EZH2 RIP-seq Identifies Tissue-specific Long Non-coding RNAs.

BackgroundPolycomb Repressive Complex 2 (PRC2) catalyzes histone methylation at H3 Lys27, and plays crucial roles during development and diseases in numerous systems. Its catalytic subunit EZH2 represents a key nuclear target for long non-coding RNAs (lncRNAs) that emerging to be a novel class of epigenetic regulator and participate in diverse cellular processes. LncRNAs are characterized by high tissue-specificity; however, little is known about the tissue profile of the EZH2- interacting lncRNAs.ObjectiveHere we performed a global screening for EZH2-binding lncRNAs in tissues including brain, lung, heart, liver, kidney, intestine, spleen, testis, muscle and blood by combining RNA immuno- precipitation and RNA sequencing. We identified 1328 EZH2-binding lncRNAs, among which 470 were shared in at least two tissues while 858 were only detected in single tissue. An RNA motif with specific secondary structure was identified in a number of lncRNAs, albeit not in all EZH2-binding lncRNAs. The EZH2-binding lncRNAs fell into four categories including intergenic lncRNA, antisense lncRNA, intron-related lncRNA and promoter-related lncRNA, suggesting diverse regulations of both cis and trans-mechanisms. A promoter-related lncRNA Hnf1aos1 bound to EZH2 specifically in the liver, a feature same as its paired coding gene Hnf1a, further confirming the validity of our study. In addition to the well known EZH2-binding lncRNAs like Kcnq1ot1, Gas5, Meg3, Hotair and Malat1, majority of the lncRNAs were firstly reported to be associated with EZH2.ConclusionOur findings provide a profiling view of the EZH2-interacting lncRNAs across different tissues, and suggest critical roles of lncRNAs during cell differentiation and maturation

Forsythiaside A inhibits hydrogen peroxide-induced inflammation, oxidative stress, and apoptosis of cardiomyocytes

Purpose: To investigate the effect of forsythiaside A on heart failure.Methods: An in vitro cell model of myocardial injury was established by incubating H9c2 primary cardiomyocytes with hydrogen peroxide (H2O2). Apoptosis was measured by flow cytometry. Expression of inflammatory factors, including tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), was determined by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and enzymelinkedimmunosorbent assay (ELISA). Oxidative stress was evaluated by measuring malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) levels by ELISA.Results: Incubation with H2O2 increased H9c2 cell apoptosis (p < 0.001). Treatment with forsythiaside A reduced Bax expression and enhanced Bcl-2 expression which suppressed apoptosis of H2O2- induced H9c2 cells. Forsythiaside A also attenuated the H2O2-induced increase in TNF-α and IL-6expressions in H9c2 cells (p < 0.001). The H2O2-induced increase in MDA and decrease in SOD and GSH-Px in H9c2 cells were reversed by treatment with forsythiaside A. IκBα protein expression was downregulated, whereas p65 phosphorylation (p-p65), p-IκBα, nuclear factor erythropoietin-2-related factor 2 (Nrf2), and heme oxygenase 1 (HO-1) were upregulated in H2O2-induced H9c2 cells. Forsythiaside A increased IκBα, Nrf2, and HO-1 expression and decreased p-p65 and p-IκBα expression in H2O2-induced H9c2 cells.Conclusion: Forsythiaside A exerts anti-inflammatory, anti-oxidant, and anti-apoptotic effects against H2O2-induced H9c2 cells through inactivation of NF-κB pathway and activation of Nrf2/HO-1 pathway. These results support the potential clinical application of forsythiaside A for the treatment of heart failure

Myanmar as an Important Pivot for China’s Indian Ocean Strategy

郑志华,上海交通大学凯原法学院。电子邮箱:[email protected]。［文摘］2012年5月19日—20日,云南大学法学院、厦门大学海洋政策与法律中心、上海交通大学海洋法律与政策研究中心、《中国海洋法学评论》在昆明联合举办了“缅甸与中国的海洋关系冶学术研讨会。与会的专家、学者以及实务部门的同仁围绕缅甸、东盟与中国的地缘政治关系,缅甸与南(中国)海的地缘政治,航运和如何利用缅甸港口资源等议题进行了深入地探讨。本文为此次学术研讨会会议综述。［Abstract］An academic conference on the“Oceanic Relations between Myanmar and China”was held jointly by the Law School of Yunnan University,Xiamen University Center for Oceans Policy and Law,Shanghai Jiao Tong University Center for Oceans Law and Policy,and the China Oceans Law Review in Kunming during May 19-20,2012.Experts,scholars and colleagues from government agencies discussed in depth the geopolitics between China and Myanmar as well as the ASEAN,and geopolitics as well as maritime shipping between Myanmar and the South China Sea bordering countries.They also had in-depth discussion on how to utilize resources of the Myanmar harbors.This article is a summary of the conference on oceanic relations between Myanmar and China

Land Use and Land Cover Change Modeling and Future Potential Landscape Risk Assessment Using Markov-CA Model and Analytical Hierarchy Process

Land use and land cover change (LULCC) has directly played an important role in the observed climate change. In this paper, we considered Dujiangyan City and its environs (DCEN) to study the future scenario in the years 2025, 2030, and 2040 based on the 2018 simulation results from 2007 and 2018 LULC maps. This study evaluates the spatial and temporal variations of future LULCC, including the future potential landscape risk (FPLR) area of the 2008 great (8.0 Mw) earthquake of south-west China. The Cellular automata–Markov chain (CA-Markov) model and multicriteria based analytical hierarchy process (MC-AHP) approach have been considered using the integration of remote sensing and GIS techniques. The analysis shows future LULC scenario in the years 2025, 2030, and 2040 along with the FPLR pattern. Based on the results of the future LULCC and FPLR scenarios, we have provided suggestions for the development in the close proximity of the fault lines for the future strong magnitude earthquakes. Our results suggest a better and safe planning approach in the Belt and Road Corridor (BRC) of China to control future Silk-Road Disaster, which will also be useful to urban planners for urban development in a safe and sustainable manner

Distributed Non-Convex Optimization with Sublinear Speedup under Intermittent Client Availability

Federated learning is a new distributed machine learning framework, where a bunch of heterogeneous clients collaboratively train a model without sharing training data. In this work, we consider a practical and ubiquitous issue when deploying federated learning in mobile environments: intermittent client availability, where the set of eligible clients may change during the training process. Such intermittent client availability would seriously deteriorate the performance of the classical Federated Averaging algorithm (FedAvg for short). Thus, we propose a simple distributed non-convex optimization algorithm, called Federated Latest Averaging (FedLaAvg for short), which leverages the latest gradients of all clients, even when the clients are not available, to jointly update the global model in each iteration. Our theoretical analysis shows that FedLaAvg attains the convergence rate of $O(E^{1/2}/(N^{1/4} T^{1/2}))$, achieving a sublinear speedup with respect to the total number of clients. We implement FedLaAvg along with several baselines and evaluate them over the benchmarking MNIST and Sentiment140 datasets. The evaluation results demonstrate that FedLaAvg achieves more stable training than FedAvg in both convex and non-convex settings and indeed reaches a sublinear speedup