Serum antioxidant capacity and peroxide level of seven healthy subjects after consumption of different foods

This article reports experimental data related to the research article entitled \u201cDifferent effectiveness of two pastas supplemented with either lipophilic or hydrophilic/phenolic antioxidants in affecting serum as evaluated by the novel Antioxidant/Oxidant Balance approach\u201d (M.N. Laus, M. Soccio, M. Alfarano, A. Pasqualone, M.S. Lenucci, G. Di Miceli, D. Pastore, 2016) [1]. Antioxidant status of blood serum of seven healthy subjects was evaluated during four hours after consumption of two functional pastas, supplemented with either bran oleoresin or bran water extract obtained from durum wheat. For comparison, the effect of a non-supplemented reference pasta was also evaluated, as well as the effects of glucose, of the wheat grain dietary supplement Lisosan G, and of the reference pasta consumed together with Lisosan G. Serum antioxidant status was evaluated by measuring both the serum antioxidant capacity, using LOX-FL, ORAC and TEAC methods, and the serum oxidant status, assessed as peroxide level

Mechanisms of Self-Organization and Finite Size Effects in a Minimal Agent Based Model

We present a detailed analysis of the self-organization phenomenon in which the stylized facts originate from finite size effects with respect to the number of agents considered and disappear in the limit of an infinite population. By introducing the possibility that agents can enter or leave the market depending on the behavior of the price, it is possible to show that the system self-organizes in a regime with a finite number of agents which corresponds to the stylized facts. The mechanism to enter or leave the market is based on the idea that a too stable market is unappealing for traders while the presence of price movements attracts agents to enter and speculate on the market. We show that this mechanism is also compatible with the idea that agents are scared by a noisy and risky market at shorter time scales. We also show that the mechanism for self-organization is robust with respect to variations of the exit/entry rules and that the attempt to trigger the system to self-organize in a region without stylized facts leads to an unrealistic dynamics. We study the self-organization in a specific agent based model but we believe that the basic ideas should be of general validity.Comment: 14 pages, 7 figure

Myocarditis and intramural coronary vasculitis in polyarteritis nodosa: an unusual treatable form of heart failure

We describe an uncommon cardiac presentation of polyarteritis nodosa. A 68-year-old woman, with a history of fatigue, weight loss, and myalgia of the lower extremities, was admitted for congestive heart failure. Coronary arteries were normal. Endomyocardial biopsy showed active lymphocytic myocarditis with associated intramural small vessels necrotizing vasculitis. The overexpression of TLR-4 and the negativity for myocardial viruses suggested an immune mediated mechanism of cardiac damage. These histologic findings associated to weight loss >4 kg not due to dieting or other factors, myalgias, and polyneuropathy, were consistent with the diagnosis of polyarteritis nodosa. Immunosuppressive treatment, consisting of cyclophosphamide and prednisolone, led to a significant improvement of cardiac function. Polyarteritis nodosa can be the cause of unexplained heart failure due to myocarditis and intramural vessels vasculitis. Its recognition is crucial to obtain a cardiac recovery with a tailored immunosuppressive treatment

Detection and Quantitative Analysis of Two Independent Binding Modes of a Small Ligand Responsible for DC-SIGN Clustering

DC-SIGN (dendritic cell-specific ICAM-3 grabbing non-integrin) is a C-type lectin receptor (CLRs) present, mainly in dendritic cells (DCs), as one of the major pattern recognition receptors (PRRs). This receptor has a relevant role in viral infection processes. Recent approaches aiming to block DC-SIGN have been presented as attractive anti-HIV strategies. DC-SIGN binds mannose or fucose-containing carbohydrates from viral proteins such as the HIV envelope glycoprotein gp120. We have previously demonstrated that multivalent dendrons bearing multiple copies of glycomimetic ligands were able to inhibit DC-SIGN-dependent HIV infection in cervical explant models. Optimization of glycomimetic ligands requires detailed characterization and analysis of their binding modes because they notably influence binding affinities. In a previous study we characterized the binding mode of DC-SIGN with ligand 1, which shows a single binding mode as demonstrated by NMR and X-ray crystallography. In this work we report the binding studies of DC-SIGN with pseudotrisaccharide 2, which has a larger affinity. Their binding was analysed by TR-NOESY and STD NMR experiments, combined with the CORCEMA-ST protocol and molecular modelling. These studies demonstrate that in solution the complex cannot be explained by a single binding mode. We describe the ensemble of ligand bound modes that best fit the experimental data and explain the higher inhibition values found for ligand

