On the emergence of the Λ{\bf\Lambda}CDM model from self-interacting Brans-Dicke theory in d=5{\bf d= 5}

We investigate whether a self-interacting Brans-Dicke theory in $d=5$ without matter and with a time-dependent metric can describe, after dimensional reduction to $d=4$, the FLRW model with accelerated expansion and non-relativistic matter. By rewriting the effective 4-dimensional theory as an autonomous three-dimensional dynamical system and studying its critical points, we show that the $\Lambda$CDM cosmology cannot emerge from such a model. This result suggests that a richer structure in $d=5$ may be needed to obtain the accelerated expansion as well as the matter content of the 4-dimensional universe.Comment: 7 pages, 7 figure

RNA Sequencing Reveals Novel Transcripts from Sympathetic Stellate Ganglia During Cardiac Sympathetic Hyperactivity.

Cardiovascular disease is the most prevalent age-related illness worldwide, causing approximately 15 million deaths every year. Hypertension is central in determining cardiovascular risk and is a strong predictive indicator of morbidity and mortality; however, there remains an unmet clinical need for disease-modifying and prophylactic interventions. Enhanced sympathetic activity is a well-established contributor to the pathophysiology of hypertension, however the cellular and molecular changes that increase sympathetic neurotransmission are not known. The aim of this study was to identify key changes in the transcriptome in normotensive and spontaneously hypertensive rats. We validated 15 of our top-scoring genes using qRT-PCR, and network and enrichment analyses suggest that glutamatergic signalling plays a key role in modulating Ca2+ balance within these ganglia. Additionally, phosphodiesterase activity was found to be altered in stellates obtained from the hypertensive rat, suggesting that impaired cyclic nucleotide signalling may contribute to disturbed Ca2+ homeostasis and sympathetic hyperactivity in hypertension. We have also confirmed the presence of these transcripts in human donor stellate samples, suggesting that key genes coupled to neurotransmission are conserved. The data described here may provide novel targets for future interventions aimed at treating sympathetic hyperactivity associated with cardiovascular disease and other dysautonomias

Increased baseline ECG R-R dispersion predicts improvement in systolic function after atrial fibrillation ablation.

BackgroundAtrial fibrillation (AF) is associated with left ventricular (LV) systolic dysfunction which may improve after AF ablation. We hypothesised that increased ventricular irregularity, as measured by R-R dispersion on the baseline ECG, would predict improvement in the left ventricular ejection fraction (LVEF) after AF ablation.MethodsPatients with LVEF <50% at two US centres (2007-2016), having both a preablation and postablation echocardiogram or cardiac MRI, were included. LVEF improvement was defined as absolute increase in LVEF by >7.5%. Multivariable logistic regression (restricted to echocardiographic/ECG variables) was performed to evaluate predictors of LVEF improvement.ResultsFifty-two patients were included in this study. LVEF improved in 30 patients (58%) and was unchanged/worsened in 22 patients (42%). Those with versus without LVEF improvement had an increased baseline R-R dispersion (645±155 ms vs 537±154 ms, p=0.02, respectively). The average baseline heart rate in all patients was 93 beats per minute. After multivariable logistic regression, increased R-R dispersion (OR 1.59, 95% CI 1.00 to 2.55, p=0.03) predicted LVEF improvement.ConclusionsIncreased R-R dispersion on ECG was independently associated with improved systolic function after AF ablation. This broadens the existing knowledge of arrhythmia-induced cardiomyopathy, demonstrating that irregular electrical activation (as measured by increased R-R dispersion on ECG) is associated with a cardiomyopathy capable of improving after AF ablation

Monomorphic Ventricular Arrhythmias in Athletes.

Ventricular arrhythmias are challenging to manage in athletes with concern for an elevated risk of sudden cardiac death (SCD) during sports competition. Monomorphic ventricular arrhythmias (MMVA), while often benign in athletes with a structurally normal heart, are also associated with a unique subset of idiopathic and malignant substrates that must be clearly defined. A comprehensive evaluation for structural and/or electrical heart disease is required in order to exclude cardiac conditions that increase risk of SCD with exercise, such as hypertrophic cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy. Unique issues for physicians who manage this population include navigating athletes through the decision of whether they can safely continue their chosen sport. In the absence of structural heart disease, therapies such as radiofrequency catheter ablation are very effective for certain arrhythmias and may allow for return to competitive sports participation. In this comprehensive review, we summarise the recommendations for evaluating and managing athletes with MMVA

Mining the Mind Research Network: A Novel Framework for Exploring Large Scale, Heterogeneous Translational Neuroscience Research Data Sources

A neuroinformatics (NI) system is critical to brain imaging research in order to shorten the time between study conception and results. Such a NI system is required to scale well when large numbers of subjects are studied. Further, when multiple sites participate in research projects organizational issues become increasingly difficult. Optimized NI applications mitigate these problems. Additionally, NI software enables coordination across multiple studies, leveraging advantages potentially leading to exponential research discoveries. The web-based, Mind Research Network (MRN), database system has been designed and improved through our experience with 200 research studies and 250 researchers from seven different institutions. The MRN tools permit the collection, management, reporting and efficient use of large scale, heterogeneous data sources, e.g., multiple institutions, multiple principal investigators, multiple research programs and studies, and multimodal acquisitions. We have collected and analyzed data sets on thousands of research participants and have set up a framework to automatically analyze the data, thereby making efficient, practical data mining of this vast resource possible. This paper presents a comprehensive framework for capturing and analyzing heterogeneous neuroscience research data sources that has been fully optimized for end-users to perform novel data mining

Influence of supramolecular forces on the linear viscoelasticity of gluten

Stress relaxation behavior of hydrated gluten networks was investigated by means of rheometry combined with μ-computed tomography (μ-CT) imaging. Stress relaxation behavior was followed over a wide temperature range (0–70 °C). Modulation of intermolecular bonds was achieved with urea or ascorbic acid in an effort to elucidate the presiding intermolecular interactions over gluten network relaxation. Master curves of viscoelasticity were constructed, and relaxation spectra were computed revealing three relaxation regimes for all samples. Relaxation commences with a well-defined short-time regime where Rouse-like modes dominate, followed by a power law region displaying continuous relaxation concluding in a terminal zone. In the latter zone, poroelastic relaxation due to water migration in the nanoporous structure of the network also contributes to the stress relief in the material. Hydrogen bonding between adjacent protein chains was identified as the determinant force that influences the relaxation of the networks. Changes in intermolecular interactions also resulted in changes in microstructure of the material that was also linked to the relaxation behavior of the networks

A Single Cell Transcriptomics Map of Paracrine Networks in the Intrinsic Cardiac Nervous System

We developed a spatially-tracked single neuron transcriptomics map of an intrinsic cardiac ganglion, the right atrial ganglionic plexus (RAGP) that is a critical mediator of sinoatrial node (SAN) activity. This 3D representation of RAGP used neuronal tracing to extensively map the spatial distribution of the subset of neurons that project to the SAN. RNA-seq of laser capture microdissected neurons revealed a distinct composition of RAGP neurons compared to the central nervous system and a surprising finding that cholinergic and catecholaminergic markers are coexpressed, suggesting multipotential phenotypes that can drive neuroplasticity within RAGP. High-throughput qPCR of hundreds of laser capture microdissected single neurons confirmed these findings and revealed a high dimensionality of neuromodulatory factors that contribute to dynamic control of the heart. Neuropeptide-receptor coexpression analysis revealed a combinatorial paracrine neuromodulatory network within RAGP informing follow-on studies on the vagal control of RAGP to regulate cardiac function in health and disease