Arsenic contamination in drinking water and foods is a prevalent concern across the world. Routine testing of inorganic arsenic ensures food safety but requires a cost effective, rapid high throughput, and simple detection method. The objective of this work is to develop a green method using X-Ray fluorescence spectroscopy (XRF) to analyze inorganic arsenic (iAs) in food and their interaction with emerging food contaminants: microplastics and titanium dioxide nanoparticles. XRF measures the secondary X-ray that is characteristic of each element emitted by the sample. In a prior study, we developed an approach that combines the Gutzeit method and elemental analysis using XRF for arsenic detection in food. This approach is based on a commercial mercury bromide strip to capture arsine gas. Concerning the high toxicity of mercury bromide, we explored the feasibility of using a greener chemical, silver nitrate, to replace mercury bromide. This would benefit the safety of the operating personnel and reduce chemical hazard impact on the environment. In addition, organic acids and zinc nanoparticles were explored for iAs detection. Optimization of various reagents was done to maximize the efficacy of iAs capture and detection. The result demonstrated the greener method has a lower quantification (3.40 µg/L) compared to the original method based on mercury bromide (16.2 µg/L) due to less elemental interferences in the XRF spectrum. The standard curves of water and apple juice were compared, no significant difference was found, suggesting matrix interference is minimal. The spiked apple juice with 0 to 133 µg/L iAs had a good recovery ranging from 85-99% with an average relative standard deviation below 20%, indicating decent reproducibility. Other than iAs detection, we also explored the XRF to study the iAs and their interaction between microplastics and titanium dioxide nanoparticles, which are considered emerging contaminants of public concerns that may serve as vectors for pollutants and potentially enhances toxicity effects. We developed a screening method to quantify the adsorption under different conditions. The result showed iAs adsorption is highly dependent of particle size and surface morphology. In conclusion, this study demonstrates the feasibility and great potential of XRF quantification of inorganic arsenic in food matrices in a cost-effective and reliable manner and the capability of rapidly quantifying the interaction with emerging contaminants such as microplastics and titanium dioxide nanoparticles.

No description available.

No description available.

This study investigated the adsorption properties of roxarsone, an organoarsenic poultry feed additive, to goethite and kaolinite in order to determine what role mineral surfaces play in controlling the mobility of roxarsone in watersheds where poultry litter is applied. Adsorption edge experiments for goethite and kaolinite showed a dependence on pH for both As(V) and roxarsone. This pattern can be explained by the pH-dependent changes in the mineral surface charge and protonation of the aqueous arsenic species. Isotherms for As(V) and roxarsone on goethite and kaolinite show surface saturation for As(V), but not for roxarsone. The overall adsorption patterns show that As(V) and roxarsone adsorption is similar, suggesting that the arsenate functional group is the dominant control on roxarsone adsorption. However, there are some subtle differences between adsorption of As(V) and roxarsone, which can be explained by the relative sizes of the molecules, the presence of functional groups, differences in solubility, and differences in the type of adsorption (monolayer versus multilayer). Comparison of roxarsone adsorption to goethite and kaolinite reveals that at the low concentrations of roxarsone that are expected to leach from poultry litter into soil water, goethite adsorbs roxarsone more strongly then kaolinite. However, due to the abundance of kaolinite, both are important controls on roxarsone mobility. / Master of Science

