Skip Navigation
Skip to contents

Diabetes Metab J : Diabetes & Metabolism Journal

Search
OPEN ACCESS

Search

Page Path
HOME > Search
4 "Hong Il Kim"
Filter
Filter
Article category
Keywords
Publication year
Authors
Funded articles
Original Articles
Pathophysiology
Metformin Ameliorates Lipotoxic β-Cell Dysfunction through a Concentration-Dependent Dual Mechanism of Action
Hong Il Kim, Ji Seon Lee, Byung Kook Kwak, Won Min Hwang, Min Joo Kim, Young-Bum Kim, Sung Soo Chung, Kyong Soo Park
Diabetes Metab J. 2019;43(6):854-866.   Published online June 27, 2019
DOI: https://doi.org/10.4093/dmj.2018.0179
  • 6,670 View
  • 115 Download
  • 14 Web of Science
  • 13 Crossref
AbstractAbstract PDFPubReader   
Background

Chronic exposure to elevated levels of free fatty acids contributes to pancreatic β-cell dysfunction. Although it is well known that metformin induces cellular energy depletion and a concomitant activation of AMP-activated protein kinase (AMPK) through inhibition of the respiratory chain, previous studies have shown inconsistent results with regard to the action of metformin on pancreatic β-cells. We therefore examined the effects of metformin on pancreatic β-cells under lipotoxic stress.

Methods

NIT-1 cells and mouse islets were exposed to palmitate and treated with 0.05 and 0.5 mM metformin. Cell viability, glucose-stimulated insulin secretion, cellular adenosine triphosphate, reactive oxygen species (ROS) levels and Rho kinase (ROCK) activities were measured. The phosphorylation of AMPK was evaluated by Western blot analysis and mRNA levels of endoplasmic reticulum (ER) stress markers and NADPH oxidase (NOX) were measured by real-time quantitative polymerase chain reaction analysis.

Results

We found that metformin has protective effects on palmitate-induced β-cell dysfunction. Metformin at a concentration of 0.05 mM inhibits NOX and suppresses the palmitate-induced elevation of ER stress markers and ROS levels in a AMPK-independent manner, whereas 0.5 mM metformin inhibits ROCK activity and activates AMPK.

Conclusion

This study suggests that the action of metformin on β-cell lipotoxicity was implemented by different molecular pathways depending on its concentration. Metformin at a usual therapeutic dose is supposed to alleviate lipotoxic β-cell dysfunction through inhibition of oxidative stress and ER stress.

