Genetic and Geo-Epidemiological Analysis of the Zika Virus Pandemic; Learning Lessons from the Recent Ebola Outbreak

“Outbreak” is a term referring to a virus or a parasite that is transmitted very aggressively and therefore could potentially cause fatalities, as the recent Ebola and Zika epidemics did. Nevertheless, looking back through history, quite a few outbreaks have been reported, which turned out so deadly that essentially changed, molded and literally re-shaped the society as it is today. In the present chapter, differences and similarities between the two most recent outbreaks have been studied, in order to pinpoint and design a trace model that will allow us to draw some conclusions for the connection of those two epidemics. Due to the high dimensionality of the problem, modern and state of the art geo-epidemiological methods have been used in an effort to provide the means necessary to establish the abovementioned model. It is only through geo-epidemiological analysis that it is possible to analyze concurrently a multitude of variables, such as genetic, environmental, behavioral, socioeconomic and a series of related infection risk factors

Impacts of The Radiation Environment At L2 On Bolometers Onboard The Herschel Space Observatory

We present the effects of cosmic rays on the detectors onboard the Herschel satellite. We describe in particular the glitches observed on the two types of cryogenic far- infrared bolometer inside the two instruments PACS and SPIRE. The glitch rates are also reported since the launch together with the SREM radiation monitors aboard Herschel and Planck spacecrafts. Both have been injected around the Lagrangian point L2 on May 2009. This allows probing the radiation environment around this orbit. The impacts on the observation are finally summarized.Comment: 8 pages, 13 figures, 2 images, Author Keywords: Bolometers, Infrared detectors, cryogenics, radiation effects, submillimeter wave technology IEEE Terms: Bolometers, Detectors, Instruments, Picture archiving and communication systems, Protons, Silicon, Space vehicles; Radiation and Its Effects on Components and Systems (RADECS), 2011 12th European Conference. Conference location: Sevilla. Date of Conference: 19-23 Sept. 2011. Session H: Radiation Environment: Space, Atmospheric and Terrestrial (PH2

Protein phosphorylation prediction: limitations, merits and pitfalls

Protein phosphorylation is a major protein post-translational modification process that plays a pivotal role in numerous cellular processes, such as recognition, signaling or degradation. It can be studied experimentally by various methodologies, including western blot analysis, site-directed mutagenesis, 2D gel electrophoresis, mass spectrometry etc. A number of in silico tools have also been developed in order to predict plausible phosphorylation sites in a given protein. In this review, we conducted a benchmark study including the leading protein phosphorylation prediction software, in an effort to determine which performs best. The first place was taken by GPS 2.2, having predicted all phosphorylation sites with a 83% fidelity while in second place came NetPhos 2.0 with 69%.  

A series of Notch3 mutations in CADASIL; insights from 3D molecular modelling and evolutionary analyses

CADASIL disease belongs to the group of rare diseases. It is well established that the Notch3 protein is primarily responsible for the development of CADASIL syndrome. Herein, we attempt to shed light to the actual molecular mechanism underlying CADASIL via insights that we have from preliminary in silico and proteomics studies on the Notch3 protein. At the moment, we are aware of a series of Notch3 point mutations that promote CADASIL. In this direction, we investigate the nature, extent, physicochemical and structural significance of the mutant species in an effort to identify the underlying mechanism of Notch3 role and implications in cell signal transduction. Overall, our in silico study has revealed a rather complex molecular mechanism of Notch3 on the structural level; depending of the nature and position of each mutation, a consensus significant loss of beta-sheet structure is observed throughout all in silico modeled mutant/wild type biological systems

Molecular dynamics simulations through GPU video games technologies

Bioinformatics is the scientific field that focuses on the application of computer technology to the management of biological information. Over the years, bioinformatics applications have been used to store, process and integrate biological and genetic information, using a wide range of methodologies. One of the most de novo techniques used to understand the physical movements of atoms and molecules is molecular dynamics (MD). MD is an in silico method to simulate the physical motions of atoms and molecules under certain conditions. This has become a state strategic technique and now plays a key role in many areas of exact sciences, such as chemistry, biology, physics and medicine. Due to their complexity, MD calculations could require enormous amounts of computer memory and time and therefore their execution has been a big problem. Despite the huge computational cost, molecular dynamics have been implemented using traditional computers with a central memory unit (CPU). A graphics processing unit (GPU) computing technology was first designed with the goal to improve video games, by rapidly creating and displaying images in a frame buffer such as screens. The hybrid GPU-CPU implementation, combined with parallel computing is a novel technology to perform a wide range of calculations. GPUs have been proposed and used to accelerate many scientific computations including MD simulations. Herein, we describe the new methodologies developed initially as video games and how they are now applied in MD simulations

Insights into the molecular mechanisms of stress and inflammation in ageing and frailty of the elderly

Frailty is a natural state of physical, cognitive and mental decline that is expected in the elderly. The role of inflammation in the pathogenesis of frailty has been hypothesized, and so far many studies have been performed in order to understand the mechanism of action underlying this association. Recent studies support this hypothesis and show a clear association between inflammation, frailty, and age-related disease. Chronic inflammation is key pathophysiologic process that contributes to the frailty directly and indirectly through other intermediate physiologic systems, such as the musculoskeletal, endocrine, and hematologic systems. The complex multifactorial etiologies of frailty also include obesity and other age-related specific diseases. Herein, we investigate the link between chronic inflammation and frailty of the older people. In particular, we present an up-to-date review of the role of cytokines, interleukins, cardiovascular abnormalities, chronic high blood pressure, hyperlipidemia and diabetes in relation to the severity of frailty in the elderly

HCV genetics and genotypes dictate future antiviral strategies

At the end of the 1980s, the hepatitis C virus (HCV) was cloned and formally identified as the cause of the majority of non-A and non-B hepatitis cases. Today, around 170 million people worldwide are infected with HCV, making it five times more common than infection with the human immunodeficiency virus (HIV).  Several methods exist which mediate the spread of infection. One of the most common and efficient is sharing or re-using injecting equipment; studies have indicated that 80-90% of individuals in some populations of intravenous drug users test positive in serum HCV assays. Contracting HCV from infected blood transfusions was also a major cause of infection before screening tests were introduced in the early 1990s.  Other possible, but less common, methods of infection transmission include mother-to-child during pregnancy, sexual contact and nosocomial acquisition (for example between surgical or dialysis patients).  It appears that concurrent HIV-1 infection increases the risk of HCV transmission via the mother-to-child or sexual routes

Estimation of a semiparametric recursive bivariate probit model with nonparametric mixing

We consider an extension of the recursive bivariate probit model for estimating the effect of a binary variable on a binary outcome in the presence of unobserved confounders, nonlinear covariate effects and overdispersion. Specifically, the model consists of a system of two binary outcomes with a binary endogenous regressor which includes smooth functions of covariates, hence allowing for flexible functional dependence of the responses on the continuous regressors, and arbitrary random intercepts to deal with overdispersion arising from correlated observations on clusters or from the omission of non-confounding covariates. We fit the model by maximizing a penalized likelihood using an Expectation-Maximisation algorithm. The issues of automatic multiple smoothing parameter selection and inference are also addressed. The empirical properties of the proposed algorithm are examined in a simulation study. The method is then illustrated using data from a survey on health, aging and wealth