“Click Peptide“: pH‐Triggered in Situ Production and Aggregation of Monomer Aβ1–42

Into neutral : We demonstrate the unique features of a pH click peptide based on an O‐acyl isopeptide method. Under acidic conditions, the click peptide remains in a monomeric form. Upon increase of the pH to 7.4, the click peptide is quickly able to convert into Aβ1–42 through an O‐to‐N intramolecular acyl migration. Further study using this pH click peptide would elucidate the pathological role of Aβ1–42 in Alzheimer's disease.

     

A nonlinear model to rank association rules based on semantic similarity and genetic network programing

Many methods have been studied for mining association rules efficiently. However, because these methods usually generate a large number of rules, it is still a heavy burden for the users to find the most interesting ones. In this paper, we propose a novel method for finding what the user is interested in by assigning several keywords, like searching documents on the Web using search engines. By considering both the semantic similarity between the rules and keywords, and the statistical information like support, confidence, chi-squared value, etc. we could rank the rules by a new method named RuleRank, where evolutionary methods are applied to find the optimal ranking model. Experiments show that our approach is effective for the users to find what they want. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Augmentation of polysialic acid by valproic acid in early postnatal mouse hippocampus and primary cultured hippocampal neurons

We examined the effects of valproic acid (VPA) on hippocampal neurons. Prenatal VPA exposure significantly increased polysialic acid (PSA) expression in the early postnatal mouse hippocampus. Moreover, VPA treatment significantly enhanced PSA expression in primary cultured hippocampal neurons and stimulated neurite growth. Our results suggest that VPA exposure in ovo affects hippocampal development.     

Analysis of energy consumption of elevator group supervisory control system based on genetic network programming

Elevator Group Supervisory Control System (EGSCS) is a traffic system, which provides the transportation services for passengers in modern buildings. As the elevator systems include uncertainty due to the future arrival of the passengers, it difficult to model, analyze, and optimize the elevator group supervisory control system. Recently, artificial intelligence technology has been used in such complex systems. Genetic Network Programming(GNP), a graph‐based evolutionary method extended from genetic algorithm and genetic programming, has been already applied to EGSCS. On the other hand, since energy consumption is becoming one of the greatest challenges in the society, it should be taken as one of the criteria of the elevator operations. The elevators with maximum energy efficiency are therefore required. In this paper, the GNP is used to solve EGSCS with energy consumption (EC). Moreover, the idle car assignment has been embedded in the proposed method. Finally, the simulations show that some factors should be introduced into GNP in order to deal with the higher EC in the light traffic of the elevator systems. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

A portfolio selection model using genetic relation algorithm and genetic network programming

In this paper, new evolutionary computation methods named genetic relation algorithm (GRA) and genetic network programming (GNP) have been applied to the portfolio selection problem. The number of brands in the stock market is generally very large, therefore, techniques for selecting the effective portfolio are likely to be of interest in the financial field. In order to pick up the most efficient portfolio, the proposed model considers the correlation coefficient between stock brands as strength, which indicates the relation between nodes in GRA. The algorithm evaluates the relationships between stock brands using a specific measure of strength and generates the optimal portfolio in the final generation. Then, the selected portfolio is further optimized by the stock trading model of GNP. In a sense, the proposed model is an integrated intelligent model. A comprehensive analysis of the results is provided, and it is clarified that the proposed model can obtain much higher profits than other traditional methods. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Image denoising using pulse coupled neural network with an adaptive Pareto genetic algorithm

Recently, pulse coupled neural network (PCNN) attracts much attention in image denoising as a nonlinear filtering technique. The PCNN‐based anisotropic diffusion (PCNN‐AD) method has been proposed previously for flicker noise reduction and its effectiveness has been demonstrated. Using the visual characteristics of PCNN, PCNN‐AD has also solved the problem of AD that AD is not able to suppress the isolate noise. However, there are still two drawbacks in PCNN‐AD, that is, time consuming and PCNN parameters' estimation. In order to improve the efficiency and the denoising performance of PCNN‐AD, a PCNN‐based method with an adaptive Pareto genetic algorithm (GA‐PCNN) has been proposed to restrain from additive white Gaussian noise (AWGN) in this paper. GA‐PCNN firstly integrates the PCNN and AD as a parallel system, then, optimizes the parameters of a simplified PCNN by the adaptive Pareto GA. Experimental results indicate that GA‐PCNN has better performances than the previous denoising techniques, i.e. median filter, Wiener filter, AD filter, and PCNN‐AD. The effectiveness of GA‐PCNN on AWGN reduction and edge preservation are shown finally. The results will also contribute to denoising in CMOS image sensors in the future. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Molecular Features and Clinical Management of Hereditary Gynecological Cancers

Hereditary gynecological cancers are caused by several inherited genes. Tumors that arise in the female reproductive system, such as ovaries and the uterus, overlap with hereditary cancers. Several hereditary cancer-related genes are important because they might lead to therapeutic targets. Treatment of hereditary cancers should be updated in line with the advent of various new methods of evaluation. Next-generation sequencing has led to rapid, economical genetic analyses that have prompted a concomitant and significant paradigm shift with respect to hereditary cancers. Molecular tumor profiling is an epochal method for determining therapeutic targets. Clinical treatment strategies are now being designed based on biomarkers based on tumor profiling. Furthermore, the National Comprehensive Cancer Network (NCCN) guidelines significantly changed the genetic testing process in 2020 to initially consider multi-gene panel (MGP) evaluation. Here, we reviewed the molecular features and clinical management of hereditary gynecological malignancies, such as hereditary breast and ovarian cancer (HBOC), and Lynch, Li–Fraumeni, Cowden, and Peutz–Jeghers syndromes. We also reviewed cancer-susceptible genes revealed by MGP tests.     

Synergetic improvement strategy on thermoelectric performance of CuAlO2 compacts

We fabricated Sr and Ca-doped CuAlO₂ compacts from the mixed powder of CuO, Cu₂O, Al₂O₃, and SrO or CaO by multi-pass hot pressing followed by spark plasma sintering (SPS). The XRD results showed the reaction of CuO, Cu₂O and Al₂O₃ was rather complete and only CuAlO₂ single phase was formed when the additive amount of SrO or CaO was appropriate. Multi-pass hot pressing increased the relative density and the usage of plate-like Al₂O₃ as reaction raw material enhanced the orientation degree. In spite of performance improvement conflicts through elemental doping, density increase and orientation improvement, the measurement on the thermoelectric performance indicated that the electrical resistivity, Seebeck coefficient, power factor, dimensionless figure of merit (ZT) were improved to varying degrees through the synergetic action of elemental doping, density increase, and orientation control. The highest power factor and ZT of the Ca-doped CuAlO₂ compacts reached 1.54?×?10^?4 W?m^?1 K^?2 and 0.015 at 973?K, respectively. The thermoelectric performance was higher than those of CuAlO₂ at the same temperature in published work before.     

Effect of Ultrasonic Irradiation on the Probability of Primary Nucleation of L-Arginine Hydrochloride

Most of the amino acids that are utilized as medical raw materials and food additives show polymorphism. To improve the functionality of amino acid crystals, an effective method of polymorph control is required in the crystallization process. Here, primary nucleation of L-arginine hydrochloride by ultrasonication was investigated. L-Arginine hydrochloride exhibits polymorphism, and it crystallizes into