Revascularization in Severe Left Ventricular Dysfunction

AbstractThe highest-risk patients with heart failure with reduced ejection fraction are those with ischemic cardiomyopathy and severe left ventricular systolic dysfunction (ejection fraction ≤35%). The cornerstone of treatment is guideline-driven medical therapy for all patients and implantable device therapy for appropriately selected patients. Surgical revascularization offers the potential for improved survival and quality of life, particularly in patients with more extensive multivessel disease and the greatest degree of left ventricular systolic dysfunction and remodeling. These are also the patients at greatest short-term risk of mortality with coronary artery bypass graft surgery. The short-term risks of surgery need to be balanced against the potential for long-term benefit. This review discusses the evolving data on the role of surgical revascularization, surgical ventricular reconstruction, and mitral valve surgery in this high-risk patient population

A unified framework based on the binding polynomial for characterizing biological systems by isothermal titration calorimetry

Isothermal titration calorimetry (ITC) has become the gold-standard technique for studying binding processes due to its high precision and sensitivity, as well as its capability for the simultaneous determination of the association equilibrium constant, the binding enthalpy and the binding stoichiometry. The current widespread use of ITC for biological systems has been facilitated by technical advances and the availability of commercial calorimeters. However, the complexity of data analysis for non-standard models is one of the most significant drawbacks in ITC. Many models for studying macromolecular interactions can be found in the literature, but it looks like each biological system requires specific modeling and data analysis approaches. The aim of this article is to solve this lack of unity and provide a unified methodological framework for studying binding interactions by ITC that can be applied to any experimental system. The apparent complexity of this methodology, based on the binding polynomial, is overcome by its easy generalization to complex systems

Predicting approximate seismic responses in multistory buildings from real-time earthquake source information, for earthquake early warning applications

Regional earthquake early warning (EEW) alerts and related risk-mitigation actions are often triggered when the expected value of a ground-motion intensity measure (IM), computed from real-time magnitude and source location estimates, exceeds a predefined critical IM threshold. However, the shaking experienced in mid- to high-rise buildings may be significantly different from that on the ground, which could lead to sub-optimal decision-making (i.e., increased occurrences of false and missed EEW alarms) with the aforementioned strategy. This study facilitates an important advancement in EEW decision-support, by developing empirical models that directly relate earthquake source parameters to resulting approximate responses in multistory buildings. The proposed models can leverage real-time earthquake information provided by a regional EEW system, to provide rapid predictions of structure-specific engineering demand parameters that can be used to more accurately determine whether or not an alert is triggered. We use a simplified continuum building model consisting of a flexural/shear beam combination and vary its parameters to capture a wide range of deformation modes in different building types. We analyse the approximate responses for the building model variations, using Italian accelerometric data and corresponding source parameter information from 54 earthquakes. The resulting empirical prediction equations are incorporated in a real-time Bayesian framework that can be used for building-specific EEW applications, such as (1) early warning of floor-shaking sensed by occupants; and (2) elevator control. Finally, we demonstrate the improvement in EEW alert accuracy that can be achieved using the proposed models

A Review of the Technical and Socio-Organizational Components of Earthquake Early Warning Systems

Every year, natural hazards affect millions of people around the world, causing significant economic and life losses. The rapid progress of technology and advances in understanding of the highly complex physical phenomena related to various natural hazards have promoted the development of new disaster-mitigation tools, such as earthquake early warning (EEW) systems. However, there is a general lack of integration between the multi- and cross-disciplinary elements of EEW, limiting its effectiveness and applications for end users. This paper reviews the current state-of-the-art in EEW, exploring both the technical components (i.e., seismological and engineering) as well as the socio-organizational components (i.e., social science, policy, and management) of EEW systems. This includes a discussion of specific evidence from case studies of Italy, United States’ West Coast, Japan, and Mexico, where EEW systems have reached varying levels of maturity. Our aim is to highlight necessary improvements for increasing the effectiveness of the technical aspects of EEW in terms of their implications on operational, political/legal, social, behavioral, and organizational drivers. Our analysis suggests open areas for research, associated with: 1) the information that needs to be included in EEW alerts to implement successful mitigation actions at both individual and organizational levels; 2) the need for response training to the community by official bodies, such as civil protection; 3) existing gaps in the attribution of accountability and development of liability policies involving EEW implementation; 4) the potential for EEW to increase seismic resilience of critical infrastructure and lifelines; 5) the need for strong organizational links with first responders and official EEW bodies; and 6) the lack of engineering-related (i.e., risk and resilience) metrics currently used to support decision making related to the triggering of alerts by various end users

