271 research outputs found
An efficient semiparametric maxima estimator of the extremal index
The extremal index , a measure of the degree of local dependence in
the extremes of a stationary process, plays an important role in extreme value
analyses. We estimate semiparametrically, using the relationship
between the distribution of block maxima and the marginal distribution of a
process to define a semiparametric model. We show that these semiparametric
estimators are simpler and substantially more efficient than their parametric
counterparts. We seek to improve efficiency further using maxima over sliding
blocks. A simulation study shows that the semiparametric estimators are
competitive with the leading estimators. An application to sea-surge heights
combines inferences about with a standard extreme value analysis of
block maxima to estimate marginal quantiles.Comment: 17 pages, 7 figures. Minor edits made to version 1 prior to journal
publication. The final publication is available at Springer via
http://dx.doi.org/10.1007/s10687-015-0221-
The Hippo component YAP localizes in the nucleus of human papilloma virus positive oropharyngeal squamous cell carcinoma
Background: HPV infection causes cervical cancer, mediated in part by the degradation of Scribble via the HPV E6 oncoprotein. Recently, Scribble has been shown to be an important regulator of the Hippo signaling cascade. Deregulation of the Hippo pathway induces an abnormal cellular transformation, epithelial to mesenchymal transition, which promotes oncogenic progression. Given the recent rise in oropharyngeal HPV squamous cell carcinoma we sought to determine if Hippo signaling components are implicated in oropharyngeal squamous cell carcinoma. Methods: Molecular and cellular techniques including immunoprecipiations, Western blotting and immunocytochemistry were used to identify the key Hippo pathway effector Yes-Associated Protein (YAP)1. Oropharyngeal tissue was collected from CO2 laser resections, and probed with YAP1 antibody in tumor and pre-malignant regions of HPV positive OPSCC tissue. Results: This study reveals that the Scribble binding protein Nitric Oxide Synthase 1 Adaptor Protein (NOS1AP) forms a complex with YAP. Further, the NOS1APa and NOS1APc isoforms show differential association with activated and non-activated YAP, and impact cellular proliferation. Consistent with deregulated Hippo signaling in OPSCC HPV tumors, we see a delocalization of Scribble and increased nuclear accumulation of YAP1 in an HPV-positive OPSCC. Conclusion: Our preliminary data indicates that NOS1AP isoforms differentially associate with YAP1, which, together with our previous findings, predicts that loss of YAP1 enhances cellular transformation. Moreover, YAP1 is highly accumulated in the nucleus of HPV-positive OPSCC, implying that Hippo signaling and possibly NOS1AP expression are de-regulated in OPSCC. Further studies will help determine if NOS1AP isoforms, Scribble and Hippo components will be useful biomarkers in OPSCC tumor biology
Multi-Ancestry Genome-Wide Association Analyses Improve Resolution of Genes and Pathways Influencing Lung Function and Chronic Obstructive Pulmonary Disease Risk
Lung-function impairment underlies chronic obstructive pulmonary disease (COPD) and predicts mortality. In the largest multi-ancestry genome-wide association meta-analysis of lung function to date, comprising 580,869 participants, we identified 1,020 independent association signals implicating 559 genes supported by ≥2 criteria from a systematic variant-to-gene mapping framework. These genes were enriched in 29 pathways. Individual variants showed heterogeneity across ancestries, age and smoking groups, and collectively as a genetic risk score showed strong association with COPD across ancestry groups. We undertook phenome-wide association studies for selected associated variants as well as trait and pathway-specific genetic risk scores to infer possible consequences of intervening in pathways underlying lung function. We highlight new putative causal variants, genes, proteins and pathways, including those targeted by existing drugs. These findings bring us closer to understanding the mechanisms underlying lung function and COPD, and should inform functional genomics experiments and potentially future COPD therapies
Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial
Background
Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy
Structural Basis of Response Regulator Dephosphorylation by Rap Phosphatases
Crystallographic, biochemical, and genetic studies reveal the mechanism of Rap protein phosphatase activity within the phosphorelay pathway leading to sporulation in Bacillus species
Swift trust and commitment: the missing links for humanitarian supply chain coordination?
