The interplay of intrinsic and extrinsic bounded noises in genetic networks

After being considered as a nuisance to be filtered out, it became recently clear that biochemical noise plays a complex role, often fully functional, for a genetic network. The influence of intrinsic and extrinsic noises on genetic networks has intensively been investigated in last ten years, though contributions on the co-presence of both are sparse. Extrinsic noise is usually modeled as an unbounded white or colored gaussian stochastic process, even though realistic stochastic perturbations are clearly bounded. In this paper we consider Gillespie-like stochastic models of nonlinear networks, i.e. the intrinsic noise, where the model jump rates are affected by colored bounded extrinsic noises synthesized by a suitable biochemical state-dependent Langevin system. These systems are described by a master equation, and a simulation algorithm to analyze them is derived. This new modeling paradigm should enlarge the class of systems amenable at modeling. We investigated the influence of both amplitude and autocorrelation time of a extrinsic Sine-Wiener noise on: $(i)$ the Michaelis-Menten approximation of noisy enzymatic reactions, which we show to be applicable also in co-presence of both intrinsic and extrinsic noise, $(ii)$ a model of enzymatic futile cycle and $(iii)$ a genetic toggle switch. In $(ii)$ and $(iii)$ we show that the presence of a bounded extrinsic noise induces qualitative modifications in the probability densities of the involved chemicals, where new modes emerge, thus suggesting the possibile functional role of bounded noises

Study of hadronic event-shape variables in multijet final states in pp collisions at √s=7 TeV

Peer reviewe

Constraints on parton distribution functions and extraction of the strong coupling constant from the inclusive jet cross section in pp collisions at √s=7 TeV

Peer reviewe

Search for new physics in the multijet and missing transverse momentum final state in proton-proton collisions at √s=8 Tev

Peer reviewe

Nutraceutical therapies for atherosclerosis

Atherosclerosis is a chronic inflammatory disease affecting large and medium arteries and is considered to be a major underlying cause of cardiovascular disease (CVD). Although the development of pharmacotherapies to treat CVD has contributed to a decline in cardiac mortality in the past few decades, CVD is estimated to be the cause of one-third of deaths globally. Nutraceuticals are natural nutritional compounds that are beneficial for the prevention or treatment of disease and, therefore, are a possible therapeutic avenue for the treatment of atherosclerosis. The purpose of this Review is to highlight potential nutraceuticals for use as antiatherogenic therapies with evidence from in vitro and in vivo studies. Furthermore, the current evidence from observational and randomized clinical studies into the role of nutraceuticals in preventing atherosclerosis in humans will also be discussed

Linear mapping approximation of gene regulatory networks with stochastic dynamics

The intractability of most stochastic models of gene regulatory networks (GRNs) limits their utility. Here, the authors present a linear-mapping approximation mapping models onto simpler ones, giving approximate but accurate analytic or semi- analytic solutions for a wide range of model GRNs

A simple and rapid flow cytometry-based assay to identify a competent embryo prior to embryo transfer

Multiple pregnancy is a risk for prematurity and preterm birth. The goal of assisted reproduction is to achieve a single pregnancy, by transferring a single embryo. This requires improved methods to identify the competent embryo. Here, we describe such a test, based on flow cytometric determination of the nucleic acid (PI+) containing extracellular vesicle (EV) count in day 5 embryo culture media. 88 women undergoing IVF were included in the study. More than 1 embryos were transferred to most patients. In 58 women, the transfer resulted in clinical pregnancy, whereas in 30 women in implantation failure. In 112 culture media of embryos from the "clinical pregnancy" group, the number of PI+ EVs was significantly lower than in those of 49 embryos, from the "implantation failure" group. In 14 women, transfer of a single embryo resulted in a singleton pregnancy, or, transfer of two embryos in twin pregnancy. The culture media of 19 out of the 20 "confirmed competent" embryos contained a lower level of PI+ EVs than the cut off level, suggesting that the competent embryo can indeed be identified by low PI+ EV counts. We developed a noninvasive, simple, inexpensive, quick test, which identifies the embryos that are most likely to implant

A Dominated Coupling From The Past algorithm for the stochastic simulation of networks of biochemical reactions

<p>Abstract</p> <p>Background</p> <p>In recent years, stochastic descriptions of biochemical reactions based on the Master Equation (ME) have become widespread. These are especially relevant for models involving gene regulation. Gillespie’s Stochastic Simulation Algorithm (SSA) is the most widely used method for the numerical evaluation of these models. The SSA produces exact samples from the distribution of the ME for finite times. However, if the stationary distribution is of interest, the SSA provides no information about convergence or how long the algorithm needs to be run to sample from the stationary distribution with given accuracy. </p> <p>Results</p> <p>We present a proof and numerical characterization of a Perfect Sampling algorithm for the ME of networks of biochemical reactions prevalent in gene regulation and enzymatic catalysis. Our algorithm combines the SSA with Dominated Coupling From The Past (DCFTP) techniques to provide guaranteed sampling from the stationary distribution. The resulting DCFTP-SSA is applicable to networks of reactions with uni-molecular stoichiometries and sub-linear, (anti-) monotone propensity functions. We showcase its applicability studying steady-state properties of stochastic regulatory networks of relevance in synthetic and systems biology.</p> <p>Conclusion</p> <p>The DCFTP-SSA provides an extension to Gillespie’s SSA with guaranteed sampling from the stationary solution of the ME for a broad class of stochastic biochemical networks.</p

Tonic Shock Induces Detachment of Giardia lamblia

The single-celled organism Giardia lamblia colonizes the small intestine of a wide variety of hosts, including humans. Giardiasis infections can cause severe gastrointestinal symptoms and pose a major health concern in the developing world. Giardia are known to attach robustly to a variety of surfaces, but the conditions that influence this attachment are not known. In this study, we examined the behavior of attached Giardia parasites exposed to rapid changes in solution properties, like those Giardia might encounter in the intestine. After systematically varying media concentration and composition, we found that only one solution property caused rapid detachment of Giardia cells: tonicity, which is a measure of the total concentration of solutes in the solution that are unable to pass through a semi-permeable membrane (here, the cell membrane of Giardia). We found similar results for Giardia initially attached to monolayers of intestinal cells. Giardia cells remaining attached after a change in tonicity are able to adapt to the change, highlighting the general ability of this organism to weather normal changes in the intestinal environment. We propose that Giardia's susceptibility to large changes in tonicity could be explored as a possible new route for treatment of giardiasis

A database of antimalarial drug resistance

A large investment is required to develop, license and deploy a new antimalarial drug. Too often, that investment has been rapidly devalued by the selection of parasite populations resistant to the drug action. To understand the mechanisms of selection, detailed information on the patterns of drug use in a variety of environments, and the geographic and temporal patterns of resistance is needed. Currently, there is no publically-accessible central database that contains information on the levels of resistance to antimalaria drugs. This paper outlines the resources that are available and the steps that might be taken to create a dynamic, open access database that would include current and historical data on clinical efficacy, in vitro responses and molecular markers related to drug resistance in Plasmodium falciparum and Plasmodium vivax. The goal is to include historical and current data on resistance to commonly used drugs, like chloroquine and sulfadoxine-pyrimethamine, and on the many combinations that are now being tested in different settings. The database will be accessible to all on the Web. The information in such a database will inform optimal utilization of current drugs and sustain the longest possible therapeutic life of newly introduced drugs and combinations. The database will protect the valuable investment represented by the development and deployment of novel therapies for malaria