprehensive ECVAM document, could be used in a tiered approach to provide a rapid and scientifically justified basis for the risk assessment of chemicals for their toxic effects in humans. The scheme starts with a preliminary risk assessment process (involving available information on hazard and exposure), followed by testing, based on physicochemical properties and (Q)SAR approaches. (Q)SAR analyses are used in conjunction with expert system and biokinetic modelling, and information on metabolism and identification of the principal metabolites in humans. The resulting information is then combined with production levels and patterns of use to assess potential human exposure. The nature and extent of any further testing should be based strictly on the need to fill essential information gaps in order to generate adequate risk assessments, and should rely on non-animal methods, as far as possible. The scheme also includes a feedback loop, so that new information is used to improve the predictivity of computational expert systems. Several recommendations are made, the most important of which is that the European Union (EU) should actively promote the improvement and validation of (Q)SAR models and expert systems, and computer-based methods for biokinetic modelling, since these offer the most realistic and most economical solution to the need to test large numbers of chemicals.     

The Privileged Chemical Space Predictor (pcsp): A computer program that identifies privileged chemical space from screens of modularly assembled chemical libraries

Modularly assembled combinatorial libraries are often used to identify ligands that bind to and modulate the function of a protein or a nucleic acid. Much of the data from screening these compounds, however, is not efficiently utilized to define structure–activity relationships (SAR). If SAR data are accurately constructed, it can enable the design of more potent binders. Herein, we describe a computer program called Privileged Chemical Space Predictor (pcsp) that statistically determines SAR from high-throughput screening (HTS) data and then identifies features in small molecules that predispose them for binding a target. Features are scored for statistical significance and can be utilized to design improved second generation compounds or more target-focused libraries. The program’s utility is demonstrated through analysis of a modularly assembled peptoid library that previously was screened for binding to and inhibiting a group I intron RNA from the fungal pathogen Candida albicans.     

SAR modeling of genotoxic phenomena: the consequence on predictive performance of deviation from a unity ratio of genotoxicants/non-genotoxicants

SAR approaches to the study of genotoxic phenomena are finding increased applications. However, the data being modeled are frequently not considered optimal due to the small size of the dataset and an uneven distribution of genotoxicants and non-genotoxicants in the dataset. The effects of such imbalances on the performance of one SAR approach were investigated with respect to the modeling of the induction of unscheduled DNA synthesis in rat hepotocytes and of sister chromatid exchanges and chromosomal aberrations in cultural CHO cells. The analyses indicate that if genotoxicants exceed non-genotoxicants, the performance of the SAR model can be improved if the dataset is supplemented with physiological chemicals which are assumed to be non-genotoxicants. On the other hand, if non-genotoxicants exceed genotoxicants, it was found that the predictive performance of the resulting SAR model is not improved by removal of genotoxicants from the dataset to achieve a ratio of genotoxicants/genotoxicants of unity. Overall, the present analyses did not result in the development of SAR models of greatly increased predictivity. Conceivably, for the particular datasets and SAR paradigm the limit of predictivity has been reached. The possibility of investigating the use of a "battery" of SAR paradigms should be considered.     

An overall strategy for the testing of chemicals for human hazard and risk assessment under the EU REACH system

In its White Paper, Strategy for a Future Chemicals Policy, published in 2001, the European Commission (EC) proposed the REACH (Registration, Evaluation and Authorisation of CHemicals) system to deal with both existing and new chemical substances. This system is based on a top-down approach to toxicity testing, in which the degree of toxicity information required is dictated primarily by production volume (tonnage). If testing is to be based on traditional methods, very large numbers of laboratory animals could be needed in response to the REACH system, causing ethical, scientific and logistical problems that would be incompatible with the time-schedule envisaged for testing. The EC has emphasised the need to minimise animal use, but has failed to produce a comprehensive strategy for doing so. The present document provides an overall scheme for predictive toxicity testing, whereby the non-animal methods identified and discussed in a recent and comprehensive ECVAM document, could be used in a tiered approach to provide a rapid and scientifically justified basis for the risk assessment of chemicals for their toxic effects in humans. The scheme starts with a preliminary risk assessment process (involving available information on hazard and exposure), followed by testing, based on physicochemical properties and (Q)SAR approaches. (Q)SAR analyses are used in conjunction with expert system and biokinetic modelling, and information on metabolism and identification of the principal metabolites in humans. The resulting information is then combined with production levels and patterns of use to assess potential human exposure. The nature and extent of any further testing should be based strictly on the need to fill essential information gaps in order to generate adequate risk assessments, and should rely on non-animal methods, as far as possible. The scheme also includes a feedback loop, so that new information is used to improve the predictivity of computational expert systems. Several recommendations are made, the most important of which is that the European Union (EU) should actively promote the improvement and validation of (Q)SAR models and expert systems, and computer-based methods for biokinetic modelling, since these offer the most realistic and most economical solution to the need to test large numbers of chemicals.     

