Effects of excess dietary iron and fat on glucose and lipid metabolism

PurposeDiets rich in fat and energy are associated with metabolic syndrome (MS). Increased body iron stores have been recognized as a feature of MS. High-fat diets (HFs), excess iron loading and MS are closely associated, but the mechanism linking them has not been clearly defined. We investigated the interaction between dietary fat and dietary Fe in the context of glucose and lipid metabolism in the body.MethodsC57BL6/J mice were divided into four groups and fed the modified AIN-93G low-fat diet (LF) and HF with adequate or excess Fe for 7 weeks. The Fe contents were increased by adding carbonyl iron (2% of diet weight) (LF+Fe and HF+Fe).ResultsHigh iron levels increased blood glucose levels but decreased high-density lipoprotein cholesterol levels. The HF group showed increases in plasma levels of glucose and insulin and insulin resistance. HF+Fe mice showed greater changes. Representative indices of iron status, such hepatic and plasma Fe levels, were not altered further by the HF. However, both the HF and excess iron loading changed the hepatic expression of hepcidin and ferroportin. The LF+Fe, HF and HF+Fe groups showed greater hepatic fat accumulation compared with the LF group. These changes were paralleled by alterations in the levels of enzymes related to hepatic gluconeogenesis and lipid synthesis, which could be due to increases in mitochondrial dysfunction and oxidative stress.ConclusionsHigh-fat diets and iron overload are associated with insulin resistance, modified hepatic lipid and iron metabolism and increased mitochondrial dysfunction and oxidative stress.     

Effect of high contents of dietary animal-derived protein or carbohydrates on canine faecal microbiota

Background

Few equations have been developed in veterinary medicine compared to human medicine to predict body composition. The present study was done to evaluate the influence of weight loss on biometry (BIO), bioimpedance analysis (BIA) and ultrasonography (US) in cats, proposing equations to estimate fat (FM) and lean (LM) body mass, as compared to dual energy x-ray absorptiometry (DXA) as the referenced method. For this were used 16 gonadectomized obese cats (8 males and 8 females) in a weight loss program. DXA, BIO, BIA and US were performed in the obese state (T0; obese animals), after 10% of weight loss (T1) and after 20% of weight loss (T2). Stepwise regression was used to analyze the relationship between the dependent variables (FM, LM) determined by DXA and the independent variables obtained by BIO, BIA and US. The better models chosen were evaluated by a simple regression analysis and means predicted vs. determined by DXA were compared to verify the accuracy of the equations.

Results

The independent variables determined by BIO, BIA and US that best correlated (p?<?0.005) with the dependent variables (FM and LM) were BW (body weight), TC (thoracic circumference), PC (pelvic circumference), R (resistance) and SFLT (subcutaneous fat layer thickness). Using Mallows??Cp statistics, p value and r ² , 19 equations were selected (12 for FM, 7 for LM); however, only 7 equations accurately predicted FM and one LM of cats.

Conclusions

The equations with two variables are better to use because they are effective and will be an alternative method to estimate body composition in the clinical routine. For estimated lean mass the equations using body weight associated with biometrics measures can be proposed. For estimated fat mass the equations using body weight associated with bioimpedance analysis can be proposed.