Propranolol Blocks Cardiac and Neuronal Voltage-Gated Sodium Channels

Propranolol is a widely used, non-selective β-adrenergic receptor antagonist with proven efficacy in treating cardiovascular disorders and in the prevention of migraine headaches. At plasma concentrations exceeding those required for β-adrenergic receptor inhibition, propranolol also exhibits anti-arrhythmic (“membrane stabilizing”) effects that are not fully explained by β-blockade. Previous in vitro studies suggested that propranolol may have local anesthetic effects. We directly tested the effects of propranolol on heterologously expressed recombinant human cardiac (NaV1.5) and brain (NaV1.1, NaV1.2, NaV1.3) sodium channels using whole-cell patch-clamp recording. We found that block was not stereospecific as we observed approximately equal IC50 values for tonic and use-dependent block by R-(+) and S-(−) propranolol (tonic block: R: 21.4 μM vs S: 23.6 μM; use-dependent block: R: 2.7 μM vs S: 2.6 μM). Metoprolol and nadolol did not block NaV1.5 indicating that sodium channel block is not a class effect of β-blockers. The biophysical effects of R-(+)-propranolol on NaV1.5 and NaV1.1 resembled that of the prototypical local anesthetic lidocaine including the requirement for a critical phenylalanine residue (F1760 in NaV1.5) in the domain 4 S6 segment. Finally, we observed that brain sodium channels exhibited less sensitivity to R-(+)-propranolol than NaV1.5 channels. Our findings establish sodium channels as targets for propranolol and may help explain some beneficial effects of the drug in treating cardiac arrhythmias, and may explain certain adverse central nervous system effects

Magnetic Excitations of Undoped Iron Oxypnictides

We study the magnetic excitations of undoped iron oxypnictides using a three-dimensional Heisenberg model with single-ion anisotropy. Analytic forms of the spin wave dispersion, velocities, and structure factor are given. Aside from quantitative comparisons which can be made to inelastic neutron scattering experiments, we also give qualitative criteria which can distinguish various regimes of coupling strength. The magnetization reduction due to quantum zero point fluctuations shows clear dependence on the c-axis coupling.Comment: 4 pages, 5 figures, to appear in Frontiers of Physics in China: a special issue on Iron-based superconductor

A critical evaluation of network and pathway based classifiers for outcome prediction in breast cancer

Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single gene classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single gene classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single gene classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single gene sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single gene classifiers for predicting outcome in breast cancer

The regulatory subunit of PKA-I remains partially structured and undergoes β-aggregation upon thermal denaturation

Background: The regulatory subunit (R) of cAMP-dependent protein kinase (PKA) is a modular flexible protein that responds with large conformational changes to the binding of the effector cAMP. Considering its highly dynamic nature, the protein is rather stable. We studied the thermal denaturation of full-length RIα and a truncated RIα(92-381) that contains the tandem cyclic nucleotide binding (CNB) domains A and B. Methodology/Principal Findings: As revealed by circular dichroism (CD) and differential scanning calorimetry, both RIα proteins contain significant residual structure in the heat-denatured state. As evidenced by CD, the predominantly α-helical spectrum at 25°C with double negative peaks at 209 and 222 nm changes to a spectrum with a single negative peak at 212-216 nm, characteristic of β-structure. A similar α→β transition occurs at higher temperature in the presence of cAMP. Thioflavin T fluorescence and atomic force microscopy studies support the notion that the structural transition is associated with cross-β-intermolecular aggregation and formation of non-fibrillar oligomers. Conclusions/Significance: Thermal denaturation of RIα leads to partial loss of native packing with exposure of aggregation-prone motifs, such as the B' helices in the phosphate-binding cassettes of both CNB domains. The topology of the β-sandwiches in these domains favors inter-molecular β-aggregation, which is suppressed in the ligand-bound states of RIα under physiological conditions. Moreover, our results reveal that the CNB domains persist as structural cores through heat-denaturation. © 2011 Dao et al

Visualizing size-dependent deformation mechanism transition in Sn

Displacive deformation via dislocation slip and deformation twinning usually plays a dominant role in the plasticity of crystalline solids at room temperature. Here we report in situ quantitative transmission electron microscope deformation tests of single crystal Sn samples. We found that when the sample size was reduced from 450 nm down to 130 nm, diffusional deformation replaces displacive plasticity as the dominant deformation mechanism at room temperature. At the same time, the strength-size relationship changed from “smaller is stronger” to “smaller is much weaker”. The effective surface diffusivity calculated based on our experimental data matches well with that reported in literature for boundary diffusion. The observed change in the deformation mode arises from the sample size-dependent competition between the Hall-Petch-like strengthening of displacive processes and Coble diffusion softening processes. Our findings have important implications for the stability and reliability of nanoscale devices such as metallic nanogaps.National Science Foundation (U.S.) (CMMI-0728069)National Science Foundation (U.S.) (DMR-1008104)National Science Foundation (U.S.) (DMR-1120901)United States. Air Force Office of Scientific Research (FA9550-08-1-0325

A new method to determine the elastopalstic properties of ductile materials by conical indentation

Based on load-displacement curves, indentation is widely used to extract the elastoplastic properties of materials. It is generally believed that such a measure is non-unique and a full stress-strain curve cannot be obtained using plural sharp and deep spherical indenters. In this paper we show that by introducing an additional dimensionless function of DA / A (the ratio of residual area to the area of an indenter profile) in the reverse analysis, the elastoplastic properties of several unknown materials that exhibit visually indistinguishable load-displacement curves can be uniquely determined with a sharp indentation