Background: In Bangladesh, more than 57 million individuals are exposed to arsenic-contaminated drinking water at concentrations that exceed the World Health Organization guideline for safe drinking water, which is 10 μg/L. Arsenic is a human carcinogen, which has also been associated with numerous non cancer outcomes, including cardiovascular disease. For many arsenic-related health outcomes, susceptibility differs by sex, with some outcomes preferentially afflicting males and others females. Although reducing exposure to arsenic-contaminated drinking water is the primary strategy for preventing arsenic toxicity, cancer risks remain elevated decades after arsenic exposure has been reduced. Therefore, public health approaches which complement arsenic remediation efforts are needed. One potential set of strategies includes nutritional interventions. Deficiencies in one-carbon metabolism (OCM nutrients can cause hyperhomocysteinemia (HHcys), which has been associated with adverse health outcomes, including cancers and cardiovascular disease. In Bangladesh, the prevalence of HHcys is quite high and differs by sex (63% among men, 26% among women). Nutrients involved in the OCM pathway may also protect against arsenic toxicity. Two potential mechanisms include: 1) by enhancing arsenic metabolism and 2) by preventing/reversing arsenic-induced epigenetic dysregulation. Arsenic metabolism facilitates urinary arsenic elimination and depends on two sequential S-adenosylmethionine (SAM)-dependent methylation steps, which yield the mono- and dimethyl arsenical species (MMA and DMA, respectively and S-adenosylhomocysteine (SAH), a potent inhibitor of most methyltransferases. SAM is synthesized via OCM, a pathway with many nutritional influences, including folate and cobalamin. There is substantial evidence from experimental studies that the OCM pathway is important for facilitating arsenic metabolism and elimination. However, the relationships between SAM, SAH, and arsenic methylation may be particularly complex in populations exposed continuously to arsenic, because 1) the arsenic metabolites compete for methylation, since each methylation step is catalyzed by the arsenic (+3) methyltransferase and requires a methyl group from SAM, and 2) folate and cobalamin nutritional status may vary between individuals. Although the mechanisms mediating arsenic toxicity remain largely unclear and are likely multifactorial, there is increasing evidence that arsenic induces epigenetic dysregulation, including alterations in both DNA methylation and posttranslational histone modifications (PTHMs), and these effects may differ by sex. Arsenic has also been shown to alter gene expression in a sex dependent manner. However, the sex-specific effects of arsenic on PTHMs and gene expression have not been confirmed in a large epidemiological study. Since many of the enzymes involved in epigenetic regulation, including DNA methyltransferases and lysine histone methyltransferases, depend on SAM, epigenetic modifications are also influenced by OCM. Previous studies have demonstrated that nutritional methyl donors involved in the OCM pathway buffer against/modify toxicant-induced alterations in DNA methylation. This may also be true for arsenic-induced alterations in PTHMs. However, the relationships between OCM indices and PTHMs have not been characterized in arsenic-exposed populations. Objectives: We had five main objectives: 1) to examine the relationships between SAM, SAH, and arsenic methylation capacity, and potential effect modification by folate and cobalamin nutritional status; 2) to characterize a specific cleavage product of histone H3, which we identified in human peripheral blood mononuclear cells (PBMCs) in our early analyses of PTHMs; 3) to evaluate the effects of arsenic exposure and arsenic removal on three candidate PTHMs (di- and tri-methylation at lysine 36 of histone H3 (H3K36me2 and H3K36me3, respectively) and di-methylation at lysine 79 of histone H3 (H3K79me2)), which were selected because they are dysregulated in cancers and are altered by arsenic and/or nutritional methyl donors in vitro; 4) to examine associations between arsenic exposure and gene-specific DNA methylation and mRNA expression, particularly for genes involved in pathways implicated in arsenic toxicity; and 5) to characterize the relationships between OCM indices and our three candidate PTHMs, and the effect of folic acid (FA) supplementation on these same PTHMs. For objectives 3-5, we also examined potential differences by sex. Methods: To address these objectives, we used data from three epidemiological studies of arsenic-exposed Bangladeshi adults: 1) the Folate and Oxidative Stress (FOX) study, a cross-sectional study of healthy individuals; 2) the Folic Acid and Creatine Trial (FACT), a randomized placebo-controlled trial (duration 24 weeks) in which healthy participants received an arsenic-removal water filter at baseline and were also randomized to one of five nutrition intervention arms: placebo, 400 μg FA/day (FA400), 800 μg FA/day (FA800), 3 g creatine/day (Creatine), and Creatine + FA400; and 3) the Bangladesh Vitamin E and Selenium Trial (BEST), a randomized placebo controlled trial (duration 6 years) in which individuals with arsenicosis were randomized to one of four nutrition intervention arms: placebo, vitamin E (alphatocopheral, 100 mg/day), selenium (L-selenomethionine, 200 μg/day), or a combination of