Health risk assessment of heavy metals in soils and screening of accumulating plants around the Wanshan mercury mine in Northeast Guizhou Province, China.

The Wanshan mercury mine, which is an abandoned mine located in northeastern Guizhou Province in Southwest China, has introduced serious Hg pollution to the local ecosystem resulting from previous mining and smelting activities. However, it is not clear to date whether soil pollution has actually improved after treatment by related departments. Therefore, the present study investigates the vegetation community and heavy metal contents of the soil and plants in the Wanshan mercury mining area. The results showed that most of Hg, Cd, As, Cu, and Zn contents in soil samples were higher than those of Soil Environment Quality Risk Control Standard for Soil Contamination of Agricultural Land in China (GB15618-2018). The observed plant species mainly consisted of Compositae, followed by Leguminosae. Unfortunately, this investigation found that heavy metal concentrations in these plants were not extremely high and far below the standard of hyperaccumulator. Despite all this, the maximum values of bioaccumulation factor for Pb, Cd, Hg, As, Cu and Zn were Serissa japonica (Thunb.) Thunb., Rhus chinensis Mill., Potentilla sibbaldii Haller f., Erigeron canadensis L., Clerodendrum bungei var. bungei. and Rhus chinensis Mill., respectively. Regardless of the carcinogenic or noncarcinogenic risk index, the potential risk to urban children is higher. Our results suggest that heavy metal pollution was indeed relieved since their contents in soil significantly decreased in comparison with those reported in other previous studies. This finding provides a reference for the long-term treatment of heavy metal pollution in the local environment and other areas employing analogous environmental protection measures.

Speciation and accumulation pattern of heavy metals from soil to rice at different growth stages in farmland of southwestern China.

Paddy rice, one of the most important food crops in Southeast Asia, is considered a main source of human exposure to heavy metal contamination because it efficiently accumulates heavy metals. In the present study, of Japonica rice grains, straw, roots, leaves, and husks and rhizosphere paddy soils (0-20 cm and 20-40 cm depth) were collected from Zunyi in northern Guizhou Province, China. The forms of heavy metals, including Cr, Cd, Pb, Cu, and Zn, in the two soil profiles were investigated using Tessier's five-stage sequential extraction procedure. There was no heavy metal pollution in the study area based on the evaluation of the geo-accumulation index and the potential ecological risk index. Accumulation varied from one area to another, and the highest metal accumulation was found in the order of root > stems > leaves. The bioaccumulation factor (BCF) results revealed that during the grain-filling stage, the rice had high BCF values (> 1) for Cd and Zn. The target hazard quotient (THQ) of ingestion peaked for Cd and reached its minimum level for Zn in not only in adults but also in children. The THQ was ranked as Cd > Cu > Pb > Cr > Zn for both adults and children. The hazard index values for adults and children for the five heavy metals were 1.81 × 10-3 and 1.55 × 10-3, respectively, indicating that these metals have little effect on the human body. The lifetime carcinogenic risk values for local adults and children were 4.28 × 10-5 and 5.92 × 10-5, respectively, both of which were within the tolerable to acceptable risk range. In summary, obvious hazards for local adults and children were not observed in this study. Considering the total amount and chemical forms of Cd, it is necessary to notify the appropriate departments about the possible rice contamination caused by Cd in the soil.

Artificial Intelligence Based Optimization for the Se(IV) Removal from Aqueous Solution by Reduced Graphene Oxide-Supported Nanoscale Zero-Valent Iron Composites.

Highly promising artificial intelligence tools, including neural network (ANN), genetic algorithm (GA) and particle swarm optimization (PSO), were applied in the present study to develop an approach for the evaluation of Se(IV) removal from aqueous solutions by reduced graphene oxide-supported nanoscale zero-valent iron (nZVI/rGO) composites. Both GA and PSO were used to optimize the parameters of ANN. The effect of operational parameters (i.e., initial pH, temperature, contact time and initial Se(IV) concentration) on the removal efficiency was examined using response surface methodology (RSM), which was also utilized to obtain a dataset for the ANN training. The ANN-GA model results (with a prediction error of 2.88%) showed a better agreement with the experimental data than the ANN-PSO model results (with a prediction error of 4.63%) and the RSM model results (with a prediction error of 5.56%), thus the ANN-GA model was an ideal choice for modeling and optimizing the Se(IV) removal by the nZVI/rGO composites due to its low prediction error. The analysis of the experimental data illustrates that the removal process of Se(IV) obeyed the Langmuir isotherm and the pseudo-second-order kinetic model. Furthermore, the Se 3d and 3p peaks found in XPS spectra for the nZVI/rGO composites after removing treatment illustrates that the removal of Se(IV) was mainly through the adsorption and reduction mechanisms.

Real-time in vitro intravascular reconstruction and navigation for endovascular aortic stent grafting.

BACKGROUND: Trans-catheter endovascular stent grafting minimizes trauma and increases the benefitting patient population. However, the alignment between stent graft branches and vasculature branches remains time-consuming and challenging, and such techniques require a significant amount of contrast agent for imaging. METHODS: A new framework for intravascular reconstruction based on sensor fusion between intravascular ultrasound (IVUS) imaging and electromagnetic (EM) tracking was proposed. A new image processing method was presented to realize fully automatic processing of IVUS imaging and 3D reconstruction in real time, as well as branch detection for alignment and deployment. Complementary navigation using CT data allows for efficient catheter advancement and assistant clinical judgement. RESULTS: The reconstruction of an in vitro descending aorta phantom with branches was realized at 35 Hz, with cross-section radius average error of 0.64 mm. CONCLUSION: The proposed method demonstrates significant potential for clinical applications, enables navigation for precise alignment and placement for stent grafting to reduce surgical time, and decreases hemorrhagic collisions and the use of contrast agent. Copyright © 2016 John Wiley & Sons, Ltd.

Fast catheter segmentation from echocardiographic sequences based on segmentation from corresponding X-ray fluoroscopy for cardiac catheterization interventions.

Echocardiography is a potential alternative to X-ray fluoroscopy in cardiac catheterization given its richness in soft tissue information and its lack of ionizing radiation. However, its small field of view and acoustic artifacts make direct automatic segmentation of the catheters very challenging. In this study, a fast catheter segmentation framework for echocardiographic imaging guided by the segmentation of corresponding X-ray fluoroscopic imaging is proposed. The complete framework consists of: 1) catheter initialization in the first X-ray frame; 2) catheter tracking in the rest of the X-ray sequence; 3) fast registration of corresponding X-ray and ultrasound frames; and 4) catheter segmentation in ultrasound images guided by the results of both X-ray tracking and fast registration. The main contributions include: 1) a Kalman filter-based growing strategy with more clinical data evalution; 2) a SURF detector applied in a constrained search space for catheter segmentation in ultrasound images; 3) a two layer hierarchical graph model to integrate and smooth catheter fragments into a complete catheter; and 4) the integration of these components into a system for clinical applications. This framework is evaluated on five sequences of porcine data and four sequences of patient data comprising more than 3000 X-ray frames and more than 1000 ultrasound frames. The results show that our algorithm is able to track the catheter in ultrasound images at 1.3 s per frame, with an error of less than 2 mm. However, although this may satisfy the accuracy for visualization purposes and is also fast, the algorithm still needs to be further accelerated for real-time clinical applications.