ABSTRACT
To explore the source and pollution characteristics of soil arsenic, mineralogy and chemical analysis methods were used to analyze the ore, waste rock, sediment, and river and soil samples around the mining area. Under a polarized light microscope, As-bearing mineral-arsenopyrite was found in the soil, ore, and waste rock around the Banbishan gold mine. Moreover, arsenopyrite in the waste rock has already experienced weathering and oxidation, and the oxidized arsenopyrite easily migrates and is released in the soil, which is potentially harmful. Because of the effect of mining transportation activities and indigenous smelting, arsenic was mainly distributed in the topsoil, at a depth of 0-20 cm, in the farmland on both sides of the road and in the places where villagers were gathered. The soil arsenic content in Xiaowulan Village and Gaozhangzi Village ranged from 7.2 to 196.2 mg·kg-1 and exceeded the rate of arsenic by 45.9% and 82.1%. According to the assessment by the RAC method, the farmland soil in Xiaowulan Village and Gaozhangzi Village were mainly at low to medium risk, although some soil points in Xiaowulan Village were at high risk. In general, the effects of the mining activities of the surrounding environment were not optimistic. As-bearing minerals in the oxidation of long-term weathering can cause much arsenic to be activated, which in turn, affects the local crops and long-term residents living around the mining area. It is suggested to carry out risk assessments for arsenic in the soil-crop-atmospheric-human system, and further study the conversion rules and mechanisms of arsenopyrite during weathering, to provide scientific guidance for the environmental protection of cultivated land.
ABSTRACT
Natural iron-containing minerals present in the geosphere in the form of crystalline minerals can be used as adsorption material for removal of arsenic from wastewater and remediation of arsenic-contaminated soils. In this paper, the adsorption and desorption of arsenic onto different iron-containing materials including hematite, limonite, siderite, ilmenite, magnetite, Fe2O3, Fe3O4, and Fe-Mn binary oxide (FMBO) were studied in laboratory experiments. The mechanism of arsenic adsorption was analyzed by scanning electron microscopy (SEM), X-ray diffraction (XRD), and fourier transform infrared spectroscopy (FTIR). The results showed that arsenic adsorption is fitted by pseudo-second-order kinetics and the Langmuir isotherm model for almost all adsorbents, suggesting monolayer adsorption of arsenic onto the minerals. The sorption efficiency and capacity of arsenic by FMBO are much higher than those of other materials. Furthermore, limonite has high sorption efficiencies for both As(â ¢) and As(â ¤) among the natural iron-containing minerals, and their adsorption capacities are 3.96 mg·g-1 and 2.99 mg·g-1, respectively. The XRD results showed that natural limonite contains a large number of weak crystalline mineral components such as goethite, which can provide relatively abundant arsenic adsorption sites. Thus, limonite appears to be the most suitable natural mineral for arsenic adsorption.
ABSTRACT
The risk factors for predicting bone metastases in patients with breast cancer are still controversial. Here, a total of 2133 patients with breast cancer, including 327 with bone metastases (15.33%) and 1806 without bone metastases (84.67%) were retrospective reviewed from January 2005 to December 2015. The spine was found to be the most common site for bone metastases, followed by ribs (57.5%), pelvis (54.1%) and sternum (44.3%). The results indicated that axillary lymph node metastases and the concentrations of CA125, CA153, ALP and hemoglobin were the independent risk factors for bone metastases in patients with breast cancer. The receiver operating characteristics (ROC) curves showed that combined axillary lymph node metastases, high CA153 and ALP, with low hemoglobin were the most accurate biomarkers for predicting bone metastases in breast cancer [area under the curve = 0.900], and the sensitivity and specificity for the prediction were 78.5% and 87.8%, respectively. Therefore, breast cancer patients with more axillary lymph node metastases, high serum concentrations of CA125, CA153, ALP and low level of hemoglobin were closely related to bone metastases. Combined axillary lymph node metastases, CA153, ALP with hemoglobin have the highest predictive accuracy for bone metastases in breast cancer.
