Syntheses and conformational studies of poly(S-menthyloxycarbonylmethyl l- and d-cysteines)

S-menthyloxycarbonylmethyl l- and d-cysteines were prepared by the reaction of l- or d-cysteine and (?)-menthyl chloroacetate in liquid ammonia and were then polymerized to poly(S-menthyloxycarbonylmethyll- and d-cysteines) by the N-carboxyanhydride (NCA) method. From the results obtained by means of infra-red spectra, X-ray diffractions, optical rotatory dispersions (o.r.d.), and circular dichroisms (c.d.), $\text{poly}\text{(S-}\text{menthyloxycarbonylmethyl-}\text{l}\text{-cysteine}\text{)}$ was found to be a right-handed α-helix in the solid state and in ethyl ether/chloroform and chloroform solutions. Similarly, $\text{poly}\text{(S-}\text{menthyloxycarbonylmethyl-}\text{d}\text{-cysteine}\text{)}$ was a left-handed α-helix. The helix-coil transition of these polymers was observed in the vicinity of 3–4% trifluoroacetic acid (TFA) in chloroform/TFA mixtures.     

Environmentally benign precipitation copolymerization of methacrylate ester and styrene to make polymeric microspheres in supercritical carbon dioxide

The polymeric microspheres were synthesized by the precipitation copolymerization of glycidyl methacrylate (GMA) with methacrylic acid(MAA) or 2‐hydoxyethyl methacrylate (2‐HEMA) containing styrene (ST) in SC‐CO₂. Scanning electron microscopy (SEM) showed that the products were spherical microparticles, with the addition of MAA and/or 2‐HEMA as the monomer, with diameter of 0.2–2 μm. The effects of copolymerization pressure, temperature, and ratios of GMA/MAA, ST, and/or GMA/2‐HEMA, on the particle size and morphology were investigated in detail. A new experiment setup is proposed for the large amount of production, based on the rule of lower monomer concentration, more stable system, and better use of the present polymerization apparatus. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 2425–2431, 2007     

Design and performance of a punch mechanism based pellet injector for alternative injection in the large helical device

A low speed single barrel pellet injector, using a mechanical punch device has been developed for alternative injection in the large helical device. A pellet is injected by the combined operation of a mechanical punch and a pneumatic propellant system. The pellet shape is cylindrical, 3 mm in diameter and 3 mm in length. Using this technique the speed of the pellet can be controlled flexibly in the range of 100-450 m/s, and a higher speed can be feasible for a higher gas pressure. The injector is equipped with a guide tube selector to direct the pellet to different injection locations. Pellets are exposed to several curved parts with the curvature radii R(c) = 0.8 and 0.3 m when they are transferred in guided tubes to the respective injection locations. Pellet speed variation with pressure at different pellet formation temperatures has been observed. Pellet intactness tests through these guide tubes show a variation in the intact speed limit over a range of pellet formation temperatures from 6.5 to 9.8 K. Pellet speed reduction of less than 6% has been observed after the pellet moves through the curved guide tubes.     

Estimation of time-dependent input from neuronal membrane potential

The set of firing rates of the presynaptic excitatory and inhibitory neurons constitutes the input signal to the postsynaptic neuron. Estimation of the time-varying input rates from intracellularly recorded membrane potential is investigated here. For that purpose, the membrane potential dynamics must be specified. We consider the Ornstein-Uhlenbeck stochastic process, one of the most common single-neuron models, with time-dependent mean and variance. Assuming the slow variation of these two moments, it is possible to formulate the estimation problem by using a state-space model. We develop an algorithm that estimates the paths of the mean and variance of the input current by using the empirical Bayes approach. Then the input firing rates are directly available from the moments. The proposed method is applied to three simulated data examples: constant signal, sinusoidally modulated signal, and constant signal with a jump. For the constant signal, the estimation performance of the method is comparable to that of the traditionally applied maximum likelihood method. Further, the proposed method accurately estimates both continuous and discontinuous time-variable signals. In the case of the signal with a jump, which does not satisfy the assumption of slow variability, the robustness of the method is verified. It can be concluded that the method provides reliable estimates of the total input firing rates, which are not experimentally measurable.     

