Turning big bang into big bounce: II. Quantum dynamics

We analyze the big bounce transition of the quantum FRW model in the setting of the nonstandard loop quantum cosmology (LQC). Elementary observables are used to quantize composite observables. The spectrum of the energy density operator is bounded and continuous. The spectrum of the volume operator is bounded from below and discrete. It has equally distant levels defining a quantum of the volume. The discreteness may imply a foamy structure of spacetime at semiclassical level which may be detected in astro-cosmo observations. The nonstandard LQC method has a free parameter that should be fixed in some way to specify the big bounce transition.Comment: 14 pages, no figures, version accepted for publication in Class. Quant. Gra

A New Class of Group Field Theories for 1st Order Discrete Quantum Gravity

Group Field Theories, a generalization of matrix models for 2d gravity, represent a 2nd quantization of both loop quantum gravity and simplicial quantum gravity. In this paper, we construct a new class of Group Field Theory models, for any choice of spacetime dimension and signature, whose Feynman amplitudes are given by path integrals for clearly identified discrete gravity actions, in 1st order variables. In the 3-dimensional case, the corresponding discrete action is that of 1st order Regge calculus for gravity (generalized to include higher order corrections), while in higher dimensions, they correspond to a discrete BF theory (again, generalized to higher order) with an imposed orientation restriction on hinge volumes, similar to that characterizing discrete gravity. The new models shed also light on the large distance or semi-classical approximation of spin foam models. This new class of group field theories may represent a concrete unifying framework for loop quantum gravity and simplicial quantum gravity approaches.Comment: 48 pages, 4 figures, RevTeX, one reference adde

Optimization principles of dendritic structure

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Gd(III) complexes intercalated into hydroxy double salts as potential MRI contrast agents

The ion exchange intercalation of two Gd-based magnetic resonance imaging contrast agents into hydroxy double salts (HDSs) is reported. The presence of Gd3+ diethylenetriaminepentaacetate and Gd3+ diethylenetriaminepenta(methylenephosphonate) complexes in the HDS lattice after intercalation was confirmed by microwave plasma-atomic emission spectroscopy. The structural aspects of the HDS-Gd composites were studied by X-ray diffraction, with the intercalates having an interlayer spacing of 14.5–18.6 Å. Infrared spectroscopy confirmed the presence of characteristic vibration peaks associated with the Gd3+ complexes in the intercalation compounds. The proton relaxivities of the Gd3+ complex-loaded composites were 2 to 5-fold higher in longitudinal relaxivity, and up to 10-fold higher in transverse relaxivity, compared to solutions of the pure complexes. These data demonstrate that the new composites reported here are potentially potent MRI contrast agents

STAT3 Regulates Monocyte TNF-Alpha Production in Systemic Inflammation Caused by Cardiac Surgery with Cardiopulmonary Bypass

BACKGROUND: Cardiopulmonary bypass (CPB) surgery initiates a controlled systemic inflammatory response characterized by a cytokine storm, monocytosis and transient monocyte activation. However, the responsiveness of monocytes to Toll-like receptor (TLR)-mediated activation decreases throughout the postoperative course. The purpose of this study was to identify the major signaling pathway involved in plasma-mediated inhibition of LPS-induced tumor necrosis factor (TNF)-α production by monocytes. METHODOLOGY/PRINCIPAL FINDINGS: Pediatric patients that underwent CPB-assisted surgical correction of simple congenital heart defects were enrolled (n = 38). Peripheral blood mononuclear cells (PBMC) and plasma samples were isolated at consecutive time points. Patient plasma samples were added back to monocytes obtained pre-operatively for ex vivo LPS stimulations and TNF-α and IL-6 production was measured by flow cytometry. LPS-induced p38 mitogen-activated protein kinase (MAPK) and nuclear factor (NF)-κB activation by patient plasma was assessed by Western blotting. A cell-permeable peptide inhibitor was used to block STAT3 signaling. We found that plasma samples obtained 4 h after surgery, regardless of pre-operative dexamethasone treatment, potently inhibited LPS-induced TNF-α but not IL-6 synthesis by monocytes. This was not associated with attenuation of p38 MAPK activation or IκB-α degradation. However, abrogation of the IL-10/STAT3 pathway restored LPS-induced TNF-α production in the presence of suppressive patient plasma. CONCLUSIONS/SIGNIFICANCE: Our findings suggest that STAT3 signaling plays a crucial role in the downregulation of TNF-α synthesis by human monocytes in the course of systemic inflammation in vivo. Thus, STAT3 might be a potential molecular target for pharmacological intervention in clinical syndromes characterized by systemic inflammation

Cholesteryl ester transfer protein: at the heart of the action of lipid-modulating therapy with statins, fibrates, niacin, and cholesteryl ester transfer protein inhibitors

Subnormal plasma levels of high-density lipoprotein cholesterol (HDL-C) constitute a major cardiovascular risk factor; raising low HDL-C levels may therefore reduce the residual cardiovascular risk that frequently presents in dyslipidaemic subjects despite statin therapy. Cholesteryl ester transfer protein (CETP), a key modulator not only of the intravascular metabolism of HDL and apolipoprotein (apo) A-I but also of triglyceride (TG)-rich particles and low-density lipoprotein (LDL), mediates the transfer of cholesteryl esters from HDL to pro-atherogenic apoB-lipoproteins, with heterotransfer of TG mainly from very low-density lipoprotein to HDL. Cholesteryl ester transfer protein activity is elevated in the dyslipidaemias of metabolic disease involving insulin resistance and moderate to marked hypertriglyceridaemia, and is intimately associated with premature atherosclerosis and high cardiovascular risk. Cholesteryl ester transfer protein inhibition therefore presents a preferential target for elevation of HDL-C and reduction in atherosclerosis. This review appraises recent evidence for a central role of CETP in the action of current lipid-modulating agents with HDL-raising potential, i.e. statins, fibrates, and niacin, and compares their mechanisms of action with those of pharmacological agents under development which directly inhibit CETP. New CETP inhibitors, such as dalcetrapib and anacetrapib, are targeted to normalize HDL/apoA-I levels and anti-atherogenic activities of HDL particles. Further studies of these CETP inhibitors, in particular in long-term, large-scale outcome trials, will provide essential information on their safety and efficacy in reducing residual cardiovascular risk

A multifactorial analysis of obesity as CVD risk factor: Use of neural network based methods in a nutrigenetics context

<p>Abstract</p> <p>Background</p> <p>Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm.</p> <p>Results</p> <p>PDM-ANN and GA-ANN were comparatively assessed in terms of their ability to identify the most important factors among the initial 63 variables describing genetic variations, nutrition and gender, able to classify a subject into one of the BMI related classes: normal and overweight. The methods were designed and evaluated using appropriate training and testing sets provided by 3-fold Cross Validation (3-CV) resampling. Classification accuracy, sensitivity, specificity and area under receiver operating characteristics curve were utilized to evaluate the resulted predictive ANN models. The most parsimonious set of factors was obtained by the GA-ANN method and included gender, six genetic variations and 18 nutrition-related variables. The corresponding predictive model was characterized by a mean accuracy equal of 61.46% in the 3-CV testing sets.</p> <p>Conclusions</p> <p>The ANN based methods revealed factors that interactively contribute to obesity trait and provided predictive models with a promising generalization ability. In general, results showed that ANNs and their hybrids can provide useful tools for the study of complex traits in the context of nutrigenetics.</p