NPY and cardiac diseases

Hypertension-induced left ventricular hypertrophy (LVH), along with ischemic heart disease, result in LV remodeling as part of a continuum that often leads to congestive heart failure. The neurohormonal model has been used to underpin many treatment strategies, but optimal outcomes have not been achieved. Neuropeptide Y (NPY) has emerged as an additional therapeutic target, ever since it was recognised as an important mediator released from sympathetic nerves in the heart, affecting coronary artery constriction and myocardial contraction. More recent interest has focused on the mitogenic and hypertrophic effects that are observed in endothelial and vascular smooth muscle cells, and cardiac myocytes. Of the six identified NPY receptor subtypes, Y-1, Y-2, and Y-5 appear to mediate the main functional responses in the heart. Plasma levels of NPY become elevated due to the increased sympathetic activation present in stress-related cardiac conditions. Also, NPY and Y receptor polymorphisms have been identified that may predispose individuals to increased risk of hypertension and cardiac complications. This review examines what understanding exists regarding the likely contribution of NPY to cardiac pathology. It appears that NPY may play a part in compensatory or detrimental remodeling of myocardial tissue subsequent to hemodynamic overload or myocardial infarction, and in angiogenic processes to regenerate myocardium after ischemic injury. However, greater mechanistic information is required in order to truly assess the potential for treatment of cardiac diseases using NPY-based drugs.

Improved conjugate gradient implementation for least squares support vector machines

As a promising method for pattern recognition and function estimation, least squares support vector machines (LS-SVM) express the training in terms of solving a linear system instead of a quadratic programming problem as for conventional support vector machines (SVM). In this paper, by using the information provided by the equality constraint, we transform the minimization problem with a single equality constraint in LS-SVM into an unconstrained minimization problem, then propose reduced formulations for LS-SVM. By introducing this transformation, the times of using conjugate gradient (CG) method, which is a greatly time-consuming step in obtaining the numerical solution, are reduced to one instead of two as proposed by Suykens et al. (1999). The comparison on computational speed of our method with the CG method proposed by Suykens et al. and the first order and second order SMO methods on several benchmark data sets shows a reduction of training time by up to 44%. (C) 2011 Elsevier B.V. All rights reserved.

Secondary prevention in the clinical management of patients with cardiovascular diseases. Core components, standards and outcome measures for referral and delivery.

Despite major improvements in diagnostics and interventional therapies, cardiovascular diseases remain a major health care and socio-economic burden both in western and developing countries, in which this burden is increasing in close correlation to economic growth. Health authorities and the general population have started to recognize that the fight against these diseases can only be won if their burden is faced by increasing our investment on interventions in lifestyle changes and prevention. There is an overwhelming evidence of the efficacy of secondary prevention initiatives including cardiac rehabilitation in terms of reduction in morbidity and mortality. However, secondary prevention is still too poorly implemented in clinical practice, often only on selected populations and over a limited period of time. The development of systematic and full comprehensive preventive programmes is warranted, integrated in the organization of national health systems. Furthermore, systematic monitoring of the process of delivery and outcomes is a necessity. Cardiology and secondary prevention, including cardiac rehabilitation, have evolved almost independently of each other and although each makes a unique contribution it is now time to join forces under the banner of preventive cardiology and create a comprehensive model that optimizes long term outcomes for patients and reduces the future burden on health care services. These are the aims that the Cardiac Rehabilitation Section of the European Association for Cardiovascular Prevention & Rehabilitation has foreseen to promote secondary preventive cardiology in clinical practice.

An expression vector containing a rhamnose-inducible promoter provides tightly regulated gene expression in Burkholderia cenocepacia

Infection of the respiratory tract caused by Burkholderia cepacia complex poses a serious risk for cystic fibrosis (CF) patients due to the high morbidity and mortality associated with the chronic infection and the lack of efficacious antimicrobial treatments. A detailed understanding of the pathogenicity of B. cepacia complex infections is hampered in part by the limited availability of genetic tools and the inherent resistance of these isolates to the most common antibiotics used for genetic selection. In this study, we report the construction of an expression vector which uses the rhamnose-regulated P(rhaB) promoter of Escherichia coli. The functionality of the vector was assessed by expressing the enhanced green fluorescent protein (eGFP) gene (e-gfp) and determining the levels of fluorescence emission. These experiments demonstrated that P(rhaB) is responsive to low concentrations of rhamnose and it can be effectively repressed with 0.2% glucose. We also demonstrate that the tight regulation of gene expression by P(rhaB) promoter allows us to extend the capabilities of this vector to the identification of essential genes.

A Kernel Interleaved Scheduling Method for Streaming Applications on Soft-core Vector Processors

Massively parallel networks of highly efficient, high performance Single Instruction Multiple Data (SIMD) processors have been shown to enable FPGA-based implementation of real-time signal processing applications with performance and
cost comparable to dedicated hardware architectures. This is achieved by exploiting simple datapath units with deep processing pipelines. However, these architectures are highly susceptible to pipeline bubbles resulting from data and control hazards; the only way to mitigate against these is manual interleaving of
application tasks on each datapath, since no suitable automated interleaving approach exists. In this paper we describe a new automated integrated mapping/scheduling approach to map algorithm tasks to processors and a new low-complexity list scheduling technique to generate the interleaved schedules. When applied to a spatial Fixed-Complexity Sphere Decoding (FSD) detector
for next-generation Multiple-Input Multiple-Output (MIMO) systems, the resulting schedules achieve real-time performance for IEEE 802.11n systems on a network of 16-way SIMD processors on FPGA, enable better performance/complexity balance than current approaches and produce results comparable to handcrafted implementations.