Hippo信号通路通过调控Skp2活性从而抑制细胞多倍体产生及肝癌发生

文章简介在这项研究中,课题组揭示了Hippo信号通路在限制肝脏细胞的染色体由两倍体向多倍/非整倍体转变过程中起关键作用,该机制异常将导致基因组不稳定继而诱发肝癌的发生发展。课题组通过对Hippo信号通路重要成员(WW45,Mst1/2,Lats1/2)肝脏特异性敲除和过表达国家自然科学基金委;;国家重点基础研究发展计划(973)项目;;青年千人计划;;中央高校基本科研基金的资

The Ets Transcription Factor GABP Is a Component of the Hippo Pathway Essential for Growth and Antioxidant Defense

这是周大旺教授继2009年首次发现了Hippo信号通路在哺乳动物中控制器官大小及肿瘤发生具有重要作用后的又一重大研究成果，该研究系统阐述了 YAP基因在转录调控水平上的的调控机理，进一步完善了人们对Hippo信号通路的认识，也为由YAP调控异常所引发的癌症提供了一个潜在的治疗靶点。 该论文的第一作者为博士生吴黉坦和硕士生肖玉波和张世浩, 通讯作者是周大旺教授和陈兰芬副教授，该工作是与厦门市中医院、中山医院和医学高等专科学校等单位合作完成的。周大旺教授是中央首批“青年千人计划”入选者并获得国家首批“优秀青年科学基金”资助。The transcriptional coactivator Yes-associated protein (YAP) plays an important role in organ-size control and tumorigenesis. However, how Yap gene expression is regulated remains unknown. This study shows that the Ets family member GABP binds to the Yap promoter and activates YAP transcription. The depletion of GABP downregulates YAP, resulting in a G1/S cell-cycle block and increased cell death, both of which are substantially rescued by reconstituting YAP. GABP can be inactivated by oxidative mechanisms, and acetaminophen-induced glutathione depletion inhibits GABP transcriptional activity and depletes YAP. In contrast, activating YAP by deleting Mst1/Mst2 strongly protects against acetaminophen-induced liver injury. Similar to its effects on YAP, Hippo signaling inhibits GABP transcriptional activity through several mechanisms. In human liver cancers, enhanced YAP expression is correlated with increased nuclear expression of GABP. Therefore, we conclude that GABP is an activator of Yap gene expression and a potential therapeutic target for cancers driven by YAP

A comprehensive update on CIDO: the community-based coronavirus infectious disease ontology

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the development of the community-based Coronavirus Infectious Disease Ontology in early 2020. As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications

The modeling of graphite oxidation behavior for HTGR fuel coolant channels under normal operating conditions

International audienceThe oxidation of graphite in normal operating conditions is a very important factor when evaluating the service time of the graphite structural material in a high temperature gas-cooled reactor (HTGR). This paper deals with the modeling of graphite oxidation by steam in the helium channel of a fuel block. The FEM software COMSOL is used: the turbulent flow of the coolant is simulated by using the k-ε model and the chemical reaction is expressed by the Langmuir-Hinshelwood equation. Calculations were carried out for steam pressures around 1 Pa and for different temperature distributions. The influence of burn-off and the diffusion in graphite porosities were both considered in the oxidation. Results show that oxidation mainly occurred on the graphite surface at the bottom of the core because of the higher temperature. The thickness of graphite with a burn-off higher than 8% was about 1 mm at the core base. Less than 15% of steam was consumed in the coolant channel of the fuel assemblies. Calculations also showed that the mean gasification rate in one channel for the second service time was larger than the first service time

