Revolutionizing hepatitis C treatment: next-gen direct-acting antivirals.

Introduction: With the introduction of highly effective and safe therapies with next-generation direct-acting antivirals (DAAs), that act without interferon, hepatitis C virus (HCV) infection remains the only treatable chronic infectious disease.

Areas Covered: The review aims to provide an overview of the therapy revolution with a description of specific DAAs, their mechanisms of action, a summary of the safety and efficacy of specific regimens, and a discussion of populations requiring special therapeutic approaches.

Expert Opinion: DAAs are highly effective, safe, and easy to use.

Parameter estimation of the fractional Ornstein-Uhlenbeck process based on quadratic variation.

Modern experiments routinely produce extensive data of the diffusive dynamics of tracer particles in a large range of systems. Often, the measured diffusion turns out to deviate from the laws of Brownian motion, i.e.

Classification of particle trajectories in living cells: Machine learning versus statistical testing hypothesis for fractional anomalous diffusion.

Single-particle tracking (SPT) has become a popular tool to study the intracellular transport of molecules in living cells. Inferring the character of their dynamics is important, because it determines the organization and functions of the cells. For this reason, one of the first steps in the analysis of SPT data is the identification of the diffusion type of the observed particles.

Time-dependent classification of protein diffusion types: A statistical detection of mean-squared-displacement exponent transitions.

In this paper, we have proposed a statistical procedure for detecting transitions of the mean-square-displacement exponent value within a single trajectory. With this procedure, we have identified three regimes of proteins dynamics on a cell membrane, namely, subdiffusion, free diffusion, and immobility. The fourth considered dynamics type, namely, superdiffusion was not detected.

Statistical testing approach for fractional anomalous diffusion classification.

Taking advantage of recent single-particle tracking data, we compare the popular standard mean-squared displacement method with a statistical testing hypothesis procedure for three testing statistics and for two particle types: membrane receptors and the G proteins coupled to them. Each method results in different classifications. For this reason, more rigorous statistical tests are analyzed here in detail.

Identifying ergodicity breaking for fractional anomalous diffusion: Criteria for minimal trajectory length.

In this paper, we study ergodic properties of α-stable autoregressive fractionally integrated moving average (ARFIMA) processes which form a large class of anomalous diffusions. A crucial practical question is how long trajectories one needs to observe in an experiment in order to claim that the analyzed data are ergodic or not. This will be solved by checking the asymptotic convergence to 0 of the empirical estimator F(n) for the dynamical functional D(n) defined as a Fourier transform of the n-lag increments of the ARFIMA process.

Ergodicity testing using an analytical formula for a dynamical functional of alpha-stable autoregressive fractionally integrated moving average processes.

In this paper we study asymptotic behavior of a dynamical functional for an α-stable autoregressive fractionally integrated moving average (ARFIMA) process. We find an analytical formula for this important statistics and show its usefulness as a diagnostic tool for ergodic properties. The obtained results point to the very fast convergence of the dynamical functional and show that even for short trajectories one may obtain reliable conclusions on the ergodic properties of the ARFIMA process.

Ergodicity testing for anomalous diffusion: small sample statistics.

The analysis of trajectories recorded in experiments often requires calculating time averages instead of ensemble averages. According to the Boltzmann hypothesis, they are equivalent only under the assumption of ergodicity. In this paper, we implement tools that allow to study ergodic properties.

Universal algorithm for identification of fractional Brownian motion. A case of telomere subdiffusion.

We present a systematic statistical analysis of the recently measured individual trajectories of fluorescently labeled telomeres in the nucleus of living human cells. The experiments were performed in the U2OS cancer cell line. We propose an algorithm for identification of the telomere motion.

Properties of the relaxation time distribution underlying the Kohlrausch-Williams-Watts photoionization of the DX centers in Cd(1-x)Mn(x)Te mixed crystals.

In this paper we clarify the relationship between the relaxation rate and relaxation time distributions underlying the Kohlrausch-Williams-Watts (KWW) photoconductivity build-ups in indium- and gallium-doped Cd(1-x)Mn(x)Te mixed crystals. We discuss the role of asymptotic properties of the corresponding probability density functions. We show that the relaxation rate distribution, as a completely asymmetric α-stable distribution, leads to an infinite mean value of the effective relaxation rate.