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Articles 1 - 5 of 5
Full-Text Articles in Medicine and Health Sciences
Neutralizing Antibodies Against Ebv Gp42 Show Potent In Vivo Protection And Define Novel Epitopes, Qian Wu, Ling Zhong, Dongmei Wei, Wanlin Zhang, Junping Hong, Yinfeng Kang, Kaiyun Chen, Yang Huang, Qingbing Zheng, Miao Xu, Mu-Sheng Zeng, Yi-Xin Zeng, Ningshao Xia, Qinjian Zhao, Claude Krummenacher, Yixin Chen, Xiao Zhang
Neutralizing Antibodies Against Ebv Gp42 Show Potent In Vivo Protection And Define Novel Epitopes, Qian Wu, Ling Zhong, Dongmei Wei, Wanlin Zhang, Junping Hong, Yinfeng Kang, Kaiyun Chen, Yang Huang, Qingbing Zheng, Miao Xu, Mu-Sheng Zeng, Yi-Xin Zeng, Ningshao Xia, Qinjian Zhao, Claude Krummenacher, Yixin Chen, Xiao Zhang
Faculty Scholarship for the College of Science & Mathematics
Epstein-Barr virus (EBV) is the first reported human oncogenic virus and infects more than 95% of the human population worldwide. EBV latent infection in B lymphocytes is essential for viral persistence. Glycoprotein gp42 is an indispensable member of the triggering complex for EBV entry into B cells. The C-type lectin domain (CTLD) of gp42 plays a key role in receptor binding and is the major target of neutralizing antibodies. Here, we isolated two rabbit antibodies, 1A7 and 6G7, targeting gp42 CTLD with potent neutralizing activity against B cell infection. Antibody 6G7 efficiently protects humanized mice from lethal EBV challenge and …
Self-Supervised Deep Clustering Of Single-Cell Rna-Seq Data To Hierarchically Detect Rare Cell Populations., Tianyuan Lei, Ruoyu Chen, Shaoqiang Zhang, Yong Chen
Self-Supervised Deep Clustering Of Single-Cell Rna-Seq Data To Hierarchically Detect Rare Cell Populations., Tianyuan Lei, Ruoyu Chen, Shaoqiang Zhang, Yong Chen
Faculty Scholarship for the College of Science & Mathematics
Single-cell RNA sequencing (scRNA-seq) is a widely used technique for characterizing individual cells and studying gene expression at the single-cell level. Clustering plays a vital role in grouping similar cells together for various downstream analyses. However, the high sparsity and dimensionality of large scRNA-seq data pose challenges to clustering performance. Although several deep learning-based clustering algorithms have been proposed, most existing clustering methods have limitations in capturing the precise distribution types of the data or fully utilizing the relationships between cells, leaving a considerable scope for improving the clustering performance, particularly in detecting rare cell populations from large scRNA-seq data. …
Sctiger: A Deep-Learning Method For Inferring Gene Regulatory Networks From Case Versus Control Scrna-Seq Datasets., Madison Dautle, Shaoqiang Zhang, Yong Chen
Sctiger: A Deep-Learning Method For Inferring Gene Regulatory Networks From Case Versus Control Scrna-Seq Datasets., Madison Dautle, Shaoqiang Zhang, Yong Chen
Faculty Scholarship for the College of Science & Mathematics
Inferring gene regulatory networks (GRNs) from single-cell RNA-seq (scRNA-seq) data is an important computational question to find regulatory mechanisms involved in fundamental cellular processes. Although many computational methods have been designed to predict GRNs from scRNA-seq data, they usually have high false positive rates and none infer GRNs by directly using the paired datasets of case-versus-control experiments. Here we present a novel deep-learning-based method, named scTIGER, for GRN detection by using the co-differential relationships of gene expression profiles in paired scRNA-seq datasets. scTIGER employs cell-type-based pseudotiming, an attention-based convolutional neural network method and permutation-based significance testing for inferring GRNs among …
Voluntary Wheel Running Promotes Resilience To The Behavioral Effects Of Unpredictable Chronic Mild Stress In Male And Female Mice., Elias Elias, Ariel Y Zhang, Abigail G White, Matthew J Pyle, Melissa T Manners
Voluntary Wheel Running Promotes Resilience To The Behavioral Effects Of Unpredictable Chronic Mild Stress In Male And Female Mice., Elias Elias, Ariel Y Zhang, Abigail G White, Matthew J Pyle, Melissa T Manners
Faculty Scholarship for the College of Science & Mathematics
Besides significant benefits to physical health, exercise promotes mental health, reduces symptoms of mental illness, and enhances psychological development. Exercise can offset the impact of chronic stress, which is a major precursor to the development of mental disorders. The effects of exercise on chronic stress-induced behaviors are contradictory in preclinical studies, primarily due to the lack of data and sex-specific investigations. We sought to evaluate the effects of exercise on chronic stress-induced behavioral changes in both male and female mice. Mice were subjected to an Unpredictable Chronic Mild Stress (UCMS) paradigm with accessibility to running wheels for 2 h daily. …
Novel Signposts On The Road From Natural Sources To Pharmaceutical Applications: A Combinative Approach Between Lc-Dad-Ms And Offline Lc-Nmr For The Biochemical Characterization Of Two Hypericum Species (H. Montbretii And H. Origanifolium), Stefania Sut, Stefano Dall'acqua, Gokhan Zengin, Ismail Senkardes, Abdullahi Ibrahim Uba, Abdelhakim Bouyahya, Abdurrahman Aktumsek
Novel Signposts On The Road From Natural Sources To Pharmaceutical Applications: A Combinative Approach Between Lc-Dad-Ms And Offline Lc-Nmr For The Biochemical Characterization Of Two Hypericum Species (H. Montbretii And H. Origanifolium), Stefania Sut, Stefano Dall'acqua, Gokhan Zengin, Ismail Senkardes, Abdullahi Ibrahim Uba, Abdelhakim Bouyahya, Abdurrahman Aktumsek
Faculty Scholarship for the College of Science & Mathematics
The members of the genus Hypericum have great potential to develop functional uses in nutraceutical and pharmaceutical applications. With this in mind, we aimed to determine the chemical profiling and biological properties of different extracts (ethyl acetate, methanol and water) from two Hypericum species (H. montbretii and H. origanifolium). We combined two approaches (LC-DAD-MS and LC-NMR) to identify and quantify chemical compounds of the extracts. Antioxidant properties (free radical quenching, reducing power and metal chelating) and enzyme inhibitory effects (cholinesterase, tyrosinase, amylase and glucosidase) were determined as biological properties. The tested extracts were rich in caffeic acid derivatives and flavonoids, …