Shannon entropies of atomic structure factors, off-diagonal order and electron correlation

Shannon entropies of one- and two-electron atomic structure factors in the position and momentum representations are used to examine the behavior of the off-diagonal elements of density matrices with respect to the uncertainty principle and to analyze the effects of electron correlation on off-diagonal order. We show that electron correlation induces off-diagonal order in position space which is characterized by larger entropic values. Electron correlation in momentum space is characterized by smaller entropic values as information is forced into regions closer to the diagonal. Related off-diagonal correlation functions are also discussed

System-adapted correlation energy density functionals from effective pair interactions

We present and discuss some ideas concerning an ``average-pair-density functional theory'', in which the ground-state energy of a many-electron system is rewritten as a functional of the spherically and system-averaged pair density. These ideas are further clarified with simple physical examples. We then show that the proposed formalism can be combined with density functional theory to build system-adapted correlation energy functionals. A simple approximation for the unknown effective electron-electron interaction that enters in this combined approach is described, and results for the He series and for the uniform electron gas are briefly reviewed.Comment: to appear in Phil. Mag. as part of Conference proceedings for the "Electron Correlations and Materials Properties", Kos Greece, July 5-9, 200

Solving Quantum Ground-State Problems with Nuclear Magnetic Resonance

Quantum ground-state problems are computationally hard problems; for general many-body Hamiltonians, there is no classical or quantum algorithm known to be able to solve them efficiently. Nevertheless, if a trial wavefunction approximating the ground state is available, as often happens for many problems in physics and chemistry, a quantum computer could employ this trial wavefunction to project the ground state by means of the phase estimation algorithm (PEA). We performed an experimental realization of this idea by implementing a variational-wavefunction approach to solve the ground-state problem of the Heisenberg spin model with an NMR quantum simulator. Our iterative phase estimation procedure yields a high accuracy for the eigenenergies (to the 10^-5 decimal digit). The ground-state fidelity was distilled to be more than 80%, and the singlet-to-triplet switching near the critical field is reliably captured. This result shows that quantum simulators can better leverage classical trial wavefunctions than classical computers.Comment: 11 pages, 13 figure

Role of macrophage sialoadhesin in host defense against the sialylated pathogen group B <em>Streptococcus</em>

ABSTRACT: Several bacterial pathogens decorate their surfaces with sialic acid (Sia) residues within cell wall components or capsular exopolysaccharides. Sialic acid expression can promote bacterial virulence by blocking complement activation or by engagement of inhibitory sialic acid-binding immunoglobulin-like lectins (Siglecs) on host leukocytes. Expressed at high levels on splenic and lymph node macrophages, sialoadhesin (Sn) is a unique Siglec with an elongated structure that lacks intracellular signaling motifs. Sialoadhesin allows macrophage to engage certain sialylated pathogens and stimulate inflammatory responses, but the in vivo significance of sialoadhesin in infection has not been shown. We demonstrate that macrophages phagocytose the sialylated pathogen group B Streptococcus (GBS) and increase bactericidal activity via sialoadhesin-sialic-acid-mediated recognition. Sialoadhesin expression on marginal zone metallophillic macrophages in the spleen trapped circulating GBS and restricted the spread of the GBS to distant organs, reducing mortality. Specific IgM antibody responses to GBS challenge were also impaired in sialoadhesin-deficient mice. Thus, sialoadhesin represents a key bridge to orchestrate innate and adaptive immune defenses against invasive sialylated bacterial pathogens. KEY MESSAGE: Sialoadhesin is critical for macrophages to phagocytose and clear GBS. Increased GBS organ dissemination in the sialoadhesin-deficient mice. Reduced anti-GBS IgM production in the sialoadhesin-deficient mice. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00109-014-1157-y) contains supplementary material, which is available to authorized users

Abnormalities in autonomic function in obese boys at-risk for insulin resistance and obstructive sleep apnea.

Study objectivesCurrent evidence in adults suggests that, independent of obesity, obstructive sleep apnea (OSA) can lead to autonomic dysfunction and impaired glucose metabolism, but these relationships are less clear in children. The purpose of this study was to investigate the associations among OSA, glucose metabolism, and daytime autonomic function in obese pediatric subjects.MethodsTwenty-three obese boys participated in: overnight polysomnography; a frequently sampled intravenous glucose tolerance test; and recordings of spontaneous cardiorespiratory data in both the supine (baseline) and standing (sympathetic stimulus) postures.ResultsBaseline systolic blood pressure and reactivity of low-frequency heart rate variability to postural stress correlated with insulin resistance, increased fasting glucose, and reduced beta-cell function, but not OSA severity. Baroreflex sensitivity reactivity was reduced with sleep fragmentation, but only for subjects with low insulin sensitivity and/or low first-phase insulin response to glucose.ConclusionsThese findings suggest that vascular sympathetic activity impairment is more strongly affected by metabolic dysfunction than by OSA severity, while blunted vagal autonomic function associated with sleep fragmentation in OSA is enhanced when metabolic dysfunction is also present

