Endothelial dysfunction in obese non-hypertensive children without evidence of sleep disordered breathing

<p>Abstract</p> <p>Background</p> <p>Endothelial dysfunction is a complication of both obesity and obstructive sleep apnea syndrome (OSAS), the latter being highly prevalent among obese children. It is unknown whether obesity causes endothelial dysfunction in children in the absence of OSAS. This study examines endothelial function in obese and non-obese children without OSAS.</p> <p>Methods</p> <p>Pre-pubertal non-hypertensive children were recruited. Endothelial function was assessed in a morning fasted state, using a modified hyperemic test involving cuff-induced occlusion of the radial and ulnar arteries. The absence of OSAS was confirmed by overnight polysomnography. Anthropometry was also performed.</p> <p>Results</p> <p>55 obese children (mean age 8.6 ± 1.4 years, mean BMI z-score: 2.3 ± 0.3) were compared to 50 non-obese children (mean age 8.0 ± 1.6 years, mean BMI z-score 0.3 ± 0.9). Significant delays to peak capillary reperfusion after occlusion release occurred in obese compared to non-obese children (45.3 ± 21.9 sec <it>vs</it>. 31.5 ± 14.1 sec, p < 0.01), but no differences in the magnitude of hyperemia emerged. Time to peak reperfusion and percentage of body fat were positively correlated (r = 0.365, p < 0.01).</p> <p>Conclusions</p> <p>Our findings confirm that endothelial dysfunction occurs early in life in obese children, even in the absence of OSAS. Thus, mechanisms underlying endothelial dysfunction in pediatric obesity are operational in the absence of sleep-disordered breathing.</p

Microdevices for extensional rheometry of low viscosity elastic liquids : a review

Extensional flows and the underlying stability/instability mechanisms are of extreme relevance to the efficient operation of inkjet printing, coating processes and drug delivery systems, as well as for the generation of micro droplets. The development of an extensional rheometer to characterize the extensional properties of low viscosity fluids has therefore stimulated great interest of researchers, particularly in the last decade. Microfluidics has proven to be an extraordinary working platform and different configurations of potential extensional microrheometers have been proposed. In this review, we present an overview of several successful designs, together with a critical assessment of their capabilities and limitations

The LSD1-Type Zinc Finger Motifs of Pisum sativa LSD1 Are a Novel Nuclear Localization Signal and Interact with Importin Alpha

Background: Genetic studies of the Arabidopsis mutant lsd1 highlight the important role of LSD1 in the negative regulation of plant programmed cell death (PCD). Arabidopsis thaliana LSD1 (AtLSD1) contains three LSD1-type zinc finger motifs, which are involved in the protein-protein interaction. Methodology/Principal Findings: To further understand the function of LSD1, we have analyzed cellular localization and functional localization domains of Pisum sativa LSD1 (PsLSD1), which is a homolog of AtLSD1. Subcellular localization analysis of green fluorescent protein (GFP)-tagged PsLSD1 indicates that PsLSD1 is localized in the nucleus. Using a series of GFP-tagged PsLSD1 deletion mutants, we found that the three LSD1-type zinc finger motifs of PsLSD1 alone can target GFP to the nucleus, whereas deletion of the three zinc finger motifs or any individual zinc finger motif causes PsLSD1 to lose its nuclear localization, indicating that the three zinc finger motifs are necessary and sufficient for its nuclear localization. Moreover, site-directed mutagenesis analysis of GFP-tagged PsLSD1 indicates that tertiary structure and basic amino acids of each zinc finger motif are necessary for PsLSD1 nuclear localization. In addition, yeast two-hybrid, pull-down, and BiFC assays demonstrate that the three zinc finger motifs of PsLSD1 directly bind to importin alpha in vitro and in vivo. Conclusions/Significance: Our data demonstrate that the LSD1-type zinc finger motifs of PsLSD1 are a novel nuclear localization signal and directly bind to importin alpha, and suggest that the nuclear import of LSD1 may rely on the interaction between its zinc finger motifs and importin alpha. Moreover, the nuclear localization of PsLSD1 suggests that LSD1 may function as a transcription regulator involved in negatively regulating PCD.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000292929500042&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Multidisciplinary SciencesSCI(E)PubMed11ARTICLE7e22131

