Search

Your search keyword '"Zhou, Dong-Mei"' showing total 654 results
Start Over Author "Zhou, Dong-Mei"
654 results on '"Zhou, Dong-Mei"'

9. Secofumitremorgins C and D, a pair of atropisomers from saltern-derived fungus Aspergillus fumigatus GXIMD00544.

Author

Zhang, Geng-Si, Li, Hai-Yan, Liang, Li-Fen, Fu, Chun-Qing, Yu, Qin, Liu, Kai, Su, Zhi-Wei, Zhou, Dong-Mei, Gao, Cheng-Hai, Xu, Xin-Ya, and Liu, Yong-Hong

Subjects
ANTIFUNGAL agents, ALKALOIDS, MICROBIAL sensitivity tests, FUNGI, PLANT extracts, PHYSICAL & theoretical chemistry, FERMENTATION, ASPERGILLUS, MOLECULAR structure, MEDICINAL plants, MOLECULAR biology, PHARMACODYNAMICS
Abstract

A pair of atropisomers secofumitremorgins C (1a) and D (1b), together with fifteen known alkaloids (2-16), were isolated from a saltern-derived fungus Aspergillus fumigatus GXIMD00544. The structures of atropisomers 1a and 1b were elucidated by the detailed spectroscopic data, chemical reaction and quantum chemical calculations. Compounds 1 and 8 displayed antifungal spore germination effects against plant pathogenic fungus associated with sugarcane Fusarium sp. with inhibitory rates of 53% and 77% at the concentration of 100 µM, repectively. Atropisomers 1 also exhibited antifouling potential against Balanus amphitrite larval settlement with an inhibitory rate of 96% at the concentration of 100 µM. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

24. Establishment and Validation of a Nomogram Model for Prediction of Diabetic Nephropathy in Type 2 Diabetic Patients with Proteinuria

Author

Zhou,Dong-mei, Wei,Jing, Zhang,Ting-ting, Shen,Feng-jie, and Yang,Jin-Kui

Subjects
Pharmacology, Internal Medicine, Targets and Therapy [Diabetes, Metabolic Syndrome and Obesity]
Abstract

Dong-mei Zhou,1,2,&ast; Jing Wei,2,&ast; Ting-ting Zhang,2 Feng-jie Shen,2 Jin-Kui Yang1 1Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People’s Republic of China; 2Department of Endocrinology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221000, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jin-Kui Yang, Department of Endocrinology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, People’s Republic of China, Email jkyang@ccmu.edu.cnPurpose: To establish and validate the nomogram model for predicting diabetic nephropathy (DN) in type 2 diabetes mellitus (T2DM) patients with proteinuria.Methods: A total of 102 patients with T2DM and proteinuria who underwent renal biopsy were included in this study. According to pathological classification of the kidney, the patients were divided into two groups, namely, a DN group (52 cases) and a non-diabetic renal disease (NDRD) group (50 cases). The clinical data were collected, and the factors associated with diabetic nephropathy (DN) were analyzed with multivariate logistic regression. A nomogram model for predicting DN risk was constructed by using R4.1 software. Receiver operator characteristic (ROC) curves were generated, and the K-fold cross-validation method was used for validation. A consistency test was performed by generating the correction curve.Results: Systolic blood pressure (SBP), diabetic retinopathy (DR), hemoglobin (Hb), fasting plasma glucose (FPG) and triglyceride/cystatin C (TG/Cys-C) ratio were independent factors for DN in T2DM patients with proteinuria (P< 0.05). The nomogram model had good prediction efficiency. If the total score of the nomogram exceeds 200, the probability of DN is as high as 95%. The area under the ROC curve was 0.9412 (95% confidence interval (CI) = 0.8981– 0.9842). The 10-fold cross-validation showed that the prediction accuracy of the model was 0.8427. The Hosmer-Lemeshow (H-L) test showed that there was no significant difference between the predicted value and the actual observed value (X2 = 6.725, P = 0.567). The calibration curve showed that the fitting degree of the DN nomogram prediction model was good.Conclusion: The nomogram model constructed in the present study improves the diagnostic efficiency of DN in T2DM patients with proteinuria, and it has a high clinical value.Keywords: diabetic nephropathy, non-diabetic renal disease, nomogram model, type 2 diabetes mellitus

Published
2022

Catalog

Books, media, physical & digital resources
See catalog results