vitamin E and selenium. In Chapter 3, we examined associations between blood SAM and SAH and the proportion (%) of each arsenic metabolite, measured in blood and urine, among FOX participants. We further examined if these associations differed within strata of folate and/or cobalamin nutritional status. In Chapter 4, we characterized a specific cleavage product of histone H3, which we identified in human PBMCs from a subset of FACT participants (n = 32). We also determined the prevalence of H3 cleavage in these samples and the impact of H3 cleavage on the measurement of downstream PTHMs. In Chapter 5, we presented sex-specific associations between pre-intervention measures of blood arsenic and creatinine-adjusted urinary arsenic (uAsCr) and PTHMs, measured in PBMCs collected from FACT participants (n = 317). We also evaluated whether PTHMs were stable for the 12 week duration after FACT participants received arsenic-removal water filters (n = 60 from placebo group). In Chapter 6, we presented associations between pre-intervention uAsCr and gene-specific DNA methylation (whole blood, n = 400) and mRNA expression (PBMCs, n = 1799) for 47 candidate genes involved in arsenic metabolism, OCM, epigenetic regulation, DNA repair, or tumor suppression/oncogenesis, using baseline-collected samples from BEST participants. We also evaluated these associations separately by sex. In Chapter 6, we examined sex-specific associations between baseline circulating concentrations of OCM indices, including folate, cobalamin, choline, betaine, and homocysteine, and PTHMs measured in PBMCs collected from FACT participants (n = 324). We also evaluated whether FA400 (n = 106), compared with placebo (n = 60), for a duration of 12 weeks increased global levels of PTHMs. Results: We observed that folate and cobalamin nutritional status significantly modified associations between SAM and the % arsenic metabolites, as hypothesized (Chapter 3). Among folate and cobalamin deficient individuals, SAM was positively associated with the %MMA, and negatively associated with the %DMA, in blood. In Chapter 4, we determined that H3 cleavage was evident in one third of the FACT PBMC samples examined. We further demonstrated that H3 cleavage impacts the measurement of certain PTHMs. In Chapter 5, we reported that biomarkers of arsenic exposure were associated with H3K36me2 in a sex-dependent manner. In particular, uAsCr was positively associated with H3K36me2 among men, but not women. Furthermore, the use of arsenic-removal water filters was associated with significant reductions in H3K36me2 over a 12 week period, but this did not differ by sex. We also observed that uAsCr was associated with the methylation and expression of several genes involved in OCM, epigenetic regulation, DNA repair, and tumor suppression, and many of these associations differed by sex (Chapter 6). The associations between several OCM indices and PTHMs were also sex-dependent (Chapter 7). Specifically, choline was positively associated with H3K36me2 among men only, while cobalamin was positively associated with H3K79me2 among women only. However, FA400 for 12 weeks did not alter global levels of the PTHMs examined. Conclusions: Given that cancer risks remain elevated decades after arsenic exposure has ceased, public health interventions which complement arsenic remediation efforts are needed. Nutritional interventions may be one promising approach. Previous studies have observed that a higher %MMA, and a lower DMA, in urine is associated with an increased risk of developing adverse health outcomes. Our finding that SAM was positively associated with %MMA, and negatively associated with %DMA, among individuals deficient for folate and cobalamin contributes additional evidence that nutritional status may explain some of the inter-individual differences in arsenic methylation capacity and, consequently, in susceptibility to arsenic toxicity. Our observation that arsenic exposure was positively associated with global levels of H3K36me2 among men, but not women, and that arsenic was associated with gene specific DNA methylation and mRNA expression in a sex-dependent manner, adds to a growing literature that arsenic induces epigenetic dysregulation differentially by sex. Furthermore, these findings suggest that this may have functional consequences, such as alterations in mRNA expression, including for genes involved in pathways implicated in arsenic toxicity. While it is tempting to speculate that this may explain some of the sex differences in susceptibility to arsenic toxicity, the clinical implications of our findings will require additional study. We also provided the first evidence from an arsenic exposed population that choline and cobalamin are associated with PTHMs(H3K36me2 and H3K79me2, respectively) in a sex-dependent manner, and that 12 weeks’ supplementation with FA, at a dose based on the recommended dietary allowance for folate, does not significantly alter global levels of H3K36me2, H3K36me3, or H3K79me2 in human PBMCs. Previous studies have shown that nutrients in the OCM pathway protect against toxicant induced alterations in DNA methylation. Our findings suggest that some OCM nutrients, particularly choline and cobalamin, may also influence PTHMs in human PBMCs. These findings lay the groundwork for future studies which further examine whether these nutrients can protect against or modify arsenic induced alterations in PTHMs.

