You are here:
Comparison of mouse and swine bioassays for determination of soil arsenic relative bioavailability
Bradham, K., G. Diamond, A. Juhasz, C. Nelson, AND D. Thomas. Comparison of mouse and swine bioassays for determination of soil arsenic relative bioavailability. APPLIED GEOCHEMISTRY. Elsevier Science Ltd, New York, NY, 88:221-225, (2018).
Arsenic (As) is the number one ranked contaminant on the priority list of hazardous substances in the United States deemed to pose a significant potential threat to human health (ATSDR, 2015). Although exposure may occur via consumption of food and drinking water, incidental ingestion of contaminated soil and dust is the major non-dietary exposure pathway for As (USEPA 2012). However, systemic exposure to As via incidental ingestion is modulated by As relative bioavailability (RBA; the percent ratio of As bioavailability in soil to that of sodium arsenate) which, in turn, is influenced by As speciation, physico-chemical characteristics of soil and dust matrices and physiological parameters associated with exposed individuals (Bradham et al., 2011; 2013; 2015; Juhasz et al., 2007; 2009; 2014). As a consequence, in order to accurately assess exposure for human health risk assessment, evaluation of As RBA via the incidental ingestion pathway is essential.
Evaluation of soil arsenic (As) relative bioavailability (RBA) is essential to accurately assess human exposure to As contaminated soils via the incidental ingestion pathway. A variety of animal bioassays have been developed to estimate As RBA in contaminated soils and dusts, with uncertainty regarding how physiological differences between animal models or differences in assay methodologies may influence As RBA estimates. This study compared As RBA estimates across 20 As pesticide and mine-impacted soils in two commonly utilized animal bioassays, a mouse model based on steady state urinary excretion factor (UEF) and two swine models based on UEF and area under the curve (AUC), to elucidate factors influencing As RBA estimates. Multiple regression analysis supported combining the RBAs from swine UEF and swine AUC assays into a single regression model. The weighted least squares regression model derived from these data was as follows: swine RBA(%) = 1.23∙mouse RBA(%) - 0.80 (R2=0.50). The mean relative percent difference between swine and mouse RBAs was +13%. This study extends and confirms conclusions from previous smaller studies to indicate that mouse and swine As RBA assays yield similar RBA estimates when applied to the same soils, although there appears to be a trend for the swine assay to predict higher RBAs than the mouse UEF assay.