The Stress and Reliability Analysis of HTR's Graphite Component

The high temperature gas cooled reactor (HTR) is developing rapidly toward a modular, compact, and integral direction. As the main structure material, graphite plays a very important role in HTR engineering, and the reliability of graphite component has a close relationship with the integrity of reactor core. The graphite components are subjected to high temperature and fast neutron irradiation simultaneously during normal operation of the reactor. With the stress accumulation induced by high temperature and irradiation, the failure risk of graphite components increases constantly. Therefore it is necessary to study and simulate the mechanical behavior of graphite component under in-core working conditions and forecast the internal stress accumulation history and the variation of reliability. The work of this paper focuses on the mechanical analysis of pebble-bed type HTR's graphite brick. The analysis process is comprised of two procedures, stress analysis and reliability analysis. Three different creep models and two different reliability models are reviewed and taken into account in simulation. The stress and failure probability calculation results are obtained and discussed. The results gained with various models are highly consistent, and the discrepancies are acceptable

The Stress and Reliability Analysis of HTR’s Graphite Component

The high temperature gas cooled reactor (HTR) is developing rapidly toward a modular, compact, and integral direction. As the main structure material, graphite plays a very important role in HTR engineering, and the reliability of graphite component has a close relationship with the integrity of reactor core. The graphite components are subjected to high temperature and fast neutron irradiation simultaneously during normal operation of the reactor. With the stress accumulation induced by high temperature and irradiation, the failure risk of graphite components increases constantly. Therefore it is necessary to study and simulate the mechanical behavior of graphite component under in-core working conditions and forecast the internal stress accumulation history and the variation of reliability. The work of this paper focuses on the mechanical analysis of pebble-bed type HTR's graphite brick. The analysis process is comprised of two procedures, stress analysis and reliability analysis. Three different creep models and two different reliability models are reviewed and taken into account in simulation. The stress and failure probability calculation results are obtained and discussed. The results gained with various models are highly consistent, and the discrepancies are acceptable

Radial Basis Function Method for Predicting the Evolution of Aerosol Size Distributions for Coagulation Problems

The dynamic evolution of particle size distributions (PSDs) during coagulation is of great importance in many atmospheric and engineering applications. To date, various numerical methods have been developed for solving the general dynamic equation under different scenarios. In this study, a radial basis function (RBF) method was proposed to solve particle coagulation evolution. This method uses a Gaussian function as the basis function to approximate the size distribution function. The original governing equation was then converted to ordinary differential equations (ODEs), along with numerical quadratures. The RBF method was compared with the analytical solutions and sectional method to validate its accuracy. The comparison results showed that the RBF method provided almost accurate predictions of the PSDs for different coagulation kernels. This method was also verified to be reliable in predicting the self-preserving distributions reached over long periods and for describing the temporal evolution of moments. For multimodal coagulation, the RBF method also accurately predicted the temporal evolution of a bimodal distribution owing to scavenging effects. Moreover, the computational times of the RBF method for these cases were usually of the order of seconds. Thus, the RBF method is verified as a reliable and efficient tool for predicting PSD evolution during coagulation

Radial Basis Function Method for Predicting the Evolution of Aerosol Size Distributions for Coagulation Problems

The dynamic evolution of particle size distributions (PSDs) during coagulation is of great importance in many atmospheric and engineering applications. To date, various numerical methods have been developed for solving the general dynamic equation under different scenarios. In this study, a radial basis function (RBF) method was proposed to solve particle coagulation evolution. This method uses a Gaussian function as the basis function to approximate the size distribution function. The original governing equation was then converted to ordinary differential equations (ODEs), along with numerical quadratures. The RBF method was compared with the analytical solutions and sectional method to validate its accuracy. The comparison results showed that the RBF method provided almost accurate predictions of the PSDs for different coagulation kernels. This method was also verified to be reliable in predicting the self-preserving distributions reached over long periods and for describing the temporal evolution of moments. For multimodal coagulation, the RBF method also accurately predicted the temporal evolution of a bimodal distribution owing to scavenging effects. Moreover, the computational times of the RBF method for these cases were usually of the order of seconds. Thus, the RBF method is verified as a reliable and efficient tool for predicting PSD evolution during coagulation