Haemodynamic Benefit of Cardiac Resynchronisation Therapy Requires Left Bundle Branch Block: A Case Report

A 55-year-old woman with dilated cardiomyopathy and rate-dependent left bundle branch block had a cardiac resynchronisation therapy (CRT) device implanted. During implantation, the maximum rate of left ventricular pressure rise (dP/dtmax) was measured invasively. This case presents a description of the acute negative effect of a left bundle branch block on dP/dtmax, and the different effect of CRT on left ventricular haemodynamic function in the presence and absence of a left bundle branch block

A semi-Markov model for stroke with piecewise-constant hazards in the presence of left, right and interval censoring.

This paper presents a parametric method of fitting semi-Markov models with piecewise-constant hazards in the presence of left, right and interval censoring. We investigate transition intensities in a three-state illness-death model with no recovery. We relax the Markov assumption by adjusting the intensity for the transition from state 2 (illness) to state 3 (death) for the time spent in state 2 through a time-varying covariate. This involves the exact time of the transition from state 1 (healthy) to state 2. When the data are subject to left or interval censoring, this time is unknown. In the estimation of the likelihood, we take into account interval censoring by integrating out all possible times for the transition from state 1 to state 2. For left censoring, we use an Expectation-Maximisation inspired algorithm. A simulation study reflects the performance of the method. The proposed combination of statistical procedures provides great flexibility. We illustrate the method in an application by using data on stroke onset for the older population from the UK Medical Research Council Cognitive Function and Ageing Study

Bayesian inference of biochemical kinetic parameters using the linear noise approximation

Background Fluorescent and luminescent gene reporters allow us to dynamically quantify changes in molecular species concentration over time on the single cell level. The mathematical modeling of their interaction through multivariate dynamical models requires the deveopment of effective statistical methods to calibrate such models against available data. Given the prevalence of stochasticity and noise in biochemical systems inference for stochastic models is of special interest. In this paper we present a simple and computationally efficient algorithm for the estimation of biochemical kinetic parameters from gene reporter data. Results We use the linear noise approximation to model biochemical reactions through a stochastic dynamic model which essentially approximates a diffusion model by an ordinary differential equation model with an appropriately defined noise process. An explicit formula for the likelihood function can be derived allowing for computationally efficient parameter estimation. The proposed algorithm is embedded in a Bayesian framework and inference is performed using Markov chain Monte Carlo. Conclusion The major advantage of the method is that in contrast to the more established diffusion approximation based methods the computationally costly methods of data augmentation are not necessary. Our approach also allows for unobserved variables and measurement error. The application of the method to both simulated and experimental data shows that the proposed methodology provides a useful alternative to diffusion approximation based methods

Criminal and Noncriminal Psychopathy: The Devil is in the Detail

Brooks, NS ORCiD: 0000-0003-1784-099XPsychopathy is prevalent and problematic in criminal populations, but is also found to be present in noncriminal populations. In 1992, Robert Hare declared that psychopaths may also “be found in the boardroom”, which has since been followed by an interest in the issue of noncriminal, or even successful, psychopathy. In this chapter, the paradox of criminal and noncriminal psychopathy is discussed with specific attention given to the similarities and differences that account for psychopathic personality across contexts. That psychopathy is a condition typified by a constellation of traits and behaviours requires wider research across diverse populations, and thus the streams of research related to criminal and noncriminal psychopathy are presented and the implications of these contrasting streams are explored

Two-dimensional Vortices in Superconductors

Superconductors have two key characteristics. They expel magnetic field and they conduct electrical current with zero resistance. However, both properties are compromised in high magnetic fields which can penetrate the material and create a mixed state of quantized vortices. The vortices move in response to an electrical current dissipating energy which destroys the zero resistance state\cite{And64}. One of the central problems for applications of high temperature superconductivity is the stabilization of vortices to ensure zero electrical resistance. We find that vortices in the anisotropic superconductor Bi$_{2}$Sr$_{2}$CaCu$_{2}$O$_{8+\delta}$ (Bi-2212) have a phase transition from a liquid state, which is inherently unstable, to a two-dimensional vortex solid. We show that at high field the transition temperature is independent of magnetic field, as was predicted theoretically for the melting of an ideal two-dimensional vortex lattice\cite{Fis80,Gla91}. Our results indicate that the stable solid phase can be reached at any field as may be necessary for applications involving superconducting magnets\cite{Has04,Sca04,COHMAG}. The vortex solid is disordered, as suggested by previous studies at lower fields\cite{Lee93,Cub93}. But its evolution with increasing magnetic field displays unexpected threshold behavior that needs further investigation.Comment: 5 pages and 4 figures. submitted to Nature Physic

