Diversity in levels of intracellular total creatine and triglycerides in human skeletal muscles observed by 1H-MRS

We used1H-magnetic resonance spectroscopy to noninvasively determine total creatine (TCr), choline-containing compounds (Cho), and intracellular (IT) and extracellular (between-muscle fibers) triglycerides (ET) in three human skeletal muscles. Subjects' (n = 15 men) TCr concentrations in soleus [Sol; 100.2 ± 8.3 (SE) mmol/kg dry wt] were lower (P < 0.05) than those in gastrocnemius (Gast; 125.3 ± 9.2 mmol/kg dry wt) and tibialis anterior (TA; 123.7 ± 8.8 mmol/kg dry wt). The Cho levels in Sol (35.8 ± 3.6 mmol/kg dry wt) and Gast (28.5 ± 3.5 mmol/kg dry wt) were higher (P < 0.001 andP < 0.01, respectively) compared with TA (13.6 ± 2.4 mmol/kg dry wt). The IT values were found to be 44.8 ± 4.6 and 36.5 ± 4.2 mmol/kg dry wt in Sol and Gast, respectively. The IT values of TA (24.5 ± 4.5 mmol/kg dry wt) were lower than those of Sol (P < 0.01) and Gast (P < 0.05). There were no differences in ET [116.0 ± 11.2 (Sol), 119.1 ± 18.5 (Gast), and 91.4 ± 19.2 mmol/kg dry wt (TA)]. It is proposed that the differences in metabolite levels may be due to the differences in fiber-type composition and deposition of metabolites due to the adaptation of different muscles during locomotion.

Genetic programming for the minimum time swing up and balance control acrobot problem

This work describes how genetic programming is applied to evolving controllers for the minimum time swing up and inverted balance tasks of the continuous state and action: limited torque acrobot. The best swing-up controller is able to swing the acrobot up to a position very close to the inverted ‘handstand’ position in a very short time, shorter than that of Coulom (2004), who applied the same constraints on the applied torque values, and to take only slightly longer than the approach by Lai et al. (2009) where far larger torque values were allowed. The best balance controller is able to balance the acrobot in the inverted position when starting from the balance position for the length of time used in the fitness function in all runs; furthermore, 47 out of 50 of the runs evolve controllers able to maintain the balance position for an extended period, an improvement on the balance controllers generated by Dracopoulos and Nichols (2012), which this paper is extended from. The most successful balance controller is also able to balance the acrobot when starting from a small offset from the balance position for this extended period.