Disposition of diadenosine 5',5"'-P1,P4-tetraphosphate (Ap4A) in rats

The disposition of diadenosine 5'5"'-P1,P4-tetraphosphate (Ap4A), an endogenous dinucleotide, was investigated in rats. The degradation of Ap4A in rat plasma was very rapid and could be explained by a Michaelis-Menten equation: Km and Vmax values were 1.69 micrograms/ml and 4.32 micrograms/min/ml, respectively. Ap4A was degraded in rat plasma to ATP and AMP, but not to 2 ADP molecules, and these nucleotides were further degraded through adenosine. The degradations kinetics were examined. After intravenous bolus injection, Ap4A in plasma declined rapidly and the rate of elimination was dose-dependent: the biological half-life was about 3s at the dose of 1 mg/kg and was longer at 3 mg/kg. When Ap4A was administered by intravenous infusion (0.5 or 1.0 mg/kg/min), the plasma level rapidly reached a steady-state, which then rapidly declined after stopping the infusion.     

High-rate Decoupled Water Electrolysis System Integrated with α-MoO3 as a Redox Mediator with Fast Anhydrous Proton Kinetics

Hydrogen is a promising alternative to fossil fuels that can reduce greenhouse gas emissions. Decoupled water electrolysis system using a reversible proton storage redox mediator, where the oxygen evolution reaction and hydrogen evolution reaction are separated in time and space, is an effective approach to producing hydrogen gas with high purity, high flexibility, and low cost. To realize fast hydrogen production in such a system, a redox mediator capable of releasing protons rapidly is required. Herein, α-MoO₃, with an ultrafast proton transfer property that can be explained by a dense hydrogen bond network in the lattice oxygen arrays of HxMoO₃, is examined as a high-rate redox mediator for fast hydrogen production in acidic electrolytes. The α-MoO₃ redox mediator shows both a large capacity of 204 mAh g⁻¹ and fast hydrogen production at a current rate of 10 A cm⁻²(≈153 A g⁻¹), outperforming most of the previously reported solid-state redox mediators.     

A combined approach for modeling particle behavior in granular impact damper using discrete element method and cellular automata

A particle impact damper is a vibration absorber type that consists of a container attached to a primary vibrating structure. It also contains many particles that are constrained to move inside the container, whereby the damping effect can be obtained by collision between particles and the container. The discrete element method (DEM) has been developed for modeling granular systems, where the kinematics of each particle are calculated numerically using the equations of motion. However, the computational time is significant since the algorithm checks for particle contacts for all possible particle combinations. The use of a cellular automata (CA) modeling technique may provide increased computational efficiency due to the local updating of variables, and the discrete treatment of time and space. In this study, we propose a new approach combining DEM with CA for modeling a granular damper under a forced excitation. We use DEM to describe the particle motion according to the equations of motion, while CA is introduced for the particle contact checks in discrete space. We also investigate the effect of simplification in the contact force model, which allows the unit time step of numerical integration to become larger than that used in the strict model. It is shown that the suggested particle contact scanning method and the force approximation model contribute to the reduction of the computational time, and neither degenerates the calculation accuracy nor causes the numerical instability.     

A chondroitin sulfate/keratan sulfate proteoglycan, PG-1000, forms complexes which are concentrated in the reticular laminae of electric organ basement membranes

Previously, we identified PG-1000 as part of a disulfide-linked complex of two large proteoglycans (PG-1000 and the beta component) and three smaller proteins purified from the extracellular matrix of elasmobranch electric organ (Iwata and Carlson, 1991, J. Biol. Chem. 266: 323-333). PG-1000 is a chondroitin sulfate/keratan sulfate proteoglycan with a molecular mass of about 1.2 x 16(6) daltons. When visualized in the electron microscope, PG-1000 has the typical "bottle-brush" appearance expected for a proteoglycan with an average total length of about 345 nm and about 20 chains of approximately 110 nm (Carlson and Wight, 1987, J. Cell Biol. 105: 3075-3086). Using immunocytochemical methods, we now demonstrate that PG-1000 is a component of the interstitial extracellular matrix of the electric organ. PG-1000 immunoreactivity is found throughout the interstitial matrix, but it is highly concentrated in that region of the matrix immediately adjacent to the basal lamina, the reticular lamina. The reticular and basal laminae together form the basement membrane. PG-1000 immunoreactivity is especially apparent on basal laminae that surround nerve fibers and nerve terminals. When the disulfide-linked PG-1000 complexes are purified and examined in the electron microscope following rotary shadowing, they appear as bottle-brush structures which are often attached at a central region and radiate like spokes of a wheel. These aggregates contain two to six proteoglycan monomers. We hypothesize that the PG-1000 complexes are disulfide-stabilized parts of an extended network of linked proteoglycans in the reticular lamina.     

