检索结果-南通市图书馆

PCC0208017,a novel small-molecule inhibitor of MARK3/MARK4,suppresses glioma progression in vitro and in vivo

在线全文

学校读者我要写书评

暂无评论

Acta Pharmaceutica Sinica B 2020年第2期10卷 289-300页

作者： Fangfang Li Zongliang Liu Heyuan Sun Chunmei Li Wenyan Wang Liang Ye Chunhong Yan Jingwei Tian Hongbo Wang School of Pharmacy Key Laboratory of Molecular Pharmacology and Drug Evaluation(Yantai University)Ministry of EducationCollaborative Innovation Center of Advanced Drug Delivery System and Biotech Drugs inUniversities of ShandongYantai UniversityYantai 264005China Department of Clinical Medicine Binzhou Medical CollegeYantai 256603China gru cancer center Augusta UniversityAugustaGA 30912USA

Gliomas are the most common primary intracranial neoplasms among all brain malignancies,and the microtubule affinity regulating kinases(MARKs)have become potential drug targets for ***,we report a novel dual small-molecule inhibitor of MARK3 and MARK4,designated as *** vitro,PCC0208017 strongly inhibited kinase activity against MARK3 and MARK4,and strongly reduced proliferation in three glioma cell *** compound attenuated glioma cell migration,glioma cell invasion,and *** mechanism studies revealed that PCC0208017 decreased the phosphorylation of Tau,disrupted microtubule dynamics,and induced a G2/M phase cell cycle *** an in vivo glioma model,PCC0208017 showed robust anti-tumor activity,blood-brain barrier permeability,and a good oral pharmacokinetic *** docking studies showed that PCC0208017 exhibited high binding affinity to MARK3 and *** together,our study describes for the first time that PCC0208017,a novel MARK3/MARK4 inhibitor,might be a promising lead compound for treatment of glioma.

关键词： Glioma PCC0208017 MARK3 MARK4 Molecular docking

Uncompromised NK cell activation is essential for virus-specific CTL activity during acute influenza virus infection

在线全文

学校读者我要写书评

暂无评论

Cellular & Molecular Immunology 2018年第9期15卷 827-837页

作者： Yuan Liu Jian Zheng Yinping Liu Liyan Wen Lei Huang Zheng Xiang Kwok-Tai Lam Aizhen Lv Huawei Mao Yu-Lung Lau Wenwei Tu Department of Pediatrics and Adolescent Medicine Li Ka Shing Faculty of MedicineThe University of Hong KongHong KongChina Medical Genetic center Guangdong Women and Children HospitalGuangzhou 511400China Department of Radiology Georgia Regents UniversityAugustaGA 30912USA gru cancer center Georgia Regents UniversityAugustaGA 30912USA Department of Pediatrics The University of Hong Kong—Shenzhen HospitalShenzhen 518053China

Natural killer (NK) cells are indispensable components of both the innate and adaptive immune response. However,their precise roles in the cross-talk between innate and adaptive immunity during influenza virus infection remaincontroversial. By comparing NK cell dynamics and activity under a sub-lethal dose and high dose of influenza virusinfection, we showed that influenza virus PR8 directly infected NK cells during natural infection, which wasconsistent with our previous findings obtained from an in vitro investigation of human NK cells. The impairments incytotoxicity and IFN-γ production by spleen NK cells following high-dose infection were accompanied by decreasedvirus-specific killing mediated by cytotoxic T lymphocytes (CTLs). Importantly, the weakened CTL activity could bereversed by adoptive transfer of spleen NK cells harvested from low-dose-infected mice but not healthy *** together, our data provide direct evidence supporting the contribution of NK cells to antiviral T-cellresponses. This study also indicates that a novel NK-targeted immune evasion strategy is used by influenza virusto shrink both innate and adaptive immune responses.

