Total contents, fractionation and bioaccessibility of nine heavy metals in household dust from 14 cities in China.

The potential health risk caused by long-term exposure to heavy metals in household dust is not only depended on their total content, but also bioaccessibility. In this study, twenty-one dust samples were collected from residential buildings, schools, and laboratories in 14 provincial-capital/industrial cities of China, aiming to evaluate the total contents, fractionation, bioaccessibility and health risks of nine heavy metals (As, Cd, Cr, Ni, Pb, Mn, Zn, Fe, and Cu). Results showed that the highest levels of Cd, Cr, Ni and Zn were found in laboratory dust, As, Pb and Mn in school dust, and Fe and Cu in residential dust, indicating different source profiles of the heavy metals. The mean bioaccessibility of the heavy metals across all samples as evaluated using SBRC (Solubility Bioavailability Research Consortium), IVG (In Vitro Gastrointestinal), and PBET (Physiologically Based Extraction Test) assays was 58.4%, 32.4% and 17.2% in gastric phase (GP), and 24.9%, 21.9% and 9.39% in intestinal phase (IP), respectively. Cadmium had the highest content in the fractions of E1+C2 (43.7%), as determined by sequential extraction, and Pb, Mn, and Zn had a higher content in E1+C2+F3 (64.2%, 67.2%, 78.8%), resulting in a higher bioaccessibility of these heavy metals than others. Moreover, the bioaccessibility of most heavy metals was inversely related to dust pH (R = -0.18 in GP; -0.18 in IP; P < 0.01) and particle size, while a positive correlation was observed with total organic carbon (R = 0.40 in GP; 0.38 in IP; P < 0.01). The exposure risk calculated by the highest bioaccessibility was generally lower than that calculated by the total content. However, Pb in one school dust sample had an unacceptable carcinogenic risk (adult risk = 1.19 × 10-4; child risk = 1.08 × 10-4). This study suggests that bioaccessibility of heavy metals in household dust is likely related to geochemical fractions and physical/chemical properties. Further research is needed to explore the sources of bioaccessible heavy metals in household dust.

Role of iron manganese plaque in the safe production of rice (Oryza sativa L.) grains: Field evidence at plot and regional scales in cadmium-contaminated paddy soils.

The relationship between iron manganese plaque (IP) and cadmium (Cd) accumulation by rice in the microenvironment of rice rhizosphere at varying field scales needs to be further explored. In this study, we selected different rice varieties and implemented tailored amendments to ensure the safe production of rice grains in heavily Cd-contaminated farmland situated around an E-waste dismantling site. Through regional surveys, we elucidated the role of IP in facilitating safe rice production. The selection of low-Cd accumulating rice varieties and application of appropriate amendments with sufficient dosages allowed for the effective reduction of Cd transport from soil to rice, resulting in a safe concentration of Cd in rice grains. Analysis using a random forest algorithm indicated that iron (Fe) played a more pivotal role than manganese in soil-rice systems in mitigating Cd accumulation in brown rice. The presence of Fe in IP (IP-Fe) at a low loading mass was unfavorable to the Cd-safe production of rice, while at an IP-Fe loading mass of 52 g/kg, the Cd content in brown rice decreased to a safe level. Furthermore, precipitation, coprecipitation, and complexation of surface functional groups contributed to Cd fixation on IP, as indicated by scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy, electron probe microanalysis, and Fourier-transform infrared spectroscopy with attenuated total reflection. Our results highlighted the key role of IP in the production of Cd-safe rice at different field scales.

Prediction of cadmium contents in rice grains from Quaternary sediment-distributed farmland using field investigations and machine learning.

