Development of an in silico evaluation system that quantitatively predicts skin sensitization using OECD Guideline No. 497 ITSv2 defined approach for skin sensitization classification.

The Integrated Testing Strategy version 2 (ITSv2) Defined Approach, which is a reliable skin sensitization hazard and multi-step risk assessment method, does not support quantitative risk assessment such as local lymph node assay EC3 values. In this study, we developed a high-performance in silico evaluation system that quantitatively predicts the EC3 values of chemical substances by combining the ITSv2 Defined Approach for hazard identification (ITSv2 HI) with machine learning models. This system uses in chemico/in vitro test data, molecular descriptors, and distance information based on read-across concepts as explanatory variables. The system achieves an R2 value of 0.617 on external-validation data. Substances misclassified in ITSv2 HI are considered to have properties that do not match the correspondence between tests expressing the adverse outcome pathway assumed in the ITSv2 Defined Approach and skin sensitization. Therefore, ITSv2 HI is assumed to be correct within the applicability domains of this system. When using only substances within the applicability domains to reconstruct CatBoost models, the R2 value reached 0.824 on the external-validation data, representing an improvement in system performance. The results demonstrate the utility of explanatory variables that reflect the read-across concept and the advantages of integrating multiple prediction methods.

Development of an oral mucosal irritation test using a three-dimensional human buccal oral mucosal model.

The oral mucosa can become irritated by oral care products and lip cosmetics. Therefore, it is important to determine the irritation potential of their ingredients and products during safety evaluations. We developed a method for oral mucosal irritation test using EpiOral, which is a three-dimensional cultured model. Exposure of sodium lauryl sulphate (SLS) to EpiOral showed a dose-dependent decrease in cell viability. Under 120 min exposure conditions, SLS irritation was detected when 60% cell viability was set as a criterion. Evaluation of the irritancy of SLS and four other raw materials used in oral products at three laboratories under the above conditions confirmed good transferability of the test. Focused on the similarity of the oral and eye mucous, 32 chemicals categorised by the UN-GHS eye-irritation classification were evaluated to ensure the reliability of our criteria at these laboratories. The concordance rate between the UN-GHS classification and our test results was 100% for irritants and 60% for non-irritants. The good intra-laboratory reproducibility of our test was confirmed from the evaluation results of negative and positive controls, and the good inter-laboratory reproducibility was confirmed from the results of 32 chemicals. These findings showed that oral mucosal irritation can be evaluated using EpiOral.

Bayesian inference of solid-liquid interfacial properties out of equilibrium.

Solid-liquid interfacial properties out of equilibrium provide the essential information required for understanding and controlling solidification microstructures in metallic materials. However, few studies have attempted to reveal all interfacial properties out of equilibrium in detail. The present study proposes an approach for simultaneously estimating all interfacial properties in a pure metal below the melting point on the basis of the Bayesian inference theory. The solid-liquid interfacial energy, interfacial mobility, and anisotropy parameters in pure Fe are estimated by combining molecular dynamics simulation with phase-field simulation using an ensemble Kalman filter, which is a data assimilation technique. Furthermore, the temperature dependences of all interfacial parameters are computed and discussed. In summary, the proposed multiscale approach integrates atomistic and microstructural simulations within the framework of data science and it has considerable potential for a wide variety of applications in materials engineering.

Heterogeneity in homogeneous nucleation from billion-atom molecular dynamics simulation of solidification of pure metal.

Can completely homogeneous nucleation occur? Large scale molecular dynamics simulations performed on a graphics-processing-unit rich supercomputer can shed light on this long-standing issue. Here, a billion-atom molecular dynamics simulation of homogeneous nucleation from an undercooled iron melt reveals that some satellite-like small grains surrounding previously formed large grains exist in the middle of the nucleation process, which are not distributed uniformly. At the same time, grains with a twin boundary are formed by heterogeneous nucleation from the surface of the previously formed grains. The local heterogeneity in the distribution of grains is caused by the local accumulation of the icosahedral structure in the undercooled melt near the previously formed grains. This insight is mainly attributable to the multi-graphics processing unit parallel computation combined with the rapid progress in high-performance computational environments.Nucleation is a fundamental physical process, however it is a long-standing issue whether completely homogeneous nucleation can occur. Here the authors reveal, via a billion-atom molecular dynamics simulation, that local heterogeneity exists during homogeneous nucleation in an undercooled iron melt.