Skeletal muscle wasting has gained interest as a primary consequence of chronic kidney disease (CKD) due to the relationship between skeletal muscle mass, mortality and major adverse cardiovascular events in this population. The combination of reductions in physical function, skeletal muscle performance and skeletal muscle mass places individuals with CKD at greater risk of sarcopenia. Therefore the monitoring of skeletal muscle composition and function may provide clinical insight into disease progression. Dual-energy X-ray absorptiometry and bioelectrical impedance analysis are frequently used to estimate body composition in people with CKD within clinical research environments, however, their translation into clinical practice has been limited. Proxy measures of skeletal muscle quality can be obtained using diagnostic ultrasound, providing a cost-effective and accessible imaging modality to aid further clinical research regarding changes in muscle composition. Clinicians and practitioners should evaluate the strengths and limitations of the available technology to determine which devices are most appropriate given their respective circumstances. Progressive resistance exercise has been shown to improve skeletal muscle hypertrophy of the lower extremities, muscular strength and health-related quality of life in end-stage renal disease, with limited evidence available in CKD predialysis. Fundamental principles (i.e. specificity, overload, variation, reversibility, individuality) can be used in the development of more advanced programs focused on improving specific neuromuscular and functional outcomes. Future research is needed to determine the applicability of skeletal muscle monitoring in clinical settings and the feasibility and efficacy of more advanced resistance exercise approaches in those with CKD predialysis.

Leptin (LEP) is associated with appetite regulation and metabolism. Concentration is linear with adiposity, suggesting LEP resistance. LEP circulates freely and bound with its soluble receptor (sOB-r); the ratio is the free leptin index (FLI), an index of leptin resistance; lower FLI suggests reduced biological action. Purpose. The aim was to determine the effect of changes in adipose tissue distribution on LEP, sOB-r, and FLI following 6 months (6 M) of a diet/exercise weight loss program (WLP). In addition, we aim to identify predictors of the FLI. Methods. 6 M WLP consisted of diet/lifestyle interventions following ADA guidelines. Body composition was assessed by DXA. LEP and sOB-r analysis were done via ELISA. Results. 10 adults completed the WLP. Significant reductions were seen in total fat percentage (% fat), nontrunk fat, (NTF), and trunk fat (TF) from base to 3 m and 6 M (p ≤ 0.05). The FLI were reduced at 3 M and 6 M for males and 6 M for females. Total body fat and body weight predicted the FLI in both sexes. Conclusions. LEP and FLI reductions following 6 M of WLP were achieved independent of sOB-r changes. We also demonstrate that the FLI can be predicted noninvasively through total fat mass and body weight in kilograms.

To investigate the effects of different loads on system and lower-body kinetics during jump squats, 12 resistance-trained men performed jumps under different loading conditions: 0%, 12%, 27%, 42%, 56%, 71%, and 85% of 1-repetition maximum (1-RM). System power output was calculated as the product of the vertical component of the ground reaction force and the vertical velocity of the bar during its ascent. Joint power output was calculated during bar ascent for the hip, knee, and ankle joints, and was also summed across the joints. System power output and joint power at knee and ankle joints were maximized at 0% 1-RM (p < 0.001) and followed the linear trends (p < 0.001) caused by power output decreasing as the load increased. Power output at the hip was maximized at 42% 1-RM (p = 0.016) and followed a quadratic trend (p = 0.030). Summed joint power could be predicted from system power (p < 0.05), while system power could predict power at the knee and ankle joints under some of the loading conditions. Power at the hip could not be predicted from system power. System power during loaded jumps reflects the power at the knee and ankle, while power at the hip does not correspond to system power.