Citations

Citations to this article as recorded by  
  • Metformin enhances METTL14-Mediated m6A methylation to alleviate NIT-1 cells apoptosis induced by hydrogen peroxide
    Si-min Zhou, Xin-ming Yao, Yi Cheng, Yu-jie Xing, Yue Sun, Qiang Hua, Shu-jun Wan, Xiang-jian Meng
    Heliyon.2024; 10(2): e24432.     CrossRef
  • Reduced Expression Level of Protein PhosphatasePPM1EServes to Maintain Insulin Secretion in Type 2 Diabetes
    Sevda Gheibi, Luis Rodrigo Cataldo, Alexander Hamilton, Mi Huang, Sebastian Kalamajski, Malin Fex, Hindrik Mulder
    Diabetes.2023; 72(4): 455.     CrossRef
  • Metformin restores prohormone processing enzymes and normalizes aberrations in secretion of proinsulin and insulin in palmitate‐exposed human islets
    Quan Wen, Azazul Islam Chowdhury, Banu Aydin, Mudhir Shekha, Rasmus Stenlid, Anders Forslund, Peter Bergsten
    Diabetes, Obesity and Metabolism.2023; 25(12): 3757.     CrossRef
  • Treatment of type 2 diabetes mellitus with stem cells and antidiabetic drugs: a dualistic and future-focused approach
    Priyamvada Amol Arte, Kanchanlata Tungare, Mustansir Bhori, Renitta Jobby, Jyotirmoi Aich
    Human Cell.2023; 37(1): 54.     CrossRef
  • Metformin disrupts insulin secretion, causes proapoptotic and oxidative effects in rat pancreatic beta‐cells in vitro
    Maíra M.R. Valle, Eloisa Aparecida Vilas‐Boas, Camila F. Lucena, Simone A. Teixeira, Marcelo N. Muscara, Angelo R. Carpinelli
    Journal of Biochemical and Molecular Toxicology.2022;[Epub]     CrossRef
  • Protection by metformin against severe Covid-19: An in-depth mechanistic analysis
    Nicolas Wiernsperger, Abdallah Al-Salameh, Bertrand Cariou, Jean-Daniel Lalau
    Diabetes & Metabolism.2022; 48(4): 101359.     CrossRef
  • Insight Into Rho Kinase Isoforms in Obesity and Energy Homeostasis
    Lei Wei, Jianjian Shi
    Frontiers in Endocrinology.2022;[Epub]     CrossRef
  • Overexpression of miR-297b-5p Promotes Metformin-Mediated Protection Against Stearic Acid-Induced Senescence by Targeting Igf1r
    Qingrui Zhao, Shenghan Su, Yuqing Lin, Xuebei Li, Lingfeng Dan, Yunjin Zhang, Chunxiao Yang, Xiaohan Li, Yimeng Dong, Chenchen Geng, Changhao Sun, Xia Chu, Huimin Lu
    SSRN Electronic Journal .2022;[Epub]     CrossRef
  • Metformin Dysregulates the Unfolded Protein Response and the WNT/β-Catenin Pathway in Endometrial Cancer Cells through an AMPK-Independent Mechanism
    Domenico Conza, Paola Mirra, Gaetano Calì, Luigi Insabato, Francesca Fiory, Francesco Beguinot, Luca Ulianich
    Cells.2021; 10(5): 1067.     CrossRef
  • NADPH Oxidase (NOX) Targeting in Diabetes: A Special Emphasis on Pancreatic β-Cell Dysfunction
    Suma Elumalai, Udayakumar Karunakaran, Jun-Sung Moon, Kyu-Chang Won
    Cells.2021; 10(7): 1573.     CrossRef
  • Metformin use and cardiovascular outcomes in patients with diabetes and chronic kidney disease: a nationwide cohort study
    Min Ho Kim, Hyung Jung Oh, Soon Hyo Kwon, Jin Seok Jeon, Hyunjin Noh, Dong Cheol Han, Hyoungnae Kim, Dong-Ryeol Ryu
    Kidney Research and Clinical Practice.2021; 40(4): 660.     CrossRef
  • Different Effects of Metformin and A769662 on Sodium Iodate-Induced Cytotoxicity in Retinal Pigment Epithelial Cells: Distinct Actions on Mitochondrial Fission and Respiration
    Chi-Ming Chan, Ponarulselvam Sekar, Duen-Yi Huang, Shu-Hao Hsu, Wan-Wan Lin
    Antioxidants.2020; 9(11): 1057.     CrossRef
  • Metformin Reduces Lipotoxicity-Induced Meta-Inflammation in β-Cells through the Activation of GPR40-PLC-IP3 Pathway
    Ximei Shen, Beibei Fan, Xin Hu, Liufen Luo, Yuanli Yan, Liyong Yang
    Journal of Diabetes Research.2019; 2019: 1.     CrossRef
A Survey on Ubiquitous Healthcare Service Demand among Diabetic Patients
Soo Lim, So-Youn Kim, Jung Im Kim, Min Kyung Kwon, Sei Jin Min, Soo Young Yoo, Seon Mee Kang, Hong Il Kim, Hye Seung Jung, Kyong Soo Park, Jun Oh Ryu, Hayley Shin, Hak Chul Jang
Diabetes Metab J. 2011;35(1):50-57.   Published online February 28, 2011
DOI: https://doi.org/10.4093/dmj.2011.35.1.50
  • 6,796 View
  • 30 Download
  • 23 Crossref
AbstractAbstract PDFPubReader   
Background

Advanced information technology can be used when developing diagnostic and treatment strategies to provide better care for diabetic patients. However, the levels of need and demand for the use of technological advances have not been investigated in diabetic patients. We proposed and developed an individualized, ubiquitous (U)-healthcare service using advanced information technology for more effective glucose control. Prior to our service initiation, we surveyed patient needs and other pertinent information.

