Data on the management of atrial fibrillation (AF) in the Balkan Region are limited. The Serbian AF Association (SAFA) prospectively investigated contemporary ‘real-world’ AF management in clinical practice in Albania, Bosnia&Herzegovina, Bulgaria, Croatia, Montenegro, Romania and Serbia through a 14-week (December 2014-February 2015) prospective, multicentre survey of consecutive AF patients. We report the results pertinent to stroke prevention strategies. Of 2712 enrolled patients, 2663 (98.2%) with complete data were included in this analysis (mean age 69.1 ± 10.9 years, female 44.6%). Overall, 1960 patients (73.6%) received oral anticoagulants (OAC) and 762 (28.6%) received antiplatelet drugs. Of patients given OAC, 17.2% received non-vitamin K antagonist oral anticoagulants (NOACs). CHA2DS2-VASc score was not significantly associated with OAC use. Of the ‘truly low-risk’ patients (CHA2DS2-VASc = 0 [males], or 1 [females]) 56.5% received OAC. Time in Therapeutic Range (TTR) was available in only 18.7% of patients (mean TTR: 49.5% ± 22.3%). Age ≥ 80 years, prior myocardial infarction and paroxysmal AF were independent predictors of OAC non-use. Our survey shows a relatively high overall use of OAC in AF patients, but with low quality of vitamin K antagonist therapy and insufficient adherence to AF guidelines. Additional efforts are needed to improve AF-related thromboprophylaxis in clinical practice in the Balkan Region.

We introduce the nested canalyzing depth of a function, which measures the extent to which it retains a nested canalyzing structure. We characterize the structure of functions with a given depth and compute the expected activities and sensitivities of the variables. This analysis quantifies how canalyzation leads to higher stability in Boolean networks. It generalizes the notion of nested canalyzing functions (NCFs), which are precisely the functions with maximum depth. NCFs have been proposed as gene regulatory network models, but their structure is frequently too restrictive and they are extremely sparse. We find that functions become decreasingly sensitive to input perturbations as the canalyzing depth increases, but exhibit rapidly diminishing returns in stability. Additionally, we show that as depth increases, the dynamics of networks using these functions quickly approach the critical regime, suggesting that real networks exhibit some degree of canalyzing depth, and that NCFs are not significantly better than functions of sufficient depth for many applications of the modeling and reverse engineering of biological networks.

An increasing number of algorithms for biochemical network inference from experimental data require discrete data as input. For example, dynamic Bayesian network methods and methods that use the framework of finite dynamical systems, such as Boolean networks, all take discrete input. Experimental data, however, are typically continuous and represented by computer floating point numbers. The translation from continuous to discrete data is crucial in preserving the variable dependencies and thus has a significant impact on the performance of the network inference algorithms. We compare the performance of two such algorithms that use discrete data using several different discretization algorithms. One of the inference methods uses a dynamic Bayesian network framework, the other-a time-and state-discrete dynamical system framework. The discretization algorithms are quantile, interval discretization, and a new algorithm introduced in this article, SSD. SSD is especially designed for short time series data and is capable of determining the optimal number of discretization states. The experiments show that both inference methods perform better with SSD than with the other methods. In addition, SSD is demonstrated to preserve the dynamic features of the time series, as well as to be robust to noise in the experimental data. A C++ implementation of SSD is available from the authors at http://polymath.vbi.vt.edu/discretization .

By means of satellite telemetry, the migrations of three young Egyptian vultures (Neophron percnopterus) from France and Bulgaria were studied and data obtained (over 4,300 Argos locations) to describe movement patterns, timing of migration, routes followed, speed of flight and ranging behaviour in Africa.

IntroductionData on management of atrial fibrillation (AF) in the Balkan Region are scarce. To capture the patterns in AF management in contemporary clinical practice in the Balkan countries a prospective survey was conducted between December 2014 and February 2015, and we report results pertinent to the use of non-vitamin K antagonist oral anticoagulants (NOACs).MethodsA 14-week prospective, multicenter survey of consecutive AF patients seen by cardiologists or internal medicine specialists was conducted in Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Montenegro, Romania, and Serbia (a total of about 50 million inhabitants).ResultsOf 2712 enrolled patients, 2663 (98.2%) had complete data relevant to oral anticoagulant (OAC) use (mean age 69.1 ± 10.9 years, female 44.6%). Overall, OAC was used in 1960 patients (73.6%) of whom 338 (17.2%) received NOACs. Malignancy [odds ratio (OR), 95% confidence interval (CI) 2.06, 1.20–3.56], rhythm control (OR 1.64, 1.25–2.16), and treatment by cardiologists were independent predictors of NOAC use (OR 2.32, 1.51–3.54) [all p < 0.01)], whilst heart failure and valvular disease were negatively associated with NOAC use (both p < 0.01). Individual stroke and bleeding risk were not significantly associated with NOAC use on multivariate analysis.ConclusionsNOACs are increasingly used in AF patients in the Balkan Region, but NOAC use is predominantly guided by factors other than evidence-based decision-making (e.g., drug availability on the market or reimbursement policy). Efforts are needed to establish an evidence-based approach to OAC selection and to facilitate the optimal use of OAC, thus improving the outcomes in AF patients in this large region.Electronic supplementary materialThe online version of this article (doi:10.1007/s12325-017-0589-5) contains supplementary material, which is available to authorized users.

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Boolean networks are an important class of computational models for molecular interaction networks. Boolean canalization, a type of hierarchical clustering of the inputs of a Boolean function, has been extensively studied in the context of network modeling where each layer of canalization adds a degree of stability in the dynamics of the network. Recently, dynamic network control approaches have been used for the design of new therapeutic interventions and for other applications such as stem cell reprogramming. This work studies the role of canalization in the control of Boolean molecular networks. It provides a method for identifying the potential edges to control in the wiring diagram of a network for avoiding undesirable state transitions. The method is based on identifying appropriate input-output combinations on undesirable transitions that can be modified using the edges in the wiring diagram of the network. Moreover, a method for estimating the number of changed transitions in the state space of the system as a result of an edge deletion in the wiring diagram is presented. The control methods of this paper were applied to a mutated cell-cycle model and to a p53-mdm2 model to identify potential control targets.

Boolean networks have long been used as models of molecular networks and play an increasingly important role in systems biology. This paper describes a software package, Polynome, offered as a web service, that helps users construct Boolean network models based on experimental data and biological input. The key feature is a discrete analog of parameter estimation for continuous models. With only experimental data as input, the software can be used as a tool for reverse-engineering of Boolean network models from experimental time course data.Comment: Web interface of the software is available at http://polymath.vbi.vt.edu/polynome