Ginseng-derived type I rhamnogalacturonan polysaccharide binds to galectin-8 and antagonizes its function

Yi Zheng,Yunlong Si,Xuejiao Xu,Hongming Gu,Zhen He,Zihan Zhao,Zhangkai Feng,Jiyong Su,Kevin H. Mayo,Yifa Zhou,Guihua Tai The Korean Society of Ginseng 2024 Journal of Ginseng Research Vol.48 No.2

Background: Panax ginseng Meyer polysaccharides exhibit various biological functions, like antagonizing galectin-3-mediated cell adhesion and migration. Galectin-8 (Gal-8), with its linker-joined N- and C-terminal carbohydrate recognition domains (CRDs), is also crucial to these biological processes, and thus plays a role in various pathological disorders. Yet the effect of ginseng-derived polysaccharides in modulating Gal-8 function has remained unclear. Methods: P. ginseng-derived pectin was chromatographically isolated and enzymatically digested to obtain a series of polysaccharides. Biolayer Interferometry (BLI) quantified their binding affinity to Gal-8, and their inhibitory effects on Gal-8 was assessed by hemagglutination, cell migration and T-cell apoptosis. Results: Our ginseng-derived pectin polysaccharides consist mostly of rhamnogalacturonan-I (RG-I) and homogalacturonan (HG). BLI shows that Gal-8 binding rests primarily in RG-I and its β-1,4-galactan side chains, with sub-micromolar K_D values. Both N- and C-terminal Gal-8 CRDs bind RG-I, with binding correlated with Gal-8-mediated function. Conclusion: P. ginseng RG-I pectin β-1,4-galactan side chains are crucial to binding Gal-8 and antagonizing its function. This study enhances our understanding of galectin-sugar interactions, information that may be used in the development of pharmaceutical agents targeting Gal-8.

Behavior of hybrid CFST with FRP-confined UHPC core under axial compression

Yi Tao,Jin-Ben Gu,Jian-Fei Chen,Peng Feng 국제구조공학회 2021 Steel and Composite Structures, An International J Vol.40 No.1

A fiber-reinforced polymer (FRP)-confined concrete core that provides high strength and ductility under axial compression can act as strength enhancement in a hybrid column. In the present study, ordinary concrete was replaced with ultra-high-performance concrete (UHPC) to form an FRP-confined UHPC core (FCUC). The FCUC was embedded in square concrete-filled steel tube (CFST) columns to form a high-performance hybrid column (SCF-UHPC column for short). The axial compressive behavior of the SCF-UHPC was experimentally investigated using 12 SCF-UHPC columns and two ordinary CFST columns for comparison. The advantages of the SCF-UHPC include excellent axial load-bearing capacity, good ductility, and stable residual load-bearing capacity. The results show that failure of an SCF-UHPC column was caused by FRP rupture of FCUC, which occurred after steel tube buckling that results in the degraded stiffness. It was also shown that the load-displacement behavior of the SCF-UHPC composite column was determined by the UHPC core diameter and the corresponding confinement provided by the outer steel tube and inner FRP jacket. A hardening effect could be achieved when the confinement demand of the UHPC core was satisfied, whereas a plateau effect appeared if the confinement was insufficient. Furthermore, the load-bearing capacity and ductility of the SCF-UHPC columns improved with increased thickness of the steel tube and the FRP.

Deep Learning in Genomic and Medical Image Data Analysis: Challenges and Approaches

( Ning Yu ),( Zeng Yu ),( Feng Gu ),( Tianrui Li ),( Xinmin Tian ),( Yi Pan ) 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.2

Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.

Deep Learning in Genomic and Medical Image Data Analysis: Challenges and Approaches

Yu, Ning,Yu, Zeng,Gu, Feng,Li, Tianrui,Tian, Xinmin,Pan, Yi Korea Information Processing Society 2017 Journal of information processing systems Vol.13 No.2

Artificial intelligence, especially deep learning technology, is penetrating the majority of research areas, including the field of bioinformatics. However, deep learning has some limitations, such as the complexity of parameter tuning, architecture design, and so forth. In this study, we analyze these issues and challenges in regards to its applications in bioinformatics, particularly genomic analysis and medical image analytics, and give the corresponding approaches and solutions. Although these solutions are mostly rule of thumb, they can effectively handle the issues connected to training learning machines. As such, we explore the tendency of deep learning technology by examining several directions, such as automation, scalability, individuality, mobility, integration, and intelligence warehousing.

Apatinib Combined with Local Irradiation Leads to Systemic Tumor Control via Reversal of Immunosuppressive Tumor Microenvironment in Lung Cancer

Li-jun Liang,Chen-xi Hu,Yi-xuan Wen,Xiao-wei Geng,Ting Chen,Guo-qing Gu,Lei Wang,You-you Xia,Yong Liu,Jia-yan Fei,Jie Dong,Feng-hua Zhao,Yiliyar Ahongjiang,Kai-yuan Hui,Xiao-dong Jiang 대한암학회 2020 Cancer Research and Treatment Vol.52 No.2