Synthesis,structure–activity relationship and crystallographic studies of 3-substituted indolin-2-one RET inhibitors

The synthesis, structure–activity relationships (SAR) and structural data of a series of indolin-2-one inhibitors of RET tyrosine kinase are described. These compounds were designed to explore the available space around the indolinone scaffold within RET active site. Several substitutions at different positions were tested and biochemical data were used to draw a molecular model of steric and electrostatic interactions, which can be applied to design more potent and selective RET inhibitors. The crystal structures of RET kinase domain in complex with three inhibitors were solved. All three compounds bound in the ATP pocket and formed two hydrogen bonds with the kinase hinge region. Crystallographic analysis confirmed predictions from molecular modelling and helped refine SAR results. These data provide important information for the development of indolinone inhibitors for the treatment of RET-driven cancers.     

Unravelling the dynamics of organisms in a changing world using ecological modelling

Understanding and predicting the dynamics of organisms is a central objective in ecology and conservation biology, and modelling provides a solution to tackling this problem. However, the complex nature of ecological systems means that for a thorough understanding of ecological dynamics at hierarchical scales, a set of modeling approaches need to be adopted. This review illustrates how modelling approaches can be used to understand the dynamics of organisms in applied ecological problems, focussing on mechanistic models at a local scale and statistical models at a broad scale. Mechanistic models incorporate ecological processes explicitly and thus are likely to be robust under novel conditions. Models based on behavioural decisions by individuals represent a typical example of the successful application of mechanistic models to applied problems. Considering the data-hungry nature of such mechanistic models, model complexity and parameterisation need to be explored further for a quick and widespread implementation of this model type. For broad-scale phenomena, statistical models play an important role in dealing with problems that are often inherent in data. Examples include models for quantifying population trends from long-term, large-scale data and those for comparative methods of extinction risk. Novel statistical approaches also allow mechanistic models to be parameterised using readily obtained data at a macro scale. In conclusion, the complementary use and improvement of multiple model types, the increased use of novel model parameterisation, the examination of model transferability and the achievement of wider biodiversity information availability are key challenges for the effective use of modelling in applied ecological problems.     

Molecular modelling of glycans: three-dimensional structure and protein fraction interaction. The example of rabbit sero-transferrin

On the basis of experimental data and of computer calculations using the Tripos 5.3 force field in order to examine the three-dimensional structures which are sterically feasible and the conformations which are energetically the most favourable, we have designed a program of molecular modelling of biantennary glycans of the N-acetyllactosaminic type (complex type). We demonstrate that, in absence of any interaction with the protein, a high number of glycan conformations exists which can be classified into five basic conformations, four of which have already been described. In fact, in addition to the Y-, T-, "bird" and "broken-wing" conformations, a "back-folded wing" conformation is energetically feasible. In contrast, the glycan linked to the protein is immobilized into only one conformation: the "broken-wing" conformation. Forming a bridge between the two lobes of the peptide chain, it probably contributes to the maintenance of the protein in a biologically active conformation.     

