Magnitude and control of mitochondrial sensitivity to ADP

The transduction function for ADP stimulation of mitochondrial ATP synthesis in skeletal muscle was reconstructed in vivo and in silico to investigate the magnitude and origin of mitochondrial sensitivity to cytoplasmic ADP concentration changes. Dynamic in vivo measurements of human leg muscle phosphocreatine (PCr) content during metabolic recovery from contractions were performed by 31P-NMR spectroscopy. The cytoplasmic ADP concentration ([ADP]) and rate of oxidative ATP synthesis (Jp) at each time point were calculated from creatine kinase equilibrium and the derivative of a monoexponential fit to the PCr recovery data, respectively. Reconstructed [ADP]-Jp relations for individual muscles containing more than 100 data points were kinetically characterized by nonlinear curve fitting yielding an apparent kinetic order and ADP affinity of 1.9 ± 0.2 and 0.022 ± 0.003 mM, respectively (means ± SD; n = 6). Next, in silico [ADP]-Jp relations for skeletal muscle were generated using a computational model of muscle oxidative ATP metabolism whereby model parameters corresponding to mitochondrial enzymes were randomly changed by 50–150% to determine control of mitochondrial ADP sensitivity. The multiparametric sensitivity analysis showed that mitochondrial ADP ultrasensitivity is an emergent property of the integrated mitochondrial enzyme network controlled primarily by kinetic properties of the adenine nucleotide translocator.

Multiparametric sensitivity analysis of energy production projects

Optimization studies of an energy production project or complex consist in determining the economic general dimensioning of the works during the prefeasibility or the feasibility stage of the studies. As these first studies are part of the iterative system planning process, they should include very exhaustive sensitivity analyses on the accuracy of all technical and economic parameters, although (and even because) so much data is uncertain during this phase.After a review of the mathematics of discounting and of the decision-making economic criteria, a nomographic approach is presented that allows the optimum dimensions of the project to be determined as a function of any combination of the following parameters: imposed discount rate, total investment cost, variations in cash flow pattern, delay in commissioning date, life expectancy of the works, monetary value of energy and power, system load growth, seasonal pattern of energy demand, effect of secondary energy, long-term average river flow, and effect of regulation on downstream developments.