Implication of the overlap representation for modelling generalized parton distributions

Based on a field theoretically inspired model of light-cone wave functions, we derive valence-like generalized parton distributions and their double distributions from the wave function overlap in the parton number conserved s-channel. The parton number changing contributions in the t-channel are restored from duality. In our construction constraints of positivity and polynomiality are simultaneously satisfied and it also implies a model dependent relation between generalized parton distributions and transverse momentum dependent parton distribution functions. The model predicts that the t-behavior of resulting hadronic amplitudes depends on the Bjorken variable x_Bj. We also propose an improved ansatz for double distributions that embeds this property.Comment: 15 pages, 8 eps figure

Meta-Analyst: software for meta-analysis of binary, continuous and diagnostic data

<p>Abstract</p> <p>Background</p> <p>Meta-analysis is increasingly used as a key source of evidence synthesis to inform clinical practice. The theory and statistical foundations of meta-analysis continually evolve, providing solutions to many new and challenging problems. In practice, most meta-analyses are performed in general statistical packages or dedicated meta-analysis programs.</p> <p>Results</p> <p>Herein, we introduce Meta-Analyst, a novel, powerful, intuitive, and free meta-analysis program for the meta-analysis of a variety of problems. Meta-Analyst is implemented in C# atop of the Microsoft .NET framework, and features a graphical user interface. The software performs several meta-analysis and meta-regression models for binary and continuous outcomes, as well as analyses for diagnostic and prognostic test studies in the frequentist and Bayesian frameworks. Moreover, Meta-Analyst includes a flexible tool to edit and customize generated meta-analysis graphs (e.g., forest plots) and provides output in many formats (images, Adobe PDF, Microsoft Word-ready RTF). The software architecture employed allows for rapid changes to be made to either the Graphical User Interface (GUI) or to the analytic modules.</p> <p>We verified the numerical precision of Meta-Analyst by comparing its output with that from standard meta-analysis routines in Stata over a large database of 11,803 meta-analyses of binary outcome data, and 6,881 meta-analyses of continuous outcome data from the Cochrane Library of Systematic Reviews. Results from analyses of diagnostic and prognostic test studies have been verified in a limited number of meta-analyses versus MetaDisc and MetaTest. Bayesian statistical analyses use the OpenBUGS calculation engine (and are thus as accurate as the standalone OpenBUGS software).</p> <p>Conclusion</p> <p>We have developed and validated a new program for conducting meta-analyses that combines the advantages of existing software for this task.</p

Evaluating heterogeneity in cumulative meta-analyses

BACKGROUND: Recently developed measures such as I(2 )and H allow the evaluation of the impact of heterogeneity in conventional meta-analyses. There has been no examination of the development of heterogeneity in the context of a cumulative meta-analysis. METHODS: Cumulative meta-analyses of five smoking cessation interventions (clonidine, nicotine replacement therapy using gum and patch, physician advice and acupuncture) were used to calculate I(2 )and H. These values were plotted by year of publication, control event rate and sample size to trace the development of heterogeneity over these covariates. RESULTS: The cumulative evaluation of heterogeneity varied according to the measure of heterogeneity used and the basis of cumulation. Plots produced from the calculations revealed areas of heterogeneity useful in the consideration of potential sources for further study. CONCLUSION: The examination of heterogeneity in conjunction with summary effect estimates in a cumulative meta-analysis offered valuable insight into the evolution of variation. Such information is not available in the context of conventional meta-analysis and has the potential to lead to the development of a richer picture of the effectiveness of interventions

Heterogeneity in Meta-Analyses of Genome-Wide Association Investigations

BACKGROUND: Meta-analysis is the systematic and quantitative synthesis of effect sizes and the exploration of their diversity across different studies. Meta-analyses are increasingly applied to synthesize data from genome-wide association (GWA) studies and from other teams that try to replicate the genetic variants that emerge from such investigations. Between-study heterogeneity is important to document and may point to interesting leads. METHODOLOGY/PRINCIPAL FINDINGS: To exemplify these issues, we used data from three GWA studies on type 2 diabetes and their replication efforts where meta-analyses of all data using fixed effects methods (not incorporating between-study heterogeneity) have already been published. We considered 11 polymorphisms that at least one of the three teams has suggested as susceptibility loci for type 2 diabetes. The I2 inconsistency metric (measuring the amount of heterogeneity not due to chance) was different from 0 (no detectable heterogeneity) for 6 of the 11 genetic variants; inconsistency was moderate to very large (I2 = 32-77%) for 5 of them. For these 5 polymorphisms, random effects calculations incorporating between-study heterogeneity revealed more conservative p-values for the summary effects compared with the fixed effects calculations. These 5 associations were perused in detail to highlight potential explanations for between-study heterogeneity. These include identification of a marker for a correlated phenotype (e.g. FTO rs8050136 being associated with type 2 diabetes through its effect on obesity); differential linkage disequilibrium across studies of the identified genetic markers with the respective culprit polymorphisms (e.g., possibly the case for CDKAL1 polymorphisms or for rs9300039 and markers in linkage disequilibrium, as shown by additional studies); and potential bias. Results were largely similar, when we treated the discovery and replication data from each GWA investigation as separate studies. SIGNIFICANCE: Between-study heterogeneity is useful to document in the synthesis of data from GWA investigations and can offer valuable insights for further clarification of gene-disease associations

