Depletion of four nitrofuran antibiotics and their tissue-bound metabolites in porcine tissues and determination using LC-MS/MS and HPLC-UV

Depletion of the nitrofuran antibiotics furazolidone, furaltadone, nitrofurantoin and nitrofurazone and their tissue-bound metabolites AOZ, AMOZ, AHD and SEM from pig muscle, liver and kidney tissues is described. Groups of pigs were given feed medicated with one of the nitrofuran drugs at a therapeutic concentration (400 mg kg(-1)) for ten days. Animals were slaughtered at intervals and tissue samples collected for analysis for six weeks following withdrawal of medicated feed. These samples were analysed both for parent nitrofurans (using LC-MS/MS and HPLC-UV), and for tissue-bound metabolites (using LC-MS/MS). The parent drugs were detectable only sporadically and only in pigs subjected to no withdrawal period whatsoever. This confirms the instability of the four major nitrofuran antibiotics in edible tissues. In contrast, the metabolites accumulated to high concentrations in tissues (ppm levels) and had depletion half lives of between 5.5 and 15.5 days. The metabolites of all four drugs were still readily detectable in tissues six weeks after cessation of treatment. This emphasizes the benefits of monitoring for the stable metabolites of the nitrofurans.

A review of recent developments in the speciation and location of arsenic and selenium in rice grain

Rice is a staple food yet is a significant dietary source of inorganic arsenic, a class 1, nonthreshold carcinogen. Establishing the location and speciation of arsenic within the edible rice grain is essential for understanding the risk and for developing effective strategies to reduce grain arsenic concentrations. Conversely, selenium is an essential micronutrient and up to 1 billion people worldwide are selenium-deficient. Several studies have suggested that selenium supplementation can reduce the risk of some cancers, generating substantial interest in biofortifying rice. Knowledge of selenium location and speciation is important, because the anti-cancer effects of selenium depend on its speciation. Germanic acid is an arsenite/silicic acid analogue, and location of germanium may help elucidate the mechanisms of arsenite transport into grain. This review summarises recent discoveries in the location and speciation of arsenic, germanium, and selenium in rice grain using state-of-the-art mass spectrometry and synchrotron techniques, and illustrates both the importance of high-sensitivity and high-resolution techniques and the advantages of combining techniques in an integrated quantitative and spatial approach.

Phase Equilibria of Binary and Ternary Systems Containing ILs, Dodecane, and Cyclohexanecarboxylic Acid

This paper reports both the binary and ternary phase behavior of ionic liquids for extracting cyclohexanecarboxylic acid (CCA) from dodecane. This system is a model for the extraction of acids representative of naphthenic acids found in crude oils. In order to develop an effective ternary liquid-liquid extraction system the preliminary selection of ionic liquids was based on CCA miscibility and the dodecane immiscibility with selected ILs. A wide range of ILs based on different cations, anions, cation alkyl-chain length, as well as the effect of temperature on the overall fluid phase behavior is reported. Factors such as variation of cation group, anion effect, alkyl-chain length, and temperature all impact the extraction to various degrees. The largest effects were found to be the lipophilicity of the IL cation and the co-ordination ability of the anion. While CCA capacity increased with lipophilicity of the cation, as did the dodecane. Highly coordinating anions such as trifluoroacetate and triflate demonstrated that highly efficient extraction could be obtained producing favorable tie-lines in the ternary phase diagram. Overall, this study demonstrates that ILs can selectively extract acids from hydrocarbon streams and offers possible treatment solutions for problems associated with the processing of high acid crude oils.

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.

Water-hydrophobic compound interactions with the microbial cell

The structural interactions of biological macromolecules, their biochemical activities and, ultimately, the metabolic function of cellular systems are dependent upon weak inter- and intra-molecular forces such as hydrogen bonds, Van der Waals forces, and the hydrophobic effect. Water molecules, and those of hydrophobic substances such as hydrocarbons, can take part in and/or modify these interactions and thereby determine the operational and structural stability of the microbial cell and its macromolecular systems. We explain how the cytosol, plasma membrane and the extracellular solution form a material and energetic continuum; and discuss the behavior of hydrophobic substances of extracellular origin as they migrate into the plasma membrane and into the cell's interior. The adverse effects of substances with a log P octanol-water =2, that partition into the hydrophobic domains of biological macromolecules, are discussed in relation to microbial cell function; and we speculate whether the cellular stress that they induce is symmetrical or asymmetrical in nature. In the context of the microbial environment, we take a situational-functional approach to consider how hydrophobic stressors interact with the microbial cell, and what types of evasion tactics microbes can employ to minimize their inhibitory activities. Finally, we discuss the ecological implications of hydrocarbon-induced cellular stress for microbial systems.

