10 results on '"Chen, Yuanwen"'
Search Results
2. Exhaled volatolomics profiling facilitates personalized screening for gastric cancer
- Author
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Chen, Jian, Ji, Yongyan, Liu, Yongqian, Cen, Zhengnan, Chen, Yuanwen, Zhang, Yixuan, Li, Xiaowen, and Li, Xiang
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- 2024
- Full Text
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3. “Fatty” or “steatotic”: Position statement from a linguistic perspective by the Chinese-speaking community
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Miao, Lei, Ye, Shu-Mian, Fan, Jian-Gao, Seto, Wai-Kay, Yu, Hon Ho, Yu, Ming-Lung, Kao, Jia-Horng, Boon-Bee Goh, George, Young, Dan Yock, Wong, Yu Jun, Chan, Wah-Kheong, Yang, Wah, Jia, Jidong, Lau, George, Wei, Lai, Shi, Junping, Zhang, Huijie, Bi, Yan, Pik-Shan Kong, Alice, Pan, Calvin Q., Zheng, Ming-Hua, Liang, Huiqing, Yang, Ling, Li, Xinhua, Zeng, Qing-Lei, Gao, Rong, Hu, Songhao, Yan, Bi, Jin, Xiaozhi, Li, Gang, Chen, En-Qiang, Hu, Dandan, Fan, Xiaotang, Hu, Peng, Chang, Xiangrong, Jin, Yihui, Cai, Yijing, Chen, Liangmiao, Wen, Qianjun, Sun, Jian, Xu, Hexiang, Li, Junfeng, Yang, Yongping, Huang, Ang, Zhang, Dongmei, Tan, Lin, Li, Dongdong, Zhu, Yueyong, Cai, Chenxi, Gu, Xuemei, Shen, Jilong, Zhong, Jianhong, Li, Lu, Li, Zhenzhen, Ma, Chiye, Liu, Yaming, Zhang, Yimin, Zhao, Lei, Han, Juqiang, Chen, Tao, Zhang, Qiang, Yang, Song, Zhang, Le, Chen, Lanlan, Feng, Gong, Wang, Qixia, Hao, Kunyan, Lu, Qinghua, Mao, Yimin, Zhong, Yandan, Wang, Ningjian, Xin, Yongning, Yu, Yongtao, Qi, Xingshun, Wang, Ke, He, Yingli, Du, Mulong, Zou, Zhengsheng, Xia, Mingfeng, Zhao, Suxian, Zhao, Jingjie, Xie, Wen, Zhang, Yao, Ji, Mao, Richeng, Du, Qingwei, Chen, Haitao, Song, Yongfeng, Wang, Cunchuan, Lu, Yan, Song, Yu, Zhang, Chi, Shi, Li, Mak, Lungyi, Chen, Li, Xu, Liang, Yuan, Hai-Yang, Hong, Liang, Hai, Li, Wu, Xiaoning, Yang, Naibin, Li, Jing-Wei, Jiejin, Zou, Zhuolin, Zheng, Wen, Zhao, Jian, Zhang, Xiang, Huang, Chen-Xiao, Yao, Ying, Yuan, Bao-Hong, Huang, Shanshan, Min, Lian, Chai, Jin, Hong, Wandong, Miao, Kai-Wen, Xiao, Tie, Chen, Shun-Ping, Ye, Feng, Song, Yuhu, Zhang, Jinshun, Zhou, Xiao-Dong, Wang, Mingwei, Dai, Kai, Lou, Jianjun, Duan, Xu, Yu, Hongyan, Jin, Xi, Fu, Liyun, Zhang, Yanliang, Ye, Junzhao, Liu, Feng, Chen, Qin-Fen, Zhou, Yong-Hai, Duan, Xiaohua, Zhang, Qun, Zhang, Faming, Cao, Zhujun, Li, Yingxu, Sun, Dan-Qin, Hu, Ai-Rong, Liu, Fenghua, Chen, Yuanwen, Zhang, Dianbao, Gao, Feng, Ye, Hua, Rao, Huiying, Luo, Kaizhong, Dai, Zhijuan, Wang, Chia-Chi, Tang, Shanhong, Hua, Jing, Deng, Cunliang, Zhou, Ling, Fan, Yu-Chen, Wu, Mingyue, Lu, Hongyan, Zhang, Xiaoxun, Zhang, Huai, Ni, Yan, Kei Ng, Stephen Ka, Li, Chunming, Liu, Chang, Zhang, Xia, Shi, Yu, Yan, Hongmei, Xu, Jinghang, Zhou, Yu-Jie, Cheng, Yuan, Bai, Honglian, Hu, Xiang, Gao, Yufeng, Lin, Biaoyang, Gu, Guangxiang, Chen, Jin, Hu, Xiaoli, Yuan, Xiwei, Wang, Jie, Chen, Qiang, Yiling, Li, Zhu, Xiao