Rapid Surface Plasmon Resonance Immunoassay for the Determination of Deoxynivalenol in Wheat, Wheat Products, and Maize-Based Baby Food

A rapid screening assay (9 min/sample) has been developed and validated for the detection of deoxynivalenol in durum wheat, wheat products, and maize-based baby foods using an SPA biosensor. Through a single laboratory validation, the limits of detection (LOD) for wheat, wheat-based breakfast cereal, and maize-based baby food were 57, 9, and 6 mu g/kg, respectively. Intra-assay and interassay precisions were calculated for each matrix at the maximum and half-maximum European Union regulatory limits and expressed as the coefficient of variation (CV). All CVs fell below 10% with the exception of the between-run CV for breakfast cereal. Recoveries at the concentrations tested ranged from 92 to 115% for all matrices. Action limits of 161, 348, and 1378 mu g/kg were calculated for baby food, wheat-based breakfast cereal, and wheat, respectively, and the linear range of the assay was determined as 250-2000 mu g/kg.

Development of a recombinant Fab-fragment based electrochemical immunosensor for deoxynivalenol detection in food samples

A reliable and cost-effective electrochemical method for the detection of deoxynivalenol (DON) in cereals and cereal-based food samples based on the use of a novel anti-DON Fab fragment is presented. The analytical system employed, Enzyme-Linked-Immunomagnetic-Electrochemical (ELIME) assay, is based on the use of immunomagnetic beads (IMBs) coupled with eight magnetized screen-printed electrodes (8-mScPEs) as electrochemical transducers.

A rapid optical immunoassay for the screening of T-2 and HT-2 toxin in cereals and maize-based baby food

A rapid surface plasmon resonance (SPR) screening assay has been developed for the combined detection of T-2 and HT-2 toxins in naturally contaminated cereals using a sensor chip coated with an HT-2 toxin derivative and a monoclonal antibody. The antibody raised against HT-2 displayed high cross-reactivity with T-2 toxin while there was no cross-reaction observed with other commonly occurring trichothecenes. A simple extraction procedure using 40% methanol was applied to baby food, breakfast cereal, and wheat samples prior to biosensor analysis. Limits of detection (LOD) for each matrix were determined as 25 mu g kg(-1) for baby food and breakfast cereal and 26 mu g kg(-1) for wheat. Intra-assay precision (n = 6) was calculated for each matrix. The results were expressed as the relative standard deviation and determined as 2.8% (100 mu g kg(-1)) and 1.8% (200 mu g kg(-1)) in breakfast cereal, 4.6% (50 mu g kg(-1)) and 3.6% (100 mu g kg(-1)) in wheat and 0.97% (25 mu g kg(-1)) and 6.3% (50 mu g kg(-1)) in baby food. Between run precision (n = 3) performed at the same levels yielded relative standard deviations of 6.7% and 3.9% for breakfast cereals, 3.3% and 1.6% for wheat and 6.8% and 0.08% for baby food, respectively. (C) 2010 Elsevier B.V. All rights reserved.

Mass spectrometry-based metabolomics applied to the chemical safety of food

Mass spectrometry (MS)-based metabolomics is emerging as an important field of research in many scientific areas, including chemical safety of food. A particular strength of this approach is its potential to reveal some physiological effects induced by complex mixtures of chemicals present at trace concentrations. The limitations of other analytical approaches currently employed to detect low-dose and mixture effects of chemicals make detection very problematic. Besides this basic technical challenge, numerous analytical choices have to be made at each step of a metabolomics study, and each step can have a direct impact on the final results obtained and their interpretation (i.e. sample preparation, sample introduction, ionization, signal acquisition, data processing, and data analysis). As the application of metabolomics to chemical analysis of food is still in its infancy, no consensus has yet been reached on defining many of these important parameters. In this context, the aim of the present study is to review all these aspects of MS-based approaches to metabolomics, and to give a comprehensive, critical overview of the current state of the art, possible pitfalls, and future challenges and trends linked to this emerging field. (C) 2010 Elsevier Ltd. All rights reserved.