Threading neural feedforward into a mechanical spring: How biology exploits physics in limb control

A solution is proposed of the hitherto unsolved problem as to how neural feedforward through inverse modelling and negative feedback realised by a mechanical spring can be combined to achieve a highly effective control of limb movement. The revised spring approach that we suggest does not require forward modelling and produces simulated data which are as close as possible to experimental human data. Control models based on peripheral sensing with forward modelling, which are favoured in the current literature, fail to create such data. Our approach suggests that current views on motor control and learning should be revisited.Acknowledgement This article is dedicated in memoriam to Gustav A. Lienert, who edited the Draht-Biege-Probe (Lienert 1961), a wire-bending test measuring complex sensorimotor skills in a genially simple manner. We thank Nicole Pledger for language assistance. This work was supported by Grants Ka 417/18 and Ka 417/24 from Deutsche Forschungsgemeinschaft (DFG).     

Distributed structure-searchable toxicity (DSSTox) public database network: a proposal.

The ability to assess the potential genotoxicity, carcinogenicity, or other toxicity of pharmaceutical or industrial chemicals based on chemical structure information is a highly coveted and shared goal of varied academic, commercial, and government regulatory groups. These diverse interests often employ different approaches and have different criteria and use for toxicity assessments, but they share a need for unrestricted access to existing public toxicity data linked with chemical structure information. Currently, there exists no central repository of toxicity information, commercial or public, that adequately meets the data requirements for flexible analogue searching, Structure-Activity Relationship (SAR) model development, or building of chemical relational databases (CRD). The distributed structure-searchable toxicity (DSSTox) public database network is being proposed as a community-supported, web-based effort to address these shared needs of the SAR and toxicology communities. The DSSTox project has the following major elements: (1) to adopt and encourage the use of a common standard file format (structure data file (SDF)) for public toxicity databases that includes chemical structure, text and property information, and that can easily be imported into available CRD applications; (2) to implement a distributed source approach, managed by a DSSTox Central Website, that will enable decentralized, free public access to structure-toxicity data files, and that will effectively link knowledgeable toxicity data sources with potential users of these data from other disciplines (such as chemistry, modeling, and computer science); and (3) to engage public/commercial/academic/industry groups in contributing to and expanding this community-wide, public data sharing and distribution effort. The DSSTox project's overall aims are to effect the closer association of chemical structure information with existing toxicity data, and to promote and facilitate structure-based exploration of these data within a common chemistry-based framework that spans toxicological disciplines.     

Integrating data mining and transmission theory in the ecology of infectious diseases

Our understanding of ecological processes is built on patterns inferred from data. Applying modern analytical tools such as machine learning to increasingly high dimensional data offers the potential to expand our perspectives on these processes, shedding new light on complex ecological phenomena such as pathogen transmission in wild populations. Here, we propose a novel approach that combines data mining with theoretical models of disease dynamics. Using rodents as an example, we incorporate statistical differences in the life history features of zoonotic reservoir hosts into pathogen transmission models, enabling us to bound the range of dynamical phenomena associated with hosts, based on their traits. We then test for associations between equilibrium prevalence, a key epidemiological metric and data on human outbreaks of rodent‐borne zoonoses, identifying matches between empirical evidence and theoretical predictions of transmission dynamics. We show how this framework can be generalized to other systems through a rubric of disease models and parameters that can be derived from empirical data. By linking life history components directly to their effects on disease dynamics, our mining‐modelling approach integrates machine learning and theoretical models to explore mechanisms in the macroecology of pathogen transmission and their consequences for spillover infection to humans.     

A web-accessible computer program for calculating electrical potentials and ion activities at cell-membrane surfaces

Aims

Increasing evidence indicates that plant responses to ions (uptake/transport, inhibition, and alleviation of inhibition) are dependent upon ion activities at the outer surface of root-cell plasma membranes (PMs) rather than activities in the bulk-phase rooting medium.

Methods

A web-accessible computer program was written to calculate the electrical potential (ψ) at the outer surface of root-cell PMs (ψ _PM). From these values of ψ _PM, activities of ion I with charge Z ({I ^Z}) can be calculated for the outer surface of the PM ({I ^Z}_PM). In addition, ψ and {I ^Z} in the Donnan phase of the cell walls (ψ _CW and {I ^Z}_CW) can be calculated.

Results

By reanalysing published data, we illustrate how this computer program can assist in the investigation of plant-ion interactions. For example, we demonstrate that in saline solutions, both Ca deficiency and Na uptake are more closely related to {Ca²⁺}_PM and {Na⁺}_PM than to {Ca²⁺}_b and {Na⁺}_b (activities in the bulk-phase media). Additional examples are given for Zn and P nutrition, Ni toxicity, and arsenate uptake.