Jia, Chen, Xu, Zhu, Yongfen, Liu, Xiaolin, Wang, Bing, Cai, Mingyan, Chen, Enguang, Chen, Jun, Chen, Jingshe, Deng, Hong, Chen, Xiaoxin, Chen, Yingxiao, Cheng, Xinran, Chen, Fei, Ding, Yang, Dong, Zhixia, Ding, Yanhua, Qingxian, Cai, Deng, Zerun, Cai, Tingchen, Chen, Yaxi, Chen, Zhongwei, Chen, Xing, Huang, Jiaofeng, Huang, Mingxing, Fu, Lei, Jin, Jianhong, Geng, Bin, Chen, Yu, Chen, Ruicong, Jin, Weimin, Li, Dongliang, Jin, Xianghong, Li, Jian-Jun, Zhang, Jie, Matsiyit, Alimjan, Wang, Guiqi, Gao, Tian, Zhang, Shu, Yan, Wenmao, Liu, Jie, Chen, Peng, Hu, Hao, Li, Ming, Yuan, Ping Ge, Chen, Yi, Dong, Zhiyong, Li, Xiaopeng, Lin, Su, Li, Jie, Li Ang, Xujing, Liu, Xin, Liu, Shousheng, Li, Min-Dian, Qian, Hui, Qi, Minghua, Peng, Liang, Luo, Fei, Dang, Shuangsuo, Mao, Xianhua, Sheng, Qiyue, Lyu, Jiaojian, Liu, Chenghai, Qi, Kemin, Ma, Honglei, Lu, Zhonghua, Pan, Qiong, Miao, Qing, Li, Xiaosong, Lin, Huapeng, Shui, Guanghou, Qu, Shen, Fei, Wang, Liu, Chang-Hai, Xia, Fan, Wang, Dan, Pan, Ziyan, Hu, Fangzheng, Xu, Long, Xiong, Qing-Fang, Yang, Rui-Xu, Wang, Qi, Chen, Ligang, W Ang, Danny, Ren, Wanhua, Tong, Xiaofei, You, Ningning, Xing, Yanqing, Sun, Chao, Yu, Zhuo, Shuangxu, Xu, Honghai, Sun, Yi, Zhang, Taotao, Wu, Wei, Zhang, Yingmei, Ye, Qing, Zhang, Zhongheng, Yan, Jie, Zhou, Bengjie, Liu, Weiqiang, Li, Yongguo, Zhao, Lili, Lei, Siyi, Zhu, Guangqi, Ouyang, Huang, Zhou, Yaoyao, Yin, Jianhui, Xia, Yongsheng, He, Qiancheng, Zhang, Xiaoyong, Yang, Qiao, Yao, Libin, Pan, Xiazhen, Wang, Xiaodong, Li, Yangyang, Zhu, Shenghao, Zhao, Xinyan, Chen, Sui-Dan, Zhu, Jiansheng, Zeng, Jing, Tang, Liangjie, Hu, Kunpeng, Yang, Wanshui, Huang, Bingyuan, Zhuang, Chengle, Xun, Yunhao, Zhou, Jianghua, Xu, Wenjing, Wu, Bian, Zhang, Xuewu, He, Yong, Mei, Zubing, Xia, Zefeng, Lu, Bin Feng, Li, Qiang, Li, Jia, Yan, Xuebing, Wen, Zhengrong, Liu, Wenyue, Xu, Dongsheng, Chen, Huiting, Wang, Jing, Song, Juan, Peng, Jie, Chen, Jionghuang, Li, Shuchen, Zheng, Yongping, Zhi-Zhi, Xing, Tang, Jieting, Liu, Chuan, Chen, Chao, Guicheng, Wu, Ye, Quanzhong, Ka, Li, Zhou, Yuping, Jia, Xiaoli, Zou, Ziyuan, Zu, Fuqiang, Cai, Yongqian, Chen, Yunzhi, Chu, Jinguo, Yan, Bing, Wang, Tie, Pan, Qiuwei, Xie, Lingling, Zeng, Xufen, Liu, Bingrong, Su, Minghua, Mu, Yibing, Zeng, Menghua, Guo, Yuntong, Yang, Yongfeng, Zhang, Xiaoguan, Wu, Shike, Pan, Jin-Shui, Cao, Li, Feng, Wenhuan, Yubin, Yang, Wang, Na, Lu, Xiaolan, Lu, Guanhua, Xiong, Jianbo, Zhuang, Jianbin, Shi, Guojun, Zhu, Yanfei, Ying, Xing, Qiao, Zengpei, Zhang, Rui, Li, Yuting, Lei, Yuanli, Xixi, Wu, Tian, Na, Lian, Liyou, Zhang, Binbin, Xiaozhu, Huang, Yan, Chen, Wenying, Liu, Kun, Zhang, Ruinan, Lai, Qintao, Wang, Fudi, Wen, Caiyun, Zhang, Xinlei, Wu, Lili, Liang, Yaqin, Jie, You, Xinzhejin, Zeng, Qiqiang, Zhu, Qiang, Chao, Zheng, Shou, Lan, Jin, Wei-Lin, Ye, Chenhui, Han, Yu, Xie, Gangqiao, Zhao, Jing, Ye, Chunyan, Wang, Hua, Song, Lintao, Feng, Juan, Huang, Yubei, Su, Wen, Bai, Juli, Wong, Vincent, Wang, Huifeng, Ming, Wai-Kit, Yu, Yue-Cheng, Jin, Yan, Zhao, Yan, Gao, Lilian, Liangwang, Chen, Hanbin, Ruifangwang, Tang, Yuhan, Chen, Gang, Liu, Dabin, Cai, Xiaobo, Xue, Feng, Yang, Qinhe, Sun, Guangyong, Zhu, Chunxia, Huang, Zhifeng, Zhou, Hongwen, Xiao, Xiao, Hou, Xin, He, Jie, Ji, Dong, Xiao, Huanming, Chi, Xiaoling, Zou, Huaibin, Shi, Yiwen, Fan, Xingliang, Hu, Xiaoyu, Huang, Zhouqin, Cao, Haixia, Jiang, Jingjing, Zhao, Qiang, Chen, Wei, Li, Shi Bo, Zhang, Fan, Chen, Zhiyun, Liu, Jinfeng, Li, Shibo, Liu, Jing, Li, Li, Li, Ruyu, Kun, Ya, Xiao, ErHui, Wang, Tingyao, Wang, Chunjiong, Aili, Aikebaier, Liu, Xiaoxia, Ding, Ran, Zhu, Chonggui, Zeng, Xin, Wu, Miao, Li, Zhen, Yang, Tao, Qin, Yunfei, Sun, Lihua, Xu, Ying, Fu, Xianghui, Li, Yongyin, and Ye, Shumian