Anomaly Mediation and Cosmology

We consider an extension of the MSSM wherein anomaly mediation is the source of supersymmetry breaking, and the tachyonic slepton problem is solved by a gauged U(1) symmetry, which is broken at high energies in a manner preserving supersymmetry, thereby also facilitating the see-saw mechanism for neutrino masses and a natural source for the Higgs mu-term. We show that these favourable outcomes can occur both in the presence and the absence of a large Fayet-Iliopoulos (FI) D-term associated with the new U(1). We explore the cosmological consequences of the model, showing that it naturally produces a period of hybrid inflation, terminating in the production of cosmic strings. In spite of the presence of a U(1) (even with an FI term), inflation is effected by the F-term, with a D-flat tree potential (the FI term, if present, being cancelled by non-zero squark and slepton fields). Calculating the 1-loop corrections to the inflaton potential, we estimate the constraints on the parameters of the model from Cosmic Microwave Background data. We will see that a consequence of these constraints is that the Higgs mu-term necessarily small. We briefly discuss the mechanisms for baryogenesis via conventional leptogenesis, the out-of-equilibrium production of neutrinos from the cosmic strings, or the Affleck-Dine mechanism. Cosmic string decays also boost the relic density of dark matter above the low value normally obtained in AMSB scenarios.Comment: 34 pages. Revised to incorporate discussion of the case when the Fayet-Ilipoulos term is absen

Online Survival Analysis Software to Assess the Prognostic Value of Biomarkers Using Transcriptomic Data in Non-Small-Cell Lung Cancer

In the last decade, optimized treatment for non-small cell lung cancer had lead to improved prognosis, but the overall survival is still very short. To further understand the molecular basis of the disease we have to identify biomarkers related to survival. Here we present the development of an online tool suitable for the real-time meta-analysis of published lung cancer microarray datasets to identify biomarkers related to survival. We searched the caBIG, GEO and TCGA repositories to identify samples with published gene expression data and survival information. Univariate and multivariate Cox regression analysis, Kaplan-Meier survival plot with hazard ratio and logrank P value are calculated and plotted in R. The complete analysis tool can be accessed online at: www.kmplot.com/lung. All together 1,715 samples of ten independent datasets were integrated into the system. As a demonstration, we used the tool to validate 21 previously published survival associated biomarkers. Of these, survival was best predicted by CDK1 (p<1E-16), CD24 (p<1E-16) and CADM1 (p = 7E-12) in adenocarcinomas and by CCNE1 (p = 2.3E-09) and VEGF (p = 3.3E-10) in all NSCLC patients. Additional genes significantly correlated to survival include RAD51, CDKN2A, OPN, EZH2, ANXA3, ADAM28 and ERCC1. In summary, we established an integrated database and an online tool capable of uni- and multivariate analysis for in silico validation of new biomarker candidates in non-small cell lung cancer

Inferring Pathway Activity toward Precise Disease Classification

The advent of microarray technology has made it possible to classify disease states based on gene expression profiles of patients. Typically, marker genes are selected by measuring the power of their expression profiles to discriminate among patients of different disease states. However, expression-based classification can be challenging in complex diseases due to factors such as cellular heterogeneity within a tissue sample and genetic heterogeneity across patients. A promising technique for coping with these challenges is to incorporate pathway information into the disease classification procedure in order to classify disease based on the activity of entire signaling pathways or protein complexes rather than on the expression levels of individual genes or proteins. We propose a new classification method based on pathway activities inferred for each patient. For each pathway, an activity level is summarized from the gene expression levels of its condition-responsive genes (CORGs), defined as the subset of genes in the pathway whose combined expression delivers optimal discriminative power for the disease phenotype. We show that classifiers using pathway activity achieve better performance than classifiers based on individual gene expression, for both simple and complex case-control studies including differentiation of perturbed from non-perturbed cells and subtyping of several different kinds of cancer. Moreover, the new method outperforms several previous approaches that use a static (i.e., non-conditional) definition of pathways. Within a pathway, the identified CORGs may facilitate the development of better diagnostic markers and the discovery of core alterations in human disease

