Enhanced Fatty Acid Oxidation and FATP4 Protein Expression after Endurance Exercise Training in Human Skeletal Muscle

FATP1 and FATP4 appear to be important for the cellular uptake and handling of long chain fatty acids (LCFA). These findings were obtained from loss- or gain of function models. However, reports on FATP1 and FATP4 in human skeletal muscle are limited. Aerobic training enhances lipid oxidation; however, it is not known whether this involves up-regulation of FATP1 and FATP4 protein. Therefore, the aim of this project was to investigate FATP1 and FATP4 protein expression in the vastus lateralis muscle from healthy human individuals and to what extent FATP1 and FATP4 protein expression were affected by an increased fuel demand induced by exercise training. Eight young healthy males were recruited to the study. All subjects were non smokers and did not participate in regular physical activity (<1 time per week for the past 6 months, VO2peak 3.4±0.1 l O2 min−1). Subjects underwent an 8 week supervised aerobic training program. Training induced an increase in VO2peak from 3.4±0.1 to 3.9±0.1 l min−1 and citrate synthase activity was increased from 53.7±2.5 to 80.8±3.7 µmol g−1 min−1. The protein content of FATP4 was increased by 33%, whereas FATP1 protein content was reduced by 20%. Interestingly, at the end of the training intervention a significant association (r2 = 0.74) between the observed increase in skeletal muscle FATP4 protein expression and lipid oxidation during a 120 min endurance exercise test was observed. In conclusion, based on the present findings it is suggested that FATP1 and FATP4 proteins perform different functional roles in handling LCFA in skeletal muscle with FATP4 apparently more important as a lipid transport protein directing lipids for lipid oxidation

Harnessing Smart Sensor Technology for Industrial Energy Efficiency- Making Process-Specific Efficiency Projects Cost Effective with a Broadly Configurable, Network-Enabled Monitoring Tool

To improve monitoring technology often re-quired by industrial energy efficiency projects, we have developed a set of power and process monitoring tools based on the IEEE 1451.2 smart sensor interface standard. These tools enable a wide-range of industrial facilities to monitor electricity use and identify opportunities for savings. Our efforts have focused on creating an 'off-the-shelf' monitoring solution that can be configured for a wide range of sensors to monitor machine and process parameters in conjunction with electrical power usage. Using these tools, we have identified energy savings opportunities for several manufacturing processes by monitoring and analyzing real-time, process-related information in conjunction with electric power consumption data. Specifically, we have found that some energy savings opportunities are only apparent after combining synchronously-collected, machine and process information with power-use profiles. In this paper we discuss examples of applying this approach to various manufacturing processes from different product sectors

Harnessing Smart Sensor Technology for Industrial Energy Efficiency- Making Process-Specific Efficiency Projects Cost Effective with a Broadly Configurable, Network-Enabled Monitoring Tool

To improve monitoring technology often re-quired by industrial energy efficiency projects, we have developed a set of power and process monitoring tools based on the IEEE 1451.2 smart sensor interface standard. These tools enable a wide-range of industrial facilities to monitor electricity use and identify opportunities for savings. Our efforts have focused on creating an 'off-the-shelf' monitoring solution that can be configured for a wide range of sensors to monitor machine and process parameters in conjunction with electrical power usage. Using these tools, we have identified energy savings opportunities for several manufacturing processes by monitoring and analyzing real-time, process-related information in conjunction with electric power consumption data. Specifically, we have found that some energy savings opportunities are only apparent after combining synchronously-collected, machine and process information with power-use profiles. In this paper we discuss examples of applying this approach to various manufacturing processes from different product sectors