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- 저자 : Ying LU (검색결과 276 건)
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Lu, Yue,Zhang, Yan-Yan,Hu, Ying-Chun,Lu, Yan-Hua 대한약학회 2014 Archives of Pharmacal Research Vol.37 No.9
2',4'-Dihydroxy-6'-methoxy-3',5'-dimethylchalcone (DMC) is a chalcone isolated from the buds of Cleistocalyx operculatus (Roxb.) Merr. et Perry, and the hepatoprotective effects of DMC on Kunming mice have been studied in previous study. However, the effects of DMC on hepatocyte toxicity and corresponding mechanism remain unclear. The aim of this study was to evaluate the hepatoprotective mechanism of DMC in human hepatocytes (L02) treated with $H_2O_2$. The results demonstrated that pretreatment with DMC effectively protected $H_2O_2$-induced cell viability loss, cell membrane damage (lactate dehydrogenase, nitric oxide production and caspase-3 accumulation. Besides, DMC pretreatment increased the amount of glutathione, decreased malondialdehyde and the percentage of apoptotic L02 cells compared with only $H_2O_2$ treated group. Taken together, these results indicated that DMC had hepatoprotective effects against $H_2O_2$-induced liver injury by alleviating oxidative stress and apoptosis process in L02 cells, and DMC might be a potential candidate for the intervention of liver diseases.
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Lu-Lu Zhang,Yi-Yang Li,Jiang Hu,Guan-Qun Zhou,Lei Chen,Wen-Fei Li,Ai-Hua Lin,Jun Ma,Zhen-Yu Qi,Ying Sun 대한암학회 2018 Cancer Research and Treatment Vol.50 No.4
Purpose Local relapse-free survival (LRFS) differs widely among patients with T4 category nasopharyngeal carcinoma (NPC). We aimed to build a nomogram incorporating clinicopathological information to predict LRFS in T4 NPC after definitive intensity-modulated radiation therapy (IMRT). Materials and Methods Retrospective study of 415 Chinese patients with non-metastatic T4 NPC treated with definitive IMRT with or without chemotherapy at our cancer center between October 2009 and September 2013. The nomogram for LRFS at 3 and 5 years was generated based on multivariate Cox proportional hazards regression, and validated using bootstrap resampling, assessing discriminative performance using the concordance index (C-index) and determining calibration ability via calibration curves. Results Five-year LRFS was 88.8%. We identified and incorporated four independent prognostic factors for LRFS: ethmoid sinus invasion, primary gross tumor volume, age, and pretreatment body mass index. The C-index of the nomogram for local recurrence was 0.732 (95% confidence interval, 0.726 to 0.738), indicating excellent predictive accuracy. The calibration curve revealed excellent agreement between nomogram-predicted and observed LRFS probabilities. Risk subgroups based on total point score cutoff values enabled effective discrimination of LRFS. Conclusion This pretreatment nomogram enables clinicians to accurately predict LRFS in T4 NPC after definitive IMRT, and could help to facilitate personalized patient counselling and treatment strategies.
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Ying Zhang,Xiaozhou Xu,Ying Yang,Jie Ma,Lulu Wang,Xiangzhi Meng,Bing Chen,Ling Qin,Tao Lu,Yan Gao 한국유방암학회 2018 Journal of breast cancer Vol.21 No.3
Purpose: Follistatin-like protein 1 (FSTL1) is a secreted glycoprotein that has been shown to play a role in various types of cancer. However, the clinical significance and function of FSTL1 in breast cancer have not been reported. We investigated the role of FSTL1 in breast cancer in this study. Methods: Enzyme-linked immunosorbent assays, western blot analysis, and reverse transcription polymerase chain reaction were used to monitor the expression of FSTL1 in breast cancer tissue and in serum samples from breast cancer patients. We employed a 4T1 breast cancer model and Fstl1+/− mice for in vivo studies. Hematoxylin and eosin staining, western blot analysis, and RNA sequencing were used to analyze the effect of FSTL1 on primary tumor growth and lung metastasis. Results: We demonstrated that the expression of FSTL1 is reduced in both the breast cancer tissue and the serum of breast cancer patients. We showed that reduced levels of FSTL1 in serum correlate with elevated expression of Ki-67 and epidermal growth factor receptor (EGFR) in cancer tissues. Moreover, lowered expression of FSTL1 was associated with decreased survival in breast cancer patients. Experiments on the Fstl1+/− mouse model established that FSTL1 deficiency had no effect on primary tumor growth, but increased the lung metastases of breast cancer cells, resulting in reduced survival of tumor-bearing mice. RNA sequencing found significantly reduced expression of Egln3 and increased expression of EGFR in Fstl1+/− mice. Thus, our results suggest that FSTL1 may affect the expression of EGFR through Egln3, inhibiting the proliferation of breast cancer cells at lung metastatic sites. Conclusion: In conclusion, we suggest a suppressor role of FSTL1 in breast cancer lung metastasis. Furthermore, FSTL1 may represent a potential prognostic biomarker and a candidate therapeutic target in breast cancer patients.
