牛血清白蛋白
脂肪变性
体外
脂肪酸
化学
白蛋白
血清白蛋白
生物化学
脂肪肝
内科学
生物
内分泌学
医学
疾病
作者
Ekaterina L. Knyazeva,D. O. Vinokhodov
出处
期刊:Вопросы биологической, медицинской и фармацевтической химии
[Russkiy Vrach Publishing House]
日期:2025-05-10
卷期号:: 66-72
标识
DOI:10.29296/25877313-2025-04-08
摘要
Introduction. Non-alcoholic fatty liver disease (NAFLD) is a major public health issue characterized by a rapidly increasing prevalence worldwide. NAFLD is associated with excessive lipid accumulation and the development of inflammation in the liver. To study the pathogenic mechanisms of the disease, a steatosis model using immortalized cell lines is widely employed. The aim of this study was to improve the in vitro steatosis model using HepG2 cells by conducting a comparative analysis of two methods of stea-tosis induction, utilizing a fatty acid (FA) complex with bovine serum albumin (BSA) prepared by simple dissolution or conjugation. Material and methods. Cell viability was assessed using the XTT assay. Lipid accumulation in HepG2 cells was measured by the GPO-PAP method, with triglyceride (TG) levels normalized to cellular protein content. Production of the pro-inflammatory cytokine IL-8, a marker of inflammation, was quantitatively determined using an enzyme-linked immunosorbent assay (ELISA). Statistical significance was evaluated using Student's t-test, with p-values < 0.05 considered statistically significant. Results. The optimal FA concentration that promoted lipid accumulation and inflammation without a marked cytotoxic effect in HepG2 cells was 0.75 mM. The conjugated FA-BSA complex led to a higher TG accumulation compared to the FA-BSA complex prepared by dissolution. However, IL-8 levels were significantly lower in the culture medium of HepG2 cells treated with the conjugated complex compared to those treated with the FA-BSA complex prepared by dissolution. Conclusions. The use of the conjugated FA-BSA complex allowed for the development of an improved in vitro steatosis model that more closely re-sembles the physiological mechanisms of NAFLD progression.
科研通智能强力驱动
Strongly Powered by AbleSci AI