- Published
- 2025
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4. Critical state shear behavior of the soil-structure interface determined by discrete element modeling
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Gu, Xiaoqiang, Chen, Yuanwen, and Huang, Maosong
- Published
- 2017
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5. Probabilistic corrosion-fatigue prognosis of rib-to-deck welded joints in coastal weathering steel bridges exposed to heavy traffics.
- Author
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Zhu, Jin, Chen, Yuanwen, Heng, Junlin, Wu, Mengxue, Zhang, Yu, and Li, Yongle
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IRON & steel bridges , *MATERIALS testing , *DETERIORATION of concrete , *CORROSION fatigue , *STEEL welding , *WELDED joints , *SERVICE life , *CARBON steel - Abstract
[Display omitted] • Elucidation of CF in rib-to-deck (RD) joints of coastal weathering steel bridges. • PCF model tailored to addresses multi-mode, multi-site failures of RD joints. • Synergy prognosis executed with traffic data, tests, simulations and predictions. • Effect of traffic-corrosivity, coatings, steel types and weld quality scrutinised. This paper introduces a pioneering probabilistic framework for predicting corrosion fatigue (CF) deterioration for coastal weathering steel bridges, employing WIM data, material testing, fracture mechanics, corrosion modelling, and numerical simulations. A comprehensive three-stage probabilistic CF (PCF) model is adapted to track CF crack growth under uncertainties. The applicability and efficacy of the proposed method are validated through a prototype cable-stayed bridge in Ningbo, China, which is subjected to severe corrosivity and heavy traffics. A thorough investigation is conducted on the impact of coating strategies, steel types, and welding quality on the service reliability of the case-study bridge. The study significantly highlights the superior corrosion fatigue performance of weathering steel bridges, elucidating an apparent improvement in the service life compared to traditional carbon steel bridges. This underscores the potential of weathering steel as a preferred material for coastal bridges facing high corrosive environments. Further enhancements can be expected with the proper design of coating strategies, which requires a defined analysis based on the site condition. In addition, the emphasis on minimizing welding flaws through improved welding processes is recommended, demonstrating a direct correlation with extended service life. [ABSTRACT FROM AUTHOR]
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- 2024
- Full Text
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6. Correlation between microRNA-21, microRNA-206 and estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2 in breast cancer.