Conclusions

The computer program presented here should assist others to develop an electrostatic view of plant-ion interactions and to re-evaluate some commonly-held views regarding mechanisms of ion transport, toxicity, competition among ions, and other phenomena.     

Assessment of Factors Governing Biodegradability of PAHs in Three Soils Aged Under Field Conditions

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous contaminants of great environmental concern due to their toxic, mutagenic and carcinogenic properties. This study correlates soil characteristics (i.e. soil organic matter, particle- and pore-size distribution) with extractability and toxicity data (LUMIStox, Ostracod) to investigate factors that govern biodegradability of PAHs in three historically contaminated soils. Desorption of PAHs occurred most readily from soil TA1 (82%), followed by soil AS3.7 (69%) and soil WG2 (20%). This is in line with toxicity data, as the soil in which the greatest contaminant desorption (SFE) was observed exhibited the highest toxicity (TA1). Of the three soils, pronounced biodegradation of 2-4-ring, and slight biodegradation of 5-ring PAHs was observed only in AS3.7, while no decrease of PAHs was reported for soils WG2 and TA1 during the degradation experiment. Strong sorption reduced pollutant bioavailability in WG2 and hence hampered biodegradation. By contrast, pollutant sorption was weak in TA1 and microbial activity was most likely inhibited due to high toxicity in this soil. Based on our results we conclude that biodegradation of PAHs in soils is determined by a number of phenomena with complex interactions between them. Consideration of a single factor will be misleading and may result in false prediction of the biodegradation potential.     

Bone Growth Dynamics of the Facial Skeleton and Mandible in <Emphasis Type="Italic">Gorilla gorilla</Emphasis> and <Emphasis Type="Italic">Pan troglodytes</Emphasis>

Adult craniofacial morphology results from complex processes that involve growth by bone modelling and interactions of skeletal components to keep a functional and structural balance. Previous analyses of growth dynamics in humans revealed critical changes during late ontogeny explaining particular morphological features in our species. Data on bone modelling patterns from other primate species could help us to determine whether postnatal changes in the growth dynamics of the craniofacial complex are human specific or are shared with other primates. However, characterizations of bone modelling patterns through ontogeny in non-human hominids are scarce and restricted to isolated data on facial and mandibular regions. In the present study, we analyse the bone modelling patterns in an ontogenetic series of Pan and Gorilla to infer the growth dynamics of their craniofacial complex during postnatal development. Our results show that both Pan troglodytes and Gorilla gorilla are characterized by species-specific bone modelling patterns indicative of a mainly forward growth direction during postnatal development. Both species show minor but consistent ontogenetic changes in the distribution of bone modelling fields in specific regions of the face and mandible, in contrast to other regions which show more constant bone modelling patterns. In addition, we carry out a preliminary integrative study merging histological and geometric morphometric data. Both approaches yield highly complementary data, each analysis providing details on specific growth dynamics unavailable to the other. Moreover, geometric morphometric data show that ontogenetic variation in the modelling pattern of the mandibular ramus may be linked to sexual dimorphism.     