Dietary fat and breast cancer survival: a systematic review and meta-analysis

As the number of breast cancer survivors increases worldwide(1), there is growing interest in the potential effect of dietary and lifestyle behaviours on overall prognosis. This is especially important as a cancer diagnosis is often referred to as a ‘teachable moment’(2) as patients seek information about lifestyle behaviours and so provision of evidence-based guidelines is essential. A positive association between dietary fat and breast cancer risk has been previously reported(3) but its influence upon breast cancer survival is unclear. The aim of this review and meta-analysis is to critically appraise the literature published to date and to conduct meta-analyses to pool the results of studies to clarify the association between dietary fat and breast cancer survival.
Relevant articles published up to March 2011 that examined dietary fat and breast cancer recurrence and survival were identified from searches in MEDLINE and EMBASE. Meta-analyses were conducted in which we evaluated the risk of all-cause or breast cancer death in women in the highest compared with the lowest categories of total fat intake (g/d) and per 20 g increase in intake of dietary fat. Multivariable adjusted relative risks (RR) and 95% CI from individual studies were weighted and combined using a random-effects model to produce a pooled estimate.
Twelve prospective cohort studies that investigated total fat intake (g) and breast cancer survival, and/or provided information on fat intake from which a linear trend could be estimated, were included in the analyses. There was no evidence of a difference in risk of breast cancer death (RR=1.14; 95% CI 0.86, 1.52; P=0.34) or all cause death (RR=1.73; 95% CI 0.82, 3.6; P=0.15) between the highest and lowest categories of total fat intake. Similarly, no significant difference in risk of breast cancer death (RR=1.03; 95% CI 0.97, 1.10; P=0.261) or all-cause death (RR=1.06; 95% CI 0.88, 1.28; P=0.52) was found per linear (20 g) increase in total fat intake.
The results of this systematic review and meta-analysis do not support an association between total dietary fat and breast cancer survival. Further investigation into the effect of specific types of dietary fat and breast cancer survival is of interest.

Arsenic behaviour from groundwater and soil to crops:impacts on agriculture and food safety

High levels of As in groundwater commonly found in Bangladesh and other parts of Asia not only pose a risk via drinking water consumption but also a risk in agricultural sustainability and food safety. This review attempts to provide an overview of current knowledge and gaps related to the assessment and management of these risks, including the behaviour of As in the soil-plant system, uptake, phytotoxicity, As speciation in foods, dietary habits, and human health risks. Special emphasis has been given to the situation in Bangladesh, where groundwater via shallow tube wells is the most important source of irrigation water in the dry season. Within the soil-plant system, there is a distinct difference in behaviour of As under flooded conditions, where arsenite (AsIII) predominates, and under nonflooded conditions, where arsenate (AsV) predominates. The former is regarded as most toxic to humans and plants. Limited data indicate that As-contaminated irrigation water can result in a slow buildup of As in the topsoil. In some cases the buildup is reflected by the As levels in crops, in others not. It is not yet possible to predict As uptake and toxicity in plants based on soil parameters. It is unknown under what conditions and in what time frame As is building up in the soil. Representative phytotoxicity data necessary to evaluate current and future soil concentrations are not yet available. Although there are no indications that crop production is currently inhibited by As, long-term risks are clearly present. Therefore, with concurrent assessments of the risks, management options to further prevent As accumulation in the topsoil should already have been explored. With regard to human health, data on As speciation in foods in combination with food consumption data are needed to assess dietary exposure, and these data should include spatial and seasonal variability. It is important to control confounding factors in assessing the risks. In a country where malnutrition is prevalent, levels of inorganic As in foods should be balanced against the nutritional value of the foods. Regarding agriculture, As is only one of the many factors that may pose a risk to the sustainability of crop production. Other risk factors such as nutrient depletion and loss of organic matter also must be taken into account to set priorities in terms of research, management, and overall strategy.

