In order to elucidate energy balance in the skeletal muscle, we cloned cDNA of a homologue of uncoupling protein (UCP) from rat skeletal muscle. We also cloned rat UCP-2 cDNA from rat brown adipose tissue (BAT). The UCP cloned from rat skeletal muscle showed 57% and 72% identity with rat UCP-1 and UCP-2. The mRNA was expressed abundantly in the skeletal muscle, moderately in the BAT, and slightly in the white adipose tissue (WAT) with a major band at 2.5 kb and a minor band at 2.8 kb, while the UCP-2 gene expression was widely detected in the whole body with substantial levels in the WAT and with slight levels in the skeletal muscle and BAT. The rat UCP cloned in the present study showed 86% identity with the recently cloned human UCP-3, which was also expressed abundantly in the skeletal muscle with a signal of 2.4 kb. Therefore, the rat UCP was considered to be rat UCP-3. In rats fed high-fat diet the UCP-3 gene expression was augmented 2-fold in the skeletal muscle while UCP-2 mRNA levels were increased significantly (1.6-fold) in the epididymal WAT. Augmented expression of UCPs may provide defense against high-fat induced obesity and impairment of glucose metabolism.

Abstract-Vascular endothelial growth factor

Recently multineuronal recording has allowed us to observe patterned firings, synchronization, oscillation, and global state transitions in the recurrent networks of central nervous systems. We propose a learning algorithm based on the process of information maximization in a recurrent network, which we call recurrent infomax (RI). RI maximizes information retention and thereby minimizes information loss through time in a network. We find that feeding in external inputs consisting of information obtained from photographs of natural scenes into an RI-based model of a recurrent network results in the appearance of Gabor-like selectivity quite similar to that existing in simple cells of the primary visual cortex. We find that without external input, this network exhibits cell assembly-like and synfire chain-like spontaneous activity as well as a critical neuronal avalanche. In addition, we find that RI embeds externally input temporal firing patterns to the network so that it spontaneously reproduces these patterns after learning. RI provides a simple framework to explain a wide range of phenomena observed in in vivo and in vitro neuronal networks, and it will provide a novel understanding of experimental results for multineuronal activity and plasticity from an information-theoretic point of view.

No abstract

Three-body interactions have been found in physics, biology, and sociology. To investigate their effect on dynamical systems, as a first step, we study numerically and theoretically a system of phase oscillators with a three-body interaction. As a result, an infinite number of multistable synchronized states appear above a critical coupling strength, while a stable incoherent state always exists for any coupling strength. Owing to the infinite multistability, the degree of synchrony in an asymptotic state can vary continuously within some range depending on the initial phase pattern.