Etravirine is a novel nonnucleoside reverse transcriptase inhibitor (NNRTI) for the treatment of HIV-1 infections. ABC transporters potentially mediate clinically relevant drug-drug interactions. We assessed substrate characteristics and the inhibitory and inductive potential of etravirine on ABC transporters. Etravirine did not inhibit P-gp/ABCB1 and was not transported by the tested ABC trans...

Artificial bee colony (ABC) algorithm invented recently by Karaboga is a biological-inspired optimization algorithm, which has been shown to be competitive with some conventional biological-inspired algorithms, such as genetic algorithm (GA), differential evolution (DE) and particle swarm optimization (PSO). However, there is still an insufficiency in ABC algorithm regarding its solution search...

Artificial bee colony (ABC) algorithm is a swarm intelligence optimization algorithm inspired by the intelligent behavior of honey bees when searching for food sources. The various versions of the ABC algorithm have been widely used to solve continuous and discrete optimization problems in different fields. In this paper a new binary version of the ABC algorithm inspired by quantum computing, c...

QUESTIONS UNDER STUDY After years of advocating ABC (Airway-Breathing-Circulation), current guidelines of cardiopulmonary resuscitation (CPR) recommend CAB (Circulation-Airway-Breathing). This trial compared ABC with CAB as initial approach to CPR from the arrival of rescuers until the completion of the first resuscitation cycle. METHODS 108 teams, consisting of two physicians each, were rand...

The artificial bee colony (ABC) algorithm is a popular swarm based technique, which is inspired from the intelligent foraging behavior of honeybee swarms. This paper proposes a new variant of ABC algorithm, namely, enhanced ABC with solution acceptance rule and probabilistic multisearch (ABC-SA) to address global optimization problems. A new solution acceptance rule is proposed where, instead o...

Approximate Bayesian computation (ABC) have become an essential tool for the analysis of complex stochastic models. Grelaud et al. [(2009) Bayesian Anal 3:427-442] advocated the use of ABC for model choice in the specific case of Gibbs random fields, relying on an intermodel sufficiency property to show that the approximation was legitimate. We implemented ABC model choice in a wide range of ph...

Sequential techniques can be adapted to the ABC algorithm to enhance its efficiency. For instance, when Sisson et al. (2007) introduced the ABC-PRC algorithm, the goal was to improve upon existing ABC-MCMC algorithms (Marjoram et al., 2003). While the ABC-PRC method is based upon the theoretical developments of Del Moral et al. (2006), the application to the setting of approximate Bayesian comp...

Approximate Bayesian Computation (ABC) is a family of statistical inference techniques, which is increasingly used in biology and other scientific fields. Its main benefit is to be applicable to models for which the computation of the model likelihood is intractable. The basic idea of ABC is to empirically approximate the model likelihood by using intensive realizations of model runs. Due to co...

Internal organs in vertebrates show distinctive left–right asymmetry. To establish left–right patterning, creation of a leftward flow plays a critical role. However, how this flow function or how this flow is sensed is still debated, because a flow sensor itself has not been identified yet. Here we show a medaka mutant abecobe (abc), isolated by our recent ENU-mediated mutagenesis screening wit...