Methods

During August 2009, we conducted a 34-item questionnaire survey among patients with diabetes who were older than 40 years in two certain hospitals in Korea.

Results

The mean age of the 228 participants was 61.2±9 years, and males made up 49.1% of the sample. Seventy-one percent replied that they wanted individualized healthcare service, and they also wanted their health information to be delivered through mobile devices such as a cellular phone or a personal digital assistant (40.4%). Most patients had never heard of U-healthcare services (81.1%); however, after explaining the concept, 71.1% of participants responded that they would use the service if it was provided. Despite their willingness, participants were concerned about technical difficulty in using the service (26.3%) as well as the cost of the service (29.8%).

Conclusion

The current study suggests that more than 70% of diabetic patients are interested in using U-healthcare services. To encourage widespread use, the application program or device of U-healthcare services should be simple, easy to use and affordable while also including a policy for the protection of private information.

Citations

Citations to this article as recorded by  
  • Willingness of diabetes mellitus patients to use mHealth applications and its associated factors for self-care management in a low-income country: an input for digital health implementation
    Agmasie Damtew Walle, Tigist Andargie Ferede, Adamu Ambachew Shibabaw, Sisay Maru Wubante, Habtamu Alganeh Guadie, Chalachew Msganaw Yehula, Addisalem Workie Demsash
    BMJ Health & Care Informatics Online.2023; 30(1): e100761.     CrossRef
  • Development and Operation of a Video Teleconsultation System Using Integrated Medical Equipment Gateway: a National Project for Workers in Underserved Areas
    Hyun Sang Park, Kwang il Kim, Jae Young Soh, Young Ho Hyun, Bang Eun Lee, Jong Hwa Lee, Jung Gwon Jo, Han Chae Lee, Hwa Sun Kim
    Journal of Medical Systems.2020;[Epub]     CrossRef
  • Patient experience with an educational mobile health application: A pilot study on usability and feasibility in a Saudi population
    Sireen Abdul Rahim Shilbayeh, Sahar Abd El Rahman Ismail, Meihua Qian
    Cogent Psychology.2020;[Epub]     CrossRef
  • Smart Care Based on Telemonitoring and Telemedicine for Type 2 Diabetes Care: Multi-Center Randomized Controlled Trial
    Ji Yun Jeong, Jae-Han Jeon, Kwi-Hyun Bae, Yeon-Kyung Choi, Keun-Gyu Park, Jung-Guk Kim, Kyu Chang Won, Bong Soo Cha, Chul Woo Ahn, Dong Won Kim, Chang Hee Lee, In-Kyu Lee
    Telemedicine and e-Health.2018; 24(8): 604.     CrossRef
  • Satisfaction Survey on Information Technology-Based Glucose Monitoring System Targeting Diabetes Mellitus in Private Local Clinics in Korea
    Hun-Sung Kim, So Jung Yang, Yoo Jin Jeong, Young-Eun Kim, Seok-Won Hong, Jae Hyoung Cho
    Diabetes & Metabolism Journal.2017; 41(3): 213.     CrossRef
  • Willingness of patients with diabetes to use an ICT-based self-management tool: a cross-sectional study
    Tomomi Shibuta, Kayo Waki, Nobuko Tomizawa, Ayumi Igarashi, Noriko Yamamoto-Mitani, Satoko Yamaguchi, Hideo Fujita, Shigeko Kimura, Katsuhito Fujiu, Hironori Waki, Yoshihiko Izumida, Takayoshi Sasako, Masatoshi Kobayashi, Ryo Suzuki, Toshimasa Yamauchi, T
    BMJ Open Diabetes Research & Care.2017; 5(1): e000322.     CrossRef
