VEGF and IL-4 gene variability and its association with the risk of coronary heart disease in north Indian population

Vascular endothelial growth factor (VEGF) is a potent angiogenic growth factor that has been shown to play a significant role in neovascularization during inflammation in atherosclerotic plaques, formation of collateral vessels to an area of ischemic myocardium and neovascularization at the edges of a myocardial infarction during its repair. Interleukin-4 (IL-4) has important role in immune cell chemotaxis, formation of endothelial cell adhesion molecules and has numerous anti-inflammatory effects which prevent the complications of atherosclerosis, the primary cause of coronary heart disease (CHD). In this study, we have analyzed the effect of 1154 A/G polymorphism of VEGF and 70 bp VNTR polymorphism of intron 3 in IL-4 genes in coronary heart disease (CHD) patients (n = 300) and their age matched controls (n = 300). To analyze polymorphic alleles, ARMS-PCR and RFLP techniques were used. Multiple logistic regression analysis was carried out with statistical software. GG genotype was associated with a decreased risk of development of CHD (OR 0.22, 95% CI 0.12–0.38, P < 0.001). However, A allele showed an increased risk whereas G allele decreased the risk of CHD with diabetes mellitus, hypertension, chronic mental stress and positive familial history of myocardial infarction (MI)/CHD. GG genotype was found to have protective effect with alcohol intake (OR 0.34, 95% CI 0.14–0.82, P < 0.01) and central obesity (OR 0.15, 95% CI 0.04–0.56, P < 0.001). GG genotype of VEGF has also shown significant association with IL-4 (P2P2 and P1P2) genotypes.     

Fluorescence-Based High-Throughput Functional Profiling of Ligand-Gated Ion Channels at the Level of Single Cells

Ion channels are involved in many physiological processes and are attractive targets for therapeutic intervention. Their functional properties vary according to their subunit composition, which in turn varies in a developmental and tissue-specific manner and as a consequence of pathophysiological events. Understanding this diversity requires functional analysis of ion channel properties in large numbers of individual cells. Functional characterisation of ligand-gated channels involves quantitating agonist and drug dose-response relationships using electrophysiological or fluorescence-based techniques. Electrophysiology is limited by low throughput and high-throughput fluorescence-based functional evaluation generally does not enable the characterization of the functional properties of each individual cell. Here we describe a fluorescence-based assay that characterizes functional channel properties at single cell resolution in high throughput mode. It is based on progressive receptor activation and iterative fluorescence imaging and delivers >100 dose-responses in a single well of a 384-well plate, using α1-3 homomeric and αβ heteromeric glycine receptor (GlyR) chloride channels as a model system. We applied this assay with transiently transfected HEK293 cells co-expressing halide-sensitive yellow fluorescent protein and different GlyR subunit combinations. Glycine EC₅₀ values of different GlyR isoforms were highly correlated with published electrophysiological data and confirm previously reported pharmacological profiles for the GlyR inhibitors, picrotoxin, strychnine and lindane. We show that inter and intra well variability is low and that clustering of functional phenotypes permits identification of drugs with subunit-specific pharmacological profiles. As this method dramatically improves the efficiency with which ion channel populations can be characterized in the context of cellular heterogeneity, it should facilitate systems-level analysis of ion channel properties in health and disease and the discovery of therapeutics to reverse pathological alterations.     

Loosely coupled coordinated management in virtualized data centers

Management is an important challenge for future enterprises. Previous work has addressed platform management (e.g., power and thermal management) separately from virtualization management (e.g., virtual machine (VM) provisioning, application performance). Coordinating the actions taken by these different management layers is important and beneficial, for reasons of performance, stability, and efficiency. Such coordination, in addition to working well with existing multi-vendor solutions, also needs to be extensible to support future management solutions potentially operating on different sensors and actuators. In response to these requirements, this paper proposes vManage, a solution to loosely couple platform and virtualization management and facilitate coordination between them in data centers. Our solution is comprised of registry and proxy mechanisms that provide unified monitoring and actuation across platform and virtualization domains, and coordinators that provide policy execution for better VM placement and runtime management, including a formal approach to ensure system stability from inefficient management actions. The solution is instantiated in a Xen environment through a platform-aware virtualization manager at a cluster management node, and a virtualization-aware platform manager on each server. Experimental evaluations using enterprise benchmarks show that compared to traditional solutions, vManage can achieve additional power savings (10% lower power) with significantly improved service-level guarantees (71% less violations) and stability (54% fewer VM migrations), at low overhead.     

Efficient optimization of time-varying inputs in a fed-batch cell culture process using design of dynamic experiments

In cell culture process development, we rely largely on an iterative, one-factor-at-a-time procedure based on experiments that explore a limited process space. Design of experiments (DoE) addresses this issue by allowing us to analyze the effects of process inputs on process responses systematically and efficiently. However, DoE cannot be applied directly to study time-varying process inputs unless an impractically large number of bioreactors is used. Here, we adopt the methodology of design of dynamic experiments (DoDE) and incorporate dynamic feeding profiles efficiently in late-stage process development of the manufacture of therapeutic monoclonal antibodies. We found that, for the specific cell line used in this article, (1) not only can we estimate the effect of nutrient feed amount on various product attributes, but we can also estimate the effect, develop a statistical model, and use the model to optimize the slope of time-trended feed rates; (2) in addition to the slope, higher-order dynamic characteristics of time-trended feed rates can be incorporated in the design but do not have any significant effect on the responses we measured. Based on the DoDE data, we developed a statistical model and used the model to optimize several process conditions. Our effort resulted in a tangible improvement in productivity—compared with the baseline process without dynamic feeding, this optimized process in a 200-L batch achieved a 27% increase in titer and > 92% viability. We anticipate our application of DoDE to be a starting point for more efficient workflows to optimize dynamic process conditions in process development.     

Design and optimization of quinazoline derivatives as melanin concentrating hormone receptor 1 (MCHR1) antagonists: part 2

Melanin concentrating hormone receptor 1 (MCHR1) antagonists have potential for the treatment of obesity and several CNS disorders. In the preceding article, we have described a novel series of quinazolines as MCHR1 antagonists and demonstrated in vivo proof of principle with an early lead. Herein we describe the detailed SAR and SPR studies to identify an optimized lead candidate having good efficacy in a sub-chronic DIO model with a good cardiovascular safety window.