Independent Data Validation of an in Vitro Method for the Prediction of the Relative Bioavailability of Arsenic in Contaminated Soils

In vitro bioaccessibility (IVBA) assays estimate arsenic (As) relative bioavailability (RBA) in contaminated soils to improve accuracy in human exposure assessments. Previous studies correlating soil As IVBA with RBA have been limited by the use of few soil types and sources of As, and the predictive value of As IVBA has not been validated using an independent set of As-contaminated soils. In this study, a robust linear model was developed to predict As RBA in mice using IVBA, and the predictive capability of the model was independently validated using a unique set of As-contaminated soils. Forty As-contaminated soils varying in soil type and contaminant source were included in this study, with 31 soils used for initial model development and nine soils used for independent model validation. The initial model reliably predicted As RBA values in the independent data set, with a mean As RBA prediction error of 5.4%. Following validation, 40 soils were used for final model development, resulting in a linear model with the equation RBA = 0.65 × IVBA + 7.8 and an <i>R</i>² of 0.81. The in vivo–in vitro correlation and independent data validation presented provide critical verification necessary for regulatory acceptance in human health risk assessment

Relating soil geochemical properties to arsenic bioaccessibility through hierarchical modeling

<p>Interest in improved understanding of relationships among soil properties and arsenic (As) bioaccessibility has motivated the use of regression models for As bioaccessibility prediction. However, limits in the numbers and types of soils included in previous studies restrict the usefulness of these models beyond the range of soil conditions evaluated, as evidenced by reduced predictive performance when applied to new data. In response, hierarchical models that consider variability in relationships among soil properties and As bioaccessibility across geographic locations and contaminant sources were developed to predict As bioaccessibility in 139 soils on both a mass fraction (mg/kg) and % basis. The hierarchical approach improved the estimation of As bioaccessibility in studied soils. In addition, the number of soil elements identified as statistically significant explanatory variables increased when compared to previous investigations. Specifically, total soil Fe, P, Ca, Co, and V were significant explanatory variables in both models, while total As, Cd, Cu, Ni, and Zn were also significant in the mass fraction model and Mg was significant in the % model. This developed hierarchical approach provides a novel tool to (1) explore relationships between soil properties and As bioaccessibility across a broad range of soil types and As contaminant sources encountered in the environment and (2) identify areas of future mechanistic research to better understand the complexity of interactions between soil properties and As bioaccessibility.</p

The Impact of Silver Nanoparticles on the Composting of Municipal Solid Waste

The study evaluates the impact of polyvinylpyrrolidone (PVP) coated silver nanoparticles (PVP-AgNPs) on the composting of municipal solid waste. The results suggest that there was no statistically significant difference in the leachate, gas, and solid quality parameters and overall composting performance between the treatments containing the AgNPs, Ag⁺, and negative control. Nonetheless, taxonomical analyses of 25 Illumina 16S rDNA barcoded libraries containing 2 393 504 sequences indicated that the bacterial communities in composted samples were highly diverse and primarily dominated by Clostridia (48.5%), Bacilli (27.9%), and beta-Proteobacteria (13.4%). Bacterial diversity studies showed that the overall bacterial community structure in the composters changed in response to the Ag-based treatments. However, the data suggest that functional performance was not significantly affected due to potential bacterial functional redundancy within the compost samples. The data also indicate that while the surface transformation of AgNPs to AgCl and Ag₂S can reduce the toxicity, complexation with organic matter may also play a major role. The results of this study further suggest that at relatively low concentrations, the organically rich waste management systems’ functionality may not be influenced by the presence of AgNPs