Dietary switching of collembola in grassland soil food webs

Soil food webs are characterised by complex direct and indirect effects among the organisms. Consumption of microorganisms by soil animals is considered as an important factor that contributes to the stability of communities, though cascading effects within the food web can be difficult to detect. In a greenhouse experiment, an addition of a high number the fungal feeding collembola Folsomia quadrioculata was applied to grassland soil food webs in monocultures of three plant species: Plantago lanceolato (forb), Lotus corniculatus (legume) and Holcus lanatus (grass). The abundance of microorganisms, determined as the abundances of phospholipid fatty acids (PLFAs) and the abundances of resident invertebrates, nematodes and collembolans, did not change due to the addition of E quadrioculata. Trophic positions of collembolans were determined by analyses of natural abundances of N-15 stable isotopes. The use of food resources by microorganisms and collembolans was determined by C-13 analysis of microbial PLFAs and solid samples of collembolans. delta C-13 values of the resident collembola Folsomia fimetaria were lower in the presence of E quadrioculata than in the control food webs indicating a use of more depleted C-13 food resources by E fimetaria. The delta N-15 values of E fimetaria did not change at the addition of E quadrioculata thus no change of trophic levels was detected. The switch of E fimetaria to a different food resource could be due to indirect interactions in the food web as the two collembolan species were positioned on different trophic positions, according to different delta N-15 values. (c) 2008 Elsevier Ltd. All rights reserved.

Metabolomic Profiling of In Vivo Plasma Responses to DioxinAssociated Dietary Contaminant Exposure in Rats: Implications for Identification of Sources of Animal and Human Exposure

Dioxin contamination of the food chain typically occurs when cocktails of combustion residues or polychlorinated biphenyl (PCB) containing oils become incorporated into animal feed. These highly toxic compounds are bioaccumulative with small amounts posing a major health risk. The ability to identify animal exposure to these compounds prior to their entry into the food chain may be an invaluable tool to safeguard public health. Dioxin-like compounds act by a common mode of action and this suggests that markers or patterns of response may facilitate identification of exposed animals. However, secondary co-contaminating compounds present in typical dioxin sources may affect responses to compounds. This study has investigated for the first time the potential of a metabolomics platform to distinguish between animals exposed to different sources of dioxin contamination through their diet. Sprague-Dawley rats were given feed containing dioxin-like toxins from hospital incinerator soot, a common PCB oil standard and pure 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) (normalized at 0.1 µg/kg TEQ) and acquired plasma was subsequently biochemically profiled using ultra high performance liquid chromatography (UPLC) quadropole time-of-flight-mass spectrometry (QTof-MS). An OPLS-DA model was generated from acquired metabolite fingerprints and validated which allowed classification of plasma from individual animals into the four dietary exposure study groups with a level of accuracy of 97-100%. A set of 24 ions of importance to the prediction model, and which had levels significantly altered between feeding groups, were positively identified as deriving from eight identifiable metabolites including lysophosphatidylcholine (16:0) and tyrosine. This study demonstrates the enormous potential of metabolomic-based profiling to provide a powerful and reliable tool for the detection of dioxin exposure in food-producing animals.

Inorganic arsenic in Chinese food and its cancer risk

Even moderate arsenic exposure may lead to health problems, and thus quantifying inorganic arsenic (iAs) exposure from food for different population groups in China is essential. By analyzing the data from the China National Nutrition and Health Survey (CNNHS) and collecting reported values of iAs in major food groups, we developed a framework of calculating average iAs daily intake for different regions of China. Based on this framework, cancer risks from As in food was deterministically and probabilistically quantified. The article presents estimates for health risk due to the ingestion of food products contaminated with arsenic. Both per individual and for total population estimates were obtained. For the total population, daily iAs intake is around 42 mu g day(-1), and rice is the largest contributor of total iAs intake accounting for about 60%. Incremental lifetime cancer risk from food iAs intake is 106 per 100,000 for adult individuals and the median population cancer risk is 177 per 100,000 varying between regions. Population in the Southern region has a higher cancer risk than that in the Northern region and the total population. Sensitive analysis indicated that cancer slope factor, ingestion rates of rice, aquatic products and iAs concentration in rice were the most relevant variables in the model, as indicated by their higher contribution to variance of the incremental lifetime cancer risk. We conclude that rice may be the largest contributor of iAs through food route for the Chinese people. The population from the South has greater cancer risk than that from the North and the whole population. (C) 2011 Elsevier Ltd. All rights reserved.