Advances in the Agent-based Modeling of Economic and Social Behavior

In this review we discuss advances in the agent-based modeling of economic and social systems. We show the state of the art of the heuristic design of agents and how behavioral economics and laboratory experiments have improved the modeling of agent behavior. We further discuss how economic networks and social systems can be modeled and we discuss novel methodology and data sources. Lastly, we present an overview of estimation techniques to calibrate and validate agent-based models and show avenues for future research

po 324 interferon regulatory factor 1 irf1 regulates inflammatory and metabolic phenotypes in pancreatic ductal adenocarcinoma

Introduction Pancreatic Ductal Adenocarcinoma (PDAC) is the most frequent neoplasia of the exocrine pancreas. This tumour is and is characterised by a pervasive heterogeneity, with the coexistence of a range of histological grades, from epithelial-like to mesenchymal-like features. We previously dissected the transcriptional and epigenetic networks underlying PDAC grading. We identified the association of low grade phenotypes with a cell-autonomous interferon-related signature. Therefore, we set out to investigate the sustainment of inflammatory and interferon-related signatures in well-differentiated pancreatic cancer cells, and to determine the role of this network in PDAC biology. Material and methods We used cell-line based models of cancer differentiation, xenografts and human samples. We used CRISPR-Cas9 mediated genome editing to delete the transcription factor IRF1 (Interferon Regulatory Factor 1) in low-grade PDAC cells. RNA-seq, metabolic assays (oxygraphy, steady state metabolomics, fluxomics) and cell biology assays were carried out in IRF1 wt and knock-out cell lines. Data validation in human PDAC samples was carried out by immunohistochemistry. Results and discussions We found that IRF1 is a transcription factor differentially expressed between low- and high-grade PDACs, both in cell lines and in human tumours. IRF1 deletion in low-grade cell lines reduced the expression of genes in the antigen processing and presentation pathways, while its overexpression promoted the expression of the same genes in high-grade cells, where they are normally not expressed. Furthermore, xenografted IRF1-deficient cell lines recruited fewer immune cells in vivo . IRF1 deletion also affected epithelial phenotypes, including growth rate, cell shape, motility and collagen remodelling ability. Alongside, we unveiled a role of IRF1 in the control of the metabolism of low-grade PDAC cells, consisting in the control of mitochondrial respiration and lipogenesis as well as of the overall lipid profile of these cells. Conclusion To conclude, our results provide hints on the regulatory networks controlling cell differentiation in human PDACs. We show that IRF1 acts as a pleiotropic regulator in the low grade component of PDACs, with wide effects on immunological and metabolic features of this cancer population. Our work reinforces the body of knowledge needed for the development of those therapeutic strategies aiming at exploiting immunological or metabolic pitfalls

The PAMELA Storage and Control Unit

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Turnover, account value and diversification of real traders: evidence of collective portfolio optimizing behavior

Despite the availability of very detailed data on financial market, agent-based modeling is hindered by the lack of information about real trader behavior. This makes it impossible to validate agent-based models, which are thus reverse-engineering attempts. This work is a contribution to the building of a set of stylized facts about the traders themselves. Using the client database of Swissquote Bank SA, the largest on-line Swiss broker, we find empirical relationships between turnover, account values and the number of assets in which a trader is invested. A theory based on simple mean-variance portfolio optimization that crucially includes variable transaction costs is able to reproduce faithfully the observed behaviors. We finally argue that our results bring into light the collective ability of a population to construct a mean-variance portfolio that takes into account the structure of transaction costsComment: 26 pages, 9 figures, Fig. 8 fixe

MoKCa database - mutations of kinases in cancer

Members of the protein kinase family are amongst the most commonly mutated genes in human cancer, and both mutated and activated protein kinases have proved to be tractable targets for the development of new anticancer therapies The MoKCa database (Mutations of Kinases in Cancer, http://strubiol.icr.ac.uk/extra/mokca) has been developed to structurally and functionally annotate, and where possible predict, the phenotypic consequences of mutations in protein kinases implicated in cancer. Somatic mutation data from tumours and tumour cell lines have been mapped onto the crystal structures of the affected protein domains. Positions of the mutated amino-acids are highlighted on a sequence-based domain pictogram, as well as a 3D-image of the protein structure, and in a molecular graphics package, integrated for interactive viewing. The data associated with each mutation is presented in the Web interface, along with expert annotation of the detailed molecular functional implications of the mutation. Proteins are linked to functional annotation resources and are annotated with structural and functional features such as domains and phosphorylation sites. MoKCa aims to provide assessments available from multiple sources and algorithms for each potential cancer-associated mutation, and present these together in a consistent and coherent fashion to facilitate authoritative annotation by cancer biologists and structural biologists, directly involved in the generation and analysis of new mutational data