Alcohol exposure impairs trophoblast survival and alters subtype-specific gene expression in vitro

Maternal alcohol consumption is common prior to pregnancy recognition and in the rat results in altered placental development and fetal growth restriction. To assess the effect of ethanol (EtOH) exposure on the differentiation of trophoblast stem (TS) cells, mouse TS lines were differentiated in vitro for 6 days in 0%, 0.2% or 1% EtOH. This reduced both trophoblast survival and expression of labyrinth and junctional zone trophoblast subtype-specific genes. This suggests that fetal growth restriction and altered placental development associated with maternal alcohol consumption in the periconceptional period could be mediated in part by direct effects on trophoblast development. (C) 2016 Elsevier Ltd. All rights reserved

Single Superfield Representation for Mixed Retarded and Advanced Correlators in Disordered Systems

We propose a new single superfield representation for mixed retarded and advanced correlators for noninteracting disordered systems. The method is tested in the simpler context of Random Matrix theory, by comparing with well known universal behavior for level spacing correlations. Our method is general and could be especially interesting to study localization properties encoded in the mixed correlators of Quantum Hall systems.Comment: 13 pages including two figures, RevTex4. Improved version. Figures changed. To appear in Journal of Physics

Comparative effectiveness and safety of low-strength and high-strength direct oral anticoagulants compared with warfarin: a sequential cohort study

OBJECTIVES:The aim of this study was to compare effectiveness and safety of low-strength and high-strength direct oral anticoagulants (DOACs) with warfarin in the Australian Veteran population. DESIGN:Sequential cohort study using inverse probability of treatment weighting (IPTW) and propensity score matching. Initiators of high-strength (apixaban 5 mg, dabigatran 150 mg, rivaroxaban 20 mg) and low-strength DOACS (apixaban 2.5 mg, dabigatran 110 mg, rivaroxaban 15 mg) were compared with warfarin initiators. SETTING:Australian Government Department of Veterans' Affairs claims database. PARTICIPANTS:4836 patients who initiated oral anticoagulants (45.8%, 26.0% and 28.2% on low-strength, high-strength DOACs and warfarin, respectively) between August 2013 and March 2015. Mean age was 85, 75 and 83 years for low-strength, high-strength DOACs and warfarin initiators, respectively. MAIN OUTCOME MEASURES:One-year risk of hospitalisation for ischaemic stroke, any bleeding event or haemorrhagic stroke. Secondary outcomes were 1-year risk of hospitalisation for myocardial infarction and death. RESULTS:Using the IPTW method, no difference in risk of ischaemic stroke or bleeding was found with low-strength DOACs compared with warfarin. As a class, no increased risk of myocardial infarction was found for low-strength DOACs, however, risk was elevated for apixaban (HR 2.25, 95% CI 1.23 to 4.13). For high-strength DOACs, no difference was found for ischaemic stroke compared with warfarin, however, there was a significant reduction in risk of bleeding events (HR 0.63, 95% CI 0.44 to 0.89) and death (HR 0.40, 95% CI 0.28 to 0.58). Propensity score matching showed no difference in risk of ischaemic stroke or bleeding. CONCLUSION:We found that in the practice setting both DOAC formulations were similar to warfarin with regard to effectiveness and had no increased risk of bleeding.Nicole L Pratt, Emmae Ramsay, Lisa M Kalisch Ellett, Katherine Duszynski, Sepehr Shakib, Mhairi Kerr, Gillian Caughey, Elizabeth Ellen Roughea

Bosonizing one-dimensional cold atomic gases

We present results for the long-distance asymptotics of correlation functions of mesoscopic one-dimensional systems with periodic and open (Dirichlet) boundary conditions, as well as at finite temperature in the thermodynamic limit. The results are obtained using Haldane's harmonic-fluid approach (also known as ``bosonization''), and are valid for both bosons and fermions, in weakly and strongly interacting regimes. The harmonic-fluid approach and the method to compute the correlation functions using conformal transformations are explained in great detail. As an application relevant to one-dimensional systems of cold atomic gases, we consider the model of bosons interacting with a zero-range potential. The Luttinger-liquid parameters are obtained from the exact solution by solving the Bethe-ansatz equations in finite-size systems. The range of applicability of the approach is discussed, and the prefactor of the one-body density matrix of bosons is fixed by finding an appropriate parametrization of the weak-coupling result. The formula thus obtained is shown to be accurate, when compared with recent diffusion Montecarlo calculations, within less than 10%. The experimental implications of these results for Bragg scattering experiments at low and high momenta are also discussed.Comment: 39 pages + 14 EPS figures; typos corrected, references update

