Update on Membranoproliferative GN

Membranoproliferative GN represents a pattern of injury seen on light microscopy. Historically, findings on electron microscopy have been used to further subclassify this pathologic entity. Recent advances in understanding of the underlying pathobiology have led to a proposed classification scheme based on immunofluorescence findings. Dysregulation of the complement system has been shown to be a major risk factor for the development of a membranoproliferative GN pattern of injury on kidney biopsy. Evaluation and treatment of this complex disorder rest on defining the underlying mechanisms

A systematic approach to echocardiography in hypertrophic cardiomyopathy: a guideline protocol from the British Society of Echocardiography.

Hypertrophic cardiomyopathy (HCM) is a relatively common inherited cardiac condition with a prevalence of approximately one in 500. It results in otherwise unexplained hypertrophy of the myocardium and predisposes the patient to a variety of disease-related complications including sudden cardiac death. Echocardiography is of vital importance in the diagnosis, assessment and follow-up of patients with known or suspected HCM. The British Society of Echocardiography (BSE) has previously published a minimum dataset for transthoracic echocardiography, providing the core parameters necessary when performing a standard echocardiographic study. However, for patients with known or suspected HCM, additional views and measurements are necessary. These additional views allow more subtle abnormalities to be detected or may provide important information in order to identify patients with an adverse prognosis. The aim of this Guideline is to outline the additional images and measurements that should be obtained when performing a study on a patient with known or suspected HCM

The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference

Background: Wiener-Granger causality (“G-causality”) is a statistical notion of causality applicable to time series data, whereby cause precedes, and helps predict, effect. It is defined in both time and frequency domains, and allows for the conditioning out of common causal influences. Originally developed in the context of econometric theory, it has since achieved broad application in the neurosciences and beyond. Prediction in the G-causality formalism is based on VAR (Vector AutoRegressive) modelling. New Method: The MVGC Matlab c Toolbox approach to G-causal inference is based on multiple equivalent representations of a VAR model by (i) regression parameters, (ii) the autocovariance sequence and (iii) the cross-power spectral density of the underlying process. It features a variety of algorithms for moving between these representations, enabling selection of the most suitable algorithms with regard to computational efficiency and numerical accuracy. Results: In this paper we explain the theoretical basis, computational strategy and application to empirical G-causal inference of the MVGC Toolbox. We also show via numerical simulations the advantages of our Toolbox over previous methods in terms of computational accuracy and statistical inference. Comparison with Existing Method(s): The standard method of computing G-causality involves estimation of parameters for both a full and a nested (reduced) VAR model. The MVGC approach, by contrast, avoids explicit estimation of the reduced model, thus eliminating a source of estimation error and improving statistical power, and in addition facilitates fast and accurate estimation of the computationally awkward case of conditional G-causality in the frequency domain. Conclusions: The MVGC Toolbox implements a flexible, powerful and efficient approach to G-causal inference. Keywords: Granger causality, vector autoregressive modelling, time series analysi

Dynamics of Simple Balancing Models with State Dependent Switching Control

Time-delayed control in a balancing problem may be a nonsmooth function for a variety of reasons. In this paper we study a simple model of the control of an inverted pendulum by either a connected movable cart or an applied torque for which the control is turned off when the pendulum is located within certain regions of phase space. Without applying a small angle approximation for deviations about the vertical position, we see structurally stable periodic orbits which may be attracting or repelling. Due to the nonsmooth nature of the control, these periodic orbits are born in various discontinuity-induced bifurcations. Also we show that a coincidence of switching events can produce complicated periodic and aperiodic solutions.Comment: 36 pages, 12 figure

Phylogenetic groups and cephalosporin resistance genes of Escherichia coli from diseased food-producing animals in Japan

A total of 318 Escherichia coli isolates obtained from different food-producing animals affected with colibacillosis between 2001 and 2006 were subjected to phylogenetic analysis: 72 bovine isolates, 89 poultry isolates and 157 porcine isolates. Overall, the phylogenetic group A was predominant in isolates from cattle (36/72, 50%) and pigs (101/157, 64.3%) whereas groups A (44/89, 49.4%) and D (40/89, 44.9%) were predominant in isolates from poultry. In addition, group B2 was not found among diseased food-producing animals except for a poultry isolate. Thus, the phylogenetic group distribution of E. coli from diseased animals was different by animal species. Among the 318 isolates, cefazolin resistance (minimum inhibitory concentrations: ≥32 μg/ml) was found in six bovine isolates, 29 poultry isolates and three porcine isolates. Of them, 11 isolates (nine from poultry and two from cattle) produced extended spectrum β-lactamase (ESBL). The two bovine isolates produced blaCTX-M-2, while the nine poultry isolates produced blaCTX-M-25 (4), blaSHV-2 (3), blaCTX-M-15 (1) and blaCTX-M-2 (1). Thus, our results showed that several types of ESBL were identified and three types of β-lactamase (SHV-2, CTX-M-25 and CTX-M-15) were observed for the first time in E. coli from diseased animals in Japan