Optimal leverage from non-ergodicity

In modern portfolio theory, the balancing of expected returns on investments against uncertainties in those returns is aided by the use of utility functions. The Kelly criterion offers another approach, rooted in information theory, that always implies logarithmic utility. The two approaches seem incompatible, too loosely or too tightly constraining investors' risk preferences, from their respective perspectives. The conflict can be understood on the basis that the multiplicative models used in both approaches are non-ergodic which leads to ensemble-average returns differing from time-average returns in single realizations. The classic treatments, from the very beginning of probability theory, use ensemble-averages, whereas the Kelly-result is obtained by considering time-averages. Maximizing the time-average growth rates for an investment defines an optimal leverage, whereas growth rates derived from ensemble-average returns depend linearly on leverage. The latter measure can thus incentivize investors to maximize leverage, which is detrimental to time-average growth and overall market stability. The Sharpe ratio is insensitive to leverage. Its relation to optimal leverage is discussed. A better understanding of the significance of time-irreversibility and non-ergodicity and the resulting bounds on leverage may help policy makers in reshaping financial risk controls.Comment: 17 pages, 3 figures. Updated figures and extended discussion of ergodicit

Artificial membrane-binding proteins stimulate oxygenation of stem cells during engineering of large cartilage tissue

Restricted oxygen diffusion can result in central cell necrosis in engineered tissue, a problem that is exacerbated when engineering large tissue constructs for clinical application. Here we show that pre-treating human mesenchymal stem cells (hMSCs) with synthetic membrane-active myoglobin-polymer–surfactant complexes can provide a reservoir of oxygen capable of alleviating necrosis at the centre of hyaline cartilage. This is achieved through the development of a new cell functionalization methodology based on polymer–surfactant conjugation, which allows the delivery of functional proteins to the hMSC membrane. This new approach circumvents the need for cell surface engineering using protein chimerization or genetic transfection, and we demonstrate that the surface-modified hMSCs retain their ability to proliferate and to undergo multilineage differentiation. The functionalization technology is facile, versatile and non-disruptive, and in addition to tissue oxygenation, it should have far-reaching application in a host of tissue engineering and cell-based therapies

Oxidative stress-dependent cyclooxygenase-2-derived prostaglandin F2α impairs endothelial function in renovascular hypertensive rats

Abstract Aims: The role of endothelium-derived contracting factors (EDCFs) in regulating renovascular function is yet to be elucidated in renovascular hypertension (RH). The current study investigated whether oxidative stress-dependent cyclooxygenase (COX)-2-derived prostaglandin F(2alpha) (PGF(2alpha)) impairs endothelial function in renal arteries of renovascular hypertensive rats (RHR). Results: Renal hypertension was induced in rats by renal artery stenosis of both kidneys using the 2-kidney 2-clip model. Acute treatment with reactive oxygen species (ROS) scavengers, COX-2 inhibitors, and thromboxane-prostanoid receptor antagonists, but not COX-1 inhibitors, improved endothelium-dependent relaxations and eliminated endothelium-dependent contractions in RHR renal arteries. Five weeks of treatment with celecoxib or tempol reduced blood pressure, increased renal blood flow, and restored endothelial function in RHRs. Increased ROS production in RHR arteries was inhibited by ROS scavengers, but unaffected by COX-2 inhibitors; whereas increased PGF(2alpha) release was reduced by both ROS scavengers and COX-2 inhibitors. ROS also induced COX-2-dependent contraction in RHR renal arteries, which was accompanied by the release of COX-2-derived PGF(2alpha). Further, chronic tempol treatment reduced COX-2 and BMP4 upregulation, p38MAPK phosphorylation, and the nitrotyrosine level in RHR renal arteries. Conclusion: These findings demonstrate the functional importance of oxidative stress, which serves as an initiator of increased COX-2 activity, and that COX-2-derived PGF(2alpha) plays an important role in mediating endothelial dysfunction in RH. Innovation: The current study, thus, suggests that drugs targeting oxidative stress-dependent COX-2-derived PGF(2alpha) may be useful in the prevention and management of RH. Antioxid. Redox Signal. 16, 363-373.published_or_final_versio

Quantifying Selective Reporting and the Proteus Phenomenon for Multiple Datasets with Similar Bias

