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RISS 인기검색어
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- 저자 : Yuanhao Liang (검색결과 2 건)
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Yuanhao Guan,Shaozheng Hu,Ping Liang,Yanfeng Zhao,Fei Wang,Xiaoxue Kang 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2019 NANO Vol.14 No.7
"In this work, a highly efficient p-type Cu3P/n-type g-C3N4 heterojunction photocatalyst was synthesized in situ. XRD, UV–Vis, N2 adsorption, TEM, XPS, PL, and EIS are used to characterize the as-prepared catalysts. The results show that Cu3P nanoparticles are highly dispersed onto the g-C3N4 surface, which obviously promotes the separation rate of electrons and holes. The charge transfer between Cu3P and g-C3N4 follows the ""Z-scheme"" mechanism. The as-prepared Cu3P/g-C3N4 heterojunction photocatalyst displays the ammonium ion production rate of 7.5 mg L -1 h -1 g cat -1, which is 28.8 times higher than that of neat g-C3N4, as well as good catalytic stability. The possible reaction mechanism is proposed."
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Xin Li,Yancheng Li,Yuanhao Liang,Ruixue Hu,Wenli Xu,Yufeng Liu 대한당뇨병학회 2021 Diabetes and Metabolism Journal Vol.45 No.2
Background: We hypothesized that specific amino acids or acylcarnitines would have benefits for the differential diagnosis of diabetes. Thus, a targeted metabolomics for amino acids and acylcarnitines in patients with diabetes and its complications was carried out. Methods: A cohort of 54 normal individuals and 156 patients with type 2 diabetes mellitus and/or diabetic complications enrolled from the First Affiliated Hospital of Jinzhou Medical University was studied. The subjects were divided into five main groups: normal individuals, impaired fasting glucose, overt diabetes, diabetic microvascular complications, and diabetic peripheral vascular disease. The technique of tandem mass spectrometry was applied to obtain the plasma metabolite profiles. Metabolomics multivariate statistics were applied for the metabolic data analysis and the differential metabolites determination. Results: A total of 10 cross-comparisons within diabetes and its complications were designed to explore the differential metabolites. The results demonstrated that eight comparisons existed and yielded significant metabolic differences. A total number of 24 differential metabolites were determined from six selected comparisons, including up-regulated amino acids, down-regulated medium-chain and long-chain acylcarnitines. Altered differential metabolites provided six panels of biomarkers, which were helpful in distinguishing diabetic patients. Conclusion: Our results demonstrated that the biomarker panels consisted of specific amino acids and acylcarnitines which could reflect the metabolic variations among the different stages of diabetes and might be useful for the differential diagnosis of prediabetes, overt diabetes and diabetic complications.
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