An exposome connectivity paradigm for the mechanistic assessment of the effects of prenatal and early life exposure to metals on neurodevelopment.

The exposome paradigm through an integrated approach to investigating the impact of perinatal exposure to metals on child neurodevelopment in two cohorts carried out in Slovenia (PHIME cohort) and Greece (HERACLES cohort) respectively, is presented herein. Heavy metals are well-known neurotoxicants with well-established links to impaired neurodevelopment. The links between in and early-life exposure to metals, metabolic pathway dysregulation, and neurodevelopmental disorders were drawn through urinary and plasma untargeted metabolomics analysis, followed by the combined application of and biostatistical methods.

Neurodevelopmental exposome: The effect of in utero co-exposure to heavy metals and phthalates on child neurodevelopment.

In this study, the exposome paradigm has been applied on a mother-child cohort adopting an optimised untargeted metabolomics approach for human urine followed by advanced bioinformatics analysis. Exposome-wide association algorithms were used to draw links between in utero co-exposure to metals and phthalates, metabolic pathways deregulation, and clinically observed phenotypes of neurodevelopmental disorders such as problems in linguistic, motor development and cognitive capacity. Children (n = 148) were tested at the first and second year of their life using the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III).

Toxic metal exposure as a possible risk factor for COVID-19 and other respiratory infectious diseases.

Multiple medical, lifestyle, and environmental conditions, including smoking and particulate pollution, have been considered as risk factors for COronaVIrus Disease 2019 (COVID-19) susceptibility and severity. Taking into account the high level of toxic metals in both particulate matter (PM2.5) and tobacco smoke, the objective of this review is to discuss recent data on the role of heavy metal exposure in development of respiratory dysfunction, immunotoxicity, and severity of viral diseases in epidemiological and experimental studies, as to demonstrate the potential crossroads between heavy metal exposure and COVID-19 severity risk.

Multi-omics analysis reveals that co-exposure to phthalates and metals disturbs urea cycle and choline metabolism.

This study aimed to evaluate the response of HepaRG cells after co-exposure to phthalates and heavy metals, using a high-dimensional biology paradigm (HDB). Liver is the main metabolism site for the majority of xenobiotics. For this reason, the HepaRG cell line was used as an in vitro model, and cells were exposed to two characteristic mixtures of phthalates and heavy metals containing phthalates (DEHP, DiNP, BBzP) and metals (lead, methylmercury, total mercury) in a concentration-dependent manner.

COVID‑19 in Northern Italy: An integrative overview of factors possibly influencing the sharp increase of the outbreak (Review).

Italy is currently one of the countries seriously affected by the COVID‑19 pandemic. As per 10 April 2020, 147,577 people were found positive in a total of 906,864 tests performed and 18,849 people lost their lives. Among all cases, 70.

Cumulative risk assessment of pesticide residues in different Iranian pistachio cultivars: Applying the source specific HQ and adversity specific HI approaches in Real Life Risk Simulations (RLRS).

Iran is a major supplier of the world pistachio market. In this study, we collected five pistachio cultivars from four main pistachio-producing zones in August and September 2016, and determined the residues of 18 organophosphorus, carbamate, pyrethroid and nicotinoid pesticide in these samples using Gas Chromatography-Mass Spectrometry, as an efficient method for determination of pesticides' residues. Next, single-chemical and chronic cumulative risk assessment was done based on the new approaches of the food specific Hazard Quotient and adversity specific Hazard Index.

Risk characterization of bisphenol-A in the Slovenian population starting from human biomonitoring data.

The current study aims to characterize exposure and risk associated to bisphenol-A (BPA) exposure in Slovenia, starting from biomonitoring data. Based on the urinary data, daily intake for the individuals was back-calculated using a physiology based biokinetic (PBBK) model properly parameterized for BPA, coupled with an exposure reconstruction algorithm. Re-running the PBBK model in forward mode allowed the estimation of biologically effective dose (free plasma BPA) and the respective daily area under the curve (AUC).