rbioacc: An R-package to analyze toxicokinetic data

Tissue-Specific Toxicokinetics of Aqueous Radium-226 in an Estuarine Mussel, Geukensia demissa

Radiological contamination of coastal habitats poses potential risk for native fauna, but the bioavailability of aqueous radium (Ra) and other dissolved metals to marine bivalves remains unclear. This study was the first to examine the tissue-specific disposition of aqueous ²²⁶Ra in a coastal mussel, specifically the Atlantic ribbed mussel Geukensia demissa. Most organ groups reached steady-state concentrations within 7 days during experimental exposure, with an average uptake rate constant of 0.0013 mL g^-1 d^-1. When moved to Ra-free synthetic seawater, mussels rapidly eliminated aqueous ²²⁶Ra (average elimination rate constant 1.56 d^-1). The biological half-life for aqueous ²²⁶Ra ranged from 8.9 h for the gills and labial palps to 15.4 h for the muscle. Although previous field studies have demonstrated notable ²²⁶Ra accumulation in the soft tissues of marine mussels and that, for freshwater mussels, tissue-incorporated ²²⁶Ra derives primarily from the aqueous phase, our tissue-specific bioconcentration factors (BCFs) were on the order of (8.3 ± 1.5) × 10^-4 indicating low accumulation potential of aqueous ²²⁶Ra in estuarine mussels. This suggests marine and estuarine mussels obtain ²²⁶Ra from an alternate route, such as particulate-sorbed Ra ingested during filter-feeding or from a contaminated food source.

Improvements in Estimating Bioaccumulation Metrics in the Light of Toxicokinetic Models and Bayesian Inference

The surveillance of chemical substances in the scope of Environmental Risk Assessment (ERA) is classically performed through bio-assays from which data are collected and then analysed and/or modelled. Some analysis are based on the fitting of toxicokinetic (TK) models to assess the bioaccumulation capacity of chemical substances via the estimation of bioaccumulation metrics as required by regulatory documents. Given that bio-assays are particularly expensive and time consuming, it is of crucial importance to deeply benefit from all information contained in the data. By revisiting the calculation of bioaccumulation metrics under a Bayesian framework, this paper suggests changes in the way of characterising the bioaccumulation capacity of chemical substances. For this purpose, a meta-analysis of a data-rich TK database was performed, considering uncertainties around bioaccumulation metrics. Our results were statistically robust enough to suggest an additional criterion to the single median estimate of bioaccumulation metrics to assign a chemical substance to a given bioaccumulation capacity. Our proposal is to use the 75th percentile of the uncertainty interval of the bioaccumulation metrics, which revealed an appropriate complement for the classification of chemical substances (e.g. PBT (persistent, bioaccumulative and toxic) and vPvB (very persistent and very bioaccumulative) under the EU chemicals legislation). The 75% quantile proved its efficiency, similarly classifying 90% of the chemical substances as the conventional method.