284 resultados para range interactions


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Many complex systems may be described by not one but a number of complex networks mapped on each other in a multi-layer structure. Because of the interactions and dependencies between these layers, the state of a single layer does not necessarily reflect well the state of the entire system. In this paper we study the robustness of five examples of two-layer complex systems: three real-life data sets in the fields of communication (the Internet), transportation (the European railway system), and biology (the human brain), and two models based on random graphs. In order to cover the whole range of features specific to these systems, we focus on two extreme policies of system's response to failures, no rerouting and full rerouting. Our main finding is that multi-layer systems are much more vulnerable to errors and intentional attacks than they appear from a single layer perspective.

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We have used genetic and molecular techniques to investigate the interactions among genes required for the initiation and regulation of septum formation in Schizosaccharomyces pombe. Our data suggest that the products of the cdc7, cdc11, cdc14 and cdc16 genes interact. These activities may regulate the function of the cdc15 gene product. A model for the control of septation in fission yeast is presented.

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BACKGROUND: Potential drug-drug interactions (PDDIs) might expand with new combination antiretroviral therapies (ART) and polypharmacy related to increasing age and comorbidities. We investigated the prevalence of comedications and PDDIs within a large HIV cohort, and their effect on ART efficacy and tolerability. METHODS: All medications were prospectively recorded in 1,497 ART-treated patients and screened for PDDIs using a customized version of the Liverpool drug interactions database. RESULTS: Overall, 68% (1,013/1,497) of patients had a comedication and 40% (599/1,497) had > or = 1 PDDI. Among patients with comedication, 2% (21/1,013) had red-flag interactions (contraindicated) and 59% (597/1,013) had orange-flag interactions (potential dose adjustment and/or close monitoring required). The latter involved mainly central nervous system drugs (49%), cardiovascular drugs (34%) and methadone (19%). In the multivariate analysis, factors associated with having a comedication were advanced age, female gender, obesity and HCV infection. Independent risk factors for PDDIs were regimens combining protease inhibitors and non-nucleoside reverse transcriptase inhibitors (odds ratio [OR] 3.06, 95% confidence interval [CI] 1.44-6.48), > or = 2 comedications (OR 1.89, 95% CI 1.32-2.70), current illicit drug use (OR 2.00, 95% CI 1.29-3.10) and patients with HCV infection (OR 1.74, 95% CI 1.19-2.56). Viral response was similar in patients with and without PDDIs (84.5% versus 86.4%; P=0.386). During follow-up, ART was modified in 134 patients with comedication regardless of the presence of PDDIs (P=0.524). CONCLUSIONS: PDDIs increase with complex ART and comorbidities. No adverse effect was noted on ART efficacy or tolerability; however, most PDDIs affected comedication but were manageable through dose adjustment or monitoring.

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We report nine cases where fluoxetine (FX) (20 mg/day) was added to maintenance treatment with methadone (MTD) (dose range: 30-100 mg) in addicts with affective disorders. MTD plasma levels were measured before and after treatment with FX under steady-state conditions. Among the nine patients, two also received fluvoxamine (FLVX) at different times. Although it is possible that in some patients a moderate FX-MTD interaction occurs, resulting in increased plasma levels of MTD, this interaction is certainly less marked than that between FLVX and MTD and unlikely to have clinical consequences.

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Hypertension affects approximately 1 billion people worldwide. Owing to population aging, hypertension-related cardiovascular burden is expected to rise in the near future. In addition to genetic variants influencing the blood pressure response to antihypertensive drugs, several genes encoding for drug-metabolizing or -transporting enzymes have been associated with blood pressure and/or hypertension in humans (e.g., ACE, CYP1A2, CYP3A5, ABCB1 and MTHFR) regardless of drug treatment. These genes are also involved in the metabolism and transport of endogenous substances and their effects may be modified by selected environmental factors, such as diet or lifestyle. However, little is currently known on the complex interplay between environmental factors, endogenous factors, genetic variants and drugs on blood pressure control. This review will discuss the respective role of population-based primary prevention and personalized medicine for arterial hypertension, taking a pharmacogenomics' perspective focusing on selected pharmacogenes.

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Universal standard goniometer is an essential tool to measure articulations' range of motion (ROM). In this time of technological advances and increasing use of smartphones, new measurement's tools appear as specific smartphone applications. This article compares the iOS application "Knee Goniometer" with universal standard goniometer to assess knee ROM. To our knowledge, this is the first study that uses a goniometer application in a clinical context. The purpose of this study is to determine if this application could be used in clinical practice.

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We survey the population genetic basis of social evolution, using a logically consistent set of arguments to cover a wide range of biological scenarios. We start by reconsidering Hamilton's (Hamilton 1964 J. Theoret. Biol. 7, 1-16 (doi:10.1016/0022-5193(64)90038-4)) results for selection on a social trait under the assumptions of additive gene action, weak selection and constant environment and demography. This yields a prediction for the direction of allele frequency change in terms of phenotypic costs and benefits and genealogical concepts of relatedness, which holds for any frequency of the trait in the population, and provides the foundation for further developments and extensions. We then allow for any type of gene interaction within and between individuals, strong selection and fluctuating environments and demography, which may depend on the evolving trait itself. We reach three conclusions pertaining to selection on social behaviours under broad conditions. (i) Selection can be understood by focusing on a one-generation change in mean allele frequency, a computation which underpins the utility of reproductive value weights; (ii) in large populations under the assumptions of additive gene action and weak selection, this change is of constant sign for any allele frequency and is predicted by a phenotypic selection gradient; (iii) under the assumptions of trait substitution sequences, such phenotypic selection gradients suffice to characterize long-term multi-dimensional stochastic evolution, with almost no knowledge about the genetic details underlying the coevolving traits. Having such simple results about the effect of selection regardless of population structure and type of social interactions can help to delineate the common features of distinct biological processes. Finally, we clarify some persistent divergences within social evolution theory, with respect to exactness, synergies, maximization, dynamic sufficiency and the role of genetic arguments.

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Two distinct, TATA box-containing promoters regulate the transcriptional activity of the Xenopus vitellogenin A1 gene. These two promoters are of different strength and are separated by 1.8 kilobase pairs of untranslated sequence. Estrogen receptor (ER) and its ligand, 17beta-estradiol, induce the activity of both promoters. The estrogen response elements (EREs) are located proximal to the downstream i promoter while no ERE-like sequences have been identified in the vicinity of the upstream io promoter. We show here, that transcriptional activity of the upstream io promoter is Sp1-dependent. Moreover, we demonstrate that estrogen inducibility of the io promoter results from functional interactions between the io bound Sp1 and the ER bound at the proximity of i. Functional interactions between Sp1 and ER do not require the presence of a TATA box for transcriptional activation, as is demonstrated using the acyl-CoA oxidase promoter. The relative positions that ER and Sp1 occupy with respect to the initiation site determines whether these two transcription activators can synergize for transcription initiation.