Shadowing in Inelastic Scattering of Muons on Carbon, Calcium and Lead at Low XBj

Nuclear shadowing is observed in the per-nucleon cross-sections of positive muons on carbon, calcium and lead as compared to deuterium. The data were taken by Fermilab experiment E665 using inelastically scattered muons of mean incident momentum 470 GeV/c. Cross-section ratios are presented in the kinematic region 0.0001 < XBj <0.56 and 0.1 < Q**2 < 80 GeVc. The data are consistent with no significant nu or Q**2 dependence at fixed XBj. As XBj decreases, the size of the shadowing effect, as well as its A dependence, are found to approach the corresponding measurements in photoproduction.Comment: 22 pages, incl. 6 figures, to be published in Z. Phys.

Measurement of the components of nonexercise activity thermogenesis.

Am J Physiol Endocrinol Metab 2001 Oct;281(4):E670-5 Related Articles, Books, LinkOut Measurement of the components of nonexercise activity thermogenesis. Levine J, Melanson EL, Westerterp KR, Hill JO. Endocrine Research Unit, Mayo Clinic, Rochester, Minnesota 55905, USA. [email protected] Nonexercise activity thermogenesis (NEAT) accounts for the vast majority of nonresting metabolic rate and changes in NEAT-predicted susceptibility to fat gain with overfeeding. Measuring physical activity and its components in free-living humans has been a long-standing challenge. In this study, we combine information about lightweight sensors that capture data on body position and motion with laboratory measures of energy expenditure to calculate nonfidgeting NEAT. This measurement of nonfidgeting NEAT was compared with total NEAT measured in a room calorimeter in 11 healthy subjects. The measurement of nonfidgeting NEAT accounted for 85 +/- 9% of total NEAT measured in the room calorimeter. The intraclass correlation coefficient for the two methods was 0.86 (95% confidence interval 0.56, 0.96; P < 0.05). This suggests that 86% of the variance is attributable to between-subject variance and 14% to between-method disagreement. These instruments are applicable to free-living subjects; they are stand-alone, are lightweight, and allow normal daily activities. This novel technology has potential application for not only assessing NEAT but also tracking physical activity in free-living humans

Tracmor system for measuring walking energy expenditure

Tracmor system for measuring walking energy expenditure. Levine J, Melanson EL, Westerterp KR, Hill JO. Endocrine Research Unit, Mayo Clinic, Rochester, MN 55905, USA. [email protected] OBJECTIVE: Walking is an important mode of exercise and is likely to represent a major component of nonexercise activity thermogenesis. The question arises, how best to quantify walking-energy expenditure (EE) in free-living individuals. The triaxial accelerometer for movement registration (Tracmor) is a valid measure of body displacement and so we wanted to evaluate this tool for quantifying walking-EE. HYPOTHESIS: In this study, we test the hypothesis that walking-EE, measured in a Room Calorimeter, can be predicted from Tracmor output using a regression equation derived from a brief Tracmor/treadmill/Metabolic Cart protocol. DESIGN: First, 11 healthy subjects completed a 40-min procedure whereby they wore a Tracmor unit and walked on a treadmill at 0, 1, 2 and 3 mph while EE was measured using a Metabolic Cart. This allowed a regression equation to be defined for each subject to convert Tracmor output to EE. Each subject then entered a Room Calorimeter wearing the Tracmor Unit and walked at two self-selected velocities ('slow', 'fast') while EE was measured. 'Tracmor/regression equation' predictions of walking-EE were compared with Room Calorimeter measurements of walking-EE for the two velocities. RESULTS: The 'Tracmor/regression equation' prediction of EE for walking slowly was 6.36+/-1.67 kJ/min, and for walking fast it was 11.0+/-2.60 kJ/min. Room Calorimeter measurements were 6.43+/-1.85 and 10.9+/-3.03 kJ/min, respectively. The intraclass correlation coefficient for slow-paced walking was 0.93 (P<0.001), and for fast-paced walking it was 0.82 (P<0.005). CONCLUSIONS: When combined with laboratory measures of EE, the Tracmor accelerometer provides useful data on walking-EE and is applicable to free-living individual

Effect of calcium from dairy and dietary supplements on faecal fat excretion: a meta-analysis of randomized controlled trials.

Summary Observational studies have found that dietary calcium intake is inversely related to body weight and body fat mass. One explanatory mechanism is that dietary calcium increases faecal fat excretion. To examine the effect of calcium from dietary supplements or dairy products on quantitative faecal fat excretion, we performed a systematic review with meta-analysis. We included randomized, controlled trials of calcium (supplements or dairy) in healthy subjects, where faecal fat excretion was measured. Meta-analyses used random-effects models with changes in faecal fat excreted expressed as standardized mean differences, as the studies assessed the same outcome but measured in different ways. An increased calcium intake resulted in increased excretion of faecal fat by a standardized mean difference of 0.99 (95% confidence intervals: 0.63-1.34; P < 0.0001; expected to correspond to approximately 2g day(-1)) with moderate heterogeneity (I(2) = 49.5%) indicating some inconsistency in trial outcomes. However, the dairy trials showed homogeneous outcomes (I(2)=0%) indicating consistency among these trials. We estimated that increasing the dairy calcium intake by 1241 mg day(-1) resulted in an increase in faecal fat of 5.2 (1.6-8.8) g day(-1). In conclusion, dietary calcium has the potential to increase faecal fat excretion to an extent that could be relevant for prevention of weight (re-)gain. Long-term studies are required to establish its potential contribution