The effect of small dose of topiroxostat on serum uric acid in patients receiving hemodialysis

Introduction : Topiroxostat, a recently developed xanthine oxidase inhibitor, is expected to have fewer adverse effects than allopurinol because it has different mechanism of action from alloprinol. However, its dosage, usage and safety have not been established in patients with impaired renal function or those undergoing dialysis at the development since no studies was conducted in these patients. Methods : Cross over clinical trial using 3 months of allopurinol and topiroxostat on 27 maintain Japanese HD patients were carried out. The effects on oxidative stress status of both drugs were also evaluated by measuring oxidation reduction potential. Findings : Twenty‐five of twenty‐seven patients completed study. The mean serum uric acid levels in the topiroxostat‐treated arm was significantly lower than it in the allopurinol‐treated arm time‐dependently (P < 0.0001). Corrected oxidative stress ratio defined as biological antioxidant potential/diacron reactive oxygen metabolites was significantly increased in topiroxostat‐arm (*P = 0.0035), but not in allopurinol‐arm (P = 0.1429). No significant difference was seen in diacron reactive oxygen metabolites, biological antioxidant potential, static oxidation‐reduction potential, and capacity oxidation‐reduction potential between pre and post treatment of both drugs. Discussion : It is suggested that a low dose of topiroxostat decreased serum uric acid sufficiently to maintain it below 7.0 mg/dL in patients receiving hemodialysis.     

The effects of amino-acid mutations on specific interactions between urokinase-type plasminogen activator and its receptor: Ab initio molecular orbital calculations

During cancer invasion, the binding of urokinase-type plasminogen activator (uPA) to its receptor (uPAR) on the surface of a cancer cell is considered a trigger for invasion. Here, we present a stable structure of the solvated complex formed between uPA and uPAR (uPA-uPAR) and investigate the specific interactions between uPA and uPAR by ab initio fragment molecular orbital (FMO) calculations. The result indicates that the electrostatic interactions between the charged amino acid residues existing in both uPA and uPAR make a large contribution to the binding between uPA and uPAR. In particular, Lys23, Lys46, Lys98 and Lys61 of uPA are found to have strong attractive interactions with uPAR. To elucidate the effect of these residues on the interactions between uPA and uPAR, we substituted each of them with the uncharged amino acid Leu and investigated the interactions between the mutated uPA and wild-type uPAR. The interaction energies indicate that Lys46 and Lys98, which bind uPA to the rim of the central ligand-binding cavity of uPAR, make greater contributions to the binding between uPA and uPAR than Lys23, which is positioned at the bottom of the ligand-binding cavity of uPAR. The effect of hydrating water molecules located between uPA and uPAR is also investigated to be significant for the specific interactions between uPA and uPAR. These results are expected to be informative for developing new peptide antagonists that block the binding of uPA to uPAR.     

LMNtal as a hierarchical logic programming language

LMNtal (pronounced “elemental”) is a simple language model based on hierarchical graph rewriting that uses logical variables to represent connectivity and membranes to represent hierarchy. LMNtal is an outcome of the attempt to unify constraint-based concurrency and Constraint Handling Rules (CHR), the two notable extensions to concurrent logic programming. LMNtal is intended to be a substrate language of various computational models, especially those addressing concurrency, mobility and multiset rewriting. Although the principal objective of LMNtal was to provide a unifying computational model, it is of interest to equip the formalism with a precise logical interpretation. In this paper, we show that it is possible to give LMNtal a simple logical interpretation based on intuitionistic linear logic and a flattening technique. This enables us to call LMNtal a hierarchical, concurrent linear logic language.     

Damage to seagrass and seaweed beds in Matsushima Bay,Japan, caused by the huge tsunami of the Great East Japan Earthquake on 11 March 2011

Damage to seagrass and seaweed beds caused by the huge tsunami of the Great East Japan Earthquake on 11 March 2011 was investigated in Matsushima Bay, Miyagi Prefecture, Japan, by comparing satellite images taken before the tsunami in November 2009 and after the tsunami in May 2011. The results showed that the tsunami destroyed 220 ha of seagrass and seaweed beds, from 320 ha in 2009 to 100 ha just after the tsunami. Zostera marina beds on the sandy and muddy bottom were rather severely damaged compared with brown seaweed beds of Sargassum horneri on the rocky substrate. Substrates of the beds and directions of the tsunami seem to be responsible for the magnitude of the damage to the beds. Maps of the spatial distributions of the beds before and after the tsunami can provide information for the restoration of seagrass and seaweed beds as natural infrastructures of coastal fisheries resources.     

