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Differences in blood concentration of sex hormones in the follicular (FP) and luteal (LP) phases may influence energy metabolism in women. We compared fasting energy metabolism and sweet taste preference on a representative day of the FP and LP in twenty healthy women (25·3 (sd 5·1) years, BMI: 22·2 (sd 2·2) kg/m2) with regular self-reported menses and without the use of hormonal contraceptives. From the self-reported duration of the three prior menstrual cycles, the predicted FP and LP visits were scheduled for days 5–12 and 20–25 after menses, respectively. The order of the FP and LP visits was randomly assigned. On each visit, RMR and RQ by indirect calorimetry, sweet taste preference by the Monell two-series forced-choice tracking procedure, serum fibroblast growth factor 21 by a commercial ELISA (FGF21, a liver-derived protein with action in energy balance, fuel oxidation and sugar preference) and dietary food intake by a 24-h dietary recall were determined. Serum progesterone and oestradiol concentrations displayed the expected differences between phases. RMR was lower in the FP v. LP (5042 (sd 460) v. 5197 (sd 490) kJ/d, respectively; P = 0·04; Cohen effect size, d rm = 0·33), while RQ showed borderline significant higher values (0·84 (sd 0·05) v. 0·81 (sd 0·05), respectively; P = 0·07; d rm = 0·62). Also, in the FP v. LP, sweet taste preference was lower (12 (sd 8) v. 16 (sd 9) %; P = 0·04; d rm = 0·47) concomitant with higher serum FGF21 concentration (294 (sd 164) v. 197 (sd 104) pg/ml; P < 0·01; d rm = 0·66). The menstrual cycle is associated with changes in energy expenditure, sweet taste preference and oxidative fuel partitioning. [ABSTRACT FROM AUTHOR]

Summary: Glucose, fatty acids, and amino acids among others are oxidized to generate adenosine triphosphate (ATP). These fuels are supplied from the environment (through food intake) and internal depots (through lipolysis, glycogenolysis, and proteolysis) at different rates throughout the day. Complex adaptive systems permit to accommodate fuel oxidation according to fuel availability. This capacity of a cell, tissue, or organism to adapt fuel oxidation to fuel availability is defined as metabolic flexibility (MetF). There are conditions, such as insulin resistance, diabetes, and obesity, in which MetF seems to be impaired. The observation that those conditions are accompanied by mitochondrial dysfunction has set the basis to propose a link between mitochondrial dysfunction, metabolic inflexibility, and metabolic health. We here highlight the evidence about the notion that MetF influences metabolic health. [ABSTRACT FROM AUTHOR]

The authors reflect on the results of a study that appeared in the journal "Obesity" which examined the effect of visceral fat on insulin resistance in the canine model. They explain that the study considered the effect of increasing canine ornamental fat through pharmacological sympathectomy on insulin sensitivity and found that visceral fat per se does not result in insulin resistance. They argue that the results may not be suitable for testing the portal hypothesis.

Objective: the aim of this study was to analyze the agreement between the resting energy expenditure (REE) obtained by indirect calorimetry (IC) and that obtained by prediction equations in a sample of healthy adults from Spain. Méthods: a descriptive cross-sectional study was conducted in 95 healthy, normal-weight adults. REE was determined by IC and 45 population-specific prediction equations which were based on weight, height, sex and/or body composition (BC). The Intraclass Correlation Coefficient (ICC) and Bland-Alman plots were used to analyze the agreement between the REE obtained by IC and that obtained by prediction equations. The level of signification was reached at p < 0,05. Results: mean age was 42 years (range: 23.0-63.2). Mean REE determined by CI was 1589 (312) kcal/d [1822.3 (224.3) kcal/d in men and 1379.3 (216.1) kcal/d in women; p < 0.05]. The De-Lorenzo, Harris-Benedict, Schofield, and especially the Korth equations showed the greatest level of agreement with respect to IC. Conclusions: there is high variability in the estimates of REE depending on the prediction equation used. The De Lorenzo, Harris-Benedict, and the Schofield equations showed a good level of agreement in our sample; however, the Korth equation was the most appropriate. Equations based on weight and/or height were more accurate than those which included body composition variables. [ABSTRACT FROM AUTHOR]