177 results  1 of 9 

1 Machine Learning Application in Diabetes and Endocrine Disorders
Namki Hong, Heajeong Park, Yumie Rhee
J Korean Diabetes.2020;21(3):130-139.   Published online 2020 September 30     DOI: http://dx.doi.org/10.4093/jkd.2020.21.3.130
2 Revisiting the Bacterial Phylum Composition in Metabolic Diseases Focused on Host Energy Metabolism
Yeonmi Lee, Hui-Young Lee
Diabetes Metab J.2020;44(5):658-667.   Published online 2020 July 9     DOI: http://dx.doi.org/10.4093/dmj.2019.0220
3 The Role of Growth Differentiation Factor 15 in Energy Metabolism
Joon Young Chang, Hyun Jung Hong, Seul Gi Kang, Jung Tae Kim, Ben Yuan Zhang, Minho Shong
Diabetes Metab J.2020;44(3):363-371.   Published online 2020 June 29     DOI: http://dx.doi.org/10.4093/dmj.2020.0087
4 Gestational Diabetes Mellitus and Long-Term Prognosis of the Offsprings
Joon Seong Won
J Korean Diabetes.2020;21(2):81-87.   Published online 2020 June 2     DOI: http://dx.doi.org/10.4093/jkd.2020.21.2.81
5 Effects of Microbiota on the Treatment of Obesity with the Natural Product Celastrol in Rats
Weiyue Hu, Lingling Wang, Guizhen Du, Quanquan Guan, Tianyu Dong, Ling Song, Yankai Xia, Xinru Wang
Diabetes Metab J.2020;44(5):747-763.   Published online 2020 May 11     DOI: http://dx.doi.org/10.4093/dmj.2019.0124
6 Role of Intestinal Microbiota in Metabolism of Voglibose In Vitro and In Vivo
Mahesh Raj Nepal, Mi Jeong Kang, Geon Ho Kim, Dong Ho Cha, Ju-Hyun Kim, Tae Cheon Jeong
Diabetes Metab J.2020;44(6):908-918.   Published online 2020 April 6     DOI: http://dx.doi.org/10.4093/dmj.2019.0147
7 Machine Learning Applications in Endocrinology and Metabolism Research: An Overview
Namki Hong, Heajeong Park, Yumie Rhee
Endocrinol Metab.2020;35(1):71-84.   Published online 2020 March 19     DOI: http://dx.doi.org/10.3803/EnM.2020.35.1.71
8 Role of CRTC2 in Metabolic Homeostasis: Key Regulator of Whole-Body Energy Metabolism?
Hye-Sook Han, Yongmin Kwon, Seung-Hoi Koo
Diabetes Metab J.2020;44(4):498-508.   Published online 2020 March 5     DOI: http://dx.doi.org/10.4093/dmj.2019.0200
9 Glucose Effectiveness from Short Insulin-Modified IVGTT and Its Application to the Study of Women with Previous Gestational Diabetes Mellitus
Micaela Morettini, Carlo Castriota, Christian Göbl, Alexandra Kautzky-Willer, Giovanni Pacini, Laura Burattini, Andrea Tura
Diabetes Metab J.2020;44(2):286-294.   Published online 2020 January 13     DOI: http://dx.doi.org/10.4093/dmj.2019.0016
10 Quantifications of Lipid Kinetics In Vivo Using Stable Isotope Tracer Methodology
Il-Young Kim, Sanghee Park, Jiwoong Jang, Robert R. Wolfe
J Lipid Atheroscler.2020;9(1):110-123.   Published online 2020 January 8     DOI: http://dx.doi.org/10.12997/jla.2020.9.1.110
11 Positioning Metabolism as a Central Player in the Diabetic Heart
Laura J. Mereweather, Claudia N. Montes Aparicio, Lisa C. Heather
J Lipid Atheroscler.2020;9(1):92-109.   Published online 2020 January 8     DOI: http://dx.doi.org/10.12997/jla.2020.9.1.92
12 Changes in Glucose Metabolism with Aging
Eun-Gyoung Hong
J Korean Diabetes.2019;20(4):215-219.   Published online 2019 December 31     DOI: http://dx.doi.org/10.4093/jkd.2019.20.4.215
13 Two Faces of White Adipose Tissue with Heterogeneous Adipogenic Progenitors
Injae Hwang, Jae Bum Kim
Diabetes Metab J.2019;43(6):752-762.   Published online 2019 December 26     DOI: http://dx.doi.org/10.4093/dmj.2019.0174
14 Medium- and long-chain triglyceride propofol reduces the activity of acetyl-coenzyme A carboxylase in hepatic lipid metabolism in HepG2 and Huh7 cells
Li-yuan Wang, Jing Wu, Ya-fen Gao, Duo-mao Lin, Jun Ma
Korean J Physiol Pharmacol.2020;24(1):19-26.   Published online 2019 December 20     DOI: http://dx.doi.org/10.4196/kjpp.2020.24.1.19
15 Hepcidin and Neutrophil Gelatinase-Associated Lipocalin as a Biomarker for Acute Kidney Injury Linked Iron Metabolism
Sun Young Cho, Mina Hur
Ann Lab Med.2020;40(2):97-98.   Published online 2019 October 23     DOI: http://dx.doi.org/10.3343/alm.2020.40.2.97
16 Implementation of a Targeted Next-Generation Sequencing Panel for Constitutional Newborn Screening in High-Risk Neonates
Hyunjoo Lee, Joohee Lim, Jeong Eun Shin, Ho Sun Eun, Min Soo Park, Kook In Park, Ran Namgung, Jin-Sung Lee
Yonsei Med J.2019;60(11):1061-1066.   Published online 2019 October 17     DOI: http://dx.doi.org/10.3349/ymj.2019.60.11.1061
17 Recent Progress on Branched-Chain Amino Acids in Obesity, Diabetes, and Beyond
Md Abu Bakkar Siddik, Andrew C. Shin
Endocrinol Metab.2019;34(3):234-246.   Published online 2019 September 26     DOI: http://dx.doi.org/10.3803/EnM.2019.34.3.234
18 Differences in dietary intakes, body compositions, and biochemical indices between metabolically healthy and metabolically abnormal obese Korean women
Eun Yeong Kang, Jung-Eun Yim
Nutr Res Pract.2019;13(6):488-497.   Published online 2019 August 13     DOI: http://dx.doi.org/10.4162/nrp.2019.13.6.488
19 Understanding the pharmacokinetics of reversible metabolism
Seungil Cho, Young-Ran Yoon
Transl Clin Pharmacol.2019;27(2):52-58.   Published online 2019 June 28     DOI: http://dx.doi.org/10.12793/tcp.2019.27.2.52
20 Prognostic value of metabolic tumor volume and total lesion glycolysis from 18F-FDG PET/CT in lymph node metastases and risk stratification of endometrial carcinoma
Dou-dou Liu, Jianfang Li, Xiaomao Li, Liangjun Xie, Luping Qin, Fangyu Peng, Mu-hua Cheng
J Gynecol Oncol.2019;30(6):e89.  Published online 2019 June 11     DOI: http://dx.doi.org/10.3802/jgo.2019.30.e89

 1 of 9