Binding of Gamma-Glutamyl Transferase to TLR4 Signalling Allows Tissue Factor Activation in Monocytes

Gamma-glutamyl transferase (GGT) is involved in the progression of atherosclerosis, since its enzymatic activity promotes the generation of reactive oxygen species (ROS). Besides, GGT may act as a prothrombotic factor by inducing tissue factor (TF) expression, independently of its enzymatic activity. The aim of this study was to assess whether GGT-induced TF stimulation was a consequence of binding to toll-like receptor 4 (TLR4) expressed on monocytes, the precursors of macrophages and foam cells which colocalize with GGT activity within atherosclerotic plaques. Experiments were performed in human peripheral blood mononuclear cells (PBMCs), THP-1 cells (a monocytic cellular model), and HEK293 cells, which were genetically modified to study the activation of TLR4. TF procoagulant activity was assessed by a one-stage clotting time test, and TF protein expression was estimated by western blot. Human recombinant (hr) GGT protein increased TF procoagulant activity and protein expression in both PBMCs and THP-1 cells. The GGT-induced TF stimulation was prevented by cellular pretreatment with TLR4/NF-κB inhibitors (LPS-Rs, CLI-095, and BAY-11-7082), and HEK293 cells lacking TLR4 confirmed that TLR4 is essential for GGT-induced activation of NF-κB. In conclusion, hrGGT induced TF expression in monocytes through a cytokine-like mechanism that involved the activation of TLR4/NF-κB signaling.     

Bactericidal/Permeability-Increasing Protein Downregulates the Inflammatory Response in In Vivo Models of Arthritis

We investigated the effects of bactericidal/permeability-increasing protein (BPI) alone or in combination with hyaluronic acid (HA) in two animal models: collagen-induced arthritis (CIA) and crystal-induced inflammation. In CIA, mice were intraperitoneally injected with PBS, HA, or BPI plus or minus HA, twice a week for 2 months, and then euthanized to collect paw and blood. Arthritis was assessed in ankle joints by clinical and histological evaluation. Pathogenic crystals were intraperitoneally injected in mice plus or minus BPI, or with a composition of BPI and HA. After sacrifice, total and differential leukocyte counts were determined. Cytokine levels were measured in serum and peritoneal fluids. In CIA mice, BPI improved clinical and histological outcomes (histological scores ≥2-fold), and downregulated inflammatory mediators (47–93%). In crystal-induced inflammation, BPI reduced leukocyte infiltration (total count: ≥60%; polymorphonuclear cells: ≥36%) and inhibited cytokine production (35–74%). In both models, when mice were co-treated with BPI and HA, the improvement of all parameters was greater than that observed after administration of the two substances alone. Results show that BPI attenuates CIA and inflammation in mice, and this effect is enhanced by HA co-administration. Combined use of BPI and HA represents an interesting perspective for new potential treatments in arthritis.     

Immobilization of Lipase B from Candida antarctica in Octyl-Vinyl Sulfone Agarose: Effect of the Enzyme-Support Interactions on Enzyme Activity,Specificity, Structure and Inactivation Pathway

Lipase B from Candida antarctica was immobilized on heterofunctional support octyl agarose activated with vinyl sulfone to prevent enzyme release under drastic conditions. Covalent attachment was established, but the blocking step using hexylamine, ethylenediamine or the amino acids glycine (Gly) and aspartic acid (Asp) altered the results. The activities were lower than those observed using the octyl biocatalyst, except when using ethylenediamine as blocking reagent and p-nitrophenol butyrate (pNPB) as substrate. The enzyme stability increased using these new biocatalysts at pH 7 and 9 using all blocking agents (much more significantly at pH 9), while it decreased at pH 5 except when using Gly as blocking agent. The stress inactivation of the biocatalysts decreased the enzyme activity versus three different substrates (pNPB, S-methyl mandelate and triacetin) in a relatively similar fashion. The tryptophane (Trp) fluorescence spectra were different for the biocatalysts, suggesting different enzyme conformations. However, the fluorescence spectra changes during the inactivation were not too different except for the biocatalyst blocked with Asp, suggesting that, except for this biocatalyst, the inactivation pathways may not be so different.     

