Running appears to decrease knee intra-articular pro-inflammatory cytokine concentration and facilitates the movement of COMP from the joint space to the serum.

Exercise may play a role in moderating eating behaviors. The purpose of this study was to examine the effect of an acute bout of exercise on neural responses to visual food stimuli in children ages 8-11 years. We hypothesized that acute exercise would result in reduced activity in reward areas of the brain. Using a randomized cross-over design, 26 healthy weight children completed two separate laboratory conditions (exercise; sedentary). During the exercise condition, each participant completed a 30-min bout of exercise at moderate-intensity (~ 67% HR maximum) on a motor-driven treadmill. During the sedentary session, participants sat continuously for 30 min. Neural responses to high- and low-calorie pictures of food were determined immediately following each condition using functional magnetic resonance imaging. There was a significant exercise condition*stimulus-type (high- vs. low-calorie pictures) interaction in the left hippocampus and right medial temporal lobe (p < 0.05). Main effects of exercise condition were observed in the left posterior central gyrus (reduced activation after exercise) (p < 0.05) and the right anterior insula (greater activation after exercise) (p < 0.05). The left hippocampus, right medial temporal lobe, left posterior central gyrus, and right anterior insula appear to be activated by visual food stimuli differently following an acute bout of exercise compared to a non-exercise sedentary session in 8-11 year-old children. Specifically, an acute bout of exercise results in greater activation to high-calorie and reduced activation to low-calorie pictures of food in both the left hippocampus and right medial temporal lobe. This study shows that response to external food cues can be altered by exercise and understanding this mechanism will inform the development of future interventions aimed at altering energy intake in children.

Background: Physical activity and corresponding energy expenditure can improve health in various ways. Existing methods to directly measure energy expenditure are currently limited to laboratory settings and/or expensive instrumentation. The purpose of this study was to evaluate accuracy of energy expenditure characterization, during walking and running, using demographic data, as well as data collected via an accelerometer and novel piezoresponsive foam sensors. Methods: 30 individuals (14 females; mass = 67 ± 10 kg; height = 1.74 ± 0.08 m; age = 23 ± 3 yrs) walked and ran at five speeds (1.34, 2.23, 2.68, 3.13, and 3.58 m/s) on a force-instrumented treadmill while wearing a metabolic analyzer and standardized athletic shoes instrumented with an accelerometer, and four novel nanocomposite piezoresponsive force sensors. Various predictive models, including demographic data and data derived from the accelerometer and force sensors, were evaluated for each gait speed. Results: The predictive models varied in ability to accurately characterize energy expenditure. For walking, the most accurate model included acceleration and body weight, and resulted in an average absolute error of 0.07 ± 0.03 kcal/min. For running, the most accurate model included sensor and acceleration data, and resulted in an average absolute error of 0.45 ± 0.14 kcal/min. Conclusions: When combined with acceleration data and body weight, the novel foam sensors can be used to inexpensively and accurately measure walking and running energy expenditure. This can be done at various speeds, outside of a traditional research laboratory. These results have application within a wide range of diverse contexts.

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