The long-term health outcome of prenatal exposure to arsenic has been associated with increased mortality in human populations. In this study, the extent to which maternal arsenic exposure impacts gene expression in the newborn was addressed. We monitored gene expression profiles in a population of newborns whose mothers experienced varying levels of arsenic exposure during pregnancy. Through the application of machine learning–based two-class prediction algorithms, we identified expression signatures from babies born to arsenic-unexposed and -exposed mothers that were highly predictive of prenatal arsenic exposure in a subsequent test population. Furthermore, 11 transcripts were identified that captured the maximal predictive capacity to classify prenatal arsenic exposure. Network analysis of the arsenic-modulated transcripts identified the activation of extensive molecular networks that are indicative of stress, inflammation, metal exposure, and apoptosis in the newborn. Exposure to arsenic is an important health hazard both in the United States and around the world, and is associated with increased risk for several types of cancer and other chronic diseases. These studies clearly demonstrate the robust impact of a mother's arsenic consumption on fetal gene expression as evidenced by transcript levels in newborn cord blood.

Nineteen elements, Mg, Al, Ca, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Se, Sr, Sb, Ba, As, Cd, Hg, and Pb, were determined in three types of popular herbal tea products, Gynostemma pentaphyllum, Camellia sinensis, and Morus alba. These herbal tea products, both imported and locally made products, are widely consumed in Thailand and worldwide. Microwave-assisted acid digestion was used for all of the samples, and the element contents were determined by ICP-MS. The concentrations of all elements varied among these herbal teas. Ca and Mg were the most abundant elements in all herbal samples (1384-34070 and 783-7739 mg/kg, respectively). Most elements in these herbal tea powders were also released into the infusions at different percentages depending on types of herbs. G. pentaphyllum infusion contained essential elements (Mg, Ca, V, and Fe) at higher levels than C. sinensis and M.alba infusions. Al and Ni were present at high levels in C. sinensis infusion, and Cd level was high in M. alba infusion. The daily intake of all elements from these herbal tea infusions (three cups/day) is still within the average daily intake. Therefore, it may not produce any health risks for human consumption, if other sources of toxic metal contaminated food are not taken at the same time.

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A continuous-flow extraction system was developed to speed up, facilitate, and improve the accuracy of the chemical fractionation of metals in solid materials. A three-step sequential extraction scheme was used to evaluate the novel system by analyzing calcium (Ca), iron (Fe), manganese (Mn), copper (Cu), and zinc (Zn) in a soil certified reference material (National Institute of Standards and Technology [NIST] SRM 2710). In the proposed system, extraction occurred in a closed chamber through which extractants were passed sequentially. The extracts were collected in a number of subfractions for subsequent name atomic absorption analysis. Apart from the advantages of simplicity, speed, and less risk of the contamination that flow analysis systems usually possess, the continuous-flow system can improve the accuracy of chemical fractionation of metals by sequential extraction. The system ensures that extraction is performed at designated pH values without any need of adjustment. Variation of sample weight to chamber volume ratios from 1:12 to 1:40 had no effect on the extractability of the metals studied. In the extraction of the acid soluble fraction, concentrations of acetic acid in the range 0.11 to 0.5 mol L(-1) had no significant effect on the amounts of metals extracted, except Fe. Increasing the concentration of hydroxylamine in the reducible fraction step from 0.04 to 0.5 mol L(-1) affected the extraction efficiency for Fe, Mn, and Zn. The extraction profile, rather than a single value of extracted concentration, of each element offers additional information about the kinetics of leaching processes and chemical associations between elements in the solid materials.

Human exposure to arsenic (As) via rice consumption is of increasing concern. In the present study, the extraction and HPLC-ICP-MS analysis for As speciation in rice were investigated. A simple extraction with water and digestion with α-amylase followed by the analysis using ion-paring mode HPLC separation was developed. The method showed good extraction efficiencies (generally >80%) and column efficiencies (>90%) for rice samples. The optimization of mobile phase showed well separated peaks of As species. The limits of quantification (LOQ) of As(III), As(V), MMA, and DMA that were calculated based on sample mass were 1.6, 2.0, 2.0, and 1.6 μg kg(-1), respectively. A total of 185 rice samples (various types of rice) collected from different four regions in Thailand and some other Asian countries were analyzed. The total As and inorganic As in rice samples were in the ranges of 22.51-375.39 and 13.89-232.62 μg kg(-1), respectively. The estimated weekly intake of inorganic As from rice by Thai people accounted for 13.91-29.22% of the provisional tolerable weekly intake (PTWI).