Complex Interactions between Dioxin-Like and Non-Dioxin-Like Compounds for in Vitro Cellular Responses: Implications for the Identification of Dioxin Exposure Biomarkers

Despite considerable advances in reducing the production of dioxin-like toxicants in recent years, contamination of the food chain still occasionally occurs resulting in huge losses to the agri-food sector and risk to human health through exposure. Dioxin-like toxicity is exhibited by a range of stable and bioaccumulative compounds including polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs), produced by certain types of combustion, and man-made coplanar polychlorinated biphenyls (PCBs), as found in electrical transformer oils. While dioxinergic compounds act by a common mode of action making exposure detection biomarker based techniques a potentially useful tool, the influence of co-contaminating toxicants on such approaches needs to be considered. To assess the impact of possible interactions, the biological responses of H4IIE cells to challenge by 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in combination with PCB-52 and benzo-a-pyrene (BaP) were evaluated by a number of methods in this study. Ethoxyresorufin-O-deethylase (EROD) induction in TCDD exposed cells was suppressed by increasing concentrations of PCB-52, PCB-153, or BaP up to 10 mu M. BaP levels below 1 mu M suppressed TCDD stimulated EROD induction, but at higher concentrations, EROD induction was greater than the maximum observed when cells were treated with TCDD alone. A similar biphasic interaction of BaP with TCDD co-exposure was noted in the AlamarBlue assay and to a lesser extent with PCB-52. Surface enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF) profiling of peptidomic responses of cells exposed to compound combinations was compared. Cells co-exposed to TCDD in the presence of BaP or PCB-52 produced the most differentiated spectra with a substantial number of non-additive interactions observed. These findings suggest that interactions between dioxin and other toxicants create novel, additive, and non-additive effects, which may be more indicative of the types of responses seen in exposed animals than those of single exposures to the individual compounds.

Electrowetting movement of an aqueous droplet between two three-dimensional electrode surfaces

In an effort to develop a novel electronic paper image display technology based on the electrowetting principle, a 3-D electrowetting cell is designed and fabricated, which consists of two 3-D bent electrodes, each having a horizontal surface made of gold and a vertical surface made of indium tin oxide (ITO) glass as a color display window, a layer of dielectric material on the 3-D electrodes, and a highly fluorinated hydrophobic layer on the surface of the dielectric layer. Results of this work show that an electrowetting-induced motion of an aqueous droplet in immiscible oils can be achieved reversibly across the boundary of the horizontal and vertical surfaces of the 3-D electrode surface. It is also shown that the droplet can maintain its wetting state on a vertical sidewall electrode free of a power supplier when the voltage is removed. This phenomenon may form the basis for color contrast modulation applications, where a power-free image display is required, such as electronic paper display technology in the future. (C) 2009 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3100201]

Exploring molecular recognition pathways within a family of gelators with different hydrogen bonding motifs

We report the synthesis of a family of gelators in which alkyl chains are connected to the amino groups of L-lysine methyl ester using a range of different hydrogen bonding linking groups (carbamate, amide, urea, thiourea and diacylhydrazine) using simple synthetic methodology based on isocyanate or acid chloride chemistry. The ability of these compounds to gelate organic solvents such as toluene or cyclohexane can be directly related to the ability of the linking group to form intermolecular hydrogen bonds. In general terms, the ability to structure solvents can be considered as: thiourea <carbamate <amide <urea similar to diacylhydrazine. This process has been confirmed by thermal measurements, scanning electron microscopy (SEM) and infrared and circular dichroism spectroscopies. By deprotecting the methyl ester group, we have demonstrated that a balance between hydrophobic and hydrophilic groups is essential-if the system has too much hydrophilicity (e. g., diacylhydrazine, urea) it will not form gels due to low solubility in the organic media. However, the less effective gelators based on amide and carbamate linkages are enhanced by converting the methyl ester to a carboxylic acid. Furthermore, subsequent mixing of the acid with a second component (diaminododecane) further enhances the ability to form networks, and, in the case of the amide, generates a two-component gel, which can immobilise a wide range of solvents of industrial interest including petrol and diesel (fuel oils), olive oil and sunflower oil (renewable food oils) and ethyl laurate, isopropyl myristate and isopropyl palmitate (oils used in pharmaceutical formulation). The gels are all thermoreversible, and may therefore be useful in controlled release/formulation applications.