Bacteriological, pharmacokinetic and clinical evaluation of azithromycin in the pediatric field]

Azithromycin (AZM), a new macrolide antibiotic, in fine granules and in capsules was studied for pharmacokinetic and clinical evaluation in the pediatric patients. Antibacterial activity of AZM against 43 clinical isolates: AZM exhibited slightly lower activity against Gram-positive bacteria and 2-8-fold higher activity against Gram-negative bacteria than erythromycin or clarithromycin. Plasma or urine samples were collected from eight patients receiving the drug in fine granular form, and two patients receiving it in capsules for the determination of drug levels. The elimination half-lives of AZM after administration at dose of 10 mg/kg/day for 3 days were 50.0 and 51.2 hours for fine granules, and 41.5 hours for capsules. AUC0-infinity was 11.7 and 24.3 micrograms.hr/ml for fine granules, and 8.3 micrograms.hr/ml for capsules. The cumulative excretion rates up to 120 hours after the start of treatment were 8.24 and 13.84% for fine granules, and 3.83% for capsules. AZM was administered to 123 patients once daily at 3.7-20.0 mg/kg body weight over 3 to 5 days with reference to the standard dose of 10 mg/kg. The drug was used to treat patients with pharyngitis, tonsillitis, scarlet fever, pneumonia, mycoplasmal pneumonia, chlamydial pneumonia, otitis media, pertussis, intestinal infection, and SSTI. The effectiveness of AZM was evaluated in 109 cases. The drug was rated "excellent" in 65.1% of the patients and "good" in 29.4%, resulting in an efficacy rate of 94.5%. Furthermore, AZM eradicated 43 of 46 (93.5%) bacteria that had been identified before the treatment. Three patients complained of side effects of urticaria (1 case) and diarrhea (2 cases). Abnormal laboratory changes were reported as follows: decreased leukocyte (3 cases), increased eosinophil (5), increased platelet (2), increased eosinophil and platelet, elevated GPT (1), and elevated GOT and GPT (1). The abnormalities, however, were mild enough to raise no clinically significant problems. In conclusion, AZM in once daily regimen was effective and safe in treatment of pediatric infections.     

Greedy versus social: resource-competing oscillator network as a model of amoeba-based neurocomputer

A single-celled amoeboid organism, the true slime mold Physarum polycephalum, exhibits rich spatiotemporal oscillatory behavior and sophisticated computational capabilities. The authors previously created a biocomputer that incorporates the organism as a computing substrate to search for solutions to combinatorial optimization problems. With the assistance of optical feedback to implement a recurrent neural network model, the organism changes its shape by alternately growing and withdrawing its photosensitive branches so that its body area can be maximized and the risk of being illuminated can be minimized. In this way, the organism succeeded in finding the optimal solution to the four-city traveling salesman problem with a high probability. However, it remains unclear how the organism collects, stores, and compares information on light stimuli using the oscillatory dynamics. To study these points, we formulate an ordinary differential equation model of the amoeba-based neurocomputer, considering the organism as a network of oscillators that compete for a fixed amount of intracellular resource. The model, called the “Resource-Competing Oscillator Network (RCON) model,” reproduces well the organism’s experimentally observed behavior, as it generates a number of spatiotemporal oscillation modes by keeping the total sum of the resource constant. Designing the feedback rule properly, the RCON model comes to face a problem of optimizing the allocation of the resource to its nodes. In the problem-solving process, “greedy” nodes having the highest competitiveness are supposed to take more resource out of other nodes. However, the resource allocation pattern attained by the greedy nodes cannot always achieve a “socially optimal” state in terms of the public cost. We prepare four test problems including a tricky one in which the greedy pattern becomes “socially unfavorable” and investigate how the RCON model copes with these problems. Comparing problem-solving performances of the oscillation modes, we show that there exist some modes often attain socially favorable patterns without being trapped in the greedy one.     