Bibliography: leaves 106-114.

Arsenic contamination in drinking water is a severe problem worldwide. The best way to prevent hazardous diseases from chronic arsenic exposure is to remove the exposure. Efforts to remediate arsenic in drinking water have taken two tracks. One is to provide surface or shallow well water sources as an alternative to the arsenic contaminated deep wells. Another approach is to remove arsenic from the contaminated water. Different removal technologies like oxidation, chemical coagulation, precipitation, adsorption and others are available. There are problems and benefits associated with each of these approaches that can be related to cultural, socio-economic and engineering influences. The method proposed in this research is adsorption of arsenic to iron coated limestone. Different iron coated limestone samples were prepared. Standard solutions of 100ppb arsenic were prepared and batch and kinetic experiments were conducted. The final solution concentrations were analyzed by Graphite Furnace Atomic Adsorption Spectroscopy (GFAAs) and the results showed that iron coated limestone removed arsenic below 10ppb with 5 grams of material. Variations in iron coverage impacted efficiency of arsenic removal.

Thesis (Ph. D.)--Ohio State University, 2005. / Title from first page of PDF file. Includes bibliographical references (p. 152-160).

Master of Science / Department of Geology / Saugata Datta / The incidence of high arsenic (As) and other oxyanions (e.g. Mn) has been examined in a ~410km[superscript]2 areas within the Bengal Delta between North and South Matlab, Bangladesh. The aim of this study was to examine the role of sediment geochemistry, coupled with microbial community studies and their relations with different colors and grain sizes of sediments, in determining evolved groundwater hydrochemistry within the aquifers in Matlab. Groundwaters are Ca–Mg–HCO[subscript]3- types in shallow aquifers, Mg-HCO[subscript]3- in the intermediate depths and Na-K-Cl rich in the deeper aquifers. Dissolved As concentration is high (~781μg/l) associated with shallow grey and dark grey sediments, whereas light grey sediments at intermediate depths contain lower As (<10 μg/l). Dissolved Fe[superscript]T on other hand in both sediment types (light grey and grey) shows good correlation with dissolved SO[subscript]4[superscript]2-. In plots of [delta]δ[superscript]18O vs [delta]δD, intermediate and deeper depth aquifer waters plot on the arrays for LMWL and GMWL, which indicates the principal recharge mechanism is likely to be from local precipitation within the shallow aquifers. Only the high As groundwaters deflect from the LMWL, indicating that recharge might be a mixture of precipitation and surficial discharges / infiltrations for these waters. Bulk extraction of sediments showed that grey and dark grey sediments from shallow depths have higher As concentrations (~31 mg/kg) and light grey sediments have comparatively less (~11mg/kg). Sequential extractions for sediment fractionations showed that most of the As was bound to amorphous and poorly crystalline hydrous oxides of Fe and Al phases. Synchrotron-aided bulk-XANES studies conducted on sediments revealed As and S speciation in the core samples at different depths indicating the occurrences of hotspots of As distributed randomly in light grey and grey sediments. As[superscript]3+ is the dominant species in Matlab sediments. More than 101 bacterial families were identified among the eight sediment samples from the South Matlab core and out of them fewer than six families comprised more than ~80% of total bacterial families. Our results indicate significant relationships between bacterial community structure, grain size fractionation, dissolved As concentration and sediment C, Mn, and Fe concentrations for these samples. Groundwater abstracted from these light grey sediments, in contrast to reduced greyish to dark greyish sediments, contain significantly lower amounts of dissolved As and can be a source of safe water for the future. Our work demonstrates that intermediate depth light grey sediments have geochemical and microbial features conducive with safe drinking water for the future.

