Arsenic exposure from food exceeds that from drinking water in endemic area of Bihar, India

Extensive evidence of elevated arsenic (As) in the food-chain, mainly rice, wheat and vegetables exists. Nevertheless, the importance of exposure from food towards total As exposure and associated health risks in areas with natural occurring As in drinking water is still often neglected, and accordingly mitigations are largely focused on drinking water only. In this study, the contribution of food over drinking water to overall As exposure was estimated for As exposed populations in Bihar, India. Increased lifetime cancer risk was predicted using probabilistic methods with input parameters based on detailed dietary assessment and estimation of As in drinking water, cooked rice, wheat flour and potato collected from 91 households covering 19 villages. Median total exposure was 0.83 μg/kgBW/day (5th and 95th percentiles were 0.21 and 11.1 μg/kgBW/day) and contribution of food (median = 49%) to overall exposure was almost equal to that from drinking water (median = 51%). More importantly and contrary to previous studies, food was found to contribute more than drinking water to As exposure, even when drinking water As was above the WHO provisional guide value of 10 μg/L. Median and 95th percentile excess lifetime cancer risks from food intake were 1.89 × 10^-4 and 7.32 × 10^-4 respectively when drinking water As was below 10 μg/L and 4.00 × 10^-4 and 1.83 × 10^-3 respectively when drinking water As was above 10 μg/L. Our results emphasise the importance of food related exposure in As-endemic areas, and, perhaps surprisingly, particularly in areas with high As concentrations in drinking water - this being partly ascribed to increases in food As due to cooking in high As water. These findings are timely to stress the importance of removing As from the food chain and not just drinking water in endemic areas.

Contaminated landslide runout deposits in rivers - Method for estimating long-term ecological risks

The potential catastrophic event of a landslide bringing contaminants to surface waters has been highlighted in public media, but there are still few scientific studies analyzing the risk of landslides with contaminated soil. The aim of this study is to present a method to estimate the risk of potential long-term ecological effects on water bodies due to contaminated soil released into a river through a landslide. The study constitutes further development of previous work focusing on the instantaneous (short-term) release of contaminants and associated effects. Risk is here defined as the probability of surface water failing to comply with environmental quality standards (EQS). The transport model formulation is kept simple enough to allow for a probabilistic analysis as a first assessment of the impact on the river water quality from a landslide runout deposit containing contaminated soil. The model is applied at a contaminated site located adjacent to the Göta Älv River that discharges into the Gothenburg estuary, in southwest Sweden. The results from the case study show that a contaminated runout deposit will likely cause contamination levels above EQSs in the near area for a long time and that it will take several years for the deposit to erode, with the greatest erosion at the beginning when water velocities are their highest above the deposit. A contaminated landslide runout deposit will thus act as a source of contamination to the downstream water system until all the contaminated deposit has been eroded away and the contaminants have been transported from the deposit to the river, and further to the river mouth - diluted but not necessarily negligible. Therefore, it is important to prevent landslides of contaminated soil or waste, and if such events were to occur, to remove the contaminated runout deposit as soon as possible.

Probabilistic validation of protein NMR chemical shift assignments

Data validation plays an important role in ensuring the reliability and reproducibility of studies. NMR investigations of the functional properties, dynamics, chemical kinetics, and structures of proteins depend critically on the correctness of chemical shift assignments. We present a novel probabilistic method named ARECA for validating chemical shift assignments that relies on the nuclear Overhauser effect data . ARECA has been evaluated through its application to 26 case studies and has been shown to be complementary to, and usually more reliable than, approaches based on chemical shift databases. ARECA is available online at http://areca.nmrfam.wisc.edu/.

Probabilistic assessment of exposure to nail cosmetics in French consumers

The aim of this study was to assess probabilistic exposure to nail cosmetics in French consumers. The exposure assessment was performed with base coat, polish, top coat and remover. This work was done for adult and child consumers. Dermal, inhalation and oral routes were taken into account for varnishes. Exposure evaluation was performed for the inhalation route with polish remover. The main route of exposure to varnishes was the ungual route. Inhalation was the secondary route of exposure, followed by dermal and oral routes. Polish contributed most to exposure, regardless of the route of exposure. For this nail product, P50 and P95 values by ungual route were respectively equal to 1.74 mg(kg bw week)(-1) and 8.55 mg(kg bw week)(-1) for women aged 18-34 years. Exposure to polish by inhalation route was equal to 0.70 mg(kg bw week)(-1) (P50) and 5.27 mg(kg bw week)(-1) (P95). P50 and P95 values by inhalation route were respectively equal to 0.08 mg(kg bw week)(-1) and 1.14 mg(kg bw week)(-1) for consumers aged 18-34 years exposed to polish remover. This work provided current exposure data for nail cosmetics, and a basis for future toxicological studies of the uptake of substances contained in nail cosmetics in order to assess systemic exposure.