Antidiabetic Effects of Bisamide Derivative of Dicarboxylic Acid in Metabolic Disorders.
Angelina Vladimirovna PakhomovaVladimir Evgenievich NebolsinOlga Victorovna PershinaVyacheslav Andreevich KrupinLubov Alexandrovna SandrikinaEdgar Sergeevich PanNatalia Nicolaevna ErmakovaOlga Evgenevna VaizovaDarius WideraWolf-Dieter GrimmViacheslav Yur'evich KravtsovSergey A AfanasievSergey Georgievich MorozovAslan Amirkhanovich KubatievAlexander Mikhaylovich DygaiEvgenii Germanovich SkurikhinPublished in: International journal of molecular sciences (2020)
In clinical practice, the metabolic syndrome can lead to multiple complications, including diabetes. It remains unclear which component of the metabolic syndrome (obesity, inflammation, hyperglycemia, or insulin resistance) has the strongest inhibitory effect on stem cells involved in beta cell regeneration. This makes it challenging to develop effective treatment options for complications such as diabetes. In our study, experiments were performed on male C57BL/6 mice where metabolic disorders have been introduced experimentally by a combination of streptozotocin-treatment and a high-fat diet. We evaluated the biological effects of Bisamide Derivative of Dicarboxylic Acid (BDDA) and its impact on pancreatic stem cells in vivo. To assess the impact of BDDA, we applied a combination of histological and biochemical methods along with a cytometric analysis of stem cell and progenitor cell markers. We show that in mice with metabolic disorders, BDDA has a positive effect on lipid and glucose metabolism. The pancreatic restoration was associated with a decrease of the inhibitory effects of inflammation and obesity factors on pancreatic stem cells. Our data shows that BDDA increases the number of pancreatic stem cells. Thus, BDDA could be used as a new compound for treating complication of the metabolic syndrome such as diabetes.
Keyphrases
- stem cells
- insulin resistance
- high fat diet
- metabolic syndrome
- high fat diet induced
- type diabetes
- glycemic control
- adipose tissue
- cell therapy
- polycystic ovary syndrome
- cardiovascular disease
- skeletal muscle
- uric acid
- oxidative stress
- clinical practice
- cardiovascular risk factors
- risk factors
- machine learning
- big data
- electronic health record
- fatty acid
- physical activity
- deep learning