AIMS This study compares clinical outcomes of Watchman vs. Amplatzer devices for left atrial appendage closure (LAAC). METHODS AND RESULTS Of two real-world registries, the Watchman registry Lichtenfels, Germany, and the Amplatzer registry Bern-Zurich, Switzerland, 303 and 333 consecutive patients, respectively, were included. After a 11 propensity score matching, 266 vs. 266 patients were compared by use of the predefined primary efficacy endpoint of stroke, systemic embolism and cardiovascular/unexplained death, the primary safety endpoint of major peri-procedural complications and major bleeding events at follow-up, and the combined hazard endpoint, a composite of all above-mentioned hazards. Mean age was 75.3 ± 7.8 (Watchman) vs. 75.1 ± 9.9 (Amplatzer) years, CHA2DS2-VASc score 4.5 ± 1.7 vs. 4.5 ± 1.5, and HAS-BLED score 3.2 ± 1.0 vs. 3.2 ± 1.0. At a mean follow-up of 2.4 ± 1.3 vs. 2.5 ± 1.5 years and 1.322 patient-years, the primary endpoints of efficacy [40/646, 6.2% [Watchman] vs. 43/676, 6.4% [Amplatzer]; hazard ratio (HR), 1.02; 95% confidence interval (CI), 0.66-1.58; P = 0.92] and safety (33/646, 5.1% vs. 30/676, 4.4%; HR, 0.57; 95% CI, 0.29-1.11; P = 0.10), as well as the combined hazard endpoint (69/646, 10.7% vs. 66/676, 9.8%; HR, 0.80; 95% CI, 0.55-1.12; P = 0.26) were similar for both groups. CONCLUSION This study suggests comparable efficacy and safety of the Watchman and Amplatzer devices. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2020. For permissions, please email journals.permissions@oup.com.MOTIVATION RNA-sequencing (RNA-seq) enables global identification of RNA editing sites in biological systems and disease. A salient step in many studies is to identify editing sites that statistically associate with treatment (e.g. case vs. control) or covary with biological factors such as age. However, RNA-seq has technical features that incumbent tests (e.g. t-test, linear regression) do not consider, which can lead to false positives and false negatives. RESULTS In this study we demonstrate the limitations of currently used tests and introduce the method, REDITs (RNA editing tests), a suite of tests that employ beta-binomial models to identify differential RNA editing. The tests in REDITs have higher sensitivity than other tests, while also maintaining the type I error (false positive) rate at the nominal level. Applied to the GTEx dataset, we unveil RNA editing changes associated with age and gender, and differential recoding profiles between brain regions. AVAILABILITY AND IMPLEMENTATION REDITs are implemented as functions in R and freely available for download at https//github.com/gxiaolab/REDITs. The repository also provides a code example for leveraging parallelization using multiple cores. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online. © The Author(s) (2020). https://www.selleckchem.com/products/KU-0063794.html Published by Oxford University Press. All rights reserved. For Permissions, please email journals.permissions@oup.com.MOTIVATION LINCS L1000 dataset contains numerous cellular expression data induced by large sets of perturbagens. Although it provides invaluable resources for drug discovery as well as understanding of disease mechanisms, the existing peak deconvolution algorithms cannot recover the accurate expression level of genes in many cases, inducing severe noise in the dataset and limiting its applications in biomedical studies. RESULTS Here, we present a novel Bayesian-based peak deconvolution algorithm that gives unbiased likelihood estimations for peak locations and characterize the peaks with probability based z-scores. Based on the above algorithm, we build a pipeline to process raw data from L1000 assay into signatures that represent the features of perturbagen. The performance of the proposed pipeline is evaluated using similarity between the signatures of bio-replicates and the drugs with shared targets, and the results show that signatures derived from our pipeline gives a substantially more reliable and informative representation for perturbagens than existing methods. Thus, the new pipeline may significantly boost the performance of L1000 data in the down-stream applications such as drug repurposing, disease modeling, and gene function prediction. AVAILABILITY The code and the precomputed data for LINCS L1000 Phase II (GSE 70138) are available at https//github.com/njpipeorgan/L1000-bayesian. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online. © The Author(s) 2020. Published by Oxford University Press.Cellular protrusions create complex cell surface topographies, but biomechanical mechanisms regulating their formation and arrangement are largely unknown. To study how protrusions form, we focused on the morphogenesis of microridges, elongated actin-based structures that are arranged in maze-like patterns on the apical surfaces of zebrafish skin cells. Microridges form by accreting simple finger-like precursors. Live imaging demonstrated that microridge morphogenesis is linked to apical constriction. A nonmuscle myosin II (NMII) reporter revealed pulsatile contractions of the actomyosin cortex, and inhibiting NMII blocked apical constriction and microridge formation. A biomechanical model suggested that contraction reduces surface tension to permit the fusion of precursors into microridges. Indeed, reducing surface tension with hyperosmolar media promoted microridge formation. In anisotropically stretched cells, microridges formed by precursor fusion along the stretch axis, which computational modeling explained as a consequence of stretch-induced cortical flow. Collectively, our results demonstrate how contraction within the 2D plane of the cortex can pattern 3D cell surfaces. © 2020 van Loon et al.In this paper, the geometric and electronic properties of heterojunctions constructed using a graphene sheet and an MASnI3 surface were investigated by performing first-principles calculations based on the density functional theory. Our results show that the interaction between graphene and the MASnI3 surface is in the scope of van der Waals interactions. In the heterojunctions, electrons transfer from graphene to the MASnI3 surface, resulting in the formation of a built-in electric field in the interface, which is favorable for the separation of electrons and holes. The absorption spectra showed that the absorption intensity of the heterojunction in the visible region is slightly smaller than that of the pristine MASnI3 surface. The energy barriers of water molecules diffusing through MASnI3 surfaces are relatively low, but when a water molecule penetrates the graphene sheet into the interior of the MASnI3 it has to overcome an energy barrier of as high as 9 eV. It is found that the water diffusions through the surfaces cause very severe damage to the structures of the graphene sheet and MASnI3 surface.