关键词： CTL influenza NK cell

Survey of Stereotactic Body Radiation Oncology for Early Staged Non-Small Cell Lung cancer in China

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

International Journal of Medical Physics, Clinical Engineering and Radiation Oncology 2014年第1期3卷 56-59页

作者： Ligang Xing Yong Yin Spring Kong Jinming Yu Department of Radiation Oncology GRU Cancer Center/Medical College of Georgia Georgia Regents University Augusta USA Department of Radiation Oncology Shandong Cancer Hospital and Institute Jinan China

Purpose: To evaluate the current status of stereotactic body radiotherapy (SBRT) for early staged non-small cell lung cancer (NSCLC) at main cancer hospitals in China. Methods and Materials: The questionnaire was sent by mail and email to 21 hospitals, which include the patient enrollment, treatment technique, dose and fractionation, quality control, disease control and side effects. Results: Nineteen hospitals responded. It was found that SBRT has been used for early staged NSCLC in most of the hospitals participating in the survey. The patient characteristics and techniques were relatively consistent, but there were many controversies regarding dose fractionation and quality control. Conclusions: SBRT for early staged NSCLC has been applied at main cancer hospitals in China. However, considerable variation exists. The establishment of clinical guidelines and standardized quality control are crucial for further improvement.

关键词： Non-Small Cell Lung cancer Stereotactic Body Radiotherapy Survey

Lx2-32c,a novel semi-synthetic taxane,exerts antitumor activity against prostate cancer cells in vitro and in vivo

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Acta Pharmaceutica Sinica B 2017年第1期7卷 52-58页

作者： Guangyao Lv Dengjun Sun Jingwen Zhang Xiaoxia Xie Xiaoqiong Wu Weishuo Fang Jingwei Tian Chunhong Yan Hongbo Wang Fenghua Fu School of Pharmacy Key Laboratory of Molecular Pharmacology and Drug Evaluation (Yantai University)Ministry of EducationYantai University Departments of Medical Oncology Affiliated Yuhuangding HospitalMedical College of Qingdao University The Military Affiliated General Hospital of Beijing PLA State Key Laboratory of Bioactive Substances and Functions of Natural Medicines Institute of Materia MedicaChinese Academy of Medical Sciences and Peking Union Medical College gru cancer center Georgia Regents University

Tubulin has been shown to be an effective target for the development of cytotoxic agents against prostate cancer. Previously, we reported that Lx2-32 c is an anti-tubulin agent with high binding affinity to tubulin. In this study, we investigated the potential of Lx2-32 c to act as an effective cytotoxic agent in the treatment of prostate cancer. MTT assays showed that Lx2-32 c was cytotoxic to all tested prostate cancer cell lines. The Lx2-32c-treated cells typically exhibited a rounded morphology associated with the onset of apoptosis, as evidenced by immunocytochemical staining. Human prostate cancer cell lines treated with Lx2-32 c arrest in the G2/M phase of the cell cycle and the treatment is associated with an increased ratio of cells in the sub-G0/G1 phase as determined by flow cytometry. Furthermore, expression of the cleaved form of poly(ADP-ribose) polymerase in prostate cancer cell lines treated with Lx2-32 c was shown by Western blotting assay. Xenograft implants of LNCa P and PC3-derived tumors in nude mice showed that Lx2-32 c treatment significant inhibited tumor growth with effects equivalent to those of docetaxel. These findings demonstrate the potential of Lx2-32 c as a candidate antitumor agent for the treatment of prostate cancer.

关键词： Lx2-32c Cephalomannine Prostate cancer Microtubule Cell cycle arrest Apoptosis

Application of the improved dung beetle optimizer,muti-head attention and hybrid deep learning algorithms to groundwater depth prediction in the Ningxia area,China

在线全文

学校读者我要写书评

暂无评论

Atmospheric and Oceanic Science Letters 2025年第1期18卷 18-23页

作者： Jiarui Cai Bo Sun Huijun Wang Yi Zheng Siyu Zhou Huixin Li Yanyan Huang Peishu Zong Collaborative Innovation center on forecast and Evaluation of Meteorological Disasters/Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjingChina Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) ZhuhaiChina China Meteorological Administration Key Laboratory of Transportation MeteorologyNanjingChina Jiangsu Meteorological Observatory NanjingChina