Contemporary specificities of labour in the health care sector: introductory notes for discussion

BACKGROUND: This paper combines the literature on public health, on economics of health and on economics of technological innovation to discuss the peculiarities of labour in the health care sector. METHOD AND FRAMEWORK: The starting point is the investigation of the economic peculiarities of medical care. RESULTS AND DISCUSSIONS: This investigation leads to the identification of the prevalence of non-market forms of medical care in the countries of the Organisation for Economic Co-operation and Development (OECD). Furthermore, the health care system has a distinctive characteristic from other economic sectors: it is the intersection between social welfare and innovation systems. The relationship between technological innovation and cost in the health care sector is surveyed. Finally, the Brazilian case is discussed as an example of a developing country. CONCLUSION: The peculiarities of labour in the health care sector suggest the need to recognize the worth of sectoral labour and to cease to treat it separately. This process should take into account the rapid development of the health innovation system and one important consequence: the obsolescence of the acquired knowledge. One way to dignify labour is to implement continued education and training of health professions personnel

Age-Related Attenuation of Dominant Hand Superiority

The decline of motor performance of the human hand-arm system with age is well-documented. While dominant hand performance is superior to that of the non-dominant hand in young individuals, little is known of possible age-related changes in hand dominance. We investigated age-related alterations of hand dominance in 20 to 90 year old subjects. All subjects were unambiguously right-handed according to the Edinburgh Handedness Inventory. In Experiment 1, motor performance for aiming, postural tremor, precision of arm-hand movement, speed of arm-hand movement, and wrist-finger speed tasks were tested. In Experiment 2, accelerometer-sensors were used to obtain objective records of hand use in everyday activities

The Gaussian graphical model in cross-sectional and time-series data

We discuss the Gaussian graphical model (GGM; an undirected network of partial correlation coefficients) and detail its utility as an exploratory data analysis tool. The GGM shows which variables predict one-another, allows for sparse modeling of covariance structures, and may highlight potential causal relationships between observed variables. We describe the utility in 3 kinds of psychological datasets: datasets in which consecutive cases are assumed independent (e.g., cross-sectional data), temporally ordered datasets (e.g., n = 1 time series), and a mixture of the 2 (e.g., n > 1 time series). In time-series analysis, the GGM can be used to model the residual structure of a vector-autoregression analysis (VAR), also termed graphical VAR. Two network models can then be obtained: a temporal network and a contemporaneous network. When analyzing data from multiple subjects, a GGM can also be formed on the covariance structure of stationary means---the between-subjects network. We discuss the interpretation of these models and propose estimation methods to obtain these networks, which we implement in the R packages graphicalVAR and mlVAR. The methods are showcased in two empirical examples, and simulation studies on these methods are included in the supplementary materials.Comment: Accepted pending revision in Multivariate Behavioral Researc

p-Adic Mathematical Physics

A brief review of some selected topics in p-adic mathematical physics is presented.Comment: 36 page

Constraint-based probabilistic learning of metabolic pathways from tomato volatiles

Clustering and correlation analysis techniques have become popular tools for the analysis of data produced by metabolomics experiments. The results obtained from these approaches provide an overview of the interactions between objects of interest. Often in these experiments, one is more interested in information about the nature of these relationships, e.g., cause-effect relationships, than in the actual strength of the interactions. Finding such relationships is of crucial importance as most biological processes can only be understood in this way. Bayesian networks allow representation of these cause-effect relationships among variables of interest in terms of whether and how they influence each other given that a third, possibly empty, group of variables is known. This technique also allows the incorporation of prior knowledge as established from the literature or from biologists. The representation as a directed graph of these relationship is highly intuitive and helps to understand these processes. This paper describes how constraint-based Bayesian networks can be applied to metabolomics data and can be used to uncover the important pathways which play a significant role in the ripening of fresh tomatoes. We also show here how this methods of reconstructing pathways is intuitive and performs better than classical techniques. Methods for learning Bayesian network models are powerful tools for the analysis of data of the magnitude as generated by metabolomics experiments. It allows one to model cause-effect relationships and helps in understanding the underlying processes