Microscopic image-based covariation network analysis for actin scaffold-modified insulin signaling.

To infer a "live" protein network in single cells, we developed a novel Protein Localization and Modification-based Covariation Network (PLOM-CON) analysis method using a large set of quantitative data on the abundance (quantity), post-translational modification state (quality), and localization/morphological information of target proteins from microscope immunostained images. The generated network exhibited synchronized time-dependent behaviors of the target proteins to visualize how a live protein network develops or changes in cells under specific experimental conditions. As a proof of concept for PLOM-CON analysis, we applied this method to elucidate the role of actin scaffolds, in which actin fibers and signaling molecules accumulate and form membrane-associated protein condensates, in insulin signaling in rat hepatoma cells. We found that the actin scaffold in cells may function as a platform for glycogenesis and protein synthesis upon insulin stimulation.

Code-division multiple-access multiuser demodulator by using quantum fluctuations.

We examine the average-case performance of a code-division multiple-access (CDMA) multiuser demodulator in which quantum fluctuations are utilized to demodulate the original message within the context of Bayesian inference. The quantum fluctuations are built into the system as a transverse field in the infinite-range Ising spin glass model. We evaluate the performance measurements by using statistical mechanics. We confirm that the CDMA multiuser modulator using quantum fluctuations achieve roughly the same performance as the conventional CDMA multiuser modulator through thermal fluctuations on average. We also find that the relationship between the quality of the original information retrieval and the amplitude of the transverse field is somehow a "universal feature" in typical probabilistic information processing, viz., in image restoration, error-correcting codes, and CDMA multiuser demodulation.

Stability analysis of associative memory network composed of stochastic neurons and dynamic synapses.

We investigate the dynamical properties of an associative memory network consisting of stochastic neurons and dynamic synapses that show short-term depression and facilitation. In the stochastic neuron model used in this study, the efficacy of the synaptic transmission changes according to the short-term depression or facilitation mechanism. We derive a macroscopic mean field model that captures the overall dynamical properties of the stochastic model. We analyze the stability and bifurcation structure of the mean field model, and show the dependence of the memory retrieval performance on the noise intensity and parameters that determine the properties of the dynamic synapses, i.e., time constants for depressing and facilitating processes. The associative memory network exhibits a variety of dynamical states, including the memory and pseudo-memory states, as well as oscillatory states among memory patterns. This study provides comprehensive insight into the dynamical properties of the associative memory network with dynamic synapses.

Effect of quantum fluctuation in error-correcting codes.

We discuss the decoding performance of error-correcting codes based on a model in which quantum fluctuations are introduced by means of a transverse field. The essential issue in this paper is whether quantum fluctuations improve the decoding quality compared with the conventional estimation based on thermal fluctuations, which is called finite-temperature decoding. We found that an estimation incorporating quantum fluctuations approaches the optimal performance of finite-temperature decoding. The results are illustrated by numerically solving saddle-point equations and performing a Monte Carlo simulation. We also evaluated the upper bound of the overlap between the original sequence and the decoded sequence derived from the equations of state for the order parameters, which is a measure of the decoding performance.

Temperature dependence for anammox bacteria enriched from freshwater sediments.

The anoxic ammonium oxidation (anammox) process has been regarded as an attractive alternative process to treat wastewater containing high ammonium concentrations. By the implementation of anammox process at moderately low temperatures (<25°C), the anammox process will be applied to more various industrial wastewater treatments. In this study, we established enrichment cultures of anammox bacteria from freshwater sediments by using an up-flow column reactor equipped with porous polyester nonwoven fabric at moderately low temperatures. Their nitrogen conversion rates reached 0.07-0.26 kg-N/m³/d. Phylogenetic analysis based on 16S rRNA gene from enrichment cultures revealed the presence of various anammox bacteria affiliated with unknown anammox bacteria as well as known anammox candidates, i.e., Candidatus Kuenenia stuttgartiensis and Candidatus Brocadia fulgida, Candidatus Scalindua wagneri. Anammox bacterial populations were influenced by enrichment conditions, i.e., seed sediments and temperature.