The Quaternary sediment-distributed regions of South China are suitable for rice cultivation, which is crucial for ensuring food security. Spatial correlations between soil cadmium (Cd) and rice Cd contents are generally poor, making the evaluation of rice quality and associated health risks challenging. In this study, we developed machine learning algorithms for predicting rice Cd contents using 654 data pairs of soil-rice samples collected in Guangxi province, China. After a comprehensive comparison, our results showed that the random forest (RF) had the better performance than artificial neural network (ANN) based on all the data (RMSEtesting 0.066 vs. 0.099 and R2testing 0.860 vs. 0.688). The feature importance analysis showed that soil CaO, Cd, elevation, and rainfall were the four most important features affecting the rice Cd contents in the study area. Using the established RF-predicated model, the rice Cd contents were predicted at the provincial level with an additional dataset of 1176 paddy soil samples. The prediction result revealed about 23 % of farmland cultivated rice with Cd content over 0.2 mg kg-1 in the study area. Therefore, it is recommended to implement strict measures by local agricultural departments to reduce rice Cd contents and ensure food safety in these areas. Our study provides valuable insights into the prediction of rice Cd contents, thus contributing to ensuring food safety and preventing Cd exposure-associated health risks.

Nickel bioaccessibility in soils with high geochemical background and anthropogenic contamination.

Abnormally high concentrations of metals including nickel (Ni) in soils result from high geochemical background (HB) or anthropogenic contamination (AC). Metal bioaccessibility in AC-soils has been extensively explored, but studies in HB-soils are limited. This study examined the Ni bioaccessibility in basalt and black shale derived HB-soils, with AC-soils and soils without contamination (CT) being used for comparison. Although HB- and AC-soils had similar Ni levels (123 ± 43.0 vs 155 ± 84.7 mg kg-1), their Ni bioaccessibility based on the gastric phase of the Solubility Bioaccessibility Research Consortium (SBRC) in vitro assay was different. Nickel bioaccessibility in HB-soils was 6.42 ± 3.78%, 2-times lower than the CT-soils (12.0 ± 9.71%) and 6-times lower than that in AC-soils (42.6 ± 16.3%). Based on the sequential extraction, a much higher residual Ni fractionation in HB-soils than that in CT- and AC-soils was observed (81.9 ± 9.52% vs 68.6 ± 9.46% and 38.7 ± 16.0%). Further, correlation analysis indicate that the available Ni (exchangeable + carbonate-bound + Fe/Mn hydroxide-bound) was highly correlated with Ni bioaccessibility, which was also related to the organic carbon content in soils. The difference in co-localization between Ni and other elements (Fe, Mn and Ca) from high-resolution NanoSIMS analysis provided additional explanation for Ni bioaccessibility. In short, based on the large difference in Ni bioaccessibility in geochemical background and anthropogenic contaminated soils, it is important to base contamination sources for proper risk assessment of Ni-contaminated soils.

Nrf2/Keap1 pathway in countering arsenic-induced oxidative stress in mice after chronic exposure at environmentally-relevant concentrations.

Contamination of drinking water by carcinogen arsenic (As) is of worldwide concern as its exposure poses potential threat to human health. As such, it is important to understand the mechanisms associated with As-induced toxicity to humans. The Nrf2/Keap1 signal pathway is one of the most important defense mechanisms in cells to counter oxidative stress; however, limited information is available regarding its role in countering As-induced stress in model animal mouse. In this study, we assessed the responses of Nrf2/keap1 pathway in mice after chronic exposure to As at environmentally-relevant concentrations of 10-200 µg L-1 for 30 days via drinking water. Our results indicate that chronic As exposure had limited effect on mouse growth. However, As induced oxidative stress to mice as indicated by increased content of malondialdehyde (MDA; 52-90%), an index of lipid peroxidation. Further, arsenic exposure reduced the activity of superoxide dismutase (SOD; 14-18%), an indication of reduced anti-oxidative activity. Besides, arsenic exposure increased MnSOD mRNA transcription by 25-66%, and decreased the mRNA transcriptions of Cu/ZnSOD by 72-83% and metallothionein by 16-75%, a cysteine-rich protein involved in metal detoxification. To counter arsenic toxicity, the expression of transcription factor for Nrf2 and Keap1 was increased by 2.8-8.9 and 0.2-8.1 fold in mice. To effectively reduce As-induced oxidative stress, the Nrf2/Keap1 transcription factor upregulated several downstream anti-oxidative genes, including heme oxygenase-1 (0.9-2.5 fold), glutamate-cysteine ligase catalytic subunit (0.6-1.7 fold), and NADH quinone dehydrogenase 1 (2.1-4.8 fold). This study shows the importance of Nrf2/Keap1 signaling pathway and associated anti-oxidative enzymes in countering As-toxicity in mice, possibly having implication for human health.