Purpose This study aimed to investigate the potential systemic antitumor effects of stereotactic ablative radiotherapy (SABR) and apatinib (a novel vascular endothelial growth factor receptor 2 inhibitor) via reversing the immunosuppressive tumor microenvironment for lung carcinoma. Materials and Methods Lewis lung cancer cells were injected into C57BL/6 mice in the left hindlimb (primary tumor; irradiated) and in the right flank (secondary tumor; nonirradiated). When both tumors grew to the touchable size, mice were randomly divided into eight treatment groups. These groups received normal saline or three distinct doses of apatinib (50 mg/kg, 150 mg/kg, and 200 mg/kg) daily for 7 days, in combination with a single dose of 15 Gy radiotherapy or not to the primary tumor. The further tumor growth/regression of mice were followed and observed. Results For the single 15 Gy modality, tumor growth delay could only be observed at the primary tumor. When combining SABR and apatinib 200 mg/kg, significant retardation of both primary and secondary tumor growth could be observed, indicated an abscopal effect was induced. Mechanism analysis suggested that programmed death-ligand 1 expression increased with SABR was counteract by additional apatinib therapy. Furthermore, when apatinib was combined with SABR, the composition of immune cells could be changed. More importantly, this two-pronged approach evoked tumor antigen–specific immune responses and the mice were resistant to another tumor rechallenge, finally, long-term survival was improved. Conclusion Our results suggested that the tumor microenvironment could be managed with apatinib, which was effective in eliciting an abscopal effect induced by SABR.

Percutaneous Sacroplasty for Sacral Metastatic Tumors Under Fluoroscopic Guidance Only

Ji Zhang,Chun-gen Wu,Yi-feng Gu,Ming-hua Li 대한영상의학회 2008 Korean Journal of Radiology Vol.9 No.6

Percutaneous sacroplasty is a safe and effective procedure for sacral insufficient fractures under CT or fluoroscopic guidance; although, few reports exist about sacral metastatic tumors. We designed a pilot study to treat intractable pain caused by a sacral metastatic tumor with sacroplasty. A 62-year-old man and a 38-year-old woman with medically intractable pain due to metastatic tumors of S1 from lymphoma and lung cancer, respectively, underwent percutaneous sacroplasty. Over the course of the follow-up period, the two patients experienced substantial and immediate pain relief that persisted over a 3-month and beyond. The woman had deposition of PMMA (polymethyl methacrylate) in the needle track, but did not experience significant symptoms. No other peri-procedural complications were observed for either patient.

Percutaneous Osteoplasty for the Management of a Femoral Head Metastasis: a Case Report

Wei-Guo Wang,Chun-Gen Wu,Yi-Feng Gu,Ming-Hua Li 대한영상의학회 2009 Korean Journal of Radiology Vol.10 No.6

Percutaneous osteoplasty (POP) as a technical extension of percutaneous vertebroplasty (PVP) has been used to treat malignant disease that affects the skeletal system. POP has demonstrated good outcome for pain relief and functional improvement. Few studies have reported on the efficiency of POP to treat malignancies located in the femoral head. We designed a pilot study with the use of POP to treat intractable pain caused by a femoral head metastatic tumor in a 43-year-old man. During the follow-up period, the patient experienced sustained pain relief and improvement of quality of life that persisted for more than three months.

A Comprehensive Review of Emerging Computational Methods for Gene Identification

Yu, Ning,Yu, Zeng,Li, Bing,Gu, Feng,Pan, Yi Korea Information Processing Society 2016 Journal of information processing systems Vol.12 No.1

Gene identification is at the center of genomic studies. Although the first phase of the Encyclopedia of DNA Elements (ENCODE) project has been claimed to be complete, the annotation of the functional elements is far from being so. Computational methods in gene identification continue to play important roles in this area and other relevant issues. So far, a lot of work has been performed on this area, and a plethora of computational methods and avenues have been developed. Many review papers have summarized these methods and other related work. However, most of them focus on the methodologies from a particular aspect or perspective. Different from these existing bodies of research, this paper aims to comprehensively summarize the mainstream computational methods in gene identification and tries to provide a short but concise technical reference for future studies. Moreover, this review sheds light on the emerging trends and cutting-edge techniques that are believed to be capable of leading the research on this field in the future.

A Comprehensive Review of Emerging Computational Methods for Gene Identification

( Ning Yu ),( Zeng Yu ),( Bing Li ),( Feng Gu ),( Yi Pan ) 한국정보처리학회 2016 Journal of information processing systems Vol.12 No.1

Gene identification is at the center of genomic studies. Although the first phase of the Encyclopedia of DNA Elements (ENCODE) project has been claimed to be complete, the annotation of the functional elements is far from being so. Computational methods in gene identification continue to play important roles in this area and other relevant issues. So far, a lot of work has been performed on this area, and a plethora of computational methods and avenues have been developed. Many review papers have summarized these methods and other related work. However, most of them focus on the methodologies from a particular aspect or perspective. Different from these existing bodies of research, this paper aims to comprehensively summarize the mainstream computational methods in gene identification and tries to provide a short but concise technical reference for future studies. Moreover, this review sheds light on the emerging trends and cutting-edge techniques that are believed to be capable of leading the research on this field in the future.

Cloning of the Correct Full Length cDNA of NF-kB-repressing Factor

Yumin Mao,Dai Jianfeng,Jin Feng,Ji Chaoneng,Zheng Zhongshou,Gu Shaohua,Wu Qihan,Wang Liu,Yin Gang,Xie Yi 한국분자세포생물학회 2003 Molecules and cells Vol.16 No.3