Characterization of Viral Insulins Reveals White Adipose Tissue Specific Effects in Mice [preprint]

Members of the insulin/IGF superfamily are well conserved across the evolutionary tree. We recently showed that four viruses in the Iridoviridae family possess genes that encode proteins highly homologous to human insulin/IGF-1. Using chemically synthesized single chain (sc), i.e. IGF-1-like, forms of the viral insulin/IGF-1 like peptides (VILPs), we previously showed that they can stimulate human receptors. Because these peptides possess potential cleavage sites to form double chain (dc), i.e. more insulin-like, VILPs, in this study, we have characterized dc forms of VILPs for Grouper iridovirus (GIV), Singapore grouper iridovirus (SGIV) and Lymphocystis disease virus-1 (LCDV-1). GIV and SGIV dcVILPs bind to both isoforms of human insulin receptor (IR-A, IR-B) and to the IGF1R, and for the latter show higher affinity than human insulin. These dcVILPs stimulate IR and IGF1R phosphorylation and post-receptor signaling in vitro and in vivo. Both GIV and SGIV dcVILPs stimulate glucose uptake in mice. In vivo infusion experiments in awake mice revealed that while insulin (0.015 nmol/kg/min) and GIV dcVILP (0.75nmol/kg/min) stimulated a comparable glucose uptake in heart, skeletal muscle and brown adipose tissue, GIV dcVILP stimulated ~2 fold higher glucose uptake in white adipose tissue (WAT) compared to insulin. This was associated with increased Akt phosphorylation and glucose transporter type 4 (GLUT4) gene expression compared to insulin. Taken together, these results show that GIV and SGIV dcVILPs are active members of the insulin superfamily with unique characteristics. Elucidating the mechanism of tissue specificity for GIV dcVILP will help us to better understand insulin action, design new analogues that specifically target the tissues, and provide new insights into their potential role in disease

Insulin-Insulin-like Growth Factors Hybrids as Molecular Probes of Hormone : Receptor Binding Specificity

Insulin, insulin-like growth factors 1 and 2 (IGF-1 and -2, respectively), and their receptors (IR and IGF-1R) are the key elements of a complex hormonal system that is essential for the development and functioning of humans. The C and D domains of IGFs (absent in insulin) likely play important roles in the differential binding of IGF-1 and -2 to IGF-1R and to the isoforms of IR (IR-A and IR-B) and specific activation of these receptors. Here, we attempted to probe the impact of IGF-1 and IGF-2 D domains (DI and DII, respectively) and the IGF-2 C domain (CII) on the receptor specificity of these hormones. For this, we made two types of insulin hybrid analogues: (i) with the C-terminus of the insulin A chain extended by the amino acids from the DI and DII domains and (ii) with the C-terminus of the insulin B chain extended by some amino acids derived from the CII domain. The receptor binding affinities of these analogues and their receptor autophosphorylation potentials were characterized. Our results indicate that the DI domain has a more negative impact than the DII domain does on binding to IR, and that the DI domain Pro-Leu-Lys residues are important factors for a different IR-A versus IR-B binding affinity of IGF-1. We also showed that the additions of amino acids that partially "mimic" the CII domain, to the C-terminus of the insulin B chain, change the binding and autophosphorylation specificity of insulin in favor of the "metabolic" IR-B isoform. This opens new venues for rational enhancement of insulin IR-B specificity by modifications beyond the C-terminus of its B chain

Ontology of core data mining entities

In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines themost essential datamining entities in a three-layered ontological structure comprising of a specification, an implementation and an application layer. It provides a representational framework for the description of mining structured data, and in addition provides taxonomies of datasets, data mining tasks, generalizations, data mining algorithms and constraints, based on the type of data. OntoDM-core is designed to support a wide range of applications/use cases, such as semantic annotation of data mining algorithms, datasets and results; annotation of QSAR studies in the context of drug discovery investigations; and disambiguation of terms in text mining. The ontology has been thoroughly assessed following the practices in ontology engineering, is fully interoperable with many domain resources and is easy to extend

Nuclear Charge Radii of Be-7,9,10 and the one-neutron halo nucleus Be-11

Nuclear charge radii of $^{7,9,10,11}$Be have been determined by high-precision laser spectroscopy. On-line measurements were performed with collinear laser spectroscopy in the $2s_{1/2} \to 2p_{1/2}$ transition on a beam of Be$^{+}$ ions. Collinear and anticollinear laser beams were used simultaneously and the absolute frequency determination using a frequency comb yielded an accuracy in the isotope-shift measurements of about 1 MHz. Combination with accurate calculations of the mass-dependent isotope shifts yield nuclear charge radii. The charge radius decreases from $^7$Be to $^{10}$Be and then increases for the halo nucleus $^{11}$Be. When comparing our results with predictions of {\it ab initio} nuclear structure calculations we find good agreement. Additionally, the nuclear magnetic moment of $^7$Be was determined to be $-1.3995(5)\mu_{\rm N}$ and that of $^{11}$Be from a previous $\beta$-NMR measurement was confirmed.Comment: 4 pages, 2 figures calculated mass shift values have been re-evaluated with the latest mass values for the beryllium isotopes and the nuclear polarization contribution for Be-11, published by K. Pachucki et al. ater submission of our manuscript, is also included no

Negatives in questions (and answers): the case of ουκουν (…) ου. Or: does Ancient Greek have a word for ‘no’?

Among the uses of ουκουν Denniston (19542: 435) mentions: "ουκουν ου, ουκουν … ου, expecting a negative answer." In this paper it is argued that Denniston’s view, which is shared by most (all?) other grammars and dictionaries (e.g. Kuhner & Gerth 1898-19043: 2, 164: "Wenn nach ουκουν eine verneinende Antwort erwartet wird, so wird demselben die Negation ου nachgesetzt", Smyth 1956: §2651a: "ουκουν ου expects the answer no", LSJ 1940: s.v. ουκουν) should be rejected. Actually, the answer is never no. As always, ουκουν expects an affirmative answer, in this case to a negated question: ‘Is it not the case, then, that not X?’ = ‘Surely, then, not X?’. To be sure, ου does occur as an answer, but this can be shown to be a proposition (or sentence) negative (= not), rather than an answering particle like no. This is compared with negatives in several other languages, notably Latin and Old French. Finally, Modern Greek is briefly discussed, which, unlike Ancient Greek, does have a negative answering particle, viz. όχι, alongside a proposition negative, viz. δε(ν)

Mechanical and corrosion properties of iron-mangan materials sintered in the presence of plasma

The current trend in development of new metallic materials for certain types of implants is turning away from permanent, biologically inert materials to the use of biodegradable materials. Fe–Mn alloys represent high perspective material for development of new generation of temporary and biodegradable implants. The aim of this work was to study mechanical and corrosion characteristics of powder samples containing 25, 30 and 35 wt % of Mn which are fabricated by pressing, sintering, and additional spark plasma sintering. The influence of preparation method (pressing and sintering) to microstructure, phased composition and corrosion behavior of prepared alloys was studied

Dimensional Changes, Microstructure, Microhardness Distributions And Corrosion Properties Of Iron And Iron-Manganese Sintered Materials

Iron samples and Fe-Mn alloys with Mn content of 25 wt.% and 30 wt.% were prepared by blending, compressing and sintering with the aim to study their dimensional changes, microstructure, microhardness distribution and primarily the electrochemical corrosion behaviour in a simulated body environment