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- 검색키워드
- 저자 : Mao-Xiong Wu (검색결과 3 건)
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Yifei Mao,Zhongtang Xiong,Songxin Wu,Zhiqing Huang,Ruoxian Zhang,Yuqin He,Yuling Peng,Yang Ye,Tianfa Dong,Hui Mai 한국유방암학회 2022 Journal of breast cancer Vol.25 No.2
Purpose: Knowing the distinction between benign and borderline/malignant phyllodes tumors (PTs) can help in the surgical treatment course. Herein, we investigated the value of magnetic resonance imaging-based texture analysis (MRI-TA) in differentiating between benign and borderline/malignant PTs. Methods: Forty-three women with 44 histologically proven PTs underwent breast MRI before surgery and were classified into benign (n = 26) and borderline/malignant groups (n = 18 [15 borderline, 3 malignant]). Clinical and routine MRI parameters (CRMP) and MRI-TA were used to distinguish benign from borderline/malignant PT. In total, 298 texture parameters were extracted from fat-suppression (FS) T2-weighted, FS unenhanced T1-weighted, and FS first-enhanced T1-weighted sequences. To evaluate the diagnostic performance, receiver operating characteristic curve analysis was performed for the K-nearest neighbor classifier trained with significantly different parameters of CRMP, MRI sequence-based TA, and the combination strategy. Results: Compared with benign PTs, borderline/malignant ones presented a higher local recurrence (p = 0.045); larger size (p < 0.001); different time-intensity curve pattern (p = 0.010); and higher frequency of strong lobulation (p = 0.024), septation enhancement (p = 0.048), cystic component (p = 0.023), and irregular cystic wall (p = 0.045). TA of FS T2- weighted images (0.86) showed a significantly higher area under the curve (AUC) than that of FS unenhanced T1-weighted (0.65, p = 0.010) or first-enhanced phase (0.72, p = 0.049) images. The texture parameters of FS T2-weighted sequences tended to have a higher AUC than CRMP (0.79, p = 0.404). Additionally, the combination strategy exhibited a similar AUC (0.89, p = 0.622) in comparison with the texture parameters of FS T2-weighted sequences. Conclusion: MRI-TA demonstrated good predictive performance for breast PT pathological grading and could provide surgical planning guidance. Clinical data and routine MRI features were also valuable for grading PTs.
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IL-33 promotes IL-10 production in macrophages: a role for IL-33 in macrophage foam cell formation
Hai-Feng Zhang,Mao-Xiong Wu,Yong-Qing Lin,Shuang-Lun Xie,Tu-Cheng Huang,Pin-Ming Liu,Ru-Qiong Nie,Qin-Qi Meng,Nian-Sang Luo,Yang-Xin Chen,Jing-Feng Wang 생화학분자생물학회 2017 Experimental and molecular medicine Vol.49 No.-
We evaluated the role of IL-10- in IL-33-mediated cholesterol reduction in macrophage-derived foam cells (MFCs) and the mechanism by which IL-33 upregulates IL-10. Serum IL-33 and IL-10 levels in coronary artery disease patients were measured. The effects of IL-33 on intra-MFC cholesterol level, IL-10, ABCA1 and CD36 expression, ERK 1/2, Sp1, STAT3 and STAT4 activation, and IL-10 promoter activity were determined. Core sequences were identified using bioinformatic analysis and sitespecific mutagenesis. The serum IL-33 levels positively correlated with those of IL-10. IL-33 decreased cellular cholesterol level and upregulated IL-10 and ABCA1 but had no effect on CD36 expression. siRNA-IL-10 partially abolished cellular cholesterol reduction and ABCA1 elevation by IL-33 but did not reverse the decreased CD36 levels. IL-33 increased IL-10 mRNA production but had little effect on its stability. IL-33 induced ERK 1/2 phosphorylation and increased the luciferase expression driven by the IL-10 promoter, with the highest extent within the − 2000 to − 1752 bp segment of the 5′-flank of the transcription start site; these effects were counteracted by U0126. IL-33 activated Sp1, STAT3 and STAT4, but only the STAT3 binding site was predicted in the above segment. Site-directed mutagenesis of the predicted STAT3-binding sites (CTGCTTCCTGGCAGCAGAA→CTGCCTGGCAGCAGAA) reduced luciferase activity, and a STAT3 inhibitor blocked the regulatory effects of IL-33 on IL-10 expression. Chromatin immunoprecipitation (CHIP) confirmed the STAT3-binding sequences within the − 1997 to − 1700 and − 1091 to − 811 bp locus regions. IL-33 increased IL-10 expression in MFCs via activating ERK 1/2 and STAT3, which subsequently promoted IL-10 transcription and thus contributed to the beneficial effects of IL-33 on MFCs.
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Bowen Tan,Yijie Zhou,Zhilei Song,Yinxuan Peng,Fang Wu,Yue Kang,Xiaomin Liu,Li Zeng,Tingting Huang,Zongying Liu,Lili Xiong,Zhiyun Guo,Jian Cui,Canquan Mao 대한화학회 2015 Bulletin of the Korean Chemical Society Vol.36 No.9
Membrane type-1 matrix metalloproteinase (MT1-MMP; also known as MMP14) is a key enzyme involved in tumor invasion and metastasis, and is a potential target for drug discovery for cancer therapy. However, till now there is no MT1-MMP- or MMP-based anticancer drugs in the market mainly because of the high conservation of the MMP family and also because there is no elucidated crystal structure for the mature MT1-MMP. The modeling of the three-dimensional structure of mature MT1-MMP and the finding of MT1-MMP targeted peptides by virtual screening are highly desired. In this study, the three-dimensional structure of mature MT1-MMP is constructed by homology and de novo modeling and later rationalized and optimized by molecular dynamics simulations. An antisense peptide library was constructed against the divergent sense peptide DEGTEEET in the specific region of MT1-MMP, which was found by multiple alignment of the whole MMP family. The antisense peptide library was virtually screened against the constructed three-dimensional model of MT1-MMP. The top 20 novel peptides were further studied, which were found well docked with MT1-MMP at the region of DEGTEEET, again confirming their specific binding to MT1-MMP. Preliminary study of one of the top-ranked peptide SFLLSPFV showed that it could inhibit the viabilities of MG63 and MDA-MB-231 tumor cells. We thus not only successfully modeled the three-dimensional structure of mature MT1-MMP but also provided a new way for the finding of peptide candidates targeting MT1-MMP based on antisense peptide library.
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