Development of a novel continuous statistical modelling technique for detecting the adulteration of extra virgin olive oil with hazelnut oil by using spectroscopic data

The adulteration of extra virgin olive oil with other vegetable oils is a certain problem with economic and health consequences. Current official methods have been proved insufficient to detect such adulterations. One of the most concerning and undetectable adulterations with other vegetable oils is the addition of hazelnut oil. The main objective of this work was to develop a novel dimensionality reduction technique able to model oil mixtures as a part of an integrated pattern recognition solution. This final solution attempts to identify hazelnut oil adulterants in extra virgin olive oil at low percentages based on spectroscopic chemical fingerprints. The proposed Continuous Locality Preserving Projections (CLPP) technique allows the modelling of the continuous nature of the produced in house admixtures as data series instead of discrete points. This methodology has potential to be extended to other mixtures and adulterations of food products. The maintenance of the continuous structure of the data manifold lets the better visualization of this examined classification problem and facilitates a more accurate utilisation of the manifold for detecting the adulterants.

Identification of vegetable oil botanical speciation in refined vegetable oil blends using an innovative combination of chromatographic and spectroscopic techniques

European Regulation 1169/2011 requires producers of foods that contain refined vegetable oils to label the oil types. A novel rapid and staged methodology has been developed for the first time to identify common oil species in oil blends. The qualitative method consists of a combination of a Fourier Transform Infrared (FTIR) spectroscopy to profile the oils and fatty acid chromatographic analysis to confirm the composition of the oils when required. Calibration models and specific classification criteria were developed and all data were fused into a simple decision-making system. The single lab validation of the method demonstrated the very good performance (96% correct classification, 100% specificity, 4% false positive rate). Only a small fraction of the samples needed to be confirmed with the majority of oils identified rapidly using only the spectroscopic procedure. The results demonstrate the huge potential of the methodology for a wide range of oil authenticity work.

Turbo-smt: Accelerating coupled sparse matrix-tensor factorizations by 200x

How can we correlate the neural activity in the human brain as it responds to typed words, with properties of these terms (like ‘edible’, ‘fits in hand’)? In short, we want to find latent variables, that jointly explain both the brain activity, as well as the behavioral responses. This is one of many settings of the Coupled Matrix-Tensor Factorization (CMTF) problem.

Can we accelerate any CMTF solver, so that it runs within a few minutes instead of tens of hours to a day, while maintaining good accuracy? We introduce Turbo-SMT, a meta-method capable of doing exactly that: it boosts the performance of any CMTF algorithm, by up to 200x, along with an up to 65 fold increase in sparsity, with comparable accuracy to the baseline.

We apply Turbo-SMT to BrainQ, a dataset consisting of a (nouns, brain voxels, human subjects) tensor and a (nouns, properties) matrix, with coupling along the nouns dimension. Turbo-SMT is able to find meaningful latent variables, as well as to predict brain activity with competitive accuracy.

A new analytical approach for the detection of palm oil in vegetable oil blends

The new Food Information Regulation (1169/2011), dictates that in a refined vegetable oil blend, the type of oil must be clearly identified in the package in contract with current practice where is labelled under the generic and often misleading term “vegetable oil”. With increase consumer awareness in food authenticity, as shown in the recent food scandal with horsemeat in beef products, the identification of the origin of species in food products becomes increasingly relevant. Palm oil is used extensively in food manufacturing and as global demand increases, producing countries suffer from the aftermath of intensive agriculture. Even if only a small portion of global production, sustainable palm oil comes in great demand from consumers and industry. It is therefore of interest to detect the presence of palm oil in food products as consumers have the right to know if it is present in the product or not, mainly from an ethical point of view. Apart from palm oil and its derivatives, rapeseed oil and sunflower oil are also included. With DNA-based methods, the gold standard for the detection of food authenticity and species recognition deemed not suitable in this analytical problem, the focus is inevitably drawn to the chromatographic and spectroscopic methods. Both chromatographic (such as GC-FID and LC-MS) and spectroscopic methods (FT-IR, Raman, NIR) are relevant. Previous attempts have not shown promising results due to oils’ natural variation in composition and complex chemical signals but the suggested two-step analytical procedure is a promising approach with very good initial results.

Identifying oil species in oil mixtures

Detection of adulteration of non-processed vegetable oil with lesser value seed oils (classic example is hazelnut in virgin olive oil) has been in the centre of scientific attention for many years and several chemical methods were proposed. The recent EC Regulation 1169/2011, however, introduces necessity for different analytical method in a more complicated matrix. From the end of 2014, food businesses required to declare the composition of the refined oil mixture in the food product label. This creates a gap since there is no analytical method currently available to perform such analysis. In the first phase the work focused on 100% oil blends of various oil species of palm oil (and derivatives), sunflower and rapeseed oil before expanding to foodstuffs. Chromatographic methods remain highly relevant although suffer from various limitations which derive from natural compositional variation. Modern multivariate techniques based on machine learning algorithms, however, when applied in FTIR, Raman spectroscopic data have a strong potential in tackling the problem.