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Chen, Yuanwen, Wu, Nian, Liu, Lei, Dong, Huaying, and Wu, Chengyi
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ESTROGEN receptors , *PROGESTERONE receptors , *BREAST cancer , *HUMAN growth , *PROTHROMBIN - Abstract
Although the function of microRNA-21 and microRNA-206 in breast cancer cells have been investigated in vitro, their association with estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) are not reported. ER, PR, HER2, and Ki-67 staining pattern were utilized to classify 75 breast cancer patients recruited. The malignancy was predicted with tumor nodes metastases (TNM) classification. RT-qPCR was performed to detect the relative expression of ER, PR, and HER2 in tumor samples and microRNA-21 and microRNA-206 in the serum. Spearman's correlation analysis was used to determine the association between different molecules. According to the staining pattern, the breast cancer patients were classified into five types. microRNA-21 was up-regulated in HER2 positive and Basal-like breast cancer types, while microRNA-206 was up-regulated in Luminal A and B types of breast cancer. microRNA-21 expression negatively correlated with the level of ER and PR but positively correlated with HER2 expression and tumor malignancy, while microRNA-206 showed the opposite trend. Neither microRNA-21 nor microRNA-206 showed any significant correlation with the age of the patients. Both microRNA-21 and microRNA-206 closely correlate with ER, PR, and HER2 expression, which can be considered as clinical biomarkers. [ABSTRACT FROM AUTHOR]
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- 2019
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7. Discrete element modeling of soil-structure interface behavior under cyclic loading.
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Huang, Maosong, Chen, Yuanwen, and Gu, Xiaoqiang
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DISCRETE element method , *SOIL-structure interaction , *CYCLIC loads , *SHEAR testing of soils , *SOIL density - Abstract
Abstract The cyclic shear behavior of the interface between soil and structure at both the macro and the micro level is investigated by interface direct shear tests under constant normal stiffness condition using discrete element modeling. The simulation results are validated qualitatively by the corresponding experiment. The influence of the initial state of the specimen (i.e. soil density and normal stress) on the cyclic behavior is systematically discussed. Moreover, the cyclic accumulative deformation of the interface is carefully studied in the view of the void ratio and the correlation between the final deformations under cyclic and monotonic loading is explored. [ABSTRACT FROM AUTHOR]
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- 2019
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8. Mast cell stabilization decreases cardiomyocyte and LV function in dogs with isolated mitral regurgitation.
- Author
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Pat B, Killingsworth C, Chen Y, Gladden JD, Walcott G, Powell PC, Denney T, Gupta H, Desai R, Tillson M, Dillon AR, Dell'italia LJ, Pat, Betty, Killingsworth, Cheryl, Chen, Yuanwen, Gladden, James D, Walcott, Greg, Powell, Pamela C, Denney, Thomas, and Gupta, Himanshu
- Abstract
Background: Mast cells are increased in isolated mitral regurgitation (MR) in the dog and may mediate extracellular matrix loss and left ventricular (LV) dilatation. We tested the hypothesis that mast cell stabilization would attenuate LV remodeling and improve function in the MR dog.Methods and Results: MR was induced in adult dogs randomized to no treatment (MR, n = 5) or to the mast cell stabilizer, ketotifen (MR + MCS, n = 4) for 4 months. LV hemodynamics were obtained at baseline and after 4 months of MR and magnetic resonance imaging (MRI) was performed at sacrifice. MRI-derived, serial, short-axis LV end-diastolic (ED) and end-systolic (ES) volumes, LVED volume/mass ratio, and LV 3-dimensional radius/wall thickness were increased in MR and MR + MCS dogs compared with normal dogs (n = 6) (P < .05). Interstitial collagen was decreased by 30% in both MR and MR + MCS versus normal dogs (P < .05). LV contractility by LV maximum time-varying elastance was significantly depressed in MR and MR + MCS dogs. Furthermore, cardiomyocyte fractional shortening was decreased in MR versus normal dogs and further depressed in MR + MCS dogs (P < .05). In vitro administration of ketotifen to normal cardiomyocytes also significantly decreased fractional shortening and calcium transients.Conclusions: Chronic mast cell stabilization did not attenuate eccentric LV remodeling or collagen loss in MR. However, MCS therapy had a detrimental effect on LV function because of a direct negative inotropic effect on cardiomyocyte function. [ABSTRACT FROM AUTHOR]- Published
- 2010
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9. Novel insights into interactions between mitochondria and xanthine oxidase in acute cardiac volume overload
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Gladden, James D., Zelickson, Blake R., Wei, Chih-Chang, Ulasova, Elena, Zheng, Junying, Ahmed, Mustafa I., Chen, Yuanwen, Bamman, Marcas, Ballinger, Scott, Darley-Usmar, Victor, and Dell'Italia, Louis J.