Selenate increased plant growth and arsenic uptake in As-hyperaccumulator Pteris vittata via glutathione-enhanced arsenic reduction and translocation.

The beneficial effects of selenium on As uptake and plant growth in As-hyperaccumulator Pteris vittata are known, but the associated mechanisms remain unclear. Here, we investigated the effects of selenate on arsenic accumulation by P. vittata under two arsenate levels. P. vittata plants were exposed to 13 (As13) or 133 µM (As133) arsenate and 5 µM selenate in 0.2-strength Hoagland solution. After 14 d of growth, plant biomass, Se and As content, As speciation, and malondialdehyde (MDA), glutathione reductase (GR), glutathione peroxidase (GPX), and glutathione (GSH and GSSG) levels were determined. The results show that selenate promoted P. vittata growth and increased As concentrations in the roots and fronds by 256% from 97 to 346 mg kg-1 and 142% from 213 to 514 mg kg-1 under As13 treatment, and by 166% from 500 to 1332 mg kg-1 and 534% from 777 to 4928 mg kg-1 under As133 treatment. In addition, selenate increased the glutathione content in P. vittata roots and fronds by 75-86% under As13 treatment and 44-45% under As133 treatment. Selenate also increased the GPX activity by 161-173%, and GR activity by 72-79% in P. vittata under As13 and As133 treatments. The HPLC-ICP-MS analysis indicated that selenate increased both AsIII and AsV levels in P. vittata, with AsIII/AsV ratio being lower in the roots and higher in the fronds, i.e., more AsIII was being translocated to the fronds. Taken together, our results suggest that, via GPX-GR mediated enhancement of GSH-GSSG cycle, selenate effectively increases plant growth and As uptake in P. vittata by improving AsV reduction in the roots and AsIII translocation from the roots to the fronds.

Evaluation of various approaches to predict cadmium bioavailability to rice grown in soils with high geochemical background in the karst region, Southwestern China.

Evaluating the bioavailability of Cd to rice (Oryza sativa L.) was essential in the karst region, Southwestern China, where the soils have previously been shown to be anomalously enriched in Cd through geogenic processes. In this research, we examined the bioavailability of Cd to rice samples collected from 278 sites in Guangxi province, where rice is the most widely cultivated cereal crop that is responsible for the largest human dietary exposure to Cd. Both soil chemical extraction and soil-plant transfer modelling approaches were used to predict the bioavailability to rice. Some of the soil types were highly enriched in Cd, but their bioavailability was low, since the soil carbonates raised soil pH and remarkably reduced Cd bioavailability. In contrast, acidic soils (Ca was largely leached) with relatively low total Cd, the grown rice plants accumulated higher Cd in their grains. Results from CaCl2 extraction experiments provided good predictions for Cd in rice grain grown in soils of different types. Stepwise multiple regressions revealed soil pH and soil Ca content were the dominant factors that control the transfer of Cd from soil to rice. An extended Freundlich-type model and a polynomial surface model provided good prediction for Cd in rice grains. The diffusive gradients in thin films (DGT) technique gave the best estimation of soil Cd bioavailability, whereas water-extracted soil solution Cd provided relatively poor fits. Regional soil threshold that derived using the models, can avoid exceedance of Cd in rice and thereby enable local agricultural practitioners or authorities to develop appropriate management for croplands with high Cd background.