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Ying-Yuan Lu,Xiao-Wei Wang,Xin Wang,Wen-Bing Dai,Qiang Zhang,Pu Li,Ya-Qing Lou,Chuang Lu,Jun-Yi Liu,Guo-Liang Zhang 대한약학회 2016 Archives of Pharmacal Research Vol.39 No.7
The purpose of this study was to characterize the disposition, distribution, excretion and plasma protein binding of 6-benzyl-1-benzyloxymethyl-5-iodouracil (W- 1) in rats. Concentrations of W-1 within biological samples were determined using a validated high performance liquid chromatography method. The plasma protein binding of W-1 was examined by equilibrium dialysis method. After oral administration of W-1 (50, 100 and 200 mg/kg, respectively) in self-microemulsifying drug delivery system formulation, the pharmacokinetic parameters of W-1 were as follows: the peak plasma concentrations (Cmax) were 0.42, 1.50 and 2.55 μg/mL, the area under the curve (AUC0-t) were 0.89, 2.27 and 3.96 lg/h mL and the plasma half-life (t1/2) were 5.15, 3.77 and 3.77 h, respectively. Moreover, the prototype of W-1 was rapidly and extensively distributed into fifteen tissues, especially higher concentrations were detected in intestine, stomach and liver, respectively. The plasma protein binding of W-1 in rat, beagle dog and human were in the range of 97.96–99.13 %. This study suggested that W-1 has an appropriate pharmacokinetics in rats, such as rapid absorption, moderate clearance, and rapid distribution to multiple tissues. Those properties provide important information for further development W-1 as an anti-HIV-1 drug candidate.
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Wet-Spinning Fabrication of Flexible Conductive Composite Fibers from Silver Nanowires and Fibroin
Ying Lu,Jianwei Jiang,Sanghyuk Park,Dong Wang,Longhai Piao,Jinkwon Kim 대한화학회 2020 Bulletin of the Korean Chemical Society Vol.41 No.2
Biocompatible flexible conductive composite fibers have attracted great research interest because of multitude of their potential applications, such as wearable devices, biomedical sensors, and actuators. Herein, highly conductive and flexible silver nanowire (AgNW)/fibroin composite fibers were fabricated by using a wet-spinning technique. The composite fiber conductivity was as high as 5670?S/cm at an AgNW concentration of 29.1?wt%. The composite fibers also exhibited high flexibilities and could be folded without losing their conductivities. Furthermore, the composite fiber fabricated with a 3? draw ratio exhibited a breaking strain of 27.3% and breaking stress of 118.1 cN/dtex. Our attempt to produce such biocompatible flexible conductive composite fibers by using sustainable regenerated silk fibroins and compatible AgNWs via wet spinning may provide a practical way for fabricating functional biocompatible fiber materials.
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Sparse Polynomial Mapping for Manifold Learning
Ying Xia,Qiang Lu,Hae-Young Bae 보안공학연구지원센터(IJSIP) 2014 International Journal of Signal Processing, Image Vol.7 No.6
Manifold learning is an approach for nonlinear dimensionality reduction and has been a hot research topic in the field of computer science. A disadvantage of manifold learning methods is, however, that there are no explicit mappings from the high-dimensional feature space to the low-dimensional representation space. It restricts the application of manifold learning methods in many practical problems such as target detection and classification. Previously, some methods have been proposed to provide linear or nonlinear mappings for manifold learning methods. However, a disadvantage of all these methods is that the learned projective functions are combinations of all the original features, thus it is often difficult to interpret the results. Moreover, the dense projection matrices of these approaches lead to a high cost of computation and storage. In this paper, a sparse polynomial mapping approach is proposed for manifold learning. We first get the low-dimensional representations of the high-dimensional input data by using a manifold learning method, and then a 1-based simplified polynomial regression is used to get a sparse polynomial mapping between the high-dimensional data and their low-dimensional representations. In particular, we apply this to the method of Laplacian eigenmap and derive a sparse nonlinear manifold learning algorithm, which is named sparse locality preserving polynomial embedding. Experimental results on real-world data show the effectiveness of our approach.
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Design of a remote expert system platform for device-dependent
Ying Lu,Mingxia Li 한국멀티미디어학회 2006 한국멀티미디어학회 국제학술대회 Vol.2006 No.-
This paper introduce the design of a remote expert system platform for device-dependent which provides an automatic equipment fault diagnosis with remote communication on time. The platform improves the accurate of automatic equipment fault diagnosis by two layer structure of three topic expert system database and fuzzy algorithm with artificial neural network.
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Lu, Ying,Jiang, Jianwei,Yoon, Sungho,Kim, Kyung-Shik,Kim, Jae-Hyun,Park, Sanghyuk,Kim, Sang-Ho,Piao, Longhai American Chemical Society 2018 ACS APPLIED MATERIALS & INTERFACES Vol.10 No.2
<P>Highly stretchable and conductive fibers have attracted great interest as a fundamental building block for the next generation of textile-based electronics. Because of its high conductivity and high aspect ratio, the Ag nanowire (AgNW) has been considered one of the most promising conducting materials for the percolation network-based conductive films and composites. However, the poor dispersibility of AgNWs in hydrophobic polymers has hindered their application to stretchable conductive composite fibers. In this paper, we present a highly stretchable and conductive composite fiber from the co-spinning of surface-modified AgNWs and thermoplastic polyurethane (PU). The surface modification of AgNWs with a polyethylene glycol derivative improved the compatibility of PU and AgNWs, which allowed the NWs to disperse homogeneously in the elastomeric matrix, forming effective percolation networks and causing the composite fiber to show enhanced electrical and mechanical performance. The maximum AgNW mass fraction in the composite fiber was 75.9 wt %, and its initial electrical conductivity was as high as 14 205 S/cm. The composite fibers also exhibited superior stretchability: the maximum rupture strain of the composite fiber with 14.6 wt % AgNW was 786%, and the composite fiber was also conductive even when it was stretched up to 200%. In addition, 2-dimensional (2-D) Ag nanoplates were added to the AgNW/PU composite fibers to increase the stability of the conductive network under repeated stretching and releasing. The Ag nanoplates acted as a bridge to effectively prevent the AgNWs from slippage and greatly improved the stability of the conductive network.</P>
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