The purpose of this study was to investigate the potential mechanism of interleukin-6 (IL-6) on the stimulation of excessive androgen secretion in human NCI-H295R adrenocortical cells. We performed transcriptome sequencing of cancer and paracancerous tissues obtained from functional adrenal cortical adenomas. The secretion of dehydroepiandrosterone sulfate (DHEAS) in NCI-H295R cells was detected by a chemiluminescence assay. The expression of messenger RNA (mRNA) was detected by real-time polymerase chain reaction and that of protein was detected by western blotting. The expression of secretogranin II (SCG2) and IL-6 were significantly increased in cancer tissues. Upregulation of mRNA and protein levels of AKR1C3, CYP11A, CYP17A1, 3βHSD, and SULT2A1 was observed after stimulation with IL-6. IL-6 could also increase the expression of StAR mRNA and proteins. Our results suggest that IL-6 can promote androgen secretion by regulating the expression of genes related to androgen pathways. © 2020 Wiley Periodicals, Inc.Results of switching behavior of the improper ferroelectric LuFeO3 are presented. Using a model set of films prepared under controlled chemical and growth-rate conditions, it is shown that defects can reduce the quasi-static switching voltage by up to 40% in qualitative agreement with first-principles calculations. Switching studies show that the coercive field has a stronger frequency dispersion for the improper ferroelectrics compared to a proper ferroelectric such as PbTiO3 . It is concluded that the primary structural order parameter controls the switching dynamics of such improper ferroelectrics. © 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.Many challenging problems in biomedical research rely on understanding how variables are associated with each other and influenced by genetic and environmental factors. Probabilistic graphical models (PGMs) are widely acknowledged as a very natural and formal language to describe relationships among variables and have been extensively used for studying complex diseases and traits. In this work, we propose methods that leverage observational Gaussian family data for learning a decomposition of undirected and directed acyclic PGMs according to the influence of genetic and environmental factors. Many structure learning algorithms are strongly based on a conditional independence test. For independent measurements of normally distributed variables, conditional independence can be tested through standard tests for zero partial correlation. In family data, the assumption of independent measurements does not hold since related individuals are correlated due to mainly genetic factors. Based on univariate polygenic linear mixed models, we propose tests that account for the familial dependence structure and allow us to assess the significance of the partial correlation due to genetic (between-family) factors and due to other factors, denoted here as environmental (within-family) factors, separately. Then, we extend standard structure learning algorithms, including the IC/PC and the really fast causal inference (RFCI) algorithms, to Gaussian family data. The algorithms learn the most likely PGM and its decomposition into two components, one explained by genetic factors and the other by environmental factors.  https://www.selleckchem.com/products/necrostatin-1.html  The proposed methods are evaluated by simulation studies and applied to the Genetic Analysis Workshop 13 simulated dataset, which captures significant features of the Framingham Heart Study. © 2020 John Wiley & Sons, Ltd.Many longitudinal databases record the occurrence of recurrent events over time. In this article, we propose a new method to estimate the average causal effect of a binary treatment for recurrent event data in the presence of confounders. We propose a doubly robust semiparametric estimator based on a weighted version of the Nelson-Aalen estimator and a conditional regression estimator under an assumed semiparametric multiplicative rate model for recurrent event data. We show that the proposed doubly robust estimator is consistent and asymptotically normal. In addition, a model diagnostic plot of residuals is presented to assess the adequacy of our proposed semiparametric model. We then evaluate the finite sample behavior of the proposed estimators under a number of simulation scenarios. Finally, we illustrate the proposed methodology via a database of circus artist injuries. © 2020 John Wiley & Sons, Ltd.INTRODUCTION Virtual-reality (VR) technology is a potential method to use in cognitive intervention, but the use of VR in cognitive stimulation intervention for older adults has not been investigated. Therefore, the aim of this study was to investigate the mood change of older adults after participating in the VR cognitive stimulation activity. METHODS This is a multicenter randomized controlled, cross-over trial. The intervention was a VR cognitive stimulation activity, and the control was a paper-and-pencil activity. The participants were older adults with age over 60 and recruited in the elderly community centres. The Positive and Negative Affect Score (PANAS) was used to measure mood change. Mean difference (MD) with 95% confidence interval (95% CI) was calculated. The Simulator sickness questionnaire was used to measure adverse events. RESULTS A total of 236 participants from 19 community centres were recruited. After the VR activity, the participants had a significant increase in total PANAS positive affect score (MD = 2.09, 95% CI = 0.69 to 3.49), and a significant reduction in total negative affect score (MD = -1.99, 95% CI = -2.55 to -1.43). The reduction in negative affect score was significantly larger in VR activity than paper-and-pencil activity (MD = -0.48, 95% CI = -0.98 to 0.00). Besides, only 3 participants reported severe advance events after VR activity. CONCLUSIONS The use of VR technology is well accepted by older adults. Therefore, the use of VR technology through smartphone and a mobile app can be a potential method for future cognitive training interventions. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.