A Potent Mimetic of the Siglec-8 Ligand 6’-Sulfo-Sialyl Lewisx

Siglecs are members of the immunoglobulin gene family containing sialic acid binding N-terminal domains. Among them, Siglec-8 is expressed on various cell types of the immune system such as eosinophils, mast cells and weakly on basophils. Cross-linking of Siglec-8 with monoclonal antibodies triggers apoptosis in eosinophils and inhibits degranulation of mast cells, making Siglec-8 a promising target for the treatment of eosinophil- and mast cell-associated diseases such as asthma. The tetrasaccharide 6’-sulfo-sialyl Lewis^x has been identified as a specific Siglec-8 ligand in glycan array screening. Here, we describe an extended study enlightening the pharmacophores of 6’-sulfo-sialyl Lewis^x and the successful development of a high-affinity mimetic. Retaining the neuraminic acid core, the introduction of a carbocyclic mimetic of the Gal moiety and a sulfonamide substituent in the 9-position gave a 20-fold improved binding affinity. Finally, the residence time, which usually is the Achilles tendon of carbohydrate/lectin interactions, could be improved.     

Integrative Analysis of Metabolomic,Proteomic and Genomic Data to Reveal Functional Pathways and Candidate Genes for Drip Loss in Pigs

The aim of this study was to integrate multi omics data to characterize underlying functional pathways and candidate genes for drip loss in pigs. The consideration of different omics levels allows elucidating the black box of phenotype expression. Metabolite and protein profiling was applied in Musculus longissimus dorsi samples of 97 Duroc × Pietrain pigs. In total, 126 and 35 annotated metabolites and proteins were quantified, respectively. In addition, all animals were genotyped with the porcine 60 k Illumina beadchip. An enrichment analysis resulted in 10 pathways, amongst others, sphingolipid metabolism and glycolysis/gluconeogenesis, with significant influence on drip loss. Drip loss and 22 metabolic components were analyzed as intermediate phenotypes within a genome-wide association study (GWAS). We detected significantly associated genetic markers and candidate genes for drip loss and for most of the metabolic components. On chromosome 18, a region with promising candidate genes was identified based on SNPs associated with drip loss, the protein “phosphoglycerate mutase 2” and the metabolite glycine. We hypothesize that association studies based on intermediate phenotypes are able to provide comprehensive insights in the genetic variation of genes directly involved in the metabolism of performance traits. In this way, the analyses contribute to identify reliable candidate genes.     

Biosynthesis of Jasmonates from Linoleic Acid by the Fungus Fusarium oxysporum. Evidence for a Novel Allene Oxide Cyclase

Fusarium oxysporum f. sp. tulipae (FOT) secretes (+)-7-iso-jasmonoyl-(S)-isoleucine ((+)-JA-Ile) to the growth medium together with about 10 times less 9,10-dihydro-(+)-7-iso-JA-Ile. Plants and fungi form (+)-JA-Ile from 18:3n-3 via 12-oxophytodienoic acid (12-OPDA), which is formed sequentially by 13S-lipoxygenase, allene oxide synthase (AOS), and allene oxide cyclase (AOC). Plant AOC does not accept linoleic acid (18:2n-6)-derived allene oxides and dihydrojasmonates are not commonly found in plants. This raises the question whether 18:2n-6 serves as the precursor of 9,10-dihydro-JA-Ile in Fusarium, or whether the latter arises by a putative reductase activity operating on the n-3 double bond of (+)-JA-Ile or one of its precursors. Incubation of pentadeuterated (d₅) 18:3n-3 with mycelia led to the formation of d₅-(+)-JA-Ile whereas d₅-9,10-dihydro-JA-Ile was not detectable. In contrast, d₅-9,10-dihydro-(+)-JA-Ile was produced following incubation of [17,17,18,18,18-²H₅]linoleic acid (d₅-18:2n-6). Furthermore, 9(S),13(S)-12-oxophytoenoic acid, the 15,16-dihydro analog of 12-OPDA, was formed upon incubation of unlabeled or d₅-18:2n-6. Appearance of the α-ketol, 12-oxo-13-hydroxy-9-octadecenoic acid following incubation of unlabeled or [¹³C₁₈]-labeled 13(S)-hydroperoxy-9(Z),11(E)-octadecadienoic acid confirmed the involvement of AOS and the biosynthesis of the allene oxide 12,13(S)-epoxy-9,11-octadecadienoic acid. The lack of conversion of this allene oxide by AOC in higher plants necessitates the conclusion that the fungal AOC is distinct from the corresponding plant enzyme.     