A novel isolator-based system promotes viability of human embryos during laboratory processing

In vitro fertilisation (IVF) and related technologies are arguably the most challenging of all cell culture applications. The starting material is a single cell from which one aims to produce an embryo capable of establishing a pregnancy eventually leading to a live birth. Laboratory processing during IVF treatment requires open manipulations of gametes and embryos, which typically involves exposure to ambient conditions. To reduce the risk of cellular stress, we have developed a totally enclosed system of interlinked isolator-based workstations designed to maintain oocytes and embryos in a physiological environment throughout the IVF process. Comparison of clinical and laboratory data before and after the introduction of the new system revealed that significantly more embryos developed to the blastocyst stage in the enclosed isolator-based system compared with conventional open-fronted laminar flow hoods. Moreover, blastocysts produced in the isolator-based system contained significantly more cells and their development was accelerated. Consistent with this, the introduction of the enclosed system was accompanied by a significant increase in the clinical pregnancy rate and in the proportion of embryos implanting following transfer to the uterus. The data indicate that protection from ambient conditions promotes improved development of human embryos. Importantly, we found that it was entirely feasible to conduct all IVF-related procedures in the isolator-based workstations

A globally consistent nonlinear least squares estimator for identification of nonlinear rational systems

© 2016 Elsevier Ltd This paper considers identification of nonlinear rational systems defined as the ratio of two nonlinear functions of past inputs and outputs. Despite its long history, a globally consistent identification algorithm remains illusive. This paper proposes a globally convergent identification algorithm for such nonlinear rational systems. To the best of our knowledge, this is the first globally convergent algorithm for the nonlinear rational systems. The technique employed is a two-step estimator. Though two-step estimators are known to produce consistent nonlinear least squares estimates if a N consistent estimate can be determined in the first step, how to find such a N consistent estimate in the first step for nonlinear rational systems is nontrivial and is not answered by any two-step estimators. The technical contribution of the paper is to develop a globally consistent estimator for nonlinear rational systems in the first step. This is achieved by involving model transformation, bias analysis, noise variance estimation, and bias compensation in the paper. Two simulation examples and a practical example are provided to verify the good performance of the proposed two-step estimator

A Genome-Wide Analysis of Promoter-Mediated Phenotypic Noise in Escherichia coli

Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as “phenotypic noise.” In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alon

Dispelling urban myths about default uncertainty factors in chemical risk assessment - Sufficient protection against mixture effects?

© 2013 Martin et al.; licensee BioMed Central LtdThis article has been made available through the Brunel Open Access Publishing Fund.Assessing the detrimental health effects of chemicals requires the extrapolation of experimental data in animals to human populations. This is achieved by applying a default uncertainty factor of 100 to doses not found to be associated with observable effects in laboratory animals. It is commonly assumed that the toxicokinetic and toxicodynamic sub-components of this default uncertainty factor represent worst-case scenarios and that the multiplication of those components yields conservative estimates of safe levels for humans. It is sometimes claimed that this conservatism also offers adequate protection from mixture effects. By analysing the evolution of uncertainty factors from a historical perspective, we expose that the default factor and its sub-components are intended to represent adequate rather than worst-case scenarios. The intention of using assessment factors for mixture effects was abandoned thirty years ago. It is also often ignored that the conservatism (or otherwise) of uncertainty factors can only be considered in relation to a defined level of protection. A protection equivalent to an effect magnitude of 0.001-0.0001% over background incidence is generally considered acceptable. However, it is impossible to say whether this level of protection is in fact realised with the tolerable doses that are derived by employing uncertainty factors. Accordingly, it is difficult to assess whether uncertainty factors overestimate or underestimate the sensitivity differences in human populations. It is also often not appreciated that the outcome of probabilistic approaches to the multiplication of sub-factors is dependent on the choice of probability distributions. Therefore, the idea that default uncertainty factors are overly conservative worst-case scenarios which can account both for the lack of statistical power in animal experiments and protect against potential mixture effects is ill-founded. We contend that precautionary regulation should provide an incentive to generate better data and recommend adopting a pragmatic, but scientifically better founded approach to mixture risk assessment. © 2013 Martin et al.; licensee BioMed Central Ltd.Oak Foundatio