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1.
Diabetes & Metabolism Journal ; : 376-385, 2016.
Article in English | WPRIM | ID: wpr-84891

ABSTRACT

BACKGROUND: Non-alcoholic fatty liver disease is the most common form of chronic liver disease in industrialized countries. Recent studies have highlighted the association between peroxisomal dysfunction and hepatic steatosis. Peroxisomes are intracellular organelles that contribute to several crucial metabolic processes, such as facilitation of mitochondrial fatty acid oxidation (FAO) and removal of reactive oxygen species through catalase or plasmalogen synthesis. Statins are known to prevent hepatic steatosis and non-alcoholic steatohepatitis (NASH), but underlying mechanisms of this prevention are largely unknown. METHODS: Seven-week-old C57BL/6J mice were given normal chow or a methionine- and choline-deficient diet (MCDD) with or without various statins, fluvastatin, pravastatin, simvastatin, atorvastatin, and rosuvastatin (15 mg/kg/day), for 6 weeks. Histological lesions were analyzed by grading and staging systems of NASH. We also measured mitochondrial and peroxisomal FAO in the liver. RESULTS: Statin treatment prevented the development of MCDD-induced NASH. Both steatosis and inflammation or fibrosis grades were significantly improved by statins compared with MCDD-fed mice. Gene expression levels of peroxisomal proliferator-activated receptor α (PPARα) were decreased by MCDD and recovered by statin treatment. MCDD-induced suppression of mitochondrial and peroxisomal FAO was restored by statins. Each statin's effect on increasing FAO and improving NASH was independent on its effect of decreasing cholesterol levels. CONCLUSION: Statins prevented NASH and increased mitochondrial and peroxisomal FAO via induction of PPARα. The ability to increase hepatic FAO is likely the major determinant of NASH prevention by statins. Improvement of peroxisomal function by statins may contribute to the prevention of NASH.


Subject(s)
Animals , Mice , Atorvastatin , Catalase , Cholesterol , Developed Countries , Diet , Fatty Liver , Fibrosis , Gene Expression , Hydroxymethylglutaryl-CoA Reductase Inhibitors , Inflammation , Liver Diseases , Liver , Metabolism , Non-alcoholic Fatty Liver Disease , Organelles , Peroxisomes , Pravastatin , Reactive Oxygen Species , Rosuvastatin Calcium , Simvastatin
2.
Korean Journal of Anesthesiology ; : 288-293, 2002.
Article in Korean | WPRIM | ID: wpr-211665

ABSTRACT

BACKGROUND: Near infrared spectroscopy (NIRS) to monitor regional cerebral oxygen saturation (rSO2) is a noninvasive and simple modal ity in clinical use. The ability of rSO2 as an index of cerebral oxygenation has been well demonstrated. However, the reliability of rSO2 to reflect the changes of cerebral vascular reactivity in the changes of arterial partial pressure of CO2 (PaCO2) has not been established. The aim of this study was to verify the reliability of rSO2 to measure the CO2 reactivity of cerebral vasculatures. METHODS: Twenty healthy adult patients undergoing general anesthesia were enrolled in this study. Anesthesia was induced with propofol and maintained with desflurane/N2O. Respiration was mechanically controlled. The radial artery and jugular bulb were cannulated. The sensor of the NIRS was attached to the ipsilateral forehead. During normocapnia (PaCO2 40 +/- 1.3 mmHg) and hypocapnia (PaCO2 30 +/- 2.4 mmHg), blood was obtained from the radial artery and jugular bulb and analyzed. rSO2 was compared with fSO2 (estimated field oxygen satuation), and the gold standard of tissue oxygen saturation. fSO2 was calculated from the following equation: fSO2 = 0.75 SjO2 + 0.25 SaO2. RESULTS: rSO2 significantly correlated with fSO2 (P = 0.000, r2 = 0.56). A bias of - 5.8% with a precision 12.94% was found. CONCLUSIONS: We concluded that rSO2 can be a reliable predictor to measure CO2 reactivity of cerebral vasculatures during normocapnia and hypocapnia.


Subject(s)
Adult , Humans , Anesthesia , Anesthesia, General , Bias , Forehead , Hypocapnia , Oxygen , Partial Pressure , Propofol , Radial Artery , Respiration , Spectrum Analysis
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