Optimal linear combination of neural networks for improvingclassification performance

This paper presents a new method for linearly combining multiple neural network classifiers based on the statistical pattern recognition theory. In our approach, several neural networks are first selected based on which works best for each class in terms of minimizing classification errors. Then, they are linearly combined to form an ideal classifier that exploits the strengths of the individual classifiers. In this approach, the minimum classification error criterion is utilized to estimate the optimal linear weights. In this formulation, because the classification decision rule is incorporated into the cost function, a more suitable better combination of weights for the classification objective could be obtained. Experimental results using artificial and real data sets show that the proposed method can construct a better combined classifier that outperforms the best single classifier in terms of overall classification errors for test data     

Parametric embedding for class visualization

We propose a new method, parametric embedding (PE), that embeds objects with the class structure into a low-dimensional visualization space. PE takes as input a set of class conditional probabilities for given data points and tries to preserve the structure in an embedding space by minimizing a sum of Kullback-Leibler divergences, under the assumption that samples are generated by a gaussian mixture with equal covariances in the embedding space. PE has many potential uses depending on the source of the input data, providing insight into the classifier's behavior in supervised, semisupervised, and unsupervised settings. The PE algorithm has a computational advantage over conventional embedding methods based on pairwise object relations since its complexity scales with the product of the number of objects and the number of classes. We demonstrate PE by visualizing supervised categorization of Web pages, semisupervised categorization of digits, and the relations of words and latent topics found by an unsupervised algorithm, latent Dirichlet allocation.     

Linearity Analysis of Concurrent Logic Programs

Automatic memory management and the hiding of the notion of pointers are the prominent features of symbolic processing languages. They make programming easy and guarantee the safety of memory references. For the memory management of linked data structures, copying garbage collection is most widely used because of its simplicity and desirable properties. However, if certain properties about runtime storage allocation and the behavior of pointers can be obtaind by static analysis, a compiler may be able to generate object code closer to that of procedural programs. In the fields of parallel, distributed and real-time computation, it is highly desirable to be able to identify data structures in a program that can be managed without using garbage collection. To this end, this paper proposes a framework of linearity analysis for a concurrent logic language Moded Flat GHC, and proves its basic property. The purpose of linearity analysis is to distinguish between fragments of data structures that may be referenced by two or more pointers and those that cannot be referenced by two or more pointers. Data structures with only one reader are amenable to compile-time garbage collection or local reuse. The proposed framework of linearity analysis is constraint-based and involves both equality and implicational constraints. It has been implemented as part of klint v2, a static analyzer for KL1 programs.     

Wide-gap layered oxychalcogenide semiconductors: Materials, electronic structures and optoelectronic properties

Applying the concept of materials design for transparent conductive oxides to layered oxychalcogenides, several p-type and n-type layered oxychalcogenides were proposed as wide-gap semiconductors and their basic optical and electrical properties were examined. The layered oxychalcogenides are composed of ionic oxide layers and covalent chalcogenide layers, which bring wide-gap and conductive properties to these materials, respectively. The electronic structures of the materials were examined by normal/inverse photoemission spectroscopy and energy band calculations. The results of the examinations suggested that these materials possess unique features more than simple wide-gap semiconductors. Namely, the layered oxychalcogenides are considered to be extremely thin quantum wells composed of the oxide and chalcogenide layers or 2D chalcogenide crystals/molecules embedded in an oxide matrix. Observation of step-like absorption edges, large band gap energy and large exciton binding energy demonstrated these features originating from 2D density of states and quantum size effects in these layered materials.     

Spectroscopic imaging and the characterization of the autofluorescence properties of human bronchus tissues using UV laser diodes

Ultraviolet laser diodes (UV-LD) were used for the excitation source of autofluorescence (AF) measurements and spectroscopic imaging of the AF originating from the human bronchus was obtained. The AF spectra from normal bronchus tissues were measured and a clear AF spectrum was obtained by using a short wavelength (400 nm) laser diode; the overlap of the AF signal and excitation source could be substantially eliminated. In order to study the origin of AF intensity deterioration from bronchus tissue due to the formation of tumor tissues, the fluorescence spectrum was measured for various AF substances under various conditions. The blue AF signal of elastin and NADH solutions, which could not be easily studied by conventional excitation light sources, as well as the green AF became weak by adding lactic acid. The AF spectrum was measured for 512/spl times/512 pixels and the intensity mapping as a function of emission wavelength was obtained. Two-dimensional information of the AF signal intensity distribution for a certain wavelength component was measured. The feature originating from a region as small as about 100 /spl mu/m could be recognized. Numerical calculations of the data were performed and precise features of the AF were revealed.