Optimizing time histograms for non-Poissonian spike trains

The time histogram is a fundamental tool for representing the inhomogeneous density of event occurrences such as neuronal firings. The shape of a histogram critically depends on the size of the bins that partition the time axis. In most neurophysiological studies, however, researchers have arbitrarily selected the bin size when analyzing fluctuations in neuronal activity. A rigorous method for selecting the appropriate bin size was recently derived so that the mean integrated squared error between the time histogram and the unknown underlying rate is minimized (Shimazaki & Shinomoto, 2007 ). This derivation assumes that spikes are independently drawn from a given rate. However, in practice, biological neurons express non-Poissonian features in their firing patterns, such that the spike occurrence depends on the preceding spikes, which inevitably deteriorate the optimization. In this letter, we revise the method for selecting the bin size by considering the possible non-Poissonian features. Improvement in the goodness of fit of the time histogram is assessed and confirmed by numerically simulated non-Poissonian spike trains derived from the given fluctuating rate. For some experimental data, the revised algorithm transforms the shape of the time histogram from the Poissonian optimization method.     

Peroxiredoxin 2 as a chemotherapy responsiveness biomarker candidate in osteosarcoma revealed by proteomics

Purpose : We aimed to identify novel chemotherapy responsiveness biomarkers for osteosarcoma (OS) by investigating the global protein expression profile of 12 biopsy samples from OS patients. Experimental design : Six patients were classified as good responders and six as poor responders, according to the Huvos grading system. The protein expression profiles obtained by 2‐D DIGE consisted of 2250 protein spots. Results : Among them, we identified 55 protein spots whose intensity was significantly different (Bonferroni adjusted p‐value<0.01) between the two patient groups. Mass spectrometric protein identification demonstrated that the 55 spots corresponded to 38 distinct gene products including peroxiredoxin 2 (PRDX 2). Use of a specific antibody against PRDX 2 confirmed the differential expression of PRDX 2 between good and poor responders, while PRDX 2 levels as measured by Western blotting correlated highly with their corresponding 2‐D DIGE values. The predictive value of PRDX 2 expression was further confirmed by examining an additional four OS cases using Western blotting. Conclusions and clinical relevance : These results establish PRDX 2 as a candidate for chemotherapy responsiveness marker in OS. Measuring PRDX 2 in biopsy samples before treatment may contribute to more effective management of OS.     

A study on a quantum-inspired evolutionary algorithm based on pair swap

A quantum-inspired evolutionary algorithm (QEA) is proposed as a stochastic algorithm to perform combinatorial optimization problems. The QEA is evolutionary computation that uses quantum bits and superposition states in quantum computation. Although the QEA is a coarse-grained parallel algorithm, it involves many parameters that must be adjusted manually. This paper proposes a new method, named pair swap, which exchanges each best solution information between two individuals instead of migration in the QEA. Experimental results show that our proposed method is a simpler algorithm and can find a high quality solution in the 0-1 knapsack problem. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

Shape from Shading with Interreflections Under a Proximal Light Source: Distortion-Free Copying of an Unfolded Book

We address the problem of recovering the 3D shape of an unfolded book surface from the shading information in a scanner image. This shape-from-shading problem in a real world environment is made difficult by a proximal, moving light source, interreflections, specular reflections, and a nonuniform albedo distribution. Taking all these factors into account, we formulate the problem as an iterative, non-linear optimization problem. Piecewise polynomial models of the 3D shape and albedo distribution are introduced to efficiently and stably compute the shape in practice. Finally, we propose a method to restore the distorted scanner image based on the reconstructed 3D shape. The image restoration experiments for real book surfaces demonstrate that much of the geometric and photometric distortions are removed by our method.     

Inorganic/Organic Double‐Network Gels Containing Ionic Liquids

Highly robust ion gels, termed double‐network (DN) ion gels, composed of inorganic/organic interpenetrating networks and a large amount of ionic liquids (ILs), are fabricated. The DN ion gels with an 80 wt% IL content show extraordinarily high mechanical strength: more than 28 MPa of compressive fracture stress. In the DN ion gel preparation, a brittle inorganic network of physically bonded silica nanoparticles and a ductile organic network of polydimethylacrylamide (PDMAAm) are formed in the IL. Because of the different reaction mechanisms of the inorganic/organic networks, the DN ion gels can be formed by an easy and free‐shapeable one‐pot synthesis. They can be prepared in a controllable manner by manipulating the formation order of the inorganic and organic networks via not only multistep but also single‐step processes. When silica particles form a network prior to the PDMAAm network formation, DN ion gels can be prepared. The brittle silica particle network in the DN ion gel, serving as sacrificial bonds, easily ruptures under loading to dissipate energy, while the ductile PDMAAm network maintains the shape of the material by the rubber elasticity. Given the reversible physical bonding between the silica particles, the DN ion gels exhibit a significant degree of self‐recovery by annealing.