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Published on: February 10, 2013
Dose-dependent and time-dependent metabolic, hemodynamic, and redox disturbances in dexamethasone-treated Wistar rats
Elvine P Nguelefack-Mbuyo1, Fernande P Peyembouo1, Christian K Fofié1
1Laboratory of Animal Physiology and Phytopharmacology, Faculty of Science, University of Dschang, Dschang, Cameroon.
Objectives:
Dexamethasone is used experimentally to induce insulin resistance and type 2 diabetes. However, data concerning the dose, the duration of treatment, and the associated comorbidities are inconsistent. The aim of this study was to compare the effects of different doses of dexamethasone and the duration of treatment necessary for the development of a model of insulin resistance that mimics the clinical condition with the associated comorbidities.
Methods:
Dexamethasone was administered intramuscularly to male Wistar rats, at doses of 500 and 1,000 µg/kg/day for the subchronic treatment (eight consecutive days) and at doses of 5, 25, 50, and 100 µg/kg/day in chronic treatment (28 consecutive days). Effects on body weight, metabolism, hemodynamics, renal function, and redox status were evaluated.
Results:
Both treatments induced a progressive body weight loss that was drastic in subchronic treatment, improved glucose tolerance without affecting fasting glycemia. Doses of 1,000 and 100 µg/kg were associated with hypertriglyceridemia, hypertension, and increased heart rate, cardiac and renal hypertrophy. Increased creatinemia associated with reduced creatinuria were observed in sub-chronic treatment while increased proteinuria and reduced creatinuria were noticed in chronic treatment. 1,000 µg/kg dexamethasone caused an increase in hepatic, and renal malondialdehyde (MDA) and glutathione (GSH) coupled with a reduction in catalase activity. The dose of 100 µg/kg induced a rise in GSH and catalase activity but reduced MDA levels in the kidney.
Conclusions:
Doses of 1,000 µg/kg for subchronic and 100 µg/kg for chronic treatment exhibited similar effects and are the best doses to respective time frames to induce the model.
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