Meta-analyses play an important role in synthesizing evidence from diverse studies and datasets that address similar questions. A major obstacle for meta-analyses arises from biases in reporting. In particular, it is speculated that findings which do not achieve formal statistical significance are less likely reported than statistically significant findings. Moreover, the patterns of bias can be complex and may also depend on the timing of the research results and their relationship with previously published work. In this paper, we present an approach that is specifically designed to analyze large-scale datasets on published results. Such datasets are currently emerging in diverse research fields, particularly in molecular medicine. We use our approach to investigate a dataset on Alzheimer's disease (AD) that covers 1167 results from case-control studies on 102 genetic markers. We observe that initial studies on a genetic marker tend to be substantially more biased than subsequent replications. The chances for initial, statistically non-significant results to be published are estimated to be about 44% (95% CI, 32% to 63%) relative to statistically significant results, while statistically non-significant replications have almost the same chance to be published as statistically significant replications (84%; 95% CI, 66% to 107%). Early replications tend to be biased against initial findings, an observation previously termed Proteus phenomenon: The chances for non-significant studies going in the same direction as the initial result are estimated to be lower than the chances for non-significant studies opposing the initial result (73%; 95% CI, 55% to 96%). Such dynamic patters in bias are difficult to capture by conventional methods, where typically simple publication bias is assumed to operate. Our approach captures and corrects for complex dynamic patterns of bias, and thereby helps generating conclusions from published results that are more robust against the presence of different coexisting types of selective reporting

Genetics, recombination and clinical features of human rhinovirus species C (HRV-C) infections; interactions of HRV-C with other respiratory viruses

To estimate the frequency, molecular epidemiological and clinical associations of infection with the newly described species C variants of human rhinoviruses (HRV), 3243 diagnostic respiratory samples referred for diagnostic testing in Edinburgh were screened using a VP4-encoding region-based selective polymerase chain reaction (PCR) for HRV-C along with parallel PCR testing for 13 other respiratory viruses. HRV-C was the third most frequently detected behind respiratory syncytial virus (RSV) and adenovirus, with 141 infection episodes detected among 1885 subjects over 13 months (7.5%). Infections predominantly targeted the very young (median age 6–12 months; 80% of infections in those &#60;2 years), occurred throughout the year but with peak incidence in early winter months. HRV-C was detected significantly more frequently among subjects with lower (LRT) and upper respiratory tract (URT) disease than controls without respiratory symptoms; HRV-C mono-infections were the second most frequently detected virus (behind RSV) in both disease presentations (6.9% and 7.8% of all cases respectively). HRV variants were classified by VP4/VP2 sequencing into 39 genotypically defined types, increasing the current total worldwide to 60. Through sequence comparisons of the 5′untranslated region (5′UTR), the majority grouped with species A (n = 96; 68%, described as HRV-Ca), the remainder forming a phylogenetically distinct 5′UTR group (HRV-Cc). Multiple and bidirectional recombination events between HRV-Ca and HRV-Cc variants and with HRV species A represents the most parsimonious explanation for their interspersed phylogeny relationships in the VP4/VP2-encoding region. No difference in age distribution, seasonality or disease associations was identified between HRV-Ca and HRV-Cc variants. HRV-C-infected subjects showed markedly reduced detection frequencies of RSV and other respiratory viruses, providing evidence for a major interfering effect of HRV-C on susceptibility to other respiratory virus infections. HRV-C's disease associations, its prevalence and evidence for interfering effects on other respiratory viruses mandates incorporation of rhinoviruses into future diagnostic virology screening

Systematic review and meta-analysis on the adverse events of rimonabant treatment: Considerations for its potential use in hepatology

<p>Abstract</p> <p>Background</p> <p>The cannabinoid-1 receptor blockers have been proposed in the management of obesity and obesity-related liver diseases (fatty liver as NAFLD or NASH). Due to increasing number of patients to be potentially treated and the need to assess the advantage of this treatment in terms of risk/benefit, we analyze the side events reported during the treatment with rimonabant by a systematic review and meta-analysis of all randomized controlled studies.</p> <p>Methods</p> <p>All published randomized controlled trials using rimonabant <it>versus </it>placebo in adult subjects were retrieved. Relative risks (RR) with 95% confidence interval for relevant adverse events and number needed to harm was calculated.</p> <p>Results</p> <p>Nine trials (n = 9635) were considered. Rimonabant 20 mg was associated with an increased risk of adverse event (RR 1.35; 95%CI 1.17-1.56), increased discontinuation rate (RR 1.79; 95%CI 1.35-2.38), psychiatric (RR 2.35; 95%CI 1.66-3.34), and nervous system adverse events (RR 2.35; 95%CI 1.49-3.70). The number needed to harm for psychiatric adverse events is 30.</p> <p>Conclusion</p> <p>Rimonabant is associated with an increased risk of adverse events. Despite of an increasing interest for its use on fatty liver, the security profile and efficacy it is needs to be carefully assessed before its recommendation. At present the use of rimonabant on fatty liver cannot be recommended.</p