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| 1 | Efficacy of water fraction from Dioscorea cirrhosa on oxidative stress and apoptosis in H9c2 cardiomyocytes induced by H2O2显示文摘OBJECTIVE:To investigate the efficacy of water fraction from Dioscorea cirrhosa(WF)on oxidative damage and apoptosis of cardiomyocytes induced by H2O2,and to study its mechanism.METHODS:Cell viability was measured by the MST assay kit.The content of malondialdehyde(MDA),release of lactate dehydrogenase(LDH)and activity of catalase(CAT)and superoxide dismutase(SOD)were detected by biochemical kit.The content of reactive oxygen species(ROS)was assessed by nonfluorescent probe 2′,7′-dichlorofluorescin diacetate(DCFH-DA).JC-1 was used to analyze the mitochondrial membrane potential(mtΔΨ)and Annexin-V-FITC/PI staining was applied to assess apoptosis of H9c2 by flow cytometry.Moreover,the expression of B-cell lymphoma-2(Bcl-2),Bcl-2-associated X(Bax),caspase-3,caspase-9,cleaved-caspase-3 and cleaved-caspase-9 proteins was determined by western blot analysis.RESULTS:WF increased cell viability and decreased LDH leakage in H9c2 cells exposed to H2O2.WF treatment decreased ROS and MDA level,enhanced SOD and CAT activities,improved mtΔΨand inhibited apoptosis.Western blot analysis demonstrated that the ratio of Bcl-2/Bax was increased and the expression cleaved-caspase-3,caspase-3,cleaved-caspase-9 and caspase-9 were decreased in group treated with WF.CONCLUSION:WF protects H9c2 myocardial cells on H2O2-induced oxidative stress and apoptosis by scavenging ROS,improving antioxidant capacity,protecting mitochondrial and regulating the proteins expression related to apoptosis. | LIU Chunhua PAN Jie WANG Aimin LAN Yanyu LI Yongjun LU Yuan SUN Jia WANG Yonglin LIU Ting LU Dingyan YOU Jingrui | 2021 | Journal of Traditional Chinese Medicine2021，41，1： | 4 |
| 2 | β-cyclodextrin modified silica nanochannel membrane for chiral separation显示文摘 | Yue Liu Ping Li Li Xie Dingyan Fan Shasheng Huang | 2014 | Journal of Membrane Science2014，，： | 1 |
| 3 | A High Robust Audio Watermarking Scheme Based on Orthogonal Decomposition显示文摘A high robust approach for the additive spread spectrum audio watermarking scheme based on orthogonal decomposition of the host signal has been proposed. By analyzing traditional spread spectrum(SS), the section of the audio signal which is parallel to the direction of watermark signal acts as an interference source in decoder. The watermark is only embedded in the section which is perpendicular to watermark signal in the proposed scheme. In this way, the interference of host signal can be removed completely in decoder. Whether the watermarks have been embedded in the audio or not is researched and an optimal threshold in detector is given to achieve the minimum false alarm probability. The simulation results show that the proposed method can achieve high robustness against various attacks. | ZHANG Kang GAO Ge CHEN Yi SONG Dingyan LIU Ying LV Bing | 2016 | Wuhan University Journal of Natural Sciences2016，21，2： | 1 |
| 4 | Facing small and biased data dilemma in drug discovery with enhanced federated learning approaches显示文摘Artificial intelligence(AI)models usually require large amounts of high-quality training data,which is in striking contrast to the situation of small and biased data faced by current drug discovery pipelines.The concept of federated learning has been proposed to utilize distributed data from different sources without leaking sensitive information of the data.This emerging decentralized machine learning paradigm is expected to dramatically improve the success rate of AI-powered drug discovery.Here,we simulated the federated learning process with different property and activity datasets from different sources,among which overlapping molecules with high or low biases exist in the recorded values.Beyond the benefit of gaining more data,we also demonstrated that federated training has a regularization effect superior to centralized training on the pooled datasets with high biases.Moreover,different network architectures for clients and aggregation algorithms for coordinators have been compared on the performance of federated learning,where personalized federated learning shows promising results.Our work demonstrates the applicability of federated learning in predicting drug-related properties and highlights its promising role in addressing the small and biased data dilemma in drug discovery. | Zhaoping Xiong Ziqiang Cheng Xinyuan Lin Chi Xu Xiaohong Liu Dingyan Wang Xiaomin Luo Yong Zhang Hualiang Jiang Nan Qiao Mingyue Zheng | 2022 | Science China(Life Sciences)2022，65，3： | 1 |
| 5 | Landscape eco-environmental research on littoral zone in China显示文摘Littoral zone is a special land/ landscape type. As an important kind of land resource in support, the use of littoral zone is vital to eastern coastal areas in China. And the research on littoral zone relates to the key theory of landscape ecology. Based on the theory of landscape ecology, the littoral zone was divided into four types: mud flat, sand beach, bench, and biological flat. The distribution of each type in China is pointed out. As a typical open system, littoral zone has six landscape ecological characteristics: (1) high sensitivity to disturbance; (2) distinct edge effect; (3) spatial aggregation of natural resources; (4) frequently spatial oscillation; (5) obviously spatial heterogeneity; and (6) noticeably spatial differentiation. Some proposals are also put forward on the land use and development of littoral zone for environmental protection and environmental management. | PENGJian WANGYang-lin JINGJuan LIWei-feng DINGYan | 2004 | Journal of Environmental Sciences2004，16，3： | 1 |
| 6 | Drug target inference by mining transcriptional data using a novel graph convolutional network framework显示文摘A fundamental challenge that arises in biomedicine is the need to characterize compounds in a relevant cellular context in order to reveal potential on-target or offtarget effects.Recently,the fast accumulation of gene transcriptional profiling data provides us an unprecedented opportunity to explore the protein targets of chemical compounds from the perspective of cell transcriptomics and RNA biology.Here,we propose a novel Siamese spectral-based graph convolutional network(SSGCN)model for inferring the protein targets of chemical compounds from gene transcriptional profiles.Although the gene signature of a compound perturbation only provides indirect clues of the interacting targets,and the biological networks under different experiment conditions further complicate the situation,the SSGCN model was successfully trained to learn from known compound-target pairs by uncovering the hidden correlations between compound perturbation profiles and gene knockdown profiles.On a benchmark set and a large time-split validation dataset,the model achieved higher target inference accuracy as compared to previous methods such as Connectivity Map.Further experimental validations of prediction results highlight the practical usefulness of SSGCN in either inferring the interacting targets of compound,or reversely,in finding novel inhibitors of a given target of interest. | Feisheng Zhong Xiaolong Wu Ruirui Yang Xutong Li Dingyan Wang Zunyun Fu Xiaohong Liu XiaoZhe Wan Tianbiao Yang Zisheng Fan Yinghui Zhang Xiaomin Luo Kaixian Chen Sulin Zhang Hualiang Jiang Mingyue Zheng | 2022 | Protein & Cell2022，13，4： | 1 |
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