Monitoring response to hepatitis B and C in EU/EEA: testing policies, availability of data on care cascade and chronic viral hepatitis-related mortality – results from two surveys (2016)

Objectives: The World Health Organization (WHO) developed a European Regional Action Plan (EAP) to fast-track action towards the goal of eliminating viral hepatitis. Robust monitoring is essential to assess national programme performance. The purpose of this study was to assess the availability of selected monitoring data sources in European Union/European Economic Area (EU/EEA) Member States (MS). Methods: Availability of data sources at EU/EEA level was assessed using two surveys distributed to 31 EU/EEA MS in 2016. The two surveys covered (A) availability of policy documents on testing; testing practices and monitoring; monitoring of diagnosis and treatment initiation, and; (B) availability of data on mortality attributable to chronic viral hepatitis. Results: Just over two-thirds of EU/EEA MS responded to the surveys. 86% (18/21) reported national testing guidance covering HBV, and 81% (17/21) covering HCV; while 33% (7/21) and 38% (8/21) of countries, respectively, monitored the number of tests performed. 71% (15/21) of countries monitored the number of chronic HBV cases diagnosed and 33% (7/21) the number of people treated. Corresponding figures for HCV were 48% (10/21) and 57% (12/21). 27% (6/22) of countries reported availability of data on mortality attributable to chronic viral hepatitis. Conclusions: The results of this study suggest that sources of information in EU/EEA Member States to monitor the progress towards the EAP milestones and targets related to viral hepatitis diagnosis, cascade of care and attributable mortality are limited. Our analysis should raise awareness among EU/EEA policy makers and stimulate higher prioritisation of efforts to improve the monitoring of national viral hepatitis programmes

Heavy Schistosomiasis Associated With Poor Short-Term Memory and Slower Reaction Times in Tanzania Schoolchildren

Cross-sectional studies of the relationship between helminth infection and cognitive function can be informative in ways that treatment studies cannot. However, interpretation of results of many previous studies has been complicated by the failure to control for many potentially confounding variables.We gave Tanzanian schoolchildren aged 9±14 a battery of 11 cognitive and three educational tests and\ud assessed their level of helminth infection. We also took measurements of an extensive range of potentially confounding or mediating factors such as socioeconomic and educational factors, anthropometric and other biomedical measures. A total of 272 children were moderately or heavily\ud infected with Schistosoma haematobium, hookworm or both helminth species and 117 were uninfected with either species. Multiple regression analyses, controlling for all confounding and mediating variables, revealed that children with a heavy S. haematobium infection had signi®cantly lower scores than uninfected children on two tests of verbal short-term memory and two reaction time tasks. In one of\ud these tests the effect was greatest for children with poor nutritional status. There was no association between infection and educational achievement, nor between moderate infection with either species of helminth and performance on the cognitive tests. We conclude that children with heavy worm burdens and poor nutritional status are most likely to suffer cognitive impairment, and the domains of verbal\ud short-term memory and speed of information processing are those most likely to be affected

Alzheimer's Disease Prediction Using Longitudinal and Heterogeneous Magnetic Resonance Imaging

Recent evidence has shown that structural magnetic resonance imaging (MRI) is an effective tool for Alzheimer's disease (AD) prediction and diagnosis. While traditional MRI-based diagnosis uses images acquired at a single time point, a longitudinal study is more sensitive and accurate in detecting early pathological changes of the AD. Two main difficulties arise in longitudinal MRI-based diagnosis: (1) the inconsistent longitudinal scans among subjects (i.e., different scanning time and different total number of scans); (2) the heterogeneous progressions of high-dimensional regions of interest (ROIs) in MRI. In this work, we propose a novel feature selection and estimation method which can be applied to extract features from the heterogeneous longitudinal MRI. A key ingredient of our method is the combination of smoothing splines and the $l_1$-penalty. We perform experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The results corroborate the advantages of the proposed method for AD prediction in longitudinal studies

Zika virus: New clinical syndromes and its emergence in the western hemisphere

Zika virus (ZIKV) had remained a relatively obscure flavivirus until a recent series of outbreaks accompanied by unexpectedly severe clinical complications brought this virus into the spotlight as causing an infection of global public health concern. In this review, we discuss the history and epidemiology of ZIKV infection, recent outbreaks in Oceania and the emergence of ZIKV in the Western Hemisphere, newly ascribed complications of ZIKV infection, including Guillain-Barré syndrome and microcephaly, potential interactions between ZIKV and dengue virus, and the prospects for the development of antiviral agents and vaccines

Progress Notes : a report from the Parkinson's Disease Center at Boston University Medical Center

News and updates from the Boston University Medical Center, Parkinson's Disease Cente

Progress Notes : a report from the Parkinson's Disease Center at Boston University Medical Center

News and updates from the Boston University Medical Center Parkinson's Disease Cente

Progress Notes : a report from the Parkinson's Disease Center at Boston University Medical Center

News and updates from the Boston University Medical Center Parkinson's Disease Cente

Fast identification of biological pathways associated with a quantitative trait using group lasso with overlaps.

Where causal SNPs (single nucleotide polymorphisms) tend to accumulate within biological pathways, the incorporation of prior pathways information into a statistical model is expected to increase the power to detect true associations in a genetic association study. Most existing pathways-based methods rely on marginal SNP statistics and do not fully exploit the dependence patterns among SNPs within pathways.We use a sparse regression model, with SNPs grouped into pathways, to identify causal pathways associated with a quantitative trait. Notable features of our "pathways group lasso with adaptive weights" (P-GLAW) algorithm include the incorporation of all pathways in a single regression model, an adaptive pathway weighting procedure that accounts for factors biasing pathway selection, and the use of a bootstrap sampling procedure for the ranking of important pathways. P-GLAW takes account of the presence of overlapping pathways and uses a novel combination of techniques to optimise model estimation, making it fast to run, even on whole genome datasets.In a comparison study with an alternative pathways method based on univariate SNP statistics, our method demonstrates high sensitivity and specificity for the detection of important pathways, showing the greatest relative gains in performance where marginal SNP effect sizes are small