International STakeholder NETwork (ISTNET): creating a developmental neurotoxicity (DNT) testing road map for regulatory purposes.

A major problem in developmental neurotoxicity (DNT) risk assessment is the lack of toxicological hazard information for most compounds. Therefore, new approaches are being considered to provide adequate experimental data that allow regulatory decisions. This process requires a matching of regulatory needs on the one hand and the opportunities provided by new test systems and methods on the other hand. Alignment of academically and industrially driven assay development with regulatory needs in the field of DNT is a core mission of the International STakeholder NETwork (ISTNET) in DNT testing. The first meeting of ISTNET was held in Zurich on 23-24 January 2014 in order to explore the concept of adverse outcome pathway (AOP) to practical DNT testing. AOPs were considered promising tools to promote test systems development according to regulatory needs. Moreover, the AOP concept was identified as an important guiding principle to assemble predictive integrated testing strategies (ITSs) for DNT. The recommendations on a road map towards AOP-based DNT testing is considered a stepwise approach, operating initially with incomplete AOPs for compound grouping, and focussing on key events of neurodevelopment. Next steps to be considered in follow-up activities are the use of case studies to further apply the AOP concept in regulatory DNT testing, making use of AOP intersections (common key events) for economic development of screening assays, and addressing the transition from qualitative descriptions to quantitative network modelling.

Dustiness and deagglomeration testing: interlaboratory comparison of systems for nanoparticle powders

Different types of aerosolization and deagglomeration testing systems exist for studying the properties of nanomaterial powders and their aerosols. However, results are dependent on the specific methods used. In order to have well-characterized aerosols, we require a better understanding of how system parameters and testing conditions influence the properties of the aerosols generated. In the present study, four experimental setups delivering different aerosolization energies were used to test the resultant aerosols of two distinct nanomaterials (hydrophobic and hydrophilic TiO2). The reproducibility of results within each system was good. However, the number concentrations and size distributions of the aerosols created varied across the four systems; for number concentrations, e.g., from 10(3) to 10(6) #/cm(3). Moreover, distinct differences were also observed between the two materials with different surface coatings. The article discusses how system characteristics and other pertinent conditions modify the test results. We propose using air velocity as a suitable proxy for estimating energy input levels in aerosolization systems. The information derived from this work will be especially useful for establishing standard operating procedures for testing nanopowders, as well as for estimating their release rates under different energy input conditions, which is relevant for occupational exposure.

Comparing Etest and Broth Microdilution for Antifungal Susceptibility Testing of the Most-Relevant Pathogenic Molds.

Invasive mold infections are life-threatening diseases for which appropriate antifungal therapy is crucial. Their epidemiology is evolving, with the emergence of triazole-resistant Aspergillus spp. and multidrug-resistant non-Aspergillus molds. Despite the lack of interpretive criteria, antifungal susceptibility testing of molds may be useful in guiding antifungal therapy. The standard broth microdilution method (BMD) is demanding and requires expertise. We assessed the performance of a commercialized gradient diffusion method (Etest method) as an alternative to BMD. The MICs or minimal effective concentrations (MECs) of amphotericin B, voriconazole, posaconazole, caspofungin, and micafungin were assessed for 290 clinical isolates of the most representative pathogenic molds (154 Aspergillus and 136 non-Aspergillus isolates) with the BMD and Etest methods. Essential agreements (EAs) within ±2 dilutions of ≥90% between the two methods were considered acceptable. EAs for amphotericin B and voriconazole were >90% for most potentially susceptible species. For posaconazole, the correlation was acceptable for Mucoromycotina but Etest MIC values were consistently lower for Aspergillus spp. (EAs of <90%). Excellent EAs were found for echinocandins with highly susceptible (MECs of <0.015 μg/ml) or intrinsically resistant (MECs of >16 μg/ml) strains. However, MEC determinations lacked consistency between methods for strains exhibiting mid-range MECs for echinocandins. We concluded that the Etest method is an appropriate alternative to BMD for antifungal susceptibility testing of molds under specific circumstances, including testing with amphotericin B or triazoles for non-Aspergillus molds (Mucoromycotina and Fusarium spp.). Additional study of molecularly characterized triazole-resistant Aspergillus isolates is required to confirm the ability of the Etest method to detect voriconazole and posaconazole resistance among Aspergillus spp.

Local effects drive heterozygosity-fitness correlations in an outcrossing long-lived tree.

Heterozygosity-fitness correlations (HFCs) have been used to understand the complex interactions between inbreeding, genetic diversity and evolution. Although frequently reported for decades, evidence for HFCs was often based on underpowered studies or inappropriate methods, and hence their underlying mechanisms are still under debate. Here, we used 6100 genome-wide single nucleotide polymorphisms (SNPs) to test for general and local effect HFCs in maritime pine (Pinus pinaster Ait.), an iconic Mediterranean forest tree. Survival was used as a fitness proxy, and HFCs were assessed at a four-site common garden under contrasting environmental conditions (total of 16 288 trees). We found no significant correlations between genome-wide heterozygosity and fitness at any location, despite variation in inbreeding explaining a substantial proportion of the total variance for survival. However, four SNPs (including two non-synonymous mutations) were involved in significant associations with survival, in particular in the common gardens with higher environmental stress, as shown by a novel heterozygosity-fitness association test at the species-wide level. Fitness effects of SNPs involved in significant HFCs were stable across maritime pine gene pools naturally growing in distinct environments. These results led us to dismiss the general effect hypothesis and suggested a significant role of heterozygosity in specific candidate genes for increasing fitness in maritime pine. Our study highlights the importance of considering the species evolutionary and demographic history and different spatial scales and testing environments when assessing and interpreting HFCs.

Fast and Rigorous Computation of Gene and Pathway Scores from SNP-Based Summary Statistics.

Integrating single nucleotide polymorphism (SNP) p-values from genome-wide association studies (GWAS) across genes and pathways is a strategy to improve statistical power and gain biological insight. Here, we present Pascal (Pathway scoring algorithm), a powerful tool for computing gene and pathway scores from SNP-phenotype association summary statistics. For gene score computation, we implemented analytic and efficient numerical solutions to calculate test statistics. We examined in particular the sum and the maximum of chi-squared statistics, which measure the strongest and the average association signals per gene, respectively. For pathway scoring, we use a modified Fisher method, which offers not only significant power improvement over more traditional enrichment strategies, but also eliminates the problem of arbitrary threshold selection inherent in any binary membership based pathway enrichment approach. We demonstrate the marked increase in power by analyzing summary statistics from dozens of large meta-studies for various traits. Our extensive testing indicates that our method not only excels in rigorous type I error control, but also results in more biologically meaningful discoveries.