In vitro approaches to assess bioavailability and human gastrointestinal mobilization of food-borne polychlorinated biphenyls (PCBs)

This study reports on the potential for gastrointestinal (GI) mobilization and bioavailability of food-borne PCBs in humans. The development and validation of a GI simulator and operational protocols, developed in compliance with the requirements of German DIN 19738 risk assessment test procedure, are presented. Food, naturally contaminated with PCBs, was homogenized with simulated saliva fluid and shaken in the GI simulator with simulated gastric fluids (containing pepsin, mucine) for 2 h at 37°C. Afterwards, the simulated intestinal fluids (containing pepsin, mucine, trypsin, pancreatin, bile) were added and the mixture shaken for a further 6 h prior to centrifugation and filtration using Buchner funnels to separate the undigested GI residues from GI fluids. PCBs were recovered from GI residues and fluids by Soxhlet and liquid-liquid extraction respectively, cleaned up using silica-SFE, and analyzed by gas chromatography mass spectrometry detection (GC-MSD). Detailed studies with fish indicate variations in mobilization and bioavailability of Σ PCBs (28, 52, 101, 118, 153, 138 and 180). For example, the bioavailable fractions (fractions mobilized) in mackerel, salmon, crab and prawn were 0.77, 0.60, 0.54, and 0.72 respectively of the Σ PCBs initially present in these food samples. The bioavailable fraction was dependent on the physicochemical characteristics of the PCBs. In mackerel bioavailable fractions for individual PCB congeners ranged from 0.47–0.82, from 0.30–0.70 in salmon, 0.44–0.64 in crab and in prawn from 0.47–0.77. Future studies will focus on understanding better, the variability in bioavailable fractions to be expected for different foodstuffs, in addition to tissue culture techniques using human gut cell lines to investigate a simultaneous mobilization and absorption of food-borne PCBs.     

Effect of Refractory on the Thermal Stability of SF6

The thermal decomposition of SF₆ is known to be oxygen-independent. Nevertheless, because of its high stability, the use of SF6 as a "conservative" surrogate in incinerator performance evaluation has been advocated and researched. This paper shows that refractory decreases markedly the stability of SF₆. The resulting increase in SF₆ decomposition was from 0 percent to 95 percent at 900°C, and the temperatures at which 90-99 percent decomposition occurred were lowered by 300-150°C. Refractory also decreased the stability of CCl₄ and C₂Cl₄, but to a lesser extent. The difference between the decompositions of C₂Cl₄ and SF₆ was reduced from several orders of magnitude to a factor of 2-4. Such a drastic and adverse change in relative stability could render SF₆ unsuitable as a "conservative" surrogate. The requirements for a "conservative" surrogate and the need for caution in its use are discussed, and further research areas are indicated.     

Use of inorganic and organic wastes for in situ immobilisation of Pb and Zn in a contaminated alkaline soil

Purpose  

This study aims to examine whether addition of immobilising agents to a sandy, alkaline (pH = 8.1) soil, which had been contaminated with Pb and Zn by airborne particles from a Pb/Zn smelter, would substantially reduce metal bioavailability.     

Contribution of sociodemographic characteristics, occupation, diet and lifestyle to DDT and DDE concentrations in serum and adipose tissue from a Bolivian cohort

The organochlorine pesticide p,p′-Dichlorodiphenyltrichloroethane (DDT) was widely used in the early 1960s-70s for vector control in tropical and subtropical areas of South America. Due to its persistence, DDT has a high potential to bioaccumulate in the food chain and living organisms and is a major public health concern, especially in South America.The main purpose of the present study was to investigate predictors of serum and adipose tissue concentrations of p,p′-DDT and its main metabolite, p,p′-dichlorodiphenyldichloroethylene (p,p′-DDE), in an adult cohort (n = 112) from Santa Cruz de la Sierra, Bolivia, using multiple linear regression models. These models explained 29.3-47.8% of the variability in adipose tissue concentrations of p,p′-DDT and p,p′-DDE, respectively, and 32.9-47.0% of that in serum. Main exposure predictors included age, occupational class, residence, diet, smoking habit, and accumulated breastfeeding time.This is one of the few studies to explore predictors of human exposure to these chemicals using a multivariate approach in a South American population. Results show that predictors of human exposure to p,p′-DDT and p,p′-DDE in Santa Cruz de la Sierra may diverge from those found in other populations of the world, due to particular sociodemographic and lifestyle characteristics of this region.     