  • Evaluating the Effect of Web-Based Iranian Diabetic Personal Health Record App on Self-Care Status and Clinical Indicators: Randomized Controlled Trial
    Amirabbas Azizi, Robab Aboutorabi, Zahra Mazloum-Khorasani, Monavar Afzal-Aghaea, Hamed Tabesh, Mahmood Tara
    JMIR Medical Informatics.2016; 4(4): e32.     CrossRef
  • Development, Validation, and Evaluation of Web-Based Iranian Diabetic Personal Health Record: Rationale for and Protocol of a Randomized Controlled Trial
    Amirabbas Azizi, Robab Aboutorabi, Zahra Mazloum-Khorasani, Monavar Afzal-Aghaea, Mahmood Tara
    JMIR Research Protocols.2016; 5(1): e39.     CrossRef
  • Randomized, Open-Label, Parallel Group Study to Evaluate the Effect of Internet-Based Glucose Management System on Subjects with Diabetes in China
    Hun-Sung Kim, Chenglin Sun, So Jung Yang, Lin Sun, Fei Li, In Young Choi, Jae-Hyoung Cho, Guixia Wang, Kun-Ho Yoon
    Telemedicine and e-Health.2016; 22(8): 666.     CrossRef
  • Environment and Its Influence on Health and Demographics in South Korea
    Ramiro Bravo Santisteban, Young Kim, Umar Farooq, Tae-Seong Kim, Sekyoung Youm, Seung-Hun Park
    International Journal of Environmental Research and Public Health.2016; 13(2): 183.     CrossRef
  • U-Healthcare Center Service in Busan City, South Korea: An Empirical Analysis and the Results of 1 Year of Service
    Ramiro D. Bravo Santisteban, Sekyoung Youm, Seung-Hun Park
    Telemedicine and e-Health.2015; 21(10): 774.     CrossRef
  • Users’ perception on telemedicine service: a comparative study of public healthcare and private healthcare
    Mi Jung Rho, Kun Ho Yoon, Hun-Sung Kim, In Young Choi
    Multimedia Tools and Applications.2015; 74(7): 2483.     CrossRef
  • An Activity Recognition Model Using Inertial Sensor Nodes in a Wireless Sensor Network for Frozen Shoulder Rehabilitation Exercises
    Hsueh-Chun Lin, Shu-Yin Chiang, Kai Lee, Yao-Chiang Kan
    Sensors.2015; 15(1): 2181.     CrossRef
  • Current Clinical Status of Telehealth in Korea: Categories, Scientific Basis, and Obstacles
    Hun-Sung Kim, Hyunah Kim, Suehyun Lee, Kye Hwa Lee, Ju Han Kim
    Healthcare Informatics Research.2015; 21(4): 244.     CrossRef
  • New Directions in Chronic Disease Management
    Hun-Sung Kim, Jae-Hyoung Cho, Kun-Ho Yoon
    Endocrinology and Metabolism.2015; 30(2): 159.     CrossRef
  • Using mobile phones in healthcare management for the elderly
    Hun-Sung Kim, Kye-Hwa Lee, Hyunah Kim, Ju Han Kim
    Maturitas.2014; 79(4): 381.     CrossRef
  • Future Prospects of Health Management Systems Using Cellular Phones
    Hun-Sung Kim, Yunji Hwang, Jae-Ho Lee, Hye Young Oh, Yi-Jun Kim, Hyeon Yoon Kwon, Hyoseung Kang, Hyunah Kim, Rae Woong Park, Ju Han Kim
    Telemedicine and e-Health.2014; 20(6): 544.     CrossRef
  • Exploring the Relationship Among User Satisfaction, Compliance, and Clinical Outcomes of Telemedicine Services for Glucose Control
    Mi Jung Rho, Si Ra Kim, Hun-Sung Kim, Jae-Hyoung Cho, Kun-Ho Yoon, Seong K. Mun, In Young Choi
    Telemedicine and e-Health.2014; 20(8): 712.     CrossRef
  • Impact of Information Technology on the Therapy of Type-1 Diabetes: A Case Study of Children and Adolescents in Germany
    Rolf-Dietrich Berndt, Claude Takenga, Petra Preik, Sebastian Kuehn, Luise Berndt, Herbert Mayer, Alexander Kaps, Ralf Schiel
    Journal of Personalized Medicine.2014; 4(2): 200.     CrossRef
  • Perception of Influencing Factors on Acceptance of Mobile Health Monitoring Service: A Comparison between Users and Non-users
