Evaluation of QSAR models for predicting mutagenicity: outcome of the Second Ames/QSAR international challenge project

Quantitative structure-activity relationship (QSAR) models are powerful in silico tools for predicting the mutagenicity of unstable compounds, impurities and metabolites that are difficult to examine using the Ames test. Ideally, Ames/QSAR models for regulatory use should demonstrate high sensitivity, low false-negative rate and wide coverage of chemical space. To promote superior model development, the Division of Genetics and Mutagenesis, National Institute of Health Sciences, Japan (DGM/NIHS), conducted the Second Ames/QSAR International Challenge Project (2020-2022) as a successor to the First Project (2014-2017), with 21 teams from 11 countries participating. The DGM/NIHS provided a curated training dataset of approximately 12,000 chemicals and a trial dataset of approximately 1,600 chemicals, and each participating team predicted the Ames mutagenicity of each trial chemical using various Ames/QSAR models. The DGM/NIHS then provided the Ames test results for trial chemicals to assist in model improvement. Although overall model performance on the Second Project was not superior to that on the First, models from the eight teams participating in both projects achieved higher sensitivity than models from teams participating in only the Second Project. Thus, these evaluations have facilitated the development of QSAR models.

A holocenic and dynamic hybrid zone between two cactophilic Drosophila species in a coastal lowland plain of the Brazilian Atlantic Forest

Hybridization and introgression are processes that contribute to shaping biological diversity. The factors promoting the formation of these processes are multiples but poorly explored in a biogeographical and ecological context. In the southeast coastal plain of the Brazilian Atlantic Forest, a hybrid zone was described between two closely related cactophilic species, Drosophila antonietae and D. serido. Here, we revisited and analysed specimens from this hybrid zone to evaluate its temporal and spatial dynamic. We examined allopatric and sympatric populations of the flies using independent sources of data such as mitochondrial and nuclear sequences, microsatellite loci, morphometrics of wings and male genitalia, and climatic niche models. We also verified the emergence of the flies from necrotic tissues of collected cacti to verify the role of host association for the population dynamics. Our results support the existence of a hybrid zone due to secondary contact and limited to the localities where the two species are currently in contact. Furthermore, we detected asymmetric bidirectional introgression and the maintenance of the species integrity, ecological association and morphological characters, suggesting selection and limited introgression. Considering our paleomodels, probably this hybrid zone is recent and the contact occurred during the Holocene to the present day, favoured by range expansion of their populations due to expansion of open and dry areas in eastern South America during palaeoclimatic and geomorphological events.

COSMOS next generation - A public knowledge base leveraging chemical and biological data to support the regulatory assessment of chemicals

The COSMOS Database (DB) was originally established to provide reliable data for cosmetics-related chemicals within the COSMOS Project funded as part of the SEURAT-1 Research Initiative. The database has subsequently been maintained and developed further into COSMOS Next Generation (NG), a combination of database and in silico tools, essential components of a knowledge base. COSMOS DB provided a cosmetics inventory as well as other regulatory inventories, accompanied by assessment results and in vitro and in vivo toxicity data. In addition to data content curation, much effort was dedicated to data governance - data authorisation, characterisation of quality, documentation of meta information, and control of data use. Through this effort, COSMOS DB was able to merge and fuse data of various types from different sources. Building on the previous effort, the COSMOS Minimum Inclusion (MINIS) criteria for a toxicity database were further expanded to quantify the reliability of studies. COSMOS NG features multiple fingerprints for analysing structure similarity, and new tools to calculate molecular properties and screen chemicals with endpoint-related public profilers, such as DNA and protein binders, liver alerts and genotoxic alerts. The publicly available COSMOS NG enables users to compile information and execute analyses such as category formation and read-across. This paper provides a step-by-step guided workflow for a simple read-across case, starting from a target structure and culminating in an estimation of a NOAEL confidence interval. Given its strong technical foundation, inclusion of quality-reviewed data, and provision of tools designed to facilitate communication between users, COSMOS NG is a first step towards building a toxicological knowledge hub leveraging many public data systems for chemical safety evaluation. We continue to monitor the feedback from the user community at support@mn-am.com.

Nursing telematics education: a critical success factor to the "best practice"

This communication aims to help demonstrating that nurses education and training, in what information and telecommunications technologies are concerned, is a critical success factor in the achievement of a strategic goal: the "best practice" in nursing. This goal is seen from the formal perspective of the quality of the nursing care process. Simultaneously, one makes a methodological approach by employing a strategical planning technique in the nursing context.