Arsenic is a naturally occurring toxic metal and its presence in food composites could be a potential risk to the health of both humans and animals. Arseniccontaminated groundwater is often used for food and animal consumption, irrigation of soils, which could potentially lead to arsenic entering the human food chain. Its side effects include multiple organ damage, cancers, heart disease, diabetes mellitus, hypertension, lung disease and peripheral vascular disease. Research investigations, epidemiologic surveys and total diet studies (market baskets) provide datasets, information and knowledge on arsenic content in foods. The determination of the concentration of arsenic in rice varieties is an active area of research. With the increasing capability to measure the concentration of arsenic in foods, there are volumes of varied and continuously generated datasets on arsenic in food groups. Visual analytics, which integrates techniques from information visualization and computational data analysis via interactive visual interfaces, presents an approach to enable data on arsenic concentrations to be visually represented. The goal of this doctoral research in Environmental Science is to address the need to provide visual analytical decision support tools on arsenic content in various foods with special emphasis on rice. The hypothesis of this doctoral thesis research is that software enabled visual representation and user interaction facilitated by visual interfaces will help discover hidden relationships between arsenic content and food categories. The specific objectives investigated were: (1) Provide insightful visual analytic views of compiled data on arsenic in food categories; (2) Categorize table ready foods by arsenic content; (3) Compare arsenic content in rice product categories and (4) Identify informative sentences on arsenic concentrations in rice. The overall research method is secondary data analyses using visual analytics techniques implemented through Tableau Software. Several datasets were utilized to conduct visual analytical representations of data on arsenic concentrations in foods. These consisted of (i) arsenic concentrations in 459 crop samples; (ii) arsenic concentrations in 328 table ready foods from multi-year total diet studies; (iii) estimates of daily inorganic arsenic intake for 49 food groups from multicountry total diet studies; (iv) arsenic content in rice product categories for 193 samples of rice and rice products; (v) 758 sentences extracted from PubMed abstracts on arsenic in rice. Several key insights were made in this doctoral research. The concentration of inorganic arsenic in instant rice was lower than those of other rice types. The concentration of Dimethylarsinic Acid (DMA) in wild rice, an aquatic grass, was notably lower than rice varieties (e.g. 0.0099 ppm versus 0.182 for a long grain white rice). The categorization of 328 table ready foods into 12 categories enhances the communication on arsenic concentrations. Outlier concentration of arsenic in rice were observed in views constructed for integrating data from four total diet studies. The 193 rice samples were grouped into two groups using a cut-off level of 3 mcg of inorganic arsenic per serving. The visual analytics views constructed allow users to specify cut-off levels desired. A total of 86 sentences from 53 PubMed abstracts were identified as informative for arsenic concentrations. The sentences enabled literature curation for arsenic concentration and additional supporting information such as location of the research. An informative sentence provided global “normal” range of 0.08 to 0.20 mg/kg for arsenic in rice. A visual analytics resource developed was a dashboard that facilitates the interaction with text and a connection to the knowledge base of the PubMed literature database. The research reported provides a foundation for additional investigations on visual analytics of data on arsenic concentrations in foods. Considering the massive and complex data associated with contaminants in foods, the development of visual analytics tools are needed to facilitate diverse human cognitive tasks. Visual analytics tools can provide integrated automated analysis; interaction with data; and data visualization critically needed to enhance decision making. Stakeholders that would benefit include consumers; food and health safety personnel; farmers; and food producers. Arsenic content of baby foods warrants attention because of the early life exposures that could have life time adverse health consequences. The action of microorganisms in the soil is associated with availability of arsenic species for uptake by plants. Genomic data on microbial communities presents wealth of data to identify mitigation strategies for arsenic uptake by plants. Arsenic metabolism pathways encoded in microbial genomes warrants further research. Visual analytics tasks could facilitate the discovery of biological processes for mitigating arsenic uptake from soil. The increasing availability of central resources on data from total diet studies and research investigations presents a need for personnel with diverse levels of skills in data management and analysis. Training workshops and courses on the foundations and applications of visual analytics can contribute to global workforce development in food safety and environmental health. Research investigations could determine learning gains accomplished through hardware and software for visual analytics. Finally, there is need to develop and evaluate informatics tools that have visual analytics capabilities in the domain of contaminants in foods. / Environmental Sciences / P. Phil. (Environmental Science)