Anisotropy dependence of the fluctuation spectroscopy in the critical and gaussian regimes in superconducting NaFe1-xCoxAs single crystals

We investigate thermal fluctuations in terms of diamagnetism and magnetotransport in superconducting NaFe1-xCoxAs single crystals with different doping levels. Results show that in the case of optimal doped and lightly overdoped (x= 0.03, 0.05) crystals the analysis in the critical as well as in the Gaussian fluctuation regions is consistent with the Ginzburg-Landau 3D fluctuation theory. However, in the case of strongly overdoped samples (x >= 0.07) the Ullah-Dorsey scaling of the fluctuation induced magnetoconductivity in the critical region confirms that thermal fluctuations exhibit a 3D anisotropic nature only in a narrow temperature region around T-c(H). This is consistent with the fact that in these samples the fluctuation effects in the Gaussian region above T-c may be described by the Lawrence-Doniach approach. Our results indicate that the anisotropy of these materials increases significantly with the doping level

A community computational challenge to predict the activity of pairs of compounds

Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction