Influence of environmental temperature and energy intake on skeletal muscle respiratory enzymes and morphology

1988 ◽  
Vol 58 (3) ◽  
pp. 239-244 ◽  
Author(s):  
M. J. Dauncey ◽  
D. L. Ingram
1974 ◽  
Vol 61 (2) ◽  
pp. 285-291 ◽  
Author(s):  
ASHA CHANDOLA ◽  
D. SURESH KUMAR ◽  
J. P. THAPLIYAL

SUMMARY Thyroidectomy and orchidectomy led to significant reduction in the oxidative metabolism of isolated liver and skeletal muscle tissue (at 30 °C) in Calotes versicolor. Thyroxine and male hormone were shown to increase this parameter in intact and orchidectomized lizards respectively. The effects of thyroidectomy and orchidectomy on tissue oxygen uptake were not additive. It is supposed that by its effect on oxidative metabolism male hormone may be of a greater physiological importance for reptiles than for other vertebrates. The present results show also that changes in environmental temperature can counteract the depressive effect of orchidectomy on the thyroid of this species of lizard.


2016 ◽  
Vol 41 (6) ◽  
pp. 611-617 ◽  
Author(s):  
Jameason D. Cameron ◽  
Ronald J. Sigal ◽  
Glen P. Kenny ◽  
Angela S. Alberga ◽  
Denis Prud’homme ◽  
...  

There has been renewed interest in examining the relationship between specific components of energy expenditure and the overall influence on energy intake (EI). The purpose of this cross-sectional analysis was to determine the strongest metabolic and anthropometric predictors of EI. It was hypothesized that resting metabolic rate (RMR) and skeletal muscle mass would be the strongest predictors of EI in a sample of overweight and obese adolescents. 304 post-pubertal adolescents (91 boys, 213 girls) aged 16.1 (±1.4) years with body mass index at or above the 95th percentile for age and sex OR at or above the 85th percentile plus an additional diabetes risk factor were measured for body weight, RMR (kcal/day) by indirect calorimetry, body composition by magnetic resonance imaging (fat free mass (FFM), skeletal muscle mass, fat mass (FM), and percentage body fat), and EI (kcal/day) using 3 day food records. Body weight, RMR, FFM, skeletal muscle mass, and FM were all significantly correlated with EI (p < 0.005). After adjusting the model for age, sex, height, and physical activity, only FFM (β = 21.9, p = 0.007) and skeletal muscle mass (β = 25.8, p = 0.02) remained as significant predictors of EI. FFM and skeletal muscle mass also predicted dietary protein and fat intake (p < 0.05), but not carbohydrate intake. In conclusion, with skeletal muscle mass being the best predictor of EI, our results support the hypothesis that the magnitude of the body’s lean tissue is related to absolute levels of EI in a sample of inactive adolescents with obesity.


Author(s):  
Jenna B. Gillen ◽  
Jorn Trommelen ◽  
Floris C. Wardenaar ◽  
Naomi Y.J. Brinkmans ◽  
Joline J. Versteegen ◽  
...  

Dietary protein intake should be optimized in all athletes to ensure proper recovery and enhance the skeletal muscle adaptive response to exercise training. In addition to total protein intake, the use of specific proteincontaining food sources and the distribution of protein throughout the day are relevant for optimizing protein intake in athletes. In the present study, we examined the daily intake and distribution of various proteincontaining food sources in a large cohort of strength, endurance and team-sport athletes. Well-trained male (n=327) and female (n=226) athletes completed multiple web-based 24-hr dietary recalls over a 2-4 wk period. Total energy intake, the contribution of animal- and plant-based proteins to daily protein intake, and protein intake at six eating moments were determined. Daily protein intake averaged 108±33 and 90±24 g in men and women, respectively, which corresponded to relative intakes of 1.5±0.4 and 1.4±0.4 g/kg. Dietary protein intake was correlated with total energy intake in strength (r=0.71, p <.001), endurance (r=0.79, p <.001) and team-sport (r=0.77, p <.001) athletes. Animal and plant-based sources of protein intake was 57% and 43%, respectively. The distribution of protein intake was 19% (19±8 g) at breakfast, 24% (25±13 g) at lunch and 38% (38±15 g) at dinner. Protein intake was below the recommended 20 g for 58% of athletes at breakfast, 36% at lunch and 8% at dinner. In summary, this survey of athletes revealed they habitually consume > 1.2 g protein/kg/d, but the distribution throughout the day may be suboptimal to maximize the skeletal muscle adaptive response to training.


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