Insulin-like Growth Factor 2 (IGF-2) and Insulin-like Growth Factor Binding Protein 7 (IGFBP-7) Are Upregulated after Atypical Antipsychotics in Spanish Schizophrenia Patients

Insulin-like growth factor 2 (IGF-2) and IGF binding protein 7 (IGFBP-7) have been related to schizophrenia (SZ) due to their implication in neurodevelopment. The purpose of this study was to assess whether the alterations in IGF-2 and IGFBP-7 in SZ patients are intrinsically related to the psychiatric disorder itself or are a secondary phenomenon due to antipsychotic treatment. In order to test this hypothesis, we measured plasma IGF-2 and IGFBP-7 in drug-naïve first episode (FE) and multiple episodes or chronic (ME) SZ Caucasian patients who have been following treatment for years. A total of 55 SZ patients (FE = 15, ME = 40) and 45 healthy controls were recruited. The Positive and Negative Syndrome Scale (PANSS) and the Self-Assessment Anhedonia Scale (SAAS) were employed to check schizophrenic symptomatology and anhedonia, respectively. Plasma IGF-2 and IGFBP-7 levels were measured by Enzyme-Linked Immunosorbent Assay (ELISA). The FE SZ patients had much lower IGF-2, but not IGFBP-7, than controls. Moreover, both IGF-2 and IGFBP-7 significantly increased after atypical antipsychotic treatment (aripiprazole, olanzapine, or risperidone) in these patients. On the other hand, chronic patients showed higher levels of both proteins when compared to controls. Our study suggests that circulatory IGF-2 and IGFBP-7 increase after antipsychotic treatment, regardless of long-term conditions and being lower in drug-naïve FE patients.     

Study of the Ghrelin/LEAP-2 Ratio in Humans and Rats during Different Phases of Pregnancy

The Liver-Expressed Antimicrobial Peptide 2 (LEAP-2) has emerged as an endogenous GHS-R antagonist and blunts the orexigenic action of ghrelin. This study aimed to determine the Ghrelin/LEAP-2 ratio in humans and rats during pregnancy. In humans, we conducted a nested case-control study within an observational prospective cohort. Healthy and mild preeclamptic pregnant women were studied at each trimester of gestation and three months postpartum. In addition, a group of non-pregnant women was studied into the follicular and luteal phases of the menstrual cycle. Furthermore, Ghrelin/LEAP-2 ratio was investigated in non-pregnant rats and at different periods of rat pregnancy. Human and rat serum ghrelin and LEAP-2 levels were determined using the commercially available ELISA kits. The Ghrelin/LEAP-2 ratio peak around the second trimester of gestation in healthy pregnant women (p < 0.05). Additionally, there were no statistically significant differences in Ghrelin/LEAP-2 ratio between healthy and preeclamptic pregnant women at each trimester of gestation (p > 0.05). The Ghrelin/LEAP-2 ratio in pregnant rat reached the peak around mid-gestation with a similar pattern to the human pregnancy. LEAP-2 was visualized by immunohistochemistry in human term placenta and rat placentas on days 12, 16 and 21 of pregnancy. In conclusion, this study provides the first evidence of a Ghrelin/LEAP-2 ratio peak around the half-way point of pregnancy onwards during human and rat pregnancy, and it might be associated with increased rates of weight gain during pregnancy. Thus, this study suggests that LEAP-2 and Ghrelin/LEAP-2 ratio might play an important role in maternal physiology adaptation of weight gain during pregnancy.     

Whole Body Vibration Improves Brain and Musculoskeletal Health by Modulating the Expression of Tissue-Specific Markers: FNDC5 as a Key Regulator of Vibration Adaptations

Whole body vibration (WBV) is well known to exert beneficial effects on multiple tissues, improving synaptic transmission, muscle mass, bone quality, and reducing anxiety and depressive behavior. However, the underlying molecular mechanisms are not yet fully understood, and organs and tissues may respond differently to the vibratory stimulus depending on multiple factors. Therefore, we investigated the WBV effects on the brain and musculoskeletal tissue of 4-month-old young mice, evaluating synaptic plasticity by electrophysiological recordings and tissue organization by histology and histomorphometric analysis. Specifically, WBV protocols were characterized by the same vibration frequency (45 Hz), but different in vibration exposure time (five series of 3 min for the B protocol and three series of 2 min and 30 s for the C protocol) and recovery time between two vibration sessions (1 min for the B protocol and 2 min and 30 s for the C protocol). In addition, immunohistochemistry was conducted to evaluate the expression of fibronectin type III domain-containing protein 5 (FNDC5), as well as that of tissue-specific markers, such as brain-derived neurotrophic factor (BDNF) in brain, myostatin in muscle and collagen I (COL-1) in bone. Our results suggest that the WBV effects depend closely on the type of protocol used and support the hypothesis that different organs or tissues have different susceptibility to vibration. Further studies will be needed to deepen our knowledge of physiological adaptations to vibration and develop customized WBV protocols to improve and preserve cognitive and motor functions.     