Properties of alkali-activated systems with stone powder sludge

This article investigates the effects of stone powder sludge on the microstructure and strength development of alkali-activated fly ash and blast furnace slag mixes. Stone powder sludge produced from a crushed aggregate factory was used to replace fly ash and granulated blast furnace slag at replacement ratios of 0%, 10%, 20%, and 30% by mass. The unit weight and compressive strength of the samples were measured, and scanning electron microscopy/energy dispersive spectroscopy and X-ray diffraction (XRD) analyses were performed. The test results indicated that the compressive strength of alkali-activated blast furnace slag mixes using stone powder sludge was higher than that of the alkali-activated blast furnace slag control mix, but the compressive strength of alkali-activated fly ash mixes decreased with increasing replacement ratio of stone powder sludge. Microscopy results indicated that for alkaliactivated blast furnace slag samples, broken surfaces were more evident than for the alkali-activated fly ash samples. For all XRD diagrams, broad and diffuse peaks were observed around 2θ = 35° (d = 2.96–3.03 Å), implying amorphous or short-ordering structure phases.     

Why ozonolysis may not increase the hydrophilicity of particles

It is commonly assumed that atmospheric oxidation of hydrocarbon particles or hydrocarbon coatings on particles leads to polar products and increased water uptake, altering atmospheric visibility and increasing the likelihood they will act as cloud condensation nuclei (CCN). We show here through laboratory experiments that increased water uptake depends on the 3-dimensional structure of the particles. Laboratory studies of particles formed during ozonolysis of surface-bound alkenes, present as terminally unsaturated self-assembled monolayers (C8= SAM) on a silica substrate, were carried out at room temperature and 1 atm pressure. SAMs were exposed to ～10¹³ O₃ molecules cm^?3 for 40 min and resultant particles were analyzed using single particle Fourier transform infrared micro-spectroscopy (micro-FTIR) and secondary ion mass spectroscopy (SIMS). Spectroscopy results show that –COOH and other polar groups are formed but are buried inside a hydrophobic shell, consistent with earlier observations (McIntire et al., 2005, Moussa et al., 2009) that water uptake does not increase after reaction of the terminal alkene with O₃. These insights into the 3-D structure of particles formed on oxidation have important implications for the ability of secondary organic aerosols to act as CCN. In addition, the nature of the surface of the particles is expected to determine their uptake into biological systems such as the surface of the lungs.     

Biomarkers of pesticide exposure and diabetes in the 1999–2004 National Health and Nutrition Examination Survey

The associations of 8 pesticides and pesticide metabolites with total diabetes (diagnosed and undiagnosed) and pre-diabetes (glycohemoglobin 5.7–6.4%) were evaluated using the National Health and Nutrition Examination Survey (NHANES), 1999–2004. Six of the pesticides were found to be associated with total diabetes in separate adjusted logistic regressions. These pesticides and pesticide metabolites were beta-hexachlorocyclohexane, p,p′-DDE, p,p′-DDT, oxychlordane, trans-nonachlor, and heptachlor epoxide. When the number of compounds elevated was tested, 4 or more, of the 6, elevated had an odds ratio of 4.99 (95% CI 1.97–12.61) compared to none elevated. When the 6 compounds were tested together in a single combined adjusted logistic regression only oxychlordane, a metabolite of chlordane, and heptachlor epoxide, a metabolite of heptachlor, were significantly associated with total diabetes. In the combined adjusted logistic regression, oxychlordane ≥ 14.5 ng/g lipid adjusted had an odds ratios of 1.90 (95% CI 1.09–3.32) compared to oxychlordane < 14.5 ng/g lipid adjusted, and heptachlor epoxide ≥ 14.6 ng/g lipid adjusted had an odds ratio of 1.70 (95% CI 1.16–2.49) compared to heptachlor epoxide < 14.6 ng/g lipid adjusted. Heptachlor epoxide and p,p′-DDT were significantly associated with pre-diabetes in separate adjusted logistic regressions. When these 2 compounds were tested together only heptachlor epoxide remained significantly associated with pre-diabetes. The evidence supporting the relationship between pesticides and pesticide metabolites, with diabetes, was strongest for heptachlor epoxide and oxychlordane, intermediate for p,p′-DDT, and least for beta-hexachlorocyclohexane, p,p′-DDE, and trans-nonachlor. Mirex and dieldrin were not associated with total diabetes or pre-diabetes.     

Machine learning for radioxenon event classification for the Comprehensive Nuclear-Test-Ban Treaty

A method of weapon detection for the Comprehensive nuclear-Test-Ban-Treaty (CTBT) consists of monitoring the amount of radioxenon in the atmosphere by measuring and sampling the activity concentration of ^131mXe, ¹³³Xe, ^133mXe, and ¹³⁵Xe by radionuclide monitoring. Several explosion samples were simulated based on real data since the measured data of this type is quite rare. These data sets consisted of different circumstances of a nuclear explosion, and are used as training data sets to establish an effective classification model employing state-of-the-art technologies in machine learning. A study was conducted involving classic induction algorithms in machine learning including Naïve Bayes, Neural Networks, Decision Trees, k-Nearest Neighbors, and Support Vector Machines, that revealed that they can successfully be used in this practical application. In particular, our studies show that many induction algorithms in machine learning outperform a simple linear discriminator when a signal is found in a high radioxenon background environment.