Level of beta-adrenergic receptor kinase 1 inhibition determines degree of cardiac dysfunction after chronic pressure overload-induced heart failure.

BACKGROUND: Heart failure is characterized by abnormalities in beta-adrenergic receptor (betaAR) signaling, including increased level of myocardial betaAR kinase 1 (betaARK1). Our previous studies have shown that inhibition of betaARK1 with the use of the Gbetagamma sequestering peptide of betaARK1 (betaARKct) can prevent cardiac dysfunction in models of heart failure. Because inhibition of betaARK activity is pivotal for amelioration of cardiac dysfunction, we investigated whether the level of betaARK1 inhibition correlates with the degree of heart failure. METHODS AND RESULTS: Transgenic (TG) mice with varying degrees of cardiac-specific expression of betaARKct peptide underwent transverse aortic constriction (TAC) for 12 weeks. Cardiac function was assessed by serial echocardiography in conscious mice, and the level of myocardial betaARKct protein was quantified at termination of the study. TG mice showed a positive linear relationship between the level of betaARKct protein expression and fractional shortening at 12 weeks after TAC. TG mice with low betaARKct expression developed severe heart failure, whereas mice with high betaARKct expression showed significantly less cardiac deterioration than wild-type (WT) mice. Importantly, mice with a high level of betaARKct expression had preserved isoproterenol-stimulated adenylyl cyclase activity and normal betaAR densities in the cardiac membranes. In contrast, mice with low expression of the transgene had marked abnormalities in betaAR function, similar to the WT mice. CONCLUSIONS: These data show that the level of betaARK1 inhibition determines the degree to which cardiac function can be preserved in response to pressure overload and has important therapeutic implications when betaARK1 inhibition is considered as a molecular target.

Opportunistic Control Over Shared Wireless Channels

© 2015 IEEE.We consider a wireless control architecture with multiple control loops over a shared wireless medium. A scheduler observes the random channel conditions that each control system experiences over the shared medium and opportunistically selects systems to transmit at a set of non-overlapping frequencies. The transmit power of each system also adapts to channel conditions and determines the probability of successfully receiving and closing the loop. We formulate the optimal design of channel-aware scheduling and power allocation that minimize the total power consumption while meeting control performance requirements for all systems. In particular, it is required that for each control system a given Lyapunov function decreases at a specified rate in expectation over the random channel conditions. We develop an offline algorithm to find the optimal communication design, as well as an online protocol which selects scheduling and power variables based on a random observed channel sequence and converges almost surely to the optimal operating point. Simulations illustrate the power savings of our approach compared to other non-channel-aware schemes.