Violence against female sex workers in Karnataka state, south India: impact on health, and reductions in violence following an intervention program

<p>Abstract</p> <p>Background</p> <p>Violence against female sex workers (FSWs) can impede HIV prevention efforts and contravenes their human rights. We developed a multi-layered violence intervention targeting policy makers, secondary stakeholders (police, lawyers, media), and primary stakeholders (FSWs), as part of wider HIV prevention programming involving >60,000 FSWs in Karnataka state. This study examined if violence against FSWs is associated with reduced condom use and increased STI/HIV risk, and if addressing violence against FSWs within a large-scale HIV prevention program can reduce levels of violence against them.</p> <p>Methods</p> <p>FSWs were randomly selected to participate in polling booth surveys (PBS 2006-2008; short behavioural questionnaires administered anonymously) and integrated behavioural-biological assessments (IBBAs 2005-2009; administered face-to-face).</p> <p>Results</p> <p>3,852 FSWs participated in the IBBAs and 7,638 FSWs participated in the PBS. Overall, 11.0% of FSWs in the IBBAs and 26.4% of FSWs in the PBS reported being beaten or raped in the past year. FSWs who reported violence in the past year were significantly less likely to report condom use with clients (zero unprotected sex acts in previous month, 55.4% vs. 75.5%, adjusted odds ratio (AOR) 0.4, 95% confidence interval (CI) 0.3 to 0.5, p < 0.001); to have accessed the HIV intervention program (ever contacted by peer educator, 84.9% vs. 89.6%, AOR 0.7, 95% CI 0.4 to 1.0, p = 0.04); or to have ever visited the project sexual health clinic (59.0% vs. 68.1%, AOR 0.7, 95% CI 0.6 to 1.0, p = 0.02); and were significantly more likely to be infected with gonorrhea (5.0% vs. 2.6%, AOR 1.9, 95% CI 1.1 to 3.3, p = 0.02). By the follow-up surveys, significant reductions were seen in the proportions of FSWs reporting violence compared with baseline (IBBA 13.0% vs. 9.0%, AOR 0.7, 95% CI 0.5 to 0.9 p = 0.01; PBS 27.3% vs. 18.9%, crude OR 0.5, 95% CI 0.4 to 0.5, p < 0.001).</p> <p>Conclusions</p> <p>This program demonstrates that a structural approach to addressing violence can be effectively delivered at scale. Addressing violence against FSWs is important for the success of HIV prevention programs, and for protecting their basic human rights.</p

Large-scale integration of cancer microarray data identifies a robust common cancer signature

<p>Abstract</p> <p>Background</p> <p>There is a continuing need to develop molecular diagnostic tools which complement histopathologic examination to increase the accuracy of cancer diagnosis. DNA microarrays provide a means for measuring gene expression signatures which can then be used as components of genomic-based diagnostic tests to determine the presence of cancer.</p> <p>Results</p> <p>In this study, we collect and integrate ~ 1500 microarray gene expression profiles from 26 published cancer data sets across 21 major human cancer types. We then apply a statistical method, referred to as the <it>T</it>op-<it>S</it>coring <it>P</it>air of <it>G</it>roups (TSPG) classifier, and a repeated random sampling strategy to the integrated training data sets and identify a common cancer signature consisting of 46 genes. These 46 genes are naturally divided into two distinct groups; those in one group are typically expressed less than those in the other group for cancer tissues. Given a new expression profile, the classifier discriminates cancer from normal tissues by ranking the expression values of the 46 genes in the cancer signature and comparing the average ranks of the two groups. This signature is then validated by applying this decision rule to independent test data.</p> <p>Conclusion</p> <p>By combining the TSPG method and repeated random sampling, a robust common cancer signature has been identified from large-scale microarray data integration. Upon further validation, this signature may be useful as a robust and objective diagnostic test for cancer.</p