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- 저자 : Yulu Sun (검색결과 2 건)
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Yulu Sun,Guijun Hao,Mengqi Zhuang,Huijuan Lv,Chunhong Liu,Keli Su 연세대학교의과대학 2022 Yonsei medical journal Vol.63 No.3
Purpose: Long non-coding RNAs (lncRNAs) may act as oncogenes in small-cell lung cancer (SCLC). Exosomes containing lncRNAsreleased from cancer-associated fibroblasts (CAF) accelerate tumorigenesis and confer chemoresistance. This studyaimed to explore the action mechanism of the CAF-derived lncRNA maternally expressed gene 3 (MEG3) on cisplatin (DDP) chemoresistanceand cell processes in SCLC. Materials and Methods: Quantitative real-time PCR was conducted to determine the expression levels of MEG3, miR-15a-5p, andCCNE1. Cell viability and metastasis were measured by 3-(4, 5-dimethyl-2-thiazolyl)-2, 5-diphenyl-2-h-tetrazolium bromide andinvasion assays, respectively. A xenograft tumor model was developed to confirm the effect of MEG3 overexpression on SCLC progressionin vivo. Relationships between miR-15a-5p and MEG3/CCNE1 were predicted using StarBase software and validated bydual luciferase reporter assay. Western blotting was used to determine protein levels. A co-culture model was established to explorethe effects of exosomes on MEG3 expression in SCLC cell lines. Results: MEG3 was overexpressed in SCLC tissues and cells. MEG3 silencing significantly repressed cell viability and metastasis inSCLC. High expression of MEG3 was observed in CAF-derived conditioned medium (CM) and exosomes, and promoted chemoresistanceand cancer progression. Additionally, MEG3 was found to serve as a sponge of miR-15a-5p to mediate CCNE1 expression. Overexpression of miR-15a-5p and knockout of CCNE1 reversed the effects of MEG3 overexpression on cell viability and metastasis. Conclusion: MEG3 lncRNA released from CAF-derived exosomes promotes DDP chemoresistance via regulation of a miR-15a-5p/CCNE1 axis. These findings may provide insight into SCLC therapy.
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Finger Vein Recognition Using Generalized Local Line Binary Pattern
( Yu Lu ),( Sook Yoon ),( Shan Juan Xie ),( Jucheng Yang ),( Zhihui Wang ),( Dong Sun Park ) 한국인터넷정보학회 2014 KSII Transactions on Internet and Information Syst Vol.8 No.5
Finger vein images contain rich oriented features. Local line binary pattern (LLBP) is a good oriented feature representation method extended from local binary pattern (LBP), but it is limited in that it can only extract horizontal and vertical line patterns, so effective information in an image may not be exploited and fully utilized. In this paper, an orientation-selectable LLBP method, called generalized local line binary pattern (GLLBP), is proposed for finger vein recognition. GLLBP extends LLBP for line pattern extraction into any orientation. To effectually improve the matching accuracy, the soft power metric is employed to calculate the matching score. Furthermore, to fully utilize the oriented features in an image, the matching scores from the line patterns with the best discriminative ability are fused using the Hamacher rule to achieve the final matching score for the last recognition. Experimental results on our database, MMCBNU_6000, show that the proposed method performs much better than state-of-the-art algorithms that use the oriented features and local features, such as LBP, LLBP, Gabor filter, steerable filter and local direction code (LDC).
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