An Algorithm for Minimum Cost Arc-Connectivity Orientations

Given a 2k-edge-connected undirected graph, we consider to find a minimum cost orientation that yields a k-arc-connected directed graph. This minimum cost k-arc-connected orientation problem is a special case of the submodular flow problem. Frank (1982) devised a combinatorial algorithm that solves the problem in O(k ² n ³ m) time, where n and m are the numbers of vertices and edges, respectively. Gabow (1995) improved Frank’s algorithm to run in O(kn ² m) time by introducing a new sophisticated data structure. We describe an algorithm that runs in O(k ³ n ³+kn ² m) time without using sophisticated data structures. In addition, we present an application of the algorithm to find a shortest dijoin in O(n ² m) time, which matches the current best bound.     

Suitable properties of ink to create inkjet-printed surface-directed microchannels that utilize the pinning effect of a triple line on a rough surface

If microfluidic devices can be directly produced using printing techniques, the combination of microfluidics and printing techniques for other applications, such as printed electronics, will make all-printed highly-functionalized microfluidic devices possible. Therefore, we have made efforts to develop a technique for producing microfluidic devices using an inkjet printer. The microchannels that could be created using this technique were a kind of surface-directed channels that utilize the pinning effect of a triple line on a rough surface. In this study, we focused on what were the required properties of the printer ink during the wetting and drying processes of the ink. As a result, one of the properties required during the wetting process was that the advancing contact angle of the ink should be smaller than a certain value, which depended on the average volume of the ink drops ejected from the printhead and the number of drops per unit area. The receding contact angle should be smaller than about one third of each advancing angle. In addition, during the drying process, a small amount of surfactant added to the ink played a critical role in order to leave a continuous stain of the ink. As an application of this inkjet-printed channel, we also created a device for mixing aqueous solutions.     

Amoeba-based Chaotic Neurocomputing: Combinatorial Optimization by Coupled Biological Oscillators

We demonstrate a neurocomputing system incorporating an amoeboid unicellular organism, the true slime mold Physarum, known to exhibit rich spatiotemporal oscillatory behavior and sophisticated computational capabilities. Introducing optical feedback applied according to a recurrent neural network model, we induce that the amoeba’s photosensitive branches grow or degenerate in a network-patterned chamber in search of an optimal solution to the traveling salesman problem (TSP), where the solution corresponds to the amoeba’s stably relaxed configuration (shape), in which its body area is maximized while the risk of being illuminated is minimized.Our system is capable of reaching the optimal solution of the four-city TSP with a high probability. Moreover, our system can find more than one solution, because the amoeba can coordinate its branches’ oscillatory movements to perform transitional behavior among multiple stable configurations by spontaneously switching between the stabilizing and destabilizing modes. We show that the optimization capability is attributable to the amoeba’s fluctuating oscillatory movements. Applying several surrogate data analyses, we present results suggesting that the amoeba can be characterized as a set of coupled chaotic oscillators.

Effective indices to characterize short sequences of human random generations

Brain impediments such as dementia are a serious problem today. It would be very useful if software for private diagnosis were available. In this paper, we show the effectiveness of the human random generation test (HRG) for such software, and propose a set of four indices to be used for classifying the HRG data. Human-generated random numbers have strong characteristics compared to computer-generated random numbers, and these are known to be correlated to the individual characters of the subjects. However, analysis using the correlation dimension or HMM requires a long data sequence, and thus is not suitable for diagnoses. We therefore focus on short sequences of HRG and search for effective indices to detect signs of brain disability hidden in the HRG data. We studied data from subjects of different age groups, and successfully differentiated the data from the different groups. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007