Due to the lack of accurate data and complex parameterization,the prediction of groundwater depth is a chal-lenge for numerical *** learning can effectively solve this issue and has been proven useful in the prediction of groundwater depth in many *** this study,two new models are applied to the prediction of groundwater depth in the Ningxia area,*** two models combine the improved dung beetle optimizer(DBO)algorithm with two deep learning models:The Multi-head Attention-Convolution Neural Network-Long Short Term Memory networks(MH-CNN-LSTM)and the Multi-head Attention-Convolution Neural Network-Gated Recurrent Unit(MH-CNN-gru).The models with DBO show better prediction performance,with larger R(correlation coefficient),RPD(residual prediction deviation),and lower RMSE(root-mean-square error).Com-pared with the models with the original DBO,the R and RPD of models with the improved DBO increase by over 1.5%,and the RMSE decreases by over 1.8%,indicating better prediction *** addition,compared with the multiple linear regression model,a traditional statistical model,deep learning models have better prediction performance.

关键词： Groundwater depth Multi-head attention Improved dung beetle optimizer CNN-LSTM CNN-gru Ningxia

Identification of Global DNA Methylation Signatures in Glioblastoma-Derived cancer Stem Cells

在线全文

学校读者我要写书评

暂无评论

Journal of Genetics and Genomics 2015年第7期42卷 355-371页

作者： Eun-Joon Lee Prakash Rath Jimei Liu Dungsung Ryu Lirong Pei Satish K.Noonepalle Austin Y.Shull Qi Feng N.Scott Litofsky Douglas C.Miller Douglas C.Anthony Mark D.Kirk John Laterra Libin Deng Hong-Bo Xin Xinguo Wang Jeong-Hyeon Choi Huidong Shi gru cancer center Georgia Regents University Department of Biology College of Art and SciencesUniversity of Missouri Office of In Vitro Diagnostics and Radiological Health Center for Devices and Radiological HealthFood and Drug Administration Department of Biochemistry and Molecular Biology Georgia Regents University Division of Neurological Surgery University of Missouri School of Medicine Department of Pathology and Anatomical Sciences University of Missouri School of Medicine Department of Pathology and Laboratory Medicine Brown University and Lifespan Academic Medical Center Department of Neurology The Hugo W.Moser Research Institute at Kennedy Krieger Inc.and The Johns Hopkins University School of Medicine Institute of Translational Medicine Nanchang University David H.Murdock Research Institute Department of Biostatistics and Epidemiology Georgia Regents University

Glioblastoma （GBM） is the most common and most aggressive primary brain tumor in adults. The existence of a small population of stem-like tumor cells that efficiently propagate tumors and resist cytotoxic therapy is one proposed mechanism leading to the resilient behavior of tumor cells and poor prognosis. In this study, we performed an in-depth analysis of the DNA methylation landscape in GBM- derived cancer stem ceils （GSCs）. Parallel comparisons of primary tumors and GSC lines derived from these tumors with normal controls （a neural stem cell （NSC） line and normal brain tissue） identified groups of hyper- and hypomethylated genes that display a trend of either increasing or decreasing methylation levels in the order of controls, primary GBMs, and their counterpart GSC lines, respectively. Interestingly, concurrent promoter hypermethylation and gene body hypomethylation were observed in a subset of genes including MGMT, AJAP1 and PTPRN2. These unique DNA methylation signatures were also found in primary GBM-derived xenograft tumors indicating that they are not tissue culture-related epigenetic changes. Integration of GSC-specific epigenetic signatures with gene expression analysis further identified candidate tumor suppressor genes that are frequently down-regulated in GBMs such as SPINT2, NEFM and PENK. Forced re-expression of SPINT2 reduced glioma cell proliferative capacity, anchorage independent growth, cell motility, and tumor sphere formation in vitro. The results from this study demonstrate that GSCs possess unique epigenetic signatures that may play important roles in the pathogenesis of GBM.