Maternal effects on anogenital distance in a wild marmot population

Peer reviewedPublisher PD

An association between K65R and HIV-1 subtype C viruses in patients treated with multiple NRTIs

Objectives: HIV-1 subtype C might have a greater propensity to develop K65R mutations in patients with virological failure compared with other subtypes. However, the strong association between viral subtype and confounding factors such as exposure groups and ethnicity affects the calculation of this propensity. We exploited the diversity of viral subtypes within the UK to undertake a direct comparative analysis. Patients and methods: We analysed only sequences with major IAS-defined mutations from patients with virological failure. Prevalence of K65R was related to subtype and exposure to the NRTIs that primarily select for this mutation (tenofovir, abacavir, didanosine and stavudine). A multivariate logistic regression model quantified the effect of subtype on the prevalence of K65R, adjusting for previous and current exposure to all four specified drugs. Results: Subtype B patients ( n  =   3410) were mostly MSM (78%) and those with subtype C ( n  =   810) were mostly heterosexual (82%). K65R was detected in 7.8% of subtype B patients compared with 14.2% of subtype C patients. The subtype difference in K65R prevalence was observed irrespective of NRTI exposure and K65R was frequently selected by abacavir, didanosine and stavudine in patients with no previous exposure to tenofovir. Multivariate logistic regression confirmed that K65R was significantly more common in subtype C viruses (adjusted OR = 2.02, 95% CI = 1.55-2.62, P  <   0.001). Conclusions: Patients with subtype C HIV-1 have approximately double the frequency of K65R in our database compared with other subtypes. The exact clinical implications of this finding need to be further elucidated

Protein structure prediction using multiple deep neural networks in the 13th Critical Assessment of Protein Structure Prediction (CASP13)

We describe AlphaFold, the protein structure prediction system that was entered by the group A7D in CASP13 Submissions were made by three free-modelling methods which combine the predictions of three neural networks. All three systems were guided by predictions of distances between pairs of residues produced by a neural network. Two systems assembled fragments produced by a generative neural network, one using scores from a network trained to regress GDT_TS. The third system shows that simple gradient descent on a properly constructed potential is able to perform on-par with more expensive traditional search techniques and without requiring domain segmentation. In the CASP13 free-modelling assessors' ranking by summed z-scores, this system scored highest with 68.3 vs 48.2 for the next closest group. (An average GDT_TS of 61.4.) The system produced high-accuracy structures (with GDT_TS scores of 70 or higher) for 11 out of 43 free-modelling domains. Despite not explicitly using template information, the results in the template category were comparable to the best performing template-based methods

Thermodynamics of Holographic Defects

Using the AdS/CFT correspondence, we study the thermodynamic properties and the phase diagram of matter fields on (2+1)-dimensional defects coupled to a (3+1)-dimensional N=4 SYM "heat bath". Considering a background magnetic field, (net) quark density, defect "magnitude" $\delta N_c$ and the mass of the matter, we study the defect contribution to the thermodynamic potentials and their first and second derivatives to map the phases and study their physical properties. We find some features that are qualitatively similar to other systems e.g. in (3+1) dimensions and a number of features that are particular to the defect nature, such as its magnetic properties, unexpected properties at T->0 and finite density; and the finite $\delta N_c$ effects, e.g. a diverging susceptibility and vanishing density of states at small temperatures, a physically consistent negative heat capacity and new types of consistent phases.Comment: 33 pages, 16 figures (jpg and pdf), typos fixed and references added, final version published in JHE