Molecular dynamics simulations of a fluid-phase dipalmitoyl phosphatidylcholine lipid bilayer in water and of neat hexadecane are reported and compared with nuclear magnetic resonance spin-lattice relaxation and quasi-elastic neutron scattering data. On the 100-picosecond time scale of the present simulations, there is effectively no difference in the reorientational dynamics of the carbons in the membrane interior and in pure hexadecane. Given that the calculated fast reorientational correlation times and the "microscopic" lateral diffusion of the lipids show excellent agreement with the experimental results, it is concluded that the apparently high viscosity of the membrane is more closely related to molecular interactions on the surface rather than in the interior.

SynopsisPermeability coefficients P for He, and C3H, in 12 different silicone polymer membranes were determined at 35.0"C and pressures up to 9 atm. Values of F for CO,, CH,, and C,H, were also determined a t 10.0 and 55.0"C. In addition, mean diffusion coefficients D and solubility coefficients S were obtained for CO,, CH,, and C3H, in 6 silicone polymers a t 10.0, 35.0, and 55.0"C. Substitution of increasingly bulkier functional groups in the side and backbone chains of silicone polymers results in a significant decrease in P for a given penetrant gas. This is due mainly to a decrease in E, whereas S decreases to a much lesser extent.Backbone substitutions appear to have a somewhat lesser effect in depressing than equivalent side-chain substitutions. The selectivity of a silicone membrane for a gas A relative to a gas €3, i.e., the permeability ratio &A)/&€%), may increase or decrease as a result of such substitutions, but only if the substituted groups are sufficiently bulky. The selectivity of the more highly permeable silicone membranes is controlled by the ratio S(A)/S(H). whereas the selectivity of the less permeable membranes depends on both the ratios D(A)/D(B) and S(A)/S(R). The permeability as well as the selectivity of one silicone membrane toward CO, were significantly enhanced by the substitution of a fluorine-containing side group that increased the solubility of CO, in that polymer.

Adverse outcome pathways (AOPs) are a recent toxicological construct that connects, in a formalized, transparent and quality-controlled way, mechanistic information to apical endpoints for regulatory purposes. AOP links a molecular initiating event (MIE) to the adverse outcome (AO) via key events (KE), in a way specified by key event relationships (KER). Although this approach to formalize mechanistic toxicological information only started in 2010, over 200 AOPs have already been established. At this stage, new requirements arise, such as the need for harmonization and re-assessment, for continuous updating, as well as for alerting about pitfalls, misuses and limits of applicability. In this review, the history of the AOP concept and its most prominent strengths are discussed, including the advantages of a formalized approach, the systematic collection of weight of evidence, the linkage of mechanisms to apical end points, the examination of the plausibility of epidemiological data, the identification of critical knowledge gaps and the design of mechanistic test methods. To prepare the ground for a broadened and appropriate use of AOPs, some widespread misconceptions are explained. Moreover, potential weaknesses and shortcomings of the current AOP rule set are addressed (1) to facilitate the discussion on its further evolution and (2) to better define appropriate vs. less suitable application areas. Exemplary toxicological studies are presented to discuss the linearity assumptions of AOP, the management of event modifiers and compensatory mechanisms, and whether a separation of toxicodynamics from toxicokinetics including metabolism is possible in the framework of pathway plasticity. Suggestions on how to compromise between different needs of AOP stakeholders have been added. A clear definition of open questions and limitations is provided to encourage further progress in the field.

Engineered nanomaterials (ENMs) have tremendous potential to produce beneficial technological impact in numerous sectors in society. Safety assessment is, of course, of paramount importance. However, the myriad variations of ENM properties makes the identification of specific features driving toxicity challenging. At the same time, reducing animal tests by introducing alternative and/or predictive in vitro and in silico methods has become a priority. It is important to embrace these new advances in the safety assessment of ENMs. Indeed, remarkable progress has been made in recent years with respect to mechanism-based hazard assessment of ENMs, including systems biology approaches as well as high-throughput screening platforms, and new tools are also emerging in risk assessment and risk management for humans and the environment across the whole life-cycle of nano-enabled products. Here, we highlight some of the key advances in the hazard and risk assessment of ENMs.

OpenTox provides an interoperable, standards-based Framework for the support of predictive toxicology data management, algorithms, modelling, validation and reporting. It is relevant to satisfying the chemical safety assessment requirements of the REACH legislation as it supports access to experimental data, (Quantitative) Structure-Activity Relationship models, and toxicological information through an integrating platform that adheres to regulatory requirements and OECD validation principles. Initial research defined the essential components of the Framework including the approach to data access, schema and management, use of controlled vocabularies and ontologies, architecture, web service and communications protocols, and selection and integration of algorithms for predictive modelling. OpenTox provides end-user oriented tools to non-computational specialists, risk assessors, and toxicological experts in addition to Application Programming Interfaces (APIs) for developers of new applications. OpenTox actively supports public standards for data representation, interfaces, vocabularies and ontologies, Open Source approaches to core platform components, and community-based collaboration approaches, so as to progress system interoperability goals.The OpenTox Framework includes APIs and services for compounds, datasets, features, algorithms, models, ontologies, tasks, validation, and reporting which may be combined into multiple applications satisfying a variety of different user needs. OpenTox applications are based on a set of distributed, interoperable OpenTox API-compliant REST web services. The OpenTox approach to ontology allows for efficient mapping of complementary data coming from different datasets into a unifying structure having a shared terminology and representation.Two initial OpenTox applications are presented as an illustration of the potential impact of OpenTox for high-quality and consistent structure-activity relationship modelling of REACH-relevant endpoints: ToxPredict which predicts and reports on toxicities for endpoints for an input chemical structure, and ToxCreate which builds and validates a predictive toxicity model based on an input toxicology dataset. Because of the extensible nature of the standardised Framework design, barriers of interoperability between applications and content are removed, as the user may combine data, models and validation from multiple sources in a dependable and time-effective way.