Coordination among actors in a humanitarian relief supply chain decides whether a relief operation can be or successful or not. In humanitarian supply chains, due to the urgency and importance of the situation combined with scarce resources, actors have to coordinate and trust each other in order to achieve joint goals. This paper investigated empirically the role of swift trust as mediating variable for achieving supply chain coordination. Based on commitment-trust theory we explore enablers of swift-trust and how swift trust translates into coordination through commitment. Based on a path analytic model we test data from the National Disaster Management Authority of India. Our study is the first testing commitment-trust theory (CTT) in the humanitarian context, highlighting the importance of swift trust and commitment for much thought after coordination. Furthermore, the study shows that information sharing and behavioral uncertainty reduction act as enablers for swift trust. The study findings offer practical guidance and suggest that swift trust is a missing link for the success of humanitarian supply chains
Treatment of chronically depressed patients: A multisite randomized controlled trial testing the effectiveness of 'Cognitive Behavioral Analysis System of Psychotherapy' (CBASP) for chronic depressions versus usual secondary care
AbstractBackground'Cognitive Behavioral Analysis System of Psychotherapy' (CBASP) is a form of psychotherapy specifically developed for patients with chronic depression. In a study in the U.S., remarkable favorable effects of CBASP have been demonstrated. However, no other studies have as yet replicated these findings and CBASP has not been tested outside the United States. This protocol describes a randomized controlled trial on the effectiveness of CBASP in the Netherlands.Methods/DesignThe purpose of the present paper is to report the study protocol of a multisite randomized controlled trial testing the effectiveness of 'Cognitive Behavioral Analysis System of Psychotherapy' (CBASP) for chronic depression in the Netherlands. In this study, CBASP in combination with medication, will be tested versus usual secondary care in combination with medication. The aim is to recruit 160 patients from three mental health care organizations. Depressive symptoms will be assessed at baseline, after 8 weeks, 16 weeks, 32 weeks and 52 weeks, using the 28-item Inventory for Depressive Symptomatology (IDS). Effect modification by co morbid anxiety, alcohol consumption, general and social functioning and working alliance will be tested. GEE analyses of covariance, controlling for baseline value and center will be used to estimate the overall treatment effectiveness (difference in IDS score) at post-treatment and follow up. The primary analysis will be by 'intention to treat' using double sided tests. An economic analysis will compare the two groups in terms of mean costs and cost-effectiveness from a societal perspective.DiscussionThe study will provide an answer to the question whether the favorable effects of CBASP can be replicated outside the US
Probabilistic Inference of Transcription Factor Binding from Multiple Data Sources
An important problem in molecular biology is to build a complete understanding of transcriptional regulatory processes in the cell. We have developed a flexible, probabilistic framework to predict TF binding from multiple data sources that differs from the standard hypothesis testing (scanning) methods in several ways. Our probabilistic modeling framework estimates the probability of binding and, thus, naturally reflects our degree of belief in binding. Probabilistic modeling also allows for easy and systematic integration of our binding predictions into other probabilistic modeling methods, such as expression-based gene network inference. The method answers the question of whether the whole analyzed promoter has a binding site, but can also be extended to estimate the binding probability at each nucleotide position. Further, we introduce an extension to model combinatorial regulation by several TFs. Most importantly, the proposed methods can make principled probabilistic inference from multiple evidence sources, such as, multiple statistical models (motifs) of the TFs, evolutionary conservation, regulatory potential, CpG islands, nucleosome positioning, DNase hypersensitive sites, ChIP-chip binding segments and other (prior) sequence-based biological knowledge. We developed both a likelihood and a Bayesian method, where the latter is implemented with a Markov chain Monte Carlo algorithm. Results on a carefully constructed test set from the mouse genome demonstrate that principled data fusion can significantly improve the performance of TF binding prediction methods. We also applied the probabilistic modeling framework to all promoters in the mouse genome and the results indicate a sparse connectivity between transcriptional regulators and their target promoters. To facilitate analysis of other sequences and additional data, we have developed an on-line web tool, ProbTF, which implements our probabilistic TF binding prediction method using multiple data sources. Test data set, a web tool, source codes and supplementary data are available at: http://www.probtf.org
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