Th1 and Th17 hypercytokinemia as early host response signature in severe pandemic influenza.

INTRODUCTION Human host immune response following infection with the new variant of A/H1N1 pandemic influenza virus (nvH1N1) is poorly understood. We utilize here systemic cytokine and antibody levels in evaluating differences in early immune response in both mild and severe patients infected with nvH1N1. METHODS We profiled 29 cytokines and chemokines and evaluated the haemagglutination inhibition activity as quantitative and qualitative measurements of host immune responses in serum obtained during the first five days after symptoms onset, in two cohorts of nvH1N1 infected patients. Severe patients required hospitalization (n = 20), due to respiratory insufficiency (10 of them were admitted to the intensive care unit), while mild patients had exclusively flu-like symptoms (n = 15). A group of healthy donors was included as control (n = 15). Differences in levels of mediators between groups were assessed by using the non parametric U-Mann Whitney test. Association between variables was determined by calculating the Spearman correlation coefficient. Viral load was performed in serum by using real-time PCR targeting the neuraminidase gene. RESULTS Increased levels of innate-immunity mediators (IP-10, MCP-1, MIP-1beta), and the absence of anti-nvH1N1 antibodies, characterized the early response to nvH1N1 infection in both hospitalized and mild patients. High systemic levels of type-II interferon (IFN-gamma) and also of a group of mediators involved in the development of T-helper 17 (IL-8, IL-9, IL-17, IL-6) and T-helper 1 (TNF-alpha, IL-15, IL-12p70) responses were exclusively found in hospitalized patients. IL-15, IL-12p70, IL-6 constituted a hallmark of critical illness in our study. A significant inverse association was found between IL-6, IL-8 and PaO2 in critical patients. CONCLUSIONS While infection with the nvH1N1 induces a typical innate response in both mild and severe patients, severe disease with respiratory involvement is characterized by early secretion of Th17 and Th1 cytokines usually associated with cell mediated immunity but also commonly linked to the pathogenesis of autoimmune/inflammatory diseases. The exact role of Th1 and Th17 mediators in the evolution of nvH1N1 mild and severe disease merits further investigation as to the detrimental or beneficial role these cytokines play in severe illness.

Inverse relation between levels of anti-oxidized-LDL antibodies and eicosapentanoic acid (EPA).

Oxidative modification of LDL is thought to play an important role in the development of atherosclerosis. Susceptibility of LDL to peroxidation may partly depend on the compositional characteristics of the antioxidant and fatty acid content. The aim of this study was to examine the association between levels of antibodies to oxidized LDL and the various serum fatty acids in women. A total of 465 women aged 18-65 years were selected randomly from the adult population census of Pizarra, a town in southern Spain. Measurement of anti-oxidized-LDL was done by ELISA and the fatty acid composition of serum phospholipids was determined by GC. The levels of anti-oxidized-LDL antibodies were significantly related with age (r - 0.341, P < 0.001), BMI (r - 0.239, P < 0.001), waist:hip ratio (r - 0.285, P < 0.001), glucose (r - 0.208, P < 0.001), cholesterol (r - 0.243, P < 0.001), LDL-cholesterol (r - 0.185, P = 0.002), EPA (r - 0.159, P = 0.003), DHA (r - 0.121, P = 0.026), and the sum of the serum phospholipid n-3 PUFA (r - 0.141, P = 0.009). Multiple regression analysis showed that the variables that explained the behaviour of the levels of anti-oxidized-LDL antibodies were age (P < 0.001) and the serum phospholipid EPA (P < 0.001). This study showed that the fatty acid composition of serum phospholipids, and especially the percentage of EPA, was inversely related with the levels of anti-oxidized-LDL antibodies.

Inverse relation between FASN expression in human adipose tissue and the insulin resistance level.

