An Investigation of a Process Constraint Treatment Analogue for Verbalizers and Visualizers

Based on the self-generated attitude change model, a process constraint treatment analogue was investigated. Differential treatment effects were explored for people that are verbalizers and visualizers. It was predicted that people who participated in the process constraint condition would benefit more if they were verbalizers than visualizers. It was also predicted that there would be no difference in effects for people in the control condition. To test these predictions, people with a fear of speaking in public were asked to speak in front of a small group. The effects of the treatment conditions were assessed using self-report, behavioral, and physiological measures of fear. Results supported the predictions on the behavioral and physiological measures, but only in part on the self-report measures. Implications of these results are discussed as well as directions for future research

Setting the Stage: A Comparative Analysis of the Sustainability Practices Employed at Selected Music Festivals

Music festivals are more than a social gathering. They hold the power to inspire great change in the world and continue to evolve with time. The purpose of this study was to compare and contrast the sustainability measures employed by Bonnaroo music festival in Tennessee and Splendour in the Grass music festival in Australia. The research for this study was conducted using a best practices instrument, designed by the researcher, to evaluate the sustainability practices of Bonnaroo and Splendour in the Grass. The study found that both festivals implement effective sustainability measures that inspire attendees to contribute in the conservation of the environment. Bonnaroo and Splendour in the Grass should maintain their effective sustainability practices and continue offering engaging experiences to their attendees

miR-196b target screen reveals mechanisms maintaining leukemia stemness with therapeutic potential.

We have shown that antagomiR inhibition of miRNA miR-21 and miR-196b activity is sufficient to ablate MLL-AF9 leukemia stem cells (LSC) in vivo. Here, we used an shRNA screening approach to mimic miRNA activity on experimentally verified miR-196b targets to identify functionally important and therapeutically relevant pathways downstream of oncogenic miRNA in MLL-r AML. We found Cdkn1b (p27Kip1) is a direct miR-196b target whose repression enhanced an embryonic stem cell–like signature associated with decreased leukemia latency and increased numbers of leukemia stem cells in vivo. Conversely, elevation of p27Kip1 significantly reduced MLL-r leukemia self-renewal, promoted monocytic differentiation of leukemic blasts, and induced cell death. Antagonism of miR-196b activity or pharmacologic inhibition of the Cks1-Skp2–containing SCF E3-ubiquitin ligase complex increased p27Kip1 and inhibited human AML growth. This work illustrates that understanding oncogenic miRNA target pathways can identify actionable targets in leukemia

Exercise capacity as an independent risk factor for adverse cardiovascular outcomes among nondiabetic and diabetic patients

Introduction: To investigate if decreased exercise capacity is an independent risk factor for major adverse cardiovascular events (MACE) in diabetics and nondiabetics. Material and methods The association of decreased exercise capacity (EC) during a treadmill exercise sestamibi stress test with MACE was investigated in 490 nondiabetics and 404 diabetics. Mean follow-up was 53 months. Results: Nondiabetics with a predicted EC < 85% had a higher prevalence of myocardial ischemia (34% vs. 19%, p = 0.0002), 2- or 3-vessel obstructive coronary artery disease (CAD) (31% vs. 13%, p = 0.016), myocardial infarction (MI) (17% vs. 7%, p = 0.0005), stroke (8% vs. 2%, p = 0.002), death (11% vs. 3%, p = 0.0002), and MI or stroke or death at follow-up (32% vs. 11%, p < 0.001) compared to nondiabetics with a predicted EC ≥ 85%. Diabetics with a predicted EC < 85% had a higher prevalence of myocardial ischemia (48% vs. 32%, p = 0.0009), 2- or 3-vessel obstructive CAD (54% vs. 28%, p = 0.001), MI (32% vs. 14%, p < 0.001), stroke (22% vs. 6%, p < 0.001), death (17% vs. 9%, p = 0.031), and MI or stroke or death at follow-up (65% vs. 27%, p < 0.001). Stepwise Cox regression analysis showed decreased EC was an independent and significant risk factor for MACE among nondiabetics (hazard ratio 3.3, p < 0.0001) and diabetics (hazard ratio 2.7, p < 0.0001). Conclusions: Diabetics and nondiabetics with decreased EC were at increased risk for MACE with nondiabetics and decreased EC at similar risk as diabetics with normal EC

The Myocardial Ischemia Reduction with Acute Cholesterol Lowering trial: MIRACuLous or not, it's time to change current practice

The Myocardial Ischemia Reduction with Aggressive Cholesterol Lowering (MIRACL) study was the first trial to assess whether statins might be of clinical benefit in those with recently unstable coronary disease. MIRACL found that high-dose atorvastatin was safe and reduced the incidence of the composite endpoint, death, non-fatal myocardial infarction, resuscitated sudden cardiac death or emergent rehospitalization for recurrent ischemia at 16 weeks when compared with placebo. Despite a number of important study limitations, MIRACL's findings and the prior observation that inpatient initiation of lipid-lowering therapy is associated with higher rates of subsequent utilization, suggest that it is prudent to begin statin therapy when patients present with an acute coronary syndrome

ToppCluster: a multiple gene list feature analyzer for comparative enrichment clustering and network-based dissection of biological systems

ToppCluster is a web server application that leverages a powerful enrichment analysis and underlying data environment for comparative analyses of multiple gene lists. It generates heatmaps or connectivity networks that reveal functional features shared or specific to multiple gene lists. ToppCluster uses hypergeometric tests to obtain list-specific feature enrichment P-values for currently 17 categories of annotations of human-ortholog genes, and provides user-selectable cutoffs and multiple testing correction methods to control false discovery. Each nameable gene list represents a column input to a resulting matrix whose rows are overrepresented features, and individual cells per-list P-values and corresponding genes per feature. ToppCluster provides users with choices of tabular outputs, hierarchical clustering and heatmap generation, or the ability to interactively select features from the functional enrichment matrix to be transformed into XGMML or GEXF network format documents for use in Cytoscape or Gephi applications, respectively. Here, as example, we demonstrate the ability of ToppCluster to enable identification of list-specific phenotypic and regulatory element features (both cis-elements and 3′UTR microRNA binding sites) among tissue-specific gene lists. ToppCluster’s functionalities enable the identification of specialized biological functions and regulatory networks and systems biology-based dissection of biological states. ToppCluster can be accessed freely at http://toppcluster.cchmc.org

ToppGene Suite for gene list enrichment analysis and candidate gene prioritization

ToppGene Suite (http://toppgene.cchmc.org; this web site is free and open to all users and does not require a login to access) is a one-stop portal for (i) gene list functional enrichment, (ii) candidate gene prioritization using either functional annotations or network analysis and (iii) identification and prioritization of novel disease candidate genes in the interactome. Functional annotation-based disease candidate gene prioritization uses a fuzzy-based similarity measure to compute the similarity between any two genes based on semantic annotations. The similarity scores from individual features are combined into an overall score using statistical meta-analysis. A P-value of each annotation of a test gene is derived by random sampling of the whole genome. The protein–protein interaction network (PPIN)-based disease candidate gene prioritization uses social and Web networks analysis algorithms (extended versions of the PageRank and HITS algorithms, and the K-Step Markov method). We demonstrate the utility of ToppGene Suite using 20 recently reported GWAS-based gene–disease associations (including novel disease genes) representing five diseases. ToppGene ranked 19 of 20 (95%) candidate genes within the top 20%, while ToppNet ranked 12 of 16 (75%) candidate genes among the top 20%