Removal of arsenic (As) from water supplies is needed to reduce As exposure through drinking water and food consumption in many regions of the world. Magnetite nanoparticles (MNPs) are promising and novel adsorbents for As removal because of their great adsorption capacity for As and easy separation. This study aimed to investigate the adsorption mechanism of arsenate, As(V), and arsenite, As(III), on MNPs by macroscopic adsorption experiments in combination with thermodynamic calculation and microspectroscopic characterization using synchrotron-radiation-based X-ray absorption spectroscopy (XAS) and X-ray photoelectron spectroscopy (XPS). Adsorption reactions are favorable endothermic processes as evidenced by increased adsorption with increasing temperatures, and high positive enthalpy change. EXAFS spectra suggested predominant formation of bidentate binuclear corner-sharing complexes ((2)C) for As(V), and tridentate hexanuclear corner-sharing ((3)C) complexes for As(III) on MNP surfaces. The macroscopic and microscopic data conclusively identified the formation of inner-sphere complexes between As and MNP surfaces. More intriguingly, XANES and XPS results revealed complex redox transformation of the adsorbed As on MNPs exposed to air: Concomitant with the oxidation of MNPs, the oxidation of As(III) and MNPs was expected, but the observed As(V) reduction was surprising because of the role played by the reactive Fe(II).

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Stroke remains a major public health problem worldwide; it causes severe disability and is associated with high mortality rates. However, early diagnosis of stroke is difficult, and no reliable biomarkers are currently established. In this study, mass-spectrometry-based metabolomics was utilized to characterize the metabolic features of the serum of patients with acute ischemic stroke (AIS) to identify novel sensitive biomarkers for diagnosis and progression. First, global metabolic profiling was performed on a training set of 80 human serum samples (40 cases and 40 controls). The metabolic profiling identified significant alterations in a series of 26 metabolites with related metabolic pathways involving amino acid, fatty acid, phospholipid, and choline metabolism. Subsequently, multiple algorithms were run on a test set consisting of 49 serum samples (26 cases and 23 controls) to develop different classifiers for verifying and evaluating potential biomarkers. Finally, a panel of five differential metabolites, including serine, isoleucine, betaine, PC(5:0/5:0), and LysoPE(18:2), exhibited potential to differentiate AIS samples from healthy control samples, with area under the receiver operating characteristic curve values of 0.988 and 0.971 in the training and test sets, respectively. These findings provided insights for the development of new diagnostic tests and therapeutic approaches for AIS.

Measurements of metals in soils by diffusive gradients in thin films (DGT) have previously been shown to be linearly related to metals measured in shoots of plants grown in pots. We examine the relationships between metals measured by DGT and other techniques with metals in the roots and unpolished grains of rice cultivated under field conditions at 18 sites in Jiangsu province, China. Rhizosphere soils of rice were collected and the concentrations of Cd, Cu, Pb, and Zn were determined on soil solution, acetic acid, and calcium chloride (CaCl2) extractions and by DGT. Simple linear regression analyses between concentrations of metals in plants and those measured using DGT and chemical extractions showed a very good fit for DGT measurements of the concentrations of all four metals in both rice roots and unpolished grains. Good fits were also found using soil solution and acetic acid extractions, but the correlation coefficients were lower than those obtained by DGT. CaCl2 extractions provided the poorest fits for all four metals. Multivariate analyses were used to assess the impact of pH, dissolved organic carbon (DOC), soil organic carbon (SOC), cation exchange capacity (CEC), and texture. Two principal components were extracted. The first was well correlated with SOC, DOC, and clay proportion and is therefore representative of "organic matter". The second primarily correlated positively with pH and negatively with CEC and is representative of "inorganic ions". When these principle components were included in multiple linear regression, correlation coefficients for plots involving metals in soil solution and in extractions using acetic acid and CaCl2 were improved, but there was little change in the correlation coefficients for comparable plots using metals measured by DGT. These results show for the first time that the DGT measurement quantitatively incorporates the main factors affecting bioavailability.