A reference business process for ecological niche modelling

Ecological niche modelling combines species occurrence points with environmental raster layers in order to obtain models for describing the probabilistic distribution of species. The process to generate an ecological niche model is complex. It requires dealing with a large amount of data, use of different software packages for data conversion, for model generation and for different types of processing and analyses, among other functionalities. A software platform that integrates all requirements under a single and seamless interface would be very helpful for users. Furthermore, since biodiversity modelling is constantly evolving, new requirements are constantly being added in terms of functions, algorithms and data formats. This evolution must be accompanied by any software intended to be used in this area. In this scenario, a Service-Oriented Architecture (SOA) is an appropriate choice for designing such systems. According to SOA best practices and methodologies, the design of a reference business process must be performed prior to the architecture definition. The purpose is to understand the complexities of the process (business process in this context refers to the ecological niche modelling problem) and to design an architecture able to offer a comprehensive solution, called a reference architecture, that can be further detailed when implementing specific systems. This paper presents a reference business process for ecological niche modelling, as part of a major work focused on the definition of a reference architecture based on SOA concepts that will be used to evolve the openModeller software package for species modelling. The basic steps that are performed while developing a model are described, highlighting important aspects, based on the knowledge of modelling experts. In order to illustrate the steps defined for the process, an experiment was developed, modelling the distribution of Ouratea spectabilis (Mart.) Engl. (Ochnaceae) using openModeller. As a consequence of the knowledge gained with this work, many desirable improvements on the modelling software packages have been identified and are presented. Also, a discussion on the potential for large-scale experimentation in ecological niche modelling is provided, highlighting opportunities for research. The results obtained are very important for those involved in the development of modelling tools and systems, for requirement analysis and to provide insight on new features and trends for this category of systems. They can also be very helpful for beginners in modelling research, who can use the process and the experiment example as a guide to this complex activity.     

Validation and discovery from computational biology models

Simulation software is often a fundamental component in systems biology projects and provides a key aspect of the integration of experimental and analytical techniques in the search for greater understanding and prediction of biology at the systems level. It is important that the modelling and analysis software is reliable and that techniques exist for automating the analysis of the vast amounts of data which such simulation environments generate. A rigorous approach to the development of complex modelling software is needed. Such a framework is presented here together with techniques for the automated analysis of such models and a process for the automatic discovery of biological phenomena from large simulation data sets. Illustrations are taken from a major systems biology research project involving the in vitro investigation, modelling and simulation of epithelial tissue.     

Coordinate Gene Activity in Response to Agents That Induce Systemic Acquired Resistance

In a variety of plant species, the development of necrotic lesions in response to pathogen infection leads to induction of generalized disease resistance in uninfected tissues. A well-studied example of this "immunity" reaction is systemic acquired resistance (SAR) in tobacco. SAR is characterized by the development of a disease-resistant state in plants that have reacted hypersensitively to previous infection by tobacco mosaic virus. Here, we show that the onset of SAR correlates with the coordinate induction of nine classes of mRNAs. Salicylic acid, a candidate for the endogenous signal that activates the resistant state, induces expression of the same "SAR genes." A novel synthetic immunization compound, methyl-2,6-dichloroisonicotinic acid, also induces both resistance and SAR gene expression. These observations are consistent with the hypothesis that induced resistance results at least partially from coordinate expression of these SAR genes. A model is presented that ties pathogen-induced necrosis to the biosynthesis of salicylic acid and the induction of SAR.     

Global pattern and local variation in species–area relationships

Aim We conducted a meta‐analysis of species–area relationships (SARs) by combining several data sets and important covariates such as types of islands, taxonomic groups, latitude and spatial extent, in a hierarchical model framework to study global pattern and local variation in SARs and its consequences for prediction. Location One thousand nine hundred and eighteen islands from 94 SAR studies from around the world. Methods We developed a generalization of the power‐law SAR model, the HSARX model, which allows: (1) the inclusion of multiple focal parameters (intercept, slope, within‐study variance), (2) use of multiple effect modifiers based on a collection of SAR studies, and (3) modelling of the between‐ and within‐study variability. Results The global pattern in the SAR was the average of local SARs and had wide confidence intervals. The global SAR slope was 0.228 with 90% confidence limits of 0.059 and 0.412. The intercept, slope and within‐study variability of local SARs showed great heterogeneity as a result of the interaction of modifying covariates. Confidence intervals for these SAR parameters were narrower when other covariates in addition to area were accounted for, thus increasing the accuracy of the predictions for species richness. The significant effect of latitude and the interaction of latitude, taxa and island type on the SAR slope indicated that the ‘typical’ latitudinal diversity gradient can be reversed in isolated systems. Main conclusions The power‐law relationship underlying the HSARX model provides a good fit for non‐nested SARs across vastly different spatial scales by taking into account other covariates. The HSARX framework allows researchers to explore the complex interactions among SAR parameters and modifying variables, to explicitly study the scale dependence, and to make robust predictions on multiple levels (island, study, global) with associated prediction intervals. From a prediction perspective, it is not the global pattern but the local variation that matters.