BACKGROUND Adipose tissue is a key regulator of energy balance playing an active role in lipid storage and may be a dynamic buffer to control fatty acid flux. Just like PPARgamma, fatty acid synthesis enzymes such as FASN have been implicated in almost all aspects of human metabolic alterations such as obesity, insulin resistance or dyslipemia. The aim of this work is to investigate how FASN and PPARgamma expression in human adipose tissue is related to carbohydrate metabolism dysfunction and obesity. METHODS The study included eighty-seven patients which were classified according to their BMI and to their glycaemia levels in order to study FASN and PPARgamma gene expression levels, anthropometric and biochemical variables. RESULTS The main result of this work is the close relation between FASN expression level and the factors that lead to hyperglycemic state (increased values of glucose levels, HOMA-IR, HbA1c, BMI and triglycerides). The correlation of the enzyme with these parameters is inversely proportional. On the other hand, PPARgamma is not related to carbohydrate metabolism. CONCLUSIONS We can demonstrate that FASN expression is a good candidate to study the pathophysiology of type II diabetes and obesity in humans.

Exendin-(9-39) is an inverse agonist of the murine glucagon-like peptide-1 receptor: implications for basal intracellular cyclic adenosine 3',5'-monophosphate levels and beta-cell glucose competence.

The effect of exendin-(9-39), a described antagonist of the glucagon-like peptide-1 (GLP-1) receptor, was evaluated on the formation of cAMP- and glucose-stimulated insulin secretion (GSIS) by the conditionally immortalized murine betaTC-Tet cells. These cells have a basal intracellular cAMP level that can be increased by GLP-1 with an EC50 of approximately 1 nM and can be decreased dose dependently by exendin-(9-39). This latter effect was receptor dependent, as a beta-cell line not expressing the GLP-1 receptor was not affected by exendin-(9-39). It was also not due to the endogenous production of GLP-1, because this effect was observed in the absence of detectable preproglucagon messenger RNA levels and radioimmunoassayable GLP-1. Importantly, GSIS was shown to be sensitive to this basal level of cAMP, as perifusion of betaTC-Tet cells in the presence of exendin-(9-39) strongly reduced insulin secretion. This reduction of GSIS, however, was observed only with growth-arrested, not proliferating, betaTC-Tet cells; it was also seen with nontransformed mouse beta-cells perifused in similar conditions. These data therefore demonstrated that 1) exendin-(9-39) is an inverse agonist of the murine GLP-1 receptor; 2) the decreased basal cAMP levels induced by this peptide inhibit the secretory response of betaTC-Tet cells and mouse pancreatic islets to glucose; 3) as this effect was observed only with growth-arrested cells, this indicates that the mechanism by which cAMP leads to potentiation of insulin secretion is different in proliferating and growth-arrested cells; and 4) the presence of the GLP-1 receptor, even in the absence of bound peptide, is important for maintaining elevated intracellular cAMP levels and, therefore, the glucose competence of the beta-cells.

Modelling of non-linear viscoelastic tissues with bar elements

In this work we develop a viscoelastic bar element that can handle multiple rheo- logical laws with non-linear elastic and non-linear viscous material models. The bar element is built by joining in series an elastic and viscous bar, constraining the middle node position to the bar axis with a reduction method, and stati- cally condensing the internal degrees of freedom. We apply the methodology to the modelling of reversible softening with sti ness recovery both in 2D and 3D, a phenomenology also experimentally observed during stretching cycles on epithelial lung cell monolayers.

Modelling world investment markets using threshold conditional correlation models

In this paper we propose a parsimonious regime-switching approach to model the correlations between assets, the threshold conditional correlation (TCC) model. This method allows the dynamics of the correlations to change from one state (or regime) to another as a function of observable transition variables. Our model is similar in spirit to Silvennoinen and Teräsvirta (2009) and Pelletier (2006) but with the appealing feature that it does not suffer from the course of dimensionality. In particular, estimation of the parameters of the TCC involves a simple grid search procedure. In addition, it is easy to guarantee a positive definite correlation matrix because the TCC estimator is given by the sample correlation matrix, which is positive definite by construction. The methodology is illustrated by evaluating the behaviour of international equities, govenrment bonds and major exchange rates, first separately and then jointly. We also test and allow for different parts in the correlation matrix to be governed by different transition variables. For this, we estimate a multi-threshold TCC specification. Further, we evaluate the economic performance of the TCC model against a constant conditional correlation (CCC) estimator using a Diebold-Mariano type test. We conclude that threshold correlation modelling gives rise to a significant reduction in portfolio´s variance.