Molecular Effects of Chronic Exposure to Palmitate in Intestinal Organoids: A New Model to Study Obesity and Diabetes

Intestinal cell dysfunctions involved in obesity and associated diabetes could be correlated with impaired intestinal cell development. To date, the molecular mechanisms underlying these dysfunctions have been poorly investigated because of the lack of a good model for studying obesity. The main aim of this study was to investigate the effects of lipotoxicity on intestinal cell differentiation in small intestinal organoid platforms, which are used to analyze the regulation of cell differentiation. Mouse intestinal organoids were grown in the presence/absence of high palmitate concentrations (0.5 mM) for 48 h to simulate lipotoxicity. Palmitate treatment altered the expression of markers involved in the differentiation of enterocytes and goblet cells in the early (Hes1) and late (Muc2) phases of their development, respectively, and it modified enterocytes and goblet cell numbers. Furthermore, the expression of enteroendocrine cell progenitors (Ngn3) and I cells (CCK) markers was also impaired, as well as CCK-positive cell numbers and CCK secretion. Our data indicate, for the first time, that lipotoxicity simultaneously influences the differentiation of specific intestinal cell types in the gut: enterocytes, goblet cells and CCK cells. Through this study, we identified novel targets associated with molecular mechanisms affected by lipotoxicity that could be important for obesity and diabetes therapy.     

Bifurcation analysis of a dynamic duopoly model with heterogeneous costs and behavioural rules

We develop a nonlinear dynamic Cournot duopoly model in discrete time, where two bounded rational quantity-setting firms, both endowed with naïve expectations, are heterogeneous as to their cost functions and output strategies. One of the two competing firms adopts best-reply behaviour, whereas the other adjusts its production according to the gradient of its profit. Although excessive reaction of the latter firm generally results in destabilization of the ‘Cournot–Nash’ equilibrium and brings about complex dynamic scenarios, this occurs via qualitatively different bifurcation routes, depending on the ratio between firms’ marginal costs. The paper also provides a preliminary exploration of the long-run sustainability of the heterogeneous duopoly competition, by investigating numerically the impact of fixed costs on firms’ survival, along different output trajectories.     

Efficient simulation of hierarchical stochastic activity network models

Stochastic extensions to Petri nets have gained widespread acceptance as a method for describing the dynamic behavior of discrete-event systems. Both simulation and analytic methods have been proposed to solve such models. This paper describes a set of efficient procedures for simulating models that are represented as stochastic activity networks (SANs, a variant of stochastic Petri nets) and composed SAN-based reward models (SBRMs). Composed SBRMs are a hierarchical representation for SANs, in which individual SAN models can be replicated and joined together with other models, in an iterative fashion. The procedures exploit the hierarchical structure and symmetries introduced by the replicate operation in a composed SBRM to reduce the cost of future event list management. The procedures have been implemented as part of a larger performance-dependability modeling package known asUltraSAN, and have been applied to real, large-scale applications. This work was supported in part by the Digital Equipment Corporation Faculty Program: Incentives for Excellence.     

Worst-case properties of the uniform distribution and randomized algorithms for robustness analysis

In this paper we study aprobabilistic approach which is an alternative to the classical worst-case algorithms for robustness analysis and design of uncertain control systems. That is, we aim to estimate the probability that a control system with uncertain parametersq restricted to a boxQ attains a given level of performance γ. Since this probability depends on the underlying distribution, we address the following question: What is a “reasonable” distribution so that the estimated probability makes sense? To answer this question, we define two worstcase criteria and prove that the uniform distribution is optimal in both cases. In the second part of the paper we turn our attention to a subsequent problem. That is, we estimate the sizes of both the so-called “good” and “bad” sets via sampling. Roughly speaking, the good set contains the parametersq∈Q with a performance level better than or equal to γ while the bad set is the set of parametersq∈Q with a performance level worse than γ. We give bounds on the minimum sample size to attain a good estimate of these sets in a certain probabilistic sense.