A randomized, double-blind, placebo-and active-controlled, half-head study to evaluate the effects of platelet-rich plasma on alopecia areata

Summary Background Alopecia areata (AA) is a common autoimmune condition, causing inflammation-induced hair loss. This disease has very limited treatment possibilities, and no treatment is either curative or preventive. Platelet-rich plasma (PRP) has emerged as a new treatment modality in dermatology, and preliminary evidence has suggested that it might have a beneficial role in hair growth. Objectives To evaluate the efficacy and safety of PRP for the treatment of AA in a randomized, double-blind, placebo-and active-controlled, half-head, parallelgroup study. Methods Forty-five patients with AA were randomized to receive intralesional injections of PRP, triamcinolone acetonide (TrA) or placebo on one half of their scalp. The other half was not treated. Three treatments were given for each patient, with intervals of 1 month. The endpoints were hair regrowth, hair dystrophy as measured by dermoscopy, burning or itching sensation, and cell proliferation as measured by Ki-67 evaluation. Patients were followed for 1 year. Results PRP was found to increase hair regrowth significantly and to decrease hair dystrophy and burning or itching sensation compared with TrA or placebo. Ki-67 levels, which served as markers for cell proliferation, were significantly higher with PRP. No side-effects were noted during treatment. Conclusions This pilot study, which is the first to investigate the effects of PRP on AA, suggests that PRP may serve as a safe and effective treatment option in AA, and calls for more extensive controlled studies with this method

Recent advances quantifying the large wood dynamics in river basins: New methods and remaining challenges

Citation: Ruiz-Villanueva, V., Piégay, H., Gurnell, A. A., Marston, R. A., & Stoffel, M. (2016). Recent advances quantifying the large wood dynamics in river basins: New methods and remaining challenges. Reviews of Geophysics. doi:10.1002/2015RG000514Large wood is an important physical component of woodland rivers and significantly influences river morphology. It is also a key component of stream ecosystems. However, large wood is also a source of risk for human activities as it may damage infrastructure, block river channels, and induce flooding. Therefore, the analysis and quantification of large wood and its mobility are crucial for understanding and managing wood in rivers. As the amount of large-wood-related studies by researchers, river managers, and stakeholders increases, documentation of commonly used and newly available techniques and their effectiveness has also become increasingly relevant as well. Important data and knowledge have been obtained from the application of very different approaches and have generated a significant body of valuable information representative of different environments. This review brings a comprehensive qualitative and quantitative summary of recent advances regarding the different processes involved in large wood dynamics in fluvial systems including wood budgeting and wood mechanics. First, some key definitions and concepts are introduced. Second, advances in quantifying large wood dynamics are reviewed; in particular, how measurements and modeling can be combined to integrate our understanding of how large wood moves through and is retained within river systems. Throughout, we present a quantitative and integrated meta-analysis compiled from different studies and geographical regions. Finally, we conclude by highlighting areas of particular research importance and their likely future trajectories, and we consider a particularly underresearched area so as to stress the future challenges for large wood research. ©2016. American Geophysical Union

Numerical scaling studies of kinetically-limited electrochemical nucleation and growth with accelerated stochastic simulations

A stochastic atomic-scale lattice-based numerical method based on the Exact Lattice First Passage Time method was developed for the simulation of the early stages of kinetically controlled electrochemical nucleation and growth. Electrochemical reaction and surface diffusion on a hexagonal lattice was accounted for in a pristine physical model system that included edge diffusion along steps, and movement over step edges with Ehrlich-Schwöbel barrier. Five cases were investigated: homoexpitaxy, heteroepitaxy, multi-layer growth, terraces, and confined regions. For each, the influence of the physical parameters, deposition conditions, and system geometry on growth morphology was investigated. Simulation based studies of multilayer surface morphology were able to distinguish between layer-by-layer and island growth modes. On stepped terraces, parameter regions associated with he surface diffusion to deposition flux ratio (D/F) and the Ehrlich-Schwöbel barrier were identified under which deposition occurred either at the step edge or by nucleation and growth of islands on the terraces. The probability of growing single crystals in a small confined region was found to scale with D/F and the radius squared. © 2014 The Electrochemical Society

An exact and efficient first passage time algorithm for reaction-diffusion processes on a 2D-lattice

We present an exact and efficient algorithm for reaction-diffusion-nucleation processes on a 2D-lattice. The algorithm makes use of first passage time (FPT) to replace the computationally intensive simulation of diffusion hops in KMC by larger jumps when particles are far away from step-edges or other particles. Our approach computes exact probability distributions of jump times and target locations in a closed-form formula, based on the eigenvectors and eigenvalues of the corresponding 1D transition matrix, maintaining atomic-scale resolution of resulting shapes of deposit islands. We have applied our method to three different test cases of electrodeposition: pure diffusional aggregation for large ranges of diffusivity rates and for simulation domain sizes of up to 4096 × 4096 sites, the effect of diffusivity on island shapes and sizes in combination with a KMC edge diffusion, and the calculation of an exclusion zone in front of a step-edge, confirming statistical equivalence to standard KMC simulations. The algorithm achieves significant speedup compared to standard KMC for cases where particles diffuse over long distances before nucleating with other particles or being captured by larger islands. © 2013 Elsevier Inc