The new paradigm of hepatitis C therapy: integration of oral therapies into best practices.

Emerging data indicate that all-oral antiviral treatments for chronic hepatitis C virus (HCV) will become a reality in the near future. In replacing interferon-based therapies, all-oral regimens are expected to be more tolerable, more effective, shorter in duration and simpler to administer. Coinciding with new treatment options are novel methodologies for disease screening and staging, which create the possibility of more timely care and treatment. Assessments of histologic damage typically are performed using liver biopsy, yet noninvasive assessments of histologic damage have become the norm in some European countries and are becoming more widespread in the United States. Also in place are new Centers for Disease Control and Prevention (CDC) initiatives to simplify testing, improve provider and patient awareness and expand recommendations for HCV screening beyond risk-based strategies. Issued in 2012, the CDC recommendations aim to increase HCV testing among those with the greatest HCV burden in the United States by recommending one-time testing for all persons born during 1945-1965. In 2013, the United States Preventive Services Task Force adopted similar recommendations for risk-based and birth-cohort-based testing. Taken together, the developments in screening, diagnosis and treatment will likely increase demand for therapy and stimulate a shift in delivery of care related to chronic HCV, with increased involvement of primary care and infectious disease specialists. Yet even in this new era of therapy, barriers to curing patients of HCV will exist. Overcoming such barriers will require novel, integrative strategies and investment of resources at local, regional and national levels

Area-level deprivation and adiposity in children: is the relationship linear?

OBJECTIVE: It has been suggested that childhood obesity is inversely associated with deprivation, such that the prevalence is higher in more deprived groups. However, comparatively few studies actually use an area-level measure of deprivation, limiting the scope to assess trends in the association with obesity for this indicator. Furthermore, most assume a linear relationship. Therefore, the aim of this study was to investigate associations between area-level deprivation and three measures of adiposity in children: body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR). DESIGN: This is a cross-sectional study in which data were collected on three occasions a year apart (2005-2007). SUBJECTS: Data were available for 13,333 children, typically aged 11-12 years, from 37 schools and 542 lower super-output areas (LSOAs). MEASURES: Stature, mass and WC. Obesity was defined as a BMI and WC exceeding the 95th centile according to British reference data. WHtR exceeding 0.5 defined obesity. The Index of Multiple Deprivation affecting children (IDACI) was used to determine area-level deprivation. RESULTS: Considerable differences in the prevalence of obesity exist between the three different measures. However, for all measures of adiposity the highest probability of being classified as obese is in the middle of the IDACI range. This relationship is more marked in girls, such that the probability of being obese for girls living in areas at the two extremes of deprivation is around half that at the peak, occurring in the middle. CONCLUSION: These data confirm the high prevalence of obesity in children and suggest that the relationship between obesity and residential area-level deprivation is not linear. This is contrary to the 'deprivation theory' and questions the current understanding and interpretation of the relationship between obesity and deprivation in children. These results could help make informed decisions at the local level

Big Data Mining and Semantic Technologies: Challenges and Opportunities

Big data a term coined due to the explosion in the quantity and diversity of high frequency digital data which is having a potential for valuable insights has drawn the most attention in the area of research and development. Converting big data to actionable insights requires depth understanding of big data, its characteristics, challenges and current technological trends. A rise of big data is changing the existing data storage, management, processing and analytical mechanisms and leads to the new architecture/ecosystems to handle big data applications. This paper covers finding of our research study about big data characteristic, various types of analysis associated with it and basic big data types. First, we are presenting the big data study from data mining and analysis perspective and discuss the challenges and next, we present the result of research study on meaningful use of big data in the context of semantic technologies. Moreover, we discuss various case studies related to social media analysis and recent development trends to identify potential research directions for big data with semantic technologies. DOI: 10.17762/ijritcc2321-8169.150711

Study of Evolution of Framework’s for Measuring Economic Empowerment of Women

Literature circling around empowerment of women has been extensively studied to craft some significant methodological stand about the measurement of empowerment (Kabeer 2002).There is increasing acknowledgement that economically empowering women is vital both to gain women’s rights and to achieve wider development goals such as economic growth, education, poverty reduction, health, and welfare. This study therefore focuses on understanding the evolution of concept on women empowerment over the years and its importance. Alongside the changed definition of women empowerment, it extensively studies the various frameworks extended for measuring women’s economic empowerment. Finally, it concludes by deducing the major constructs or indictors that pay a pivotal role in measuring economic empowerment of women. It is through measurement of these constructs that effective policy can be formulated for effectively empowering women globally

Kinetic modelling of competition and depletion of shared miRNAs by competing endogenous RNAs

