Predicting oral relative bioavailability of arsenic in soil from in vitro bioaccessibility.

Several investigations have been conducted to develop in vitro bioaccessibility (IVBA) assays that reliably predict in vivo oral relative bioavailability (RBA) of arsenic (As). This study describes a meta-regression model relating soil As RBA and IVBA that is based upon data combined from previous investigations that examined the relationship between As IVBA and RBA when IVBA was determined using an extraction of soil in 0.4 M glycine at pH 1.5. Data used to develop the model included paired IVBA and RBA estimates for 83 soils from various types of sites such as mining, smelting, and pesticide or herbicide application. The following linear regression model accounted for 87% of the observed variance in RBA (R(2) = .87): RBA(%) = 0.79 × IVBA(%) + 3. This regression model is more robust than previously reported models because it includes a larger number of soil samples, and also accounts for variability in RBA and IVBA measurements made on samples collected from sites contaminated with different As sources and conducted in different labs that have utilized different experimental models for estimating RBA.

Exposure-response modeling of non-cancer effects in humans exposed to Libby Amphibole Asbestos; update.

The United States Environmental Protection Agency (EPA) developed a quantitative exposure-response model for the non-cancer effects of Libby Amphibole Asbestos (LAA) (EPA, 2014). The model is based on the prevalence of localized pleural thickening (LPT) in workers exposed to LAA at a workplace in Marysville, Ohio (Lockey et al., 1984; Rohs et al., 2008). Recently, Lockey et al. (2015a) published a follow-up study of surviving Marysville workers. The data from this study increases the number of cases of LPT and extends the observation period for a number of workers, thereby providing a strengthened data set to define and constrain the optimal exposure-response model for non-cancer effects from inhalation exposure to LAA. The new data were combined with the previous data to update the exposure-response modeling for LPT. The results indicate that a bivariate model using cumulative exposure and time since first exposure is appropriate, and the benchmark concentration is similar to the findings previously reported by EPA (2014). In addition, the data were also used to develop initial exposure-response models for diffuse pleural thickening (DPT) and small interstitial opacities (SIO).

Measurement of arsenic relative bioavailability in swine.

This study describes a method for measuring the relative oral bioavailability (RBA) of arsenic (As) in soil and other soil-like media using young swine as the animal model. Groups of animals are exposed to site soil or sodium arsenate orally for 12 d. Forty-eight-hour urine samples were collected from each animal on d 6-7, 8-9, and 10-11 and were analyzed for total As. The urinary excretion fraction (UEF) for each group was estimated by plotting the mass of As excreted in urine by each animal as a function of the dose administered, and then fitting a linear model to the data using simultaneous weighted linear regression. The RBA of a test material is calculated as the ratio of the UEF value for the test material divided by the UEF of the reference material. Uncertainty around the RBA estimate is calculated using Fieller's theorem. Application of this method to a series of test soils indicates that RBA values for As can range from 18 to 52%. This wide variability supports the conclusion that there may be important differences in RBA between sites, and that use of a site-specific RBA value is likely to increase the accuracy of risk estimates for exposure to As in soil.

An in vitro method for estimation of arsenic relative bioavailability in soil.

This report summarizes the results of a study to develop an in vitro bioaccessibility (IVBA) extraction technique for estimating the relative bioavailability (RBA) of arsenic (As) in soil. The study was implemented in several steps. In step 1, key variables in the extraction protocol were identified. In step 2, 21 different extraction conditions were tested on 12 different soils with reliable RBA values measured in swine or monkeys to identify which yielded useful in vivo-in vitro correlations (IVIVC). In step 3, three extraction conditions were evaluated using 39 different test soils to make a final selection of the best IVIVC. In step 4, the within- and between-lab reproducibility of the extraction method was examined. The optimum IVIVC model for swine utilized a pH 1.5 IVBA extraction fluid, with an R (2) value of .723. For monkeys, the optimum IVIVC model was obtained using a pH 7 IVBA extraction fluid that contained phosphate, with an R (2) value of .755. Within-lab precision of IVBA results was typically less than 3%, with an average of 0.8% for all 4 labs. Between-lab variation in mean IVBA values was generally less than 7%, with an overall average of 3%. The principal advantages of this IVBA method compared to other in vitro methods described in the literature are that (1) the fluids and extraction conditions are simple, (2) the results have been calibrated against a larger data set than any other method, and (3) the method has been demonstrated to be reproducible both within and between labs.