Inverse agonism and neutral antagonism at alpha(1a)- and alpha(1b)-adrenergic receptor subtypes.

We have characterized the pharmacological antagonism, i.e., neutral antagonism or inverse agonism, displayed by a number of alpha-blockers at two alpha1-adrenergic receptor (AR) subtypes, alpha(1a)- and alpha(1b)-AR. Constitutively activating mutations were introduced into the alpha(1a)-AR at the position homologous to A293 of the alpha(1b)-AR where activating mutations were previously described. Twenty-four alpha-blockers differing in their chemical structures were initially tested for their effect on the agonist-independent inositol phosphate response mediated by the constitutively active A271E and A293E mutants expressed in COS-7 cells. A selected number of drugs also were tested for their effect on the small, but measurable spontaneous activity of the wild-type alpha(1a)- and alpha(1b)-AR expressed in COS-7 cells. The results of our study demonstrate that a large number of structurally different alpha-blockers display profound negative efficacy at both the alpha(1a)- and alpha(1b)-AR subtypes. For other drugs, the negative efficacy varied at the different constitutively active mutants. The most striking difference concerns a group of N-arylpiperazines, including 8-[2-[4-(5-chloro-2-methoxyphenyl)-1-piperazinyl]ethyl]-8-azaspiro [4, 5] decane-7,9-dione (REC 15/3039), REC 15/2739, and REC 15/3011, which are inverse agonists with profound negative efficacy at the wild-type alpha(1b)-AR, but not at the alpha(1a)-AR.

Modelling of Mercury’s surface composition and remote detection from the orbit with the BepiColombo Mercury Planetary Orbiter

It can be assumed that the composition of Mercury’s thin gas envelope (exosphere) is related to thecomposition of the planets crustal materials. If this relationship is true, then inferences regarding the bulkchemistry of the planet might be made from a thorough exospheric study. The most vexing of allunsolved problems is the uncertainty in the source of each component. Historically, it has been believedthat H and He come primarily from the solar wind, while Na and K originate from volatilized materialspartitioned between Mercury’s crust and meteoritic impactors. The processes that eject atoms andmolecules into the exosphere of Mercury are generally considered to be thermal vaporization, photonstimulateddesorption (PSD), impact vaporization, and ion sputtering. Each of these processes has its owntemporal and spatial dependence. The exosphere is strongly influenced by Mercury’s highly ellipticalorbit and rapid orbital speed. As a consequence the surface undergoes large fluctuations in temperatureand experiences differences of insolation with longitude. We will discuss these processes but focus moreon the expected surface composition and solar wind particle sputtering which releases material like Caand other elements from the surface minerals and discuss the relevance of composition modelling

Modelling the Human Values Scale from Consumers Transactional Data Bases

The main objective of this paper aims at developing a methodology that takes into account the human factor extracted from the data base used by the recommender systems, and which allow to resolve the specific problems of prediction and recommendation. In this work, we propose to extract the user's human values scale from the data base of the users, to improve their suitability in open environments, such as the recommender systems. For this purpose, the methodology is applied with the data of the user after interacting with the system. The methodology is exemplified with a case study

Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Modelling scenarios of diffusion and control of pandemic influenza, italy

En aquest article es resumeixen els resultats publicats en un informe de l' ISS (Istituto Superiore di Sanità) del desembre de 2006, sobre un model matemàtic desenvolupat per un grup de treball que inclou a investigadors de les Universitats de Trento, Pisa i Roma, i els Instituts Nacionals de Salut (Istituto Superiore di Sanità, ISS), per avaluar i mesurar l'impacte de la transmissió i el control de la pandèmia de grip

Overcoming the rare species modelling paradox: test of a novel hierarchical framework with an Iberian endemic plant

Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the "rare species modelling paradox" and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models aren't overfitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.

Modelling the cardiovascular system for automatic interpretation of the blood pressure curve

A four compartment model of the cardiovascular system is developed. To allow for easy interpretation and to minimise the number of parameters, an effort was made to keep the model as simple as possible. A sensitivity analysis is first carried out to determine which are the most important model parameters to characterise the blood pressure signal. A four stage process is then described which accurately determines all parameter values. This process is applied to data from three patients and good agreement is shown in all cases.