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XANTHINE oxidase , *MITOCHONDRIA , *RESPIRATION , *HEART cells , *LEFT heart ventricle , *HEART failure - Abstract
Abstract: Xanthine oxidoreductase (XOR) is increased in the left ventricle (LV) of humans with volume overload (VO), and mitochondrial inhibition of the respiratory chain occurs in animal models of VO. Because mitochondria are both a source and a target of reactive oxygen and nitrogen species, we hypothesized that activation of XOR and mitochondrial dysfunction are interdependent. To test this we used the aortocaval fistula (ACF) rat model of VO and a simulation of the stretch response in isolated adult cardiomyocytes with and without the inhibitor of XOR, allopurinol, or the mitochondrially targeted antioxidant MitoQ. Xanthine oxidase (XO) activity was increased in cardiomyocytes from ACF vs sham rats (24h) without an increase in XO protein. A twofold increase in LV end-diastolic pressure/wall stress and a decrease in LV systolic elastance with ACF were improved when allopurinol treatment (100mg/kg) was started at ACF induction. Subsarcolemmal State 3 mitochondrial respiration was significantly decreased in ACF and normalized by allopurinol. Cardiomyocytes subjected to 3h cyclical stretch resulted in an increase in XO activity and mitochondrial swelling, which was prevented by allopurinol or MitoQ pretreatment. These studies establish an early interplay between cardiomyocyte XO activation and bioenergetic dysfunction that may provide a new target that prevents progression to heart failure in VO. [Copyright &y& Elsevier]
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- 2011
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10. Prolyl endopeptidase disruption reduces hepatic inflammation and oxidative stress in methionine-choline-deficient diet-induced steatohepatitis.
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Zhang, Jianbin, Jiang, Daixi, Lin, Shuangzhe, Cheng, Yuqing, Pan, Jiaxing, Ding, Wenjin, Chen, Yuanwen, and Fan, Jiangao
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OXIDATIVE stress , *METHIONINE , *PALMITIC acid , *FATTY liver , *IMMUNOSTAINING , *GENES , *LIVER analysis - Abstract
Prolyl endopeptidase (PREP) is a serine endopeptidase widely distributed in the body, and accumulated evidence suggests that PREP participates in inflammation and oxidative stress. Here, we explored the effect of PREP gene disruption on hepatic inflammation and oxidative stress status in a methionine-choline-deficient (MCD)-induced nonalcoholic steatohepatitis (NASH) model. PREP gene disruption (PREPgt) mice and wild-type (WT) littermates were placed on a control or an MCD diet for 4 weeks, respectively. The liver histopathological analysis and the number of inflammatory cells were determined by hematoxylin-eosin (HE) and immunohistochemical staining. Inflammation-associated genes and cytokine levels in liver tissue were evaluated by quantitative PCR and ELISA. The levels of P53, Sesn2, Nrf2, HO-1, and oxidative stress indicators in mice and the palmitic acid (PA)-treated human hepatocellular carcinoma cells (HepG2) were examined by immunoblotting and commercially available kits, respectively. We found that PREP expression was upregulated in the MCD-induced NASH model. In addition, PREP disruption alleviated MCD-induced hepatic inflammation accompanied by diminished infiltration of inflammatory cells and secretion of inflammatory mediators. More importantly, the results of this study indicate that targeting PREP can improve oxidative stress status in the liver of MCD-diet mice and PA-exposed HepG2 cells. The effect is most likely mediated by the activation of P53 and its downstream signaling pathways (Sesn2/Nrf2/HO-1). Our results showed that PREP disruption (or inhibition) could decrease oxidative stress and inflammation and improve liver function, indicating that targeting PREP might be a new potential therapeutic option for NAFLD/NASH. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
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