Analysis of Crude Oils by Frequency Domain Spectroscopy—Effect of Composition and Physical Properties on Conductivity and Dielectric Response

The dielectric properties and the composition of fourteen light to heavy crude oils have been analyzed. Frequency domain spectroscopy (FDS) has been used in order to determine their dielectric response in the frequency range 0.01 to 1000 Hz. For all the crude oils, over the whole frequency range under study, dielectric loss, ?″, shows a linear dependence of frequency indicating a pure direct current (DC) conductivity. As temperature is gradually increased, the dielectric loss, ?″, increases as well, showing a strong temperature dependence. The storage modulus, ?′, shows an explicit behaviour at low frequency that could be due to adsorption of oil components onto the electrodes. We tried to correlate some physical and chemical properties (density, viscosity, SARA, TAN, water content) of the studied crude oils with their conductivity measured at various temperatures. No correlation was found and different hypothesis are suggested by the authors to explain this phenomenon.     

Experimental and Kinetic Modeling Study of Methanol Ignition and Oxidation at High Pressure

A detailed chemical kinetic model for oxidation of CH₃OH at high pressure and intermediate temperatures has been developed and validated experimentally. Ab initio calculations and Rice–Ramsperger–Kassel–Marcus/transition state theory (RRKM/TST) analysis were used to obtain rate coefficients for , , , and . The experiments, involving CH₃OH/O₂ mixtures diluted in N₂, were carried out in a high‐pressure flow reactor at 600–900 K and 20–100 bar, varying the reaction stoichiometry from very lean to fuel‐rich conditions. Under the conditions studied, the onset temperature for methanol oxidation was not dependent on the stoichiometry, whereas increasing pressure shifted the ignition temperature toward lower values. Model predictions of the present experimental results, as well as rapid compression machine data from the literature, were generally satisfactory. The governing reaction pathways have been outlined based on calculations with the kinetic model. Unlike what has been observed for unsaturated hydrocarbons, the oxidation pathways for CH₃OH under the investigated conditions were very similar to those prevailing at higher temperatures and lower pressures. At the high pressures, the modeling predictions for onset of reaction were particularly sensitive to the reaction.     

On Resin Modification of Monosaccharides

Ellman's dihydropyran resin was used for selective protection of monosaccharide thioglycosides and glycosides. Following on‐resin acylation and subsequent cleavage of the polymer‐bound intermediates, product components having selectively unblocked hydroxyl functions could be obtained.      

Facile One‐Step Syntheses of Modified O‐Glycoprotein Galβ1‐3GalNAc Structures by Transglycosylation Employing Three β‐Galactosidases from Bovine Testes,Xanthomonas manihotis,and Bacillus circulans *

Natural O‐glycoproteins such as the Thomsen‐Friedenreich antigen or gangliosides contain the motif Galβ1‐3GalNAc as an important disaccharide with significant biologic activity. The arrangement of spatial functionalities in this structure are of particular interest with regard to the development of potential leads en route to pharmaceuticals. Therefore, it was desired to obtain access to a range of modified derivatives of the aforementioned motif paying particular attention to introducing specific deoxy functions instead of hydroxyl groups.     

Development of 7TM receptor-ligand complex models using ligand-biased, semi-empirical helix-bundle repacking in torsion space: application to the agonist interaction of the human dopamine D2 receptor

Prediction of 3D structures of membrane proteins, and of G-protein coupled receptors (GPCRs) in particular, is motivated by their importance in biological systems and the difficulties associated with experimental structure determination. In the present study, a novel method for the prediction of 3D structures of the membrane-embedded region of helical membrane proteins is presented. A large pool of candidate models are produced by repacking of the helices of a homology model using Monte Carlo sampling in torsion space, followed by ranking based on their geometric and ligand-binding properties. The trajectory is directed by weak initial restraints to orient helices towards the original model to improve computation efficiency, and by a ligand to guide the receptor towards a chosen conformational state. The method was validated by construction of the β₁ adrenergic receptor model in complex with (S)-cyanopindolol using bovine rhodopsin as template. In addition, models of the dopamine D₂ receptor were produced with the selective and rigid agonist (R)-N-propylapomorphine ((R)-NPA) present. A second quality assessment was implemented by evaluating the results from docking of a library of 29 ligands with known activity, which further discriminated between receptor models. Agonist binding and recognition by the dopamine D₂ receptor is interpreted using the 3D structure model resulting from the approach. This method has a potential for modeling of all types of helical transmembrane proteins for which a structural template with sequence homology sufficient for homology modeling is not available or is in an incorrect conformational state, but for which sufficient empirical information is accessible.     

Discovery and validation of urinary exposure markers for different plant foods by untargeted metabolomics

While metabolomics is increasingly used to investigate the food metabolome and identify new markers of food exposure, limited attention has been given to the validation of such markers. The main objectives of the present study were to (1) discover potential food exposure markers (PEMs) for a range of plant foods in a study setting with a mixed dietary background and (2) validate PEMs found in a previous meal study. Three-day weighed dietary records and 24-h urine samples were collected three times during a 6-month parallel intervention study from 107 subjects randomized to two distinct dietary patterns. An untargeted UPLC-qTOF-MS metabolomics analysis was performed on the urine samples, and all features detected underwent strict data analyses, including an iterative paired t test and sensitivity and specificity analyses for foods. A total of 22 unique PEMs were identified that covered 7 out of 40 investigated food groups (strawberry, cabbages, beetroot, walnut, citrus, green beans and chocolate). The PEMs reflected foods with a distinct composition rather than foods eaten more frequently or in larger amounts. We found that 23 % of the PEMs found in a previous meal study were also valid in the present intervention study. The study demonstrates that it is possible to discover and validate PEMs for several foods and food classes in an intervention study with a mixed dietary background, despite the large variability in such a dataset. Final validation of PEMs for intake of foods should be performed by quantitative analysis.

Graphene-based sensors for detection of heavy metals in water: a review

Graphene (G) is attracting significant attention because of its unique physical and electronic properties. The production of graphene through the reduction of graphene oxide (GO) is a low-cost method. The reduction of GO can further lead to electrically conductive reduced GO. These graphene-based nanomaterials are attractive for high-performance water sensors due to their unique properties, such as high specific surface areas, high electron mobilities, and exceptionally low electronic noise. Because of potential risks to the environment and human health arising from heavy-metal pollution in water, G-/GO-based water sensors are being developed for rapid and sensitive detection of heavy-metal ions. In this review, a general introduction to graphene and GO properties, as well as their syntheses, is provided. Recent advances in optical, electrochemical, and electrical detection of heavy-metal ions using graphene or GO are then highlighted. Finally, challenges facing G/GO-based water sensor development and outlook for future research are discussed.