    Jaebeom Lee, Mi Jung Rho
    Healthcare Informatics Research.2013; 19(3): 167.     CrossRef
  • Telerehabilitation Needs: A Bidirectional Survey of Health Professionals and Individuals with Spinal Cord Injury in South Korea
    Jongbae Kim, Shinyoung Lim, Jayeon Yun, Da-hye Kim
    Telemedicine and e-Health.2012; 18(9): 713.     CrossRef
  • Development of a smartphone-based diabetes self-care management system
    Sang Youl Rhee, Jeong-taek Woo, Young Seol Kim, Young Kil Choi
    Personalized Medicine Universe.2012; 1(1): 85.     CrossRef
  • Features of Mobile Diabetes Applications: Review of the Literature and Analysis of Current Applications Compared Against Evidence-Based Guidelines
    Taridzo Chomutare, Luis Fernandez-Luque, Eirik Årsand, Gunnar Hartvigsen
    Journal of Medical Internet Research.2011; 13(3): e65.     CrossRef
Retraction of Publication
Retraction: Polymorphisms of Kir6.2 Gene are Associated with Type 2 Diabetes and Blood Pressure in the Korean Population.
Bo Kyeong Koo, Hong Il Kim, Eu Jin Lee, Young Min Cho, Hyoung Doo Shin, Hak Chul Jang, Hong Kyu Lee, Kyong Soo Park
Korean Diabetes J. 2007;31(2):185-185.   Published online March 1, 2007
DOI: https://doi.org/10.4093/jkda.2007.31.2.185
  • 1,674 View
  • 19 Download
PDF
Original Article
Polymorphisms of Kir6.2 Gene are Associated with Type 2 Diabetes and Blood Pressure in the Korean Population.
Bo Kyeong Koo, Hong Il Kim, Eu Jin Lee, Young Min Cho, Hyoung Doo Shin, Hak Chul Jang, Hong Kyu Lee, Kyong Soo Park
Korean Diabetes J. 2005;29(5):440-450.   Published online September 1, 2005
  • 1,023 View
  • 18 Download
AbstractAbstract PDF
BACKGOUND: ATP-sensitive potassium channels are a heterooctamer of SUR1 and Kir6.2, which are key components in the insulin secretory mechanism. Whether common variants in the Kir6.2 gene are associated with type 2 diabetes and/or its associated phenotypes was investigated. METHODS: The Kir6.2 gene was sequenced in 24Korean DNA samples to identify common polymorphisms (frequency > 0.05). The common variants found among these samples were genotyped in a larger population including type 2 diabetic patients and nondiabetic subjects. RESULTS: Thirteen single nucleotide polymorphisms and one insertion/deletion polymorphism were identified in the Kir6.2 gene, with six common variants(g.-1709A>T, g.-1525T>C, g.67G >A [E23K], g.570C>T [A190A], g.1009A>G [1337V], and g.1388C>T) genotyped in 761 type 2 diabetic patients and 675 nondiabetic subjects. Four individual polymorphisms(g.-1525T > C, g.67G>A, g.1009A>G and g.1388C>T) appeared to be associated with type 2 diabetes (age, sex and BMI-adjusted odds ratio[OR]=0.751[0.584-0.967] in the recessive model on g-1525T>C, 1.193 [1.020-1.394] in the additive model in g.67G>A, 1.195 [1.022-1.399] in the additive model on g.1009A>G, 0.835 [0.717-0.973] in the additive model in g.1388C >T). The haplotype "ATACGC" in the Kir6.2 gene, composed of rare allele in the g.67 and g.1009, was also associated with a higher prevalence of type 2 diabetes (age, sex, and BMI- adjusted OR = 1.256 [1.067-1.479], P for logistic regression = 0.006). In addition g.67G>A and g.1009A >G in the KCNJ11 were strongly associated with a high systolic blood pressure. CONCLUSION: Polymorphisms in the Kir6.2 gene are associated with type 2 diabetes and blood pressure in the Korean population.

Diabetes Metab J : Diabetes & Metabolism Journal