Tuong Nguyen

Family History of Diabetes Links Impaired Substrate Switching and Reduced Mitochondrial Content in Skeletal Muscle

Insulin resistance is associated with metabolic inflexibility, impaired switching of substrate oxidation from fatty acids to glucose in response to insulin. Impaired switching to fat oxidation in response to a high-fat diet (HFD) is hypothesized to contribute to insulin resistance. The objective of this study was to test the hypothesis that defects in substrate switching in response to insulin and a HFD are linked to reduced mitochondrial biogenesis and occur before the development of diabetes. Metabolic flexibility was measured in young sedentary men with (n = 16) or without (n = 34) a family history of diabetes by euglycemic-hyperinsulinemic clamp. Flexibility correlated with fat oxidation measured in a respiratory chamber after a 3-day HFD. Muscle mitochondrial content was higher in flexible subjects with high fat oxidation after a HFD and contributed 49% of the variance. Subjects with a family history of diabetes were inflexible and had reduced HFD-induced fat oxidation and muscle mitochondrial content but did not differ in the amount of body or visceral fat. Metabolic inflexibility, lower adaptation to a HFD, and reduced muscle mitochondrial mass cluster together in subjects with a family history of diabetes, supporting the role of an intrinsic metabolic defect of skeletal muscle in the pathogenesis of insulin resistance.

Chamber for indirect calorimetry with accurate measurement and time discrimination of metabolic plateaus of over 20 min

A robust algorithm for pull-calorimeters that provides a rapid response to changes in respiratory gas exchange has been implemented. Metabolic plateaus (over 20 min), such as that generated by steady treadmill exercise, can be measured accurately (<2.0% error for an energy expenditure level of 16.7 kJ min−1). The time resolution for changes between plateaus can be accurately found with 1 min discrimination. Implementation required only software changes but no structural or instrumentation changes to the chamber. The algorithm was based on the one developed for the push-calorimeter at the Sahlgrenska Hospital in Sweden. The method utilises published equations for the rate of O2 consumption and CO2 production in the chamber, along with techniques for suppressing noise and identifying trends. Using the exact solution of the equations for steady state, the O2 concentrations from the preceding 30 min period are fitted to two connected exponential segments, of variable length, using the least-squares method. The smoothed O2 concentration and associated time derivative are then determined for the time point 15 min earlier and substituted into the respiration equations. The CO2 concentrations are subjected to the same analysis. The process is repeated every minute, and the newly computed rates of O2 consumption and CO2 production, as well as metabolic rate, are then presented. Gas injection tests proved that the chamber can respond instantaneously to a change from one steady state of respiration to another and correctly averages repeated changes in respiration with periods less than 15 min (<1.4% error for simulated, alternating O2 consumption levels of 0.81 min−1 and 0.01 min−1). The successful integration of the algorithm into the Pennington chambers allows for traditional 24 h energy expenditure measurements and various metabolic experiments requiring rapid responses.

Prediction of energy expenditure in a whole body indirect calorimeter at both low and high levels of physical activity

OBJECTIVES: In studies that involve the use of a room calorimeter, 24 h energy intake is often larger than 24 h energy expenditure (24 h EE) because of a decrease in activity energy expenditure due to the confined space. This positive energy balance can have large consequences for the interpretation of substrate balances. The objective of this study was to develop a method for predicting an individuals 24 h EE in a room calorimeter at both low (1.4×RMR) and high (1.8×RMR) levels of physical activity.METHODS: Two methods are presented that predict an individuals 24 h EE in a metabolic chamber. The first method was based on three components: (1) a 30 min measurement of resting metabolic rate (RMR) using a ventilated hood system; (2) measurement of exercise energy expenditure during 10 min of treadmill walking; and (3) estimation of free-living energy expenditure using a tri-axial motion sensor. Using these measurements we calculated the amount of treadmill time needed for each individual in order to obtain a total 24 h EE at either a low (1.4×RMR) or a high (1.8×RMR) level of physical activity. We also developed a method to predict total 24 h EE during the chamber stay by using the energy expenditure values for the different levels of activity as measured during the hours already spent in the chamber. This would provide us with a tool to adjust the exercise time and/or energy intake during the chamber stay.RESULTS: Method 1: there was no significant difference in expected and measured 24 h EE under either low (9.35±0.56 vs 9.51±0.47 MJ/day; measured vs predicted) or high activity conditions (13.41±0.74 vs 13.97±0.78 MJ/day; measured vs predicted). Method 2: the developed algorithm predicted 24 h EE for 97.6±4.0% of the final value at 3 h into the test day, and for 98.6±3.7% at 7 h into the test day.CONCLUSION: Both methods provide accurate prediction of energy expenditure in a room calorimeter at both high and low levels of physical activity. It equally shows that it is possible to accurately predict total 24 h EE from energy expenditure values obtained at 3 and 7 h into the study.

The Cost Effectiveness of Three Different Measures of Breast Volume

BackgroundSeveral methods including water displacement, casting, the Grossman–Roudner measuring device, photographs, mammograms, ultrasound, and magnetic resonance imaging (MRI) have been proposed for the measurement of breast volume. The most cost-effective method has not been determined.MethodsThis study compared breast volume measurements using the Grossman–Roudner measuring device (a piece of circular plastic with a cut along a radius line), plaster casting, and MRI. The Grossman–Roudner measuring device was formed into a cone around the breast, and the volume was read from a graduated scale on the overlapping edges. The volume of the cast was measured using a butter–sand mixture and water displacement. The volume from the MRI slices was calculated using the ANALYZE bioimaging software. For five women with breast sizes AA, A, B, C, and D, the three volume measures were repeated three times. For a single volume measurement, the cost of the time and materials was

Effect of 6-month calorie restriction on biomarkers of longevity, metabolic adaptation, and oxidative stress in overweight individuals: a randomized controlled trial.

1 for the Grossman–Roudner cone,

Fat and carbohydrate balances during adaptation to a high-fat diet

20 for the cast, and

Concurrent physical activity increases fat oxidation during the shift to a high-fat diet

1,400 for the MRI. Using the mean and standard deviations of the measurements, a power analysis determined the number of subjects needed to detect a 5% change in volume. The number of subjects was multiplied by the price per test to determine relative cost.ResultsAs compared with the cost for the Grossman–Roudner cone method, the cost for the volume measurements was 64 to 189 times more using the cast and 373 to 33,500 more using MRI.ConclusionsThe Grossman–Roudner cone was clearly the most cost-effective method for determining breast volume changes in studies testing topical therapies to alter breast size.