Assessing population-level effects of zinc exposure to brown trout (Salmo trutta) in the Arkansas River at Leadville, Colorado.

We assessed population-level risk to upper Arkansas River brown trout (Salmo trutta L.) due to juvenile exposure to Zn. During spring, individuals in the sensitive young-of-the-year life stage are exposed to elevated Zn concentrations from acid mine drainage. We built and used a simple life-history population model for the risk assessment, with survival and fecundity parameter values drawn from published data on brown trout populations located in the United States and Europe. From experimental data, we derived a toxicity model to predict mortality in brown trout fry after chronic exposure to Zn. We tested sensitivity of risk estimates to uncertainties in the life-history parameters. We reached 5 conclusions. First, population projections are highly uncertain. A wide range of estimates for brown trout population growth is consistent with the scientific literature. The low end of this range corresponds to an unsustainable population, a physically unrealistic condition due to combining minimum parameter values from several studies. The upper end of the range corresponds to an annual population growth rate of 281%. Second, excess mortality from Zn exposure is relatively more predictable. Using our exposure-response model for excess mortality to brown trout fry due to Zn exposure in the upper Arkansas River at the mouth of California Gulch in the years 2000 to 2005, we derived a mean estimate of 6.1% excess mortality (90% confidence interval = 1.6%-14.1%). Third, population projections are sensitive to all the parameters that contribute to the onset of reproduction. The weight of evidence suggests that young-of-the-year survival is most important; it is inconclusive about the ranking of other parameters. Fourth, population-level risk from Zn exposure is sensitive to young-of-the-year survival. If young-of-the-year survival exceeds 20% to 25%, then the marginal effect of excess juvenile mortality on population growth is low. The potential effect increases if young-of-the-year survival is less than 20%. Fifth, the effect of Zn on population growth is predictable despite high uncertainty in population projections. The estimate was insensitive to model uncertainties. This work could be useful to ecological risk assessors and managers interested in using population-level endpoints in other risk assessments.

Evaluation of small arms range soils for metal contamination and lead bioavailability.

Although small arms ranges are known to be contaminated with lead, the full extent of metal contamination has not been described, nor has the oral bioavailability of lead in these soils. In this work, soil samples from ranges with diverse geochemical backgrounds were sieved to <250 microm and analyzed for total metal content. Soils had consistently high levels of lead and copper, ranging from 4549 to 24 484 microg/g and 223 to 2936 microg/g, respectively, while arsenic, antimony, nickel, and zinc concentrations were 100-fold lower. For lead bioavailability measurements, two widely accepted methods were used: an in vivo juvenile swine relative bioavailability method measuring lead absorption from ingested soils relative to equivalent lead acetate concentrations and an in vitro bioaccessibility procedure which measured acid-extractable lead as a percent of total lead in the soil. For eight samples, the mean relative bioavailability and bioaccessibility of lead for the eight soils was about 100% (108 +/- 18% and 95 +/- 6%, respectively) showing good agreement between both methods. Risk assessment and/or remediation of small arms ranges should therefore assume high bioavailability of lead.

Estimation of relative bioavailability of lead in soil and soil-like materials using young Swine.

In this article we summarize the results of a series of studies that measured the relative bioavailability (RBA) of lead in a variety of soil and soil-like test materials. Reference material (Pb acetate) or Pb-contaminated soils were administered orally to juvenile swine twice a day for 15 days. Blood samples were collected from each animal at multiple times during the course of the study, and samples of liver, kidney, and bone were collected at sacrifice. All samples were analyzed for Pb. We estimated the RBA of a test material by fitting mathematical models to the dose-response curves for each measurement end point and finding the ratio of doses that gave equal responses. The final RBA for a test material is the simple average of the four end point-specific RBA values. Results from 19 different test materials reveal a wide range of RBA values across different exposure materials, ranging from 6 to 105%. This variability in RBA between different samples highlights the importance of reliable RBA data to help improve risk assessments for Pb in soil. Although the RBA value for a sample depends on the relative amounts of the different chemical and physical forms of Pb present, data are not yet adequate to allow reliable quantitative predictions of RBA from chemical speciation data alone.