Non-conding RNAs play a key role in the post-transcriptional regulation of mRNA translation and turnover in eukaryotes. miRNAs, in particular, interact with their target RNAs through protein-mediated, sequence-specific binding, giving rise to extended and highly heterogeneous miRNA-RNA interaction networks. Within such networks, competition to bind miRNAs can generate an effective positive coupling between their targets. Competing endogenous RNAs (ceRNAs) can in turn regulate each other through miRNA-mediated crosstalk. Albeit potentially weak, ceRNA interactions can occur both dynamically, affecting e.g. the regulatory clock, and at stationarity, in which case ceRNA networks as a whole can be implicated in the composition of the cell's proteome. Many features of ceRNA interactions, including the conditions under which they become significant, can be unraveled by mathematical and in silico models. We review the understanding of the ceRNA effect obtained within such frameworks, focusing on the methods employed to quantify it, its role in the processing of gene expression noise, and how network topology can determine its reach.Comment: review article, 29 pages, 7 figure

Concurrent use of prescription drugs and herbal medicinal products in older adults: A systematic review

This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.The use of herbal medicinal products (HMPs) is common among older adults. However, little is known about concurrent use with prescription drugs as well as the potential interactions associated with such combinations. Objective Identify and evaluate the literature on concurrent prescription and HMPs use among older adults to assess prevalence, patterns, potential interactions and factors associated with this use. Methods Systematic searches in MEDLINE, PsycINFO, EMBASE, CINAHL, AMED, Web of Science and Cochrane from inception to May 2017 for studies reporting concurrent use of prescription medicines with HMPs in adults (≥65 years). Quality was assessed using the Joanna Briggs Institute checklists. The Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-Centre) three stage approach to mixed method research was used to synthesise data. Results Twenty-two studies were included. A definition of HMPs or what was considered HMP was frequently missing. Prevalence of concurrent use by older adults varied widely between 5.3% and 88.3%. Prescription medicines most combined with HMPs were antihypertensive drugs, beta blockers, diuretics, antihyperlipidemic agents, anticoagulants, analgesics, antihistamines, antidiabetics, antidepressants and statins. The HMPs most frequently used were: ginkgo, garlic, ginseng, St John’s wort, Echinacea, saw palmetto, evening primrose oil and ginger. Potential risks of bleeding due to use of ginkgo, garlic or ginseng with aspirin or warfarin was the most reported herb-drug interaction. Some data suggests being female, a lower household income and less than high school education were associated with concurrent use. Conclusion Prevalence of concurrent prescription drugs and HMPs use among older adults is substantial and potential interactions have been reported. Knowledge of the extent and manner in which older adults combine prescription drugs will aid healthcare professionals can appropriately identify and manage patients at risk.Peer reviewedFinal Published versio

Web-based monitoring tools for Resistive Plate Chambers in the CMS experiment at CERN

The Resistive Plate Chambers (RPC) are used in the CMS experiment at the trigger level and also in the standard offline muon reconstruction. In order to guarantee the quality of the data collected and to monitor online the detector performance, a set of tools has been developed in CMS which is heavily used in the RPC system. The Web-based monitoring (WBM) is a set of java servlets that allows users to check the performance of the hardware during data taking, providing distributions and history plots of all the parameters. The functionalities of the RPC WBM monitoring tools are presented along with studies of the detector performance as a function of growing luminosity and environmental conditions that are tracked over time

A Comprehensive Review On Anti-Microbial And Antioxidant Properties Of Betel Leaf

Piper betel L. is a member of the Piperaceae family, which is sometimes referred to as Paan. In Sri Lanka, India, Thailand, Taiwan, and other Southeast Asian nations, it is widely grown.The leaves have a caustic, bittersweet, spicy, and somewhat sweet flavor. It contains a significant number of biomolecules with a range of pharmacological actions, including laxative, carminative, stomachic, anti-elminthic, tonic, and aphrodisiac properties. The leaves are used to treat a variety of conditions, including styptic, bronchitis, ozoena, cough, and foul-smelling mouth. They also clear the throat. In the current investigation, four distinct extracts of piper betel leaves (water, methanol, ethyl acetate, and petroleum ether) were evaluated against four distinct pathogenic bacteria: Escherichia coli, Proteus vulgaris, Staphylococcus aureus, and Streptococcus pyogenes. This current review showed that betel leaves extract, essential oil could inhibit microbial growth and kill various Gram-negative and Gram-positive bacteria as well as fungal species, including those that are multidrug-resistant and cause serious infectious diseases

The convergence of budding reckoning Soft computing technologies

Soft Computing methodologies represents the amalgamation of promising problem - solving technologies such as Neural Networks (NNs), Fuzzy Logic (FL), Probabilistic Reasoning (PR) and Genetic Algorithms (GAs) . We present a collection of tools and methods that can be used to perform diagnostics, estimation, and control. These tools are an enormous match for real - world applications that are characterized by imprecise, uncertain data and incomplete domain knowledge. Each of these technologies offer us with complementary reasoning and sear ching methods to solve complex problems. In this paper after a brief description of each of these technologies, we will analyze some of their most useful combinations, such as the use of FL to control GAs and NNs parameters; the application of GAs to evolv e NNs or to tune FL controllers; and the implementation of FL controllers as NNs tuned by back propagation - type algorithms . We summarize the recompense of SC techniques and in particular the synergy derived from the use of hybrid SC system