Dermal application of nitric oxide releasing acidified nitrite-containing liniments significantly reduces blood pressure in humans

Vascular ischemic diseases, hypertension, and other systemic hemodynamic and vascular disorders may be the result of impaired bioavailability of nitric oxide (NO). NO but also its active derivates like nitrite or nitroso compounds are important effector and signal molecules with vasodilating properties. Our previous findings point to a therapeutical potential of cutaneous administration of NO in the treatment of systemic hemodynamic disorders. Unfortunately, no reliable data are available on the mechanisms, kinetics and biological responses of dermal application of nitric oxide in humans in vivo. The aim of the study was to close this gap and to explore the therapeutical potential of dermal nitric oxide application. We characterized with human skin in vitro and in vivo the capacity of NO, applied in a NO-releasing acidified form of nitrite-containing liniments, to penetrate the epidermis and to influence local as well as systemic hemodynamic parameters. We found that dermal application of NO led to a very rapid and significant transepidermal translocation of NO into the underlying tissue. Depending on the size of treated skin area, this translocation manifests itself through a significant systemic increase of the NO derivates nitrite and nitroso compounds, respectively. In parallel, this translocation was accompanied by an increased systemic vasodilatation and blood flow as well as reduced blood pressure. We here give evidence that in humans dermal application of NO has a therapeutic potential for systemic hemodynamic disorders that might arise from local or systemic insufficient availability of NO or its bio-active NO derivates, respectively.     

Structural analysis of ConBr reveals molecular correlation between the carbohydrate recognition domain and endothelial NO synthase activation

Diocleinae lectins are highly homologous in their primary structure which features metal binding sites and a carbohydrate recognition domain (CRD). Differences in the biological activity of legume lectins have been widely investigated using hemagglutination inhibition assays, isothermal titration microcalorimetry and co-crystallization with mono- and oligosaccharides. Here we report a new lectin crystal structure (ConBr) extracted from seeds of Canavalia brasiliensis, predict dimannoside binding by docking, identify the α-aminobutyric acid (Abu) binding pocket and compare the CRD of ConBr to that of homologous lectins. Based on the hypothesis that the carbohydrate affinity of lectins depends on CRD configuration, the relationship between tridimensional structure and endothelial NO synthase activation was used to clarify differences in biological activity. Our study established a correlation between the position of CRD amino acid side chains and the stimulation of NO release from endothelium.     

Bayesian multisensory integration and cross-modal spatial links.

Our perception of the word is the result of combining information between several senses, such as vision, audition and proprioception. These sensory modalities use widely different frames of reference to represent the properties and locations of object. Moreover, multisensory cues come with different degrees of reliability, and the reliability of a given cue can change in different contexts. The Bayesian framework--which we describe in this review--provides an optimal solution to deal with this issue of combining cues that are not equally reliable. However, this approach does not address the issue of frames of references. We show that this problem can be solved by creating cross-modal spatial links in basis function networks. Finally, we show how the basis function approach can be combined with the Bayesian framework to yield networks that can perform optimal multisensory combination. On the basis of this theory, we argue that multisensory integration is a dialogue between sensory modalities rather that the convergence of all sensory information onto a supra-modal area.     

Towards biocompatible vaccine delivery systems: interactions of colloidal PECs based on polysaccharides with HIV-1 p24 antigen

This work reports on the interactions of a model protein (p24, the capside protein of HIV-1 virus) with colloids obtained from polyelectrolyte complexes (PECs) involving two polysaccharides: chitosan and dextran sulfate (DS). The PECs were elaborated by a one-shot addition of default amounts of one counterpart to the polymer in excess. Depending on the nature of the excess polyelectrolyte, the submicrometric colloid was either positively or negatively charged. HIV-1 capsid p24 protein was chosen as antigen, the ultrapure form, lipopolysaccharide-free (endotoxin-, vaccine grade) was used in most experiments, as the level of purity of the protein had a great impact on the immobilization process. p24 sorption kinetics, isotherms, and loading capacities were investigated for positively and negatively charged particles of chitosans and dextran sulfates differing in degrees of polymerization (DP) or acetylation (DA). Compared with the positive particles, negatively charged colloids had higher binding capacities, faster kinetics, and a better stability of the adsorbed p24. Capacities up to 600 mg x g(-1) (protein-colloid) were obtained, suggesting that the protein interacted within the shell of the particles. Small-angle X-rays scattering experiments confirmed this hypothesis. Finally, the immunogenicity of the p24-covered particles was assessed for vaccine purposes in mice. The antibody titers obtained with immobilized p24 was dose dependent and in the same range as for Freund's adjuvant, a gold standard for humoral responses.     

Methods to account for spatial autocorrelation in the analysis of species distributional data: a review

Species distributional or trait data based on range map (extent‐of‐occurrence) or atlas survey data often display spatial autocorrelation, i.e. locations close to each other exhibit more similar values than those further apart. If this pattern remains present in the residuals of a statistical model based on such data, one of the key assumptions of standard statistical analyses, that residuals are independent and identically distributed (i.i.d), is violated. The violation of the assumption of i.i.d. residuals may bias parameter estimates and can increase type I error rates (falsely rejecting the null hypothesis of no effect). While this is increasingly recognised by researchers analysing species distribution data, there is, to our knowledge, no comprehensive overview of the many available spatial statistical methods to take spatial autocorrelation into account in tests of statistical significance. Here, we describe six different statistical approaches to infer correlates of species’ distributions, for both presence/absence (binary response) and species abundance data (poisson or normally distributed response), while accounting for spatial autocorrelation in model residuals: autocovariate regression; spatial eigenvector mapping; generalised least squares; (conditional and simultaneous) autoregressive models and generalised estimating equations. A comprehensive comparison of the relative merits of these methods is beyond the scope of this paper. To demonstrate each method's implementation, however, we undertook preliminary tests based on simulated data. These preliminary tests verified that most of the spatial modeling techniques we examined showed good type I error control and precise parameter estimates, at least when confronted with simplistic simulated data containing spatial autocorrelation in the errors. However, we found that for presence/absence data the results and conclusions were very variable between the different methods. This is likely due to the low information content of binary maps. Also, in contrast with previous studies, we found that autocovariate methods consistently underestimated the effects of environmental controls of species distributions. Given their widespread use, in particular for the modelling of species presence/absence data (e.g. climate envelope models), we argue that this warrants further study and caution in their use. To aid other ecologists in making use of the methods described, code to implement them in freely available software is provided in an electronic appendix.