Arsenic Speciation in Food and Estimation of the Dietary Intake of Inorganic Arsenic in a Rural Village of West Bengal, India

Arsenic (As) species were quantified by HPLC-HG-AFS in water and vegetables from a rural area of West Bengal (India). Inorganic species predominated in vegetables (including rice) and drinking water; in fact, inorganic arsenic (i-As) represented more than 80% of the total arsenic (t-As) content. To evaluate i-As intake in an arsenic affected rural village, a food survey was carried out on 129 people (69 men and 60 women). The data from the survey showed that the basic diet, of this rural population, was mainly rice and vegetables, representing more than 50% of their total daily food intake. During the periods when nonvegetarian foods (fish and meat) were scarce, the importance of rice increased, and rice alone represented more than 70% of the total daily food intake. The food analysis and the food questionnaires administrated led us to establish a daily intake of i-As of about 170 mu g i-As day(-1), which was above the tolerable daily intake of 150 mu g i-As day(-1), generally admitted. Our results clearly demonstrated that food is a very important source of i-As and that this source should never be forgotten in populations depending heavily on vegetables (mainly rice) for their diet.

Effect of cooking method and rice type on arsenic concentration in cooked rice and the estimation of arsenic dietary intake in a rural village in West Bengal, India

Arsenic (As) contamination of rice plants can result in high total As concentrations (t-As) in cooked rice, especially if As-contaminated water is used for cooking. This study examines two variables: (1) the cooking method (water volume and inclusion of a washing step); and (2) the rice type (atab and boiled). Cooking water and raw atab and boiled rice contained 40 g As l-1 and 185 and 315 g As kg-1, respectively. In general, all cooking methods increased t-As from the levels in raw rice; however, raw boiled rice decreased its t-As by 12.7% when cooked by the traditional method, but increased by 15.9% or 23.5% when cooked by the intermediate or contemporary methods, respectively. Based on the best possible scenario (the traditional cooking method leading to the lowest level of contamination, and the atab rice type with the lowest As content), t-As daily intake was estimated to be 328 g, which was twice the tolerable daily intake of 150 g.

A Posteriori Dietary Patterns Are Related to Risk of Type 2 Diabetes: Findings from a Systematic Review and Meta-Analysis

Our review and meta-analysis examined the association between a posteriori–derived dietary patterns (DPs) and risk of type 2 diabetes mellitus. MEDLINE and EMBASE were searched for articles published up to July 2012 and data were extracted by two independent reviewers. Overall, 19 cross-sectional, 12 prospective cohort, and two nested case-control studies were eligible for inclusion. Results from cross-sectional studies reported an inconsistent association between DPs and measures of insulin resistance and/or glucose abnormalities, or prevalence of type 2 diabetes. A meta-analysis was carried out on nine prospective cohort studies that had examined DPs derived by principle component/factor analysis and incidence of type 2 diabetes risk (totaling 309,430 participants and 16,644 incident cases). Multivariate-adjusted odds ratios were combined using a random-effects meta-analysis. Two broad DPs (Healthy/Prudent and Unhealthy/Western) were identified based on food factor loadings published in original studies. Pooled results indicated a 15% lower type 2 diabetes risk for those in the highest category of Healthy/Prudent pattern compared with those in the lowest category (95% CI 0.80 to 0.91; P<0.0001). Compared with the lowest category of Unhealthy/Western DP, those in the highest category had a 41% increased risk of type 2 diabetes (95% CI 1.32 to 1.52; P<0.0001). These results provide evidence that DPs are consistently associated with risk of type 2 diabetes even when other lifestyle factors are controlled for. Thus, greater adherence to a DP characterized by high intakes of fruit, vegetables, and complex carbohydrate and low intakes of refined carbohydrate, processed meat, and fried food may be one strategy that could have a positive influence on the global public health burden of type 2 diabetes.