New high precision orbital and physical parameters of the double-lined low-mass spectroscopic binary BY Draconis

We present the most precise to date orbital and physical parameters of the well known short period (P=5.975 d), eccentric (e=0.3) double-lined spectroscopic binary BY Draconis, a prototype of a class of late-type, active, spotted flare stars. We calculate the full spectroscopic/astrometric orbital solution by combining our precise radial velocities (RVs) and the archival astrometric measurements from the Palomar Testbed Interferometer (PTI). The RVs were derived based on the high resolution echelle spectra taken between 2004 and 2008 with the Keck I/HIRES, Shane/CAT/HamSpec and TNG/SARG telescopes/spectrographs using our novel iodine-cell technique for double-lined binary stars. The RVs and available PTI astrometric data spanning over 8 years allow us to reach 0.2-0.5% level of precision in M sin3(i) and the parallax but the geometry of the orbit (i=154 deg) hampers the absolute mass precision to 3.3%, which is still an order of magnitude better than for previous studies. We compare our results with a set of Yonsei-Yale theoretical stellar isochrones and conclude that BY Dra is probably a main sequence system more metal-rich than the Sun. Using the orbital inclination and the available rotational velocities of the components, we also conclude that the rotational axes of the components are likely misaligned with the orbital angular momentum. Given BY Dra's main sequence status, late spectral type and the relatively short orbital period, its high orbital eccentricity and probable spin-orbit misalignment are not in agreement with the tidal theory. This disagreement may possibly be explained by smaller rotational velocities of the components and the presence of a substellar mass companion to BY Dra AB.Comment: 10 pages, 7 figures, 4 tables, to appear in MNRA

A minimum dataset for a standard adult transthoracic echocardiogram: a guideline protocol from the British Society of Echocardiography.

There have been significant advances in the field of echocardiography with the introduction of a number of new techniques into standard clinical practice. Consequently, a 'standard' echocardiographic examination has evolved to become a more detailed and time-consuming examination that requires a high level of expertise. This Guideline produced by the British Society of Echocardiography (BSE) Education Committee aims to provide a minimum dataset that should be obtained in a comprehensive standard echocardiogram. In addition, the layout proposes a recommended sequence in which to acquire the images. If abnormal pathology is detected, additional views and measurements should be obtained with reference to other BSE protocols when appropriate. Adherence to these recommendations will promote an increased quality of echocardiography and facilitate accurate comparison of studies performed either by different operators or at different departments

Detectability of Granger causality for subsampled continuous-time neurophysiological processes

Background: Granger causality is well established within the neurosciences for inference of directed functional connectivity from neurophysiological data. These data usually consist of time series which subsample a continuous-time biophysiological process. While it is well known that subsampling can lead to imputation of spurious causal connections where none exist, less is known about the effects of subsampling on the ability to reliably detect causal connections which do exist. New Method: We present a theoretical analysis of the effects of subsampling on Granger-causal inference. Neurophysiological processes typically feature signal propagation delays on multiple time scales; accordingly, we base our analysis on a distributed-lag, continuous-time stochastic model, and consider Granger causality in continuous time at finite prediction horizons. Via exact analytical solutions, we identify relationships among sampling frequency, underlying causal time scales and detectability of causalities. Results: We reveal complex interactions between the time scale(s) of neural signal propagation and sampling frequency. We demonstrate that detectability decays exponentially as the sample time interval increases beyond causal delay times, identify detectability “black spots” and “sweet spots”, and show that downsampling may potentially improve detectability. We also demonstrate that the invariance of Granger causality under causal, invertible filtering fails at finite prediction horizons, with particular implications for inference of Granger causality from fMRI data. Comparison with Existing Method(s): Our analysis emphasises that sampling rates for causal analysis of neurophysiological time series should be informed by domain-specific time scales, and that state-space modelling should be preferred to purely autoregressive modelling. Conclusions: On the basis of a very general model that captures the structure of neurophysiological processes, we are able to help identify confounds, and other practical insights, for successful detection of causal connectivity from neurophysiological recordings