关键词： Glioblastoma cancer stem cells DNA methylation SPINT2

Morphology and kinematics of the gas envelope of the variable AGB star π^1 gruis

在线全文

学校读者我要写书评

暂无评论

Research in Astronomy and Astrophysics 2016年第7期16卷 97-104页

作者： Pham Tuyet Nhung Do Thi Hoai Pham Ngoc Diep Nguyen Thi Phuong Nguyen Thi Thao Pham Tuan Anh Pierre Darriulat Department of Astrophysics Vietnam National Satellite CenterVAST

Observations of the ^12CO（3–2） emission from the circumstellar envelope（CSE） of the variable star π1gru using the compact array of the ALMA observatory have been recently made accessible to the public. An analysis of the morphology and kinematics of the CSE is presented with a result very similar to that obtained earlier for ^12CO（2–1） emission using the Submillimeter Array. A quantitative comparison is made using their flared disk model. A new model is presented that provides a significantly better description of the data, using radial winds and smooth evolutions of the radio emission and wind velocity from the stellar equator to the poles.

关键词： stars AGB and post-AGB circumstellar matter star individual(π1gru) stars massloss radio lines stars

Time-sensitive prediction of NO_(2) concentration in China using an ensemble machine learning model from multi-source data

在线全文

学校读者我要写书评

暂无评论

Journal of Environmental Sciences 2024年第3期137卷 30-40页

作者： Chenliang Tao Man Jia Guoqiang Wang Yuqiang Zhang Qingzhu Zhang Xianfeng Wang Qiao Wang Wenxing Wang Big Data Research center for Ecology and Environment Environment Research InstituteShandong UniversityQingdao 266237China Shandong Provincial Eco-environment Monitoring center Jinan 250101China

Nitrogen dioxide(NO_(2))poses a critical potential risk to environmental quality and public health.A reliable machine learning(ML)forecasting framework will be useful to provide valuable information to support government *** on the data from1609 air quality monitors across China from 2014-2020,this study designed an ensemble ML model by integrating multiple types of spatial-temporal variables and three sub-models for time-sensitive prediction over a wide *** ensemble ML model incorporates a residual connection to the gated recurrent unit(gru)network and adopts the advantage of Transformer,extreme gradient boosting(XGBoost)and gru with residual connection network,resulting in a 4.1%±1.0%lower root mean square error over XGBoost for the test *** ensemble model shows great prediction performance,with coefficient of determination of 0.91,0.86,and 0.77 for 1-hr,3-hr,and 24-hr averages for the test results,*** particular,this model has achieved excellent performance with low spatial uncertainty in Central,East,and North China,the major site-dense *** the interpretability analysis based on the Shapley value for different temporal resolutions,we found that the contribution of atmospheric chemical processes is more important for hourly predictions compared with the daily scale predictions,while the impact of meteorological conditions would be ever-prominent for the *** with existing models for different spatiotemporal scales,the present model can be implemented at any air quality monitoring station across China to facilitate achieving rapid and dependable forecast of NO_(2),which will help developing effective control policies.

关键词： Air quality prediction Deep learning Ensemble method Nitrogen dioxide Spatiotemporal covariates

Gated recurrent unit model for a sequence tagging problem

在线全文

学校读者我要写书评

暂无评论

High Technology Letters 2019年第1期25卷 81-87页

作者： Rekia Kadari Zhang Yu Zhang Weinan Liu Ting Research center for Social Computing and Information Retrieval Harbin Institute of Technology

Combinatory categorial grammer(CCG) supertagging is an important subtask that takes place before full parsing and can benefit many natural language processing(NLP) tasks like question answering and machine translation. CCG supertagging can be regarded as a sequence labeling problem that remains a challenging problem where each word is assigned to a CCG lexical category and the number of the probably associated CCG supertags to each word is large. To address this, recently recurrent neural networks(RNNs), as extremely powerful sequential models, have been proposed for CCG supertagging and achieved good performances. In this paper, a variant of recurrent networks is proposed whose design makes it much easier to train and memorize information for long range dependencies based on gated recurrent units(grus), which have been recently introduced on some but not all tasks. Results of the experiments revealed the effectiveness of the proposed method on the CCGBank datasets and show that the model has comparable accuracy with the previously proposed models for CCG supertagging.

关键词： combinatory categorial grammer (CCG) CCG supertagging deep learning gated recurrent unit (gru)