Allosteric Inhibitors of the NS3 Protease from the Hepatitis C Virus

The nonstructural protein 3 (NS3) from the hepatitis C virus processes the non-structural region of the viral precursor polyprotein in infected hepatic cells. The NS3 protease activity has been considered a target for drug development since its identification two decades ago. Although specific inhibitors have been approved for clinical therapy very recently, resistance-associated mutations have already been reported for those drugs, compromising their long-term efficacy. Therefore, there is an urgent need for new anti-HCV agents with low susceptibility to resistance-associated mutations. Regarding NS3 protease, two strategies have been followed: competitive inhibitors blocking the active site and allosteric inhibitors blocking the binding of the accessory viral protein NS4A. In this work we exploit the intrinsic Zn+2-regulated plasticity of the protease to identify a new type of allosteric inhibitors. In the absence of Zn+2, the NS3 protease adopts a partially-folded inactive conformation. We found ligands binding to the Zn+2-free NS3 protease, trap the inactive protein, and block the viral life cycle. The efficacy of these compounds has been confirmed in replicon cell assays. Importantly, direct calorimetric assays reveal a low impact of known resistance-associated mutations, and enzymatic assays provide a direct evidence of their inhibitory activity. They constitute new low molecular-weight scaffolds for further optimization and provide several advantages: 1) new inhibition mechanism simultaneously blocking substrate and cofactor interactions in a non-competitive fashion, appropriate for combination therapy; 2) low impact of known resistance-associated mutations; 3) inhibition of NS4A binding, thus blocking its several effects on NS3 protease

The right hippocampus leads the bilateral integration of gamma-parsed lateralized information

It is unclear whether the two hippocampal lobes convey similar or different activities and how they cooperate. Spatial discrimination of electric fields in anesthetized rats allowed us to compare the pathway-specific field potentials corresponding to the gamma-paced CA3 output (CA1 Schaffer potentials) and CA3 somatic inhibition within and between sides. Bilateral excitatory Schaffer gamma waves are generally larger and lead from the right hemisphere with only moderate covariation of amplitude, and drive CA1 pyramidal units more strongly than unilateral waves. CA3 waves lock to the ipsilateral Schaffer potentials, although bilateral coherence was weak. Notably, Schaffer activity may run laterally, as seen after the disruption of the connecting pathways. Thus, asymmetric operations promote the entrainment of CA3-autonomous gamma oscillators bilaterally, synchronizing lateralized gamma strings to converge optimally on CA1 targets. The findings support the view that interhippocampal connections integrate different aspects of information that flow through the left and right lobes

Fluctuation geometry: A counterpart approach of inference geometry

Starting from an axiomatic perspective, \emph{fluctuation geometry} is developed as a counterpart approach of inference geometry. This approach is inspired on the existence of a notable analogy between the general theorems of \emph{inference theory} and the the \emph{general fluctuation theorems} associated with a parametric family of distribution functions $dp(I|\theta)=\rho(I|\theta)dI$, which describes the behavior of a set of \emph{continuous stochastic variables} driven by a set of control parameters $\theta$. In this approach, statistical properties are rephrased as purely geometric notions derived from the \emph{Riemannian structure} on the manifold $\mathcal{M}_{\theta}$ of stochastic variables $I$. Consequently, this theory arises as an alternative framework for applying the powerful methods of differential geometry for the statistical analysis. Fluctuation geometry has direct implications on statistics and physics. This geometric approach inspires a Riemannian reformulation of Einstein fluctuation theory as well as a geometric redefinition of the information entropy for a continuous distribution.Comment: Version submitted to J. Phys. A. 26 pages + 2 eps figure