High-Throughput Analysis of Ovarian Cycle Disruption by Mixtures of Aromatase Inhibitors.

Background: Combining computational toxicology with ExpoCast exposure estimates and ToxCast™ assay data gives us access to predictions of human health risks stemming from exposures to chemical mixtures.

Objectives: We explored, through mathematical modeling and simulations, the size of potential effects of random mixtures of aromatase inhibitors on the dynamics of women's menstrual cycles.

Methods: We simulated random exposures to millions of potential mixtures of 86 aromatase inhibitors.

Compilation of Data and Modelling of Nanoparticle Interactions and Toxicity in the NanoPUZZLES Project.

The particular properties of nanomaterials have led to their rapidly increasing use in diverse fields of application. However, safety assessment is not keeping pace and there are still gaps in the understanding of their hazards. Computational models predicting nanotoxicity, such as (quantitative) structure-activity relationships ((Q)SARs), can contribute to safety evaluation, in line with general efforts to apply alternative methods in chemical risk assessment.

A solid-phase extraction procedure coupled to 1H NMR, with chemometric analysis, to seek reliable markers of the botanical origin of honey.

The aim of this work was to establish an analytical method for identifying the botanical origin of honey, as an alternative to conventional melissopalynological, organoleptic and instrumental methods (gas-chromatography coupled to mass spectrometry (GC-MS), high-performance liquid chromatography HPLC). The procedure is based on the (1)H nuclear magnetic resonance (NMR) profile coupled, when necessary, with electrospray ionisation-mass spectrometry (ESI-MS) and two-dimensional NMR analyses of solid-phase extraction (SPE)-purified honey samples, followed by chemometric analyses. Extracts of 44 commercial Italian honeys from 20 different botanical sources were analyzed.