Multimodal interventions to enhance adherence to secondary preventive medication after stroke: a systematic review and meta-analyses

Summary: Introduction: Nonadherence to secondary preventative medications after stroke is common and is associated with poor outcomes. Numerous strategies exist to promote adherence. We performed a systematic review and meta-analysis to describe the efficacy of strategies to improve adherence to stroke secondary prevention. Methods: We created a sensitive search strategy and searched multiple electronic databases (MEDLINE, EMBASE, CINAHL, PsycINFO, CENTRAL, and Web of Knowledge) for studies of interventions that aimed to enhance adherence to secondary preventative medication after stroke. We assessed quality of included studies using the Cochrane tool for assessing risk of bias. We performed narrative review and performed meta-analysis where data allowed. Results: From 12,237 titles, we included seventeen studies in our review. Eleven studies were considered to have high risk of bias, 3 with unclear risk, and 3 of low risk. Meta-analysis of available data suggested that these interventions improved adherence to individual medication classes (blood pressure-lowering drugs – OR, 2.21; 95% CI (1.63, 2.98), [P < 0.001], lipid-lowering drugs – OR, 2.11; 95% CI (1.00, 4.46), [P = 0.049], and antithrombotic drugs – OR, 2.32; 95% CI (1.18, 4.56, [P = 0.014]) but did not improve adherence to an overall secondary preventative medication regimen (OR, 1.96; 95% CI (0.50, 7.67), [P = 0.332]). Conclusion: Interventions can lead to improvement in adherence to secondary preventative medication after stroke. However, existing data is limited as several interventions, duration of follow-up, and various definitions were used. These findings need to be interpreted with caution

Predicting the likelihood of heart failure with a multi level risk assessment using decision tree

Heart failure comes in the top causes of death worldwide. The number of deaths from heart failure exceeds the number of deaths resulting from any other causes. Recent studies have focused on the use of machine learning techniques to develop predictive models that are able to predict the incidence of heart failure. The majority of these studies have used a binary output class, in which the prediction would be either the presence or absence of heart failure. In this study, a multi-level risk assessment of developing heart failure has been proposed, in which a five risk levels of heart failure can be predicted using C4.5 decision tree classifier. On the other hand, we are boosting the early prediction of heart failure through involving three main risk factors with the heart failure data set. Our predictive model shows an improvement on existing studies with 86.5% sensitivity, 95.5% specificity, and 86.53% accuracy

VCU-UNITE: Identifying Recognition Mechanisms for University-Community Engagement

The aims of the project were to determine what process would be appropriate to recognize significant contributions of university and community partners to joint community engagement projects. Our view was that several different award ceremonies exist in VCU, none of which are well attended and suggesting that this form of recognition may not be a high priority for participants. Thus, we sought to determine the awareness and extent of involvement of VCU faculty, staff and students in community engagement projects, and to find out what format of recognition process would be appealing to both university and community participants. We gathered this information through surveys and focus groups, analyzed the data and determined that university and community partners had differing views on what types of recognition would be desirous. Next, we designed a web portal through which nominations could be made by members of the university and by the community. We propose a streamlined nomination and online review process, leading to a quarterly award consisting of a letter of thanks from the Division of Community Engagement, and a photograph and narrative placed on the VCU website. Recipients of quarterly awards would automatically compete for an annual award, such as P&T credit or additional community leave time (university), or a scholarship, a plaque, or recognition at a VCU event (community)

Study of Small-Scale Anisotropy of Ultrahigh Energy Cosmic Rays Observed in Stereo by HiRes

The High Resolution Fly's Eye (HiRes) experiment is an air fluorescence detector which, operating in stereo mode, has a typical angular resolution of 0.6 degrees and is sensitive to cosmic rays with energies above 10^18 eV. HiRes is thus an excellent instrument for the study of the arrival directions of ultrahigh energy cosmic rays. We present the results of a search for anisotropies in the distribution of arrival directions on small scales (<5 degrees) and at the highest energies (>10^19 eV). The search is based on data recorded between 1999 December and 2004 January, with a total of 271 events above 10^19 eV. No small-scale anisotropy is found, and the strongest clustering found in the HiRes stereo data is consistent at the 52% level with the null hypothesis of isotropically distributed arrival directions.Comment: 4 pages, 3 figures. Matches accepted ApJL versio

Cn-AMP2 from green coconut water is an anionic anticancer peptide

Globally, death due to cancers is likely to rise to over 20 million by 2030,which has created an urgent need for novel approaches to anticancer therapies such as the development of host defence peptides. Cn-AMP2 (TESYFVFSVGM), an anionic host defence peptide from green coconut water of the plant Cocos nucifera, showed anti-proliferative activity against the 1321N1 and =U87MG human glioma cell lines with IC50 values of 1.25 and 1.85mM, respectively. The membrane interactive formof the peptide was found to be an extended conformation, which primarily included β-type structures (levels>45%) and random coil architecture (levels>45%). On the basis of these and other data, it is suggested that the short anionic N-terminal sequence(TES) of Cn-AMP2 interacts with positively charged moieties in the cancer cell membrane. Concomitantly, the long hydrophobic C-terminal sequence (YFVFSVGM) of the peptide penetrates the membrane core region, thereby driving the translocation of Cn-AMP2 across the cancer cell membrane to attack intracellular targets and induce anti-proliferative mechanisms. This work is the first to demonstrate that anionic host defence peptides have activity against human glioblastoma, which potentially provides an untapped source of lead compounds for development as novel agents in the treatment of these and other cancers. Copyright © 2014 European Peptide Society and John Wiley & Sons, Ltd

Supersymmetric Higgs Yukawa Couplings to Bottom Quarks at next-to-next-to-leading Order

The effective bottom Yukawa couplings are analyzed for the minimal supersymmetric extension of the Standard Model at two-loop accuracy within SUSY-QCD. They include the resummation of the dominant corrections for large values of tg(beta). In particular the two-loop SUSY-QCD corrections to the leading SUSY-QCD and top-induced SUSY-electroweak contributions are addressed. The residual theoretical uncertainties range at the per-cent level.Comment: 25 pages, 9 figures, added comments and references, typos corrected, results unchanged, published versio

Measurement of the Flux of Ultrahigh Energy Cosmic Rays from Monocular Observations by the High Resolution Fly's Eye Experiment

We have measured the cosmic ray spectrum above 10^17.2 eV using the two air fluorescence detectors of the High Resolution Fly's Eye observatory operating in monocular mode. We describe the detector, photo-tube and atmospheric calibrations, as well as the analysis techniques for the two detectors. We fit the spectrum to a model consisting of galactic and extra-galactic sources.Comment: 4 pages, 4 figures. Uses 10pt.rtx, amsmath.sty, aps.rtx, revsymb.sty, revtex4.cl

A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

Parents’ experiences of health visiting for children with Down syndrome

© MA Healthcare Limited.Children with Down syndrome have an increased likelihoodof experiencing serious health conditions. Health visitors canhave an important role in monitoring and promoting healthand development for young children with Down syndrome.This study aimed to explore parents’ experiences of healthvisiting services for children with Down syndrome. Twentyfour parents of children with Down syndrome aged 0–5 yearscompleted a brief questionnaire about the number and natureof visits from health visitors in the previous 12 months andtheir support needs. Some parents commented that otherprofessionals met the needs of their child, whereas others saidthat they would like more advice and support from healthvisitors. A further exploration of broader health serviceprovision, including health visiting, for young children withDown syndrome is needed.Peer reviewedFinal Accepted Versio