Carbon nanotubes: are they dispersed or dissolved in liquids?

Carbon nanotubes (CNTs) constitute a novel class of nanomaterials with remarkable applications in diverse domains. However, the main intrincsic problem of CNTs is their insolubility or very poor solubility in most of the common solvents. The basic key question here is: are carbon nanotubes dissolved or dispersed in liquids, specifically in water? When analyzing the scientific research articles published in various leading journals, we found that many researchers confused between "dispersion" and "solubilization" and use the terms interchangeably, particularly when stating the interaction of CNTs with liquids. In this article, we address this fundamental issue to give basic insight specifically to the researchers who are working with CNTs as well asgenerally to scientists who deal with nano-related research domains.Among the various nanomaterials, CNTs gained widespread attention owing to their exceptional properties, good chemical stability, and large surface area [1,2]. CNTs are extremely thin tubes and feature an extremely enviable combination of mechanical, thermal, electrical, and optical properties. Their size, shape, and properties construct them as prime contenders for exploiting the growth of a potentially revolutionary material for diverse applications.Nevertheless, the main intrinsic drawback of CNTs is their insolubility or extremely poor solubility in most of the common solvents due to their hydrophobicity, thus creating it tricky to explore and understand the chemistry of such material at the molecular level and device applications. Though diverse approaches [3] have been introduced to improve the dispersion of CNTs in different solvents including water, challenges still remain in developing simple, green, facile, and effective strategies for a large-scale production of CNT dispersions. To this end, in many studies a wide range of agents have been used. To give a few examples: solvents [4], biopolymers [5], and surfactants [6]. Meanwhile, when analyzing the scientific research articles published in various leading journals, regarding the dispersion of CNTs, it is really puzzling owing to the usage of different terminologies with respect to the dispersion of CNTs. Most of the studies indicated "dispersion"; however, considerable quantities of articles were published with the term "solubilization", which can be evidently seen from the literature analysis [7]. Hence, many researchers confound "dispersion" and "solubilization" and use the terms interchangeably, especially when describing the interaction of CNTs with solvents. Many scientists have mentioned that CNTs can be "solubilized in water or organic solvents" by means of polymers and/or surfactants, which is ambiguous. It is evident that there is, as a result of that, a lot of confusion regarding this fundamental matter. The basic and fundamental key question here is: are CNTs dissolved or dispersed in a liquid?Basically, "dispersion" and "solubilization" are different phenomena. Dispersion and solubilization can be defined as "a system, in which particles of any nature (e.g., solid, liquid, or gas) are dispersed in a continuous phase of a different composition (or state)" [8] and a "process, by which an agent increases the solubility or the rate of dissolution of a solid or liquid solute" [9], respectively. Hence, in general, the dispersion of solute particles in solvents leads to the formation of colloids or suspensions, and solutions may be obtained as a result of solubilization of solute molecules or ions in the specified solvent. Furthermore, dispersion is mostly related to solute particles, whereas solubility or solubilization is generally connected with solute molecules or ions.The main differences between a colloid and a solution are: A solution is homogenous and remains stable and does not separate after standing for any period of time. Further it cannot be separated by standard separation techniques such as filtration or centrifugation. A solution looks transparent and it can transmit the light. Also, solutions contain the solute in a size at the molecular or ionic level, typically less than 1 nm or maximum a few nm in all dimensions. A colloid is a mixture with particles sizes between 1 and 1000 nm in at least one dimension. It is opaque, non-transparent, and the particles are large enough to scatter light. Colloids are not as stable as solutions and the dispersed particles (comparatively larger-sized particles) may be conveniently separated by standard separation techniques such as (ultra)centrifugation or filtration. Frequently, dispersed particles in colloidal systems may slowly agglomerate owing to inter-particle attractions over prolonged periods of time and, as a result, colloidal dispersions may form flocs or flakes.As far as CNTs are concerned, even though the diameter of the tubes is in the nanometer range (approximately between 0.4 and 3 nm for single-walled carbon nanotubes, and 1.4 and 100 nm for multi-walled carbon nanotubes) [10], their length can be up to several micrometers to millimeters. Further, it is a well-known fact that CNTs are not equal in size with respect to both diameter and length. Hence, the result of dispersion techniques mostly used and adopted to produce well-dispersed CNTs in either aqueous and/or organic media are typically dispersions of differently sized tubes. Consequently, based on the definition [6,7] and the abovementioned points, the mixture of CNTs and water or organic solvents, whether in the presence or non-presence of dispersing agents such as surfactants or polymers, is just a colloidal dispersion and not a solution. Figure ​Figure11 shows the schematic illustration for the formation of dispersed CNTs in a liquid with the aid of a dispersing agent. Simultaneously, the dispersion can result in a debundling or individualization of the bundled CNTs.Open in a separate windowFigure 1Schematic showing the transition of the bundled to the individualized, dispersed state of carbon nanotubes in a liquid with the aid of a dispersing agent.Therefore, "solubilization" is a process to achieve a stable solution, whereas "dispersion" is a form of colloidal system. Here we conclude that the mixture obtained by using CNTs and a liquid medium (water or organic solvents) with or without surfactants or polymers is a dispersion of CNTs in the medium, but not a solution. Further, in our opinion, one cannot solubilize CNTs in water or organic solvents. Hence, we recommend to restrict the use of the term "solubilization" or "solution," instead we should use the term "dispersion" or "colloid," when dealing with CNTs. Further, we think that this should be also applicable for nanoparticles of comparable dimensions such as metal and metal oxide nanoparticles, polymer nanoparticles, etc., if the criteria of the definitions given above are fulfilled.In short, the term "dispersion" should exclusively be used as far as CNTs are concerned, and the use of the term "solution" should be avoided or restricted.     

Self- and mutual-diffusion coefficients in the dodecane/polystyrene system

The self-diffusion coefficient of dodecane in cross-linked polystyrene was measured using pulsed gradient spin echo nuclear magnetic resonance (PGSE–NMR) spectroscopy. The concentration and temperature dependence of the diffusion coefficient was analyzed by the Fujita and Vrentas–Duda models. Parameters describing the Fujita model were determined from fitting of diffusion data to the PVT behavior of the system. Parameters describing the Vrentas–Duda model were determined from the analysis of the viscosity of dodecane, the viscoelastic relaxation properties, and the glass transition temperature of polystyrene as well as from the diffusion coefficient of the system, measured from independent experiments. Both the Fujita and Vrentas–Duda models described well the concentration and temperature dependence of the diffusion coefficient. Mutual diffusion coefficients were determined from these results. © 1994 John Wiley & Sons, Inc.     

Atomic Friction Investigations on Ordered Superstructures

We review recent friction measurements on ordered superstructures performed by atomic force microscopy. In particular, we consider ultrathin KBr films on NaCl(001) and Cu(001) surfaces, single and bilayer graphene on SiC(0001), and the herringbone reconstruction of Au(111). Atomically resolved friction images of these systems show periodic features spanning across several unit cells. Although the physical mechanisms responsible for the formation of these superstructures are quite different, the experimental results can be interpreted within the same phenomenological framework. A comparison between experiments and modeling shows that, in the cases of KBr films on NaCl(001) and of graphene films, the tip-surface interaction is well described by a potential with the periodicity of the substrate which is modulated or, respectively, superimposed with a potential with the symmetry of the superstructure.     

Associative Grammar Combination Operators for Tree-Based Grammars

Polarized unification grammar (PUG) is a linguistic formalism which uses polarities to better control the way grammar fragments interact. The grammar combination operation of PUG was conjectured to be associative. We show that PUG grammar combination is not associative, and even attaching polarities to objects does not make it order-independent. Moreover, we prove that no non-trivial polarity system exists for which grammar combination is associative. We then redefine the grammar combination operator, moving to the powerset domain, in a way that guarantees associativity. The method we propose is general and is applicable to a variety of tree-based grammar formalisms.     

Where the wind blows

The power systems in Denmark, Spain, Ireland, and New Zealand have some of the highest wind penetrations in the world (see Table 1). The management of the different power systems to date, with increasing amounts of wind energy, has been successful. There have been no incidents in which the wind has directly or indirectly been a major factor causing operational problems for the system. However, there are a number of parameters that are being monitored that indicate the need for active management in the near future (and in some cases already today). In this article, we briefly describe the situations in these four countries, giving special emphasis to the market integration of wind power, the use of wind forecasting, and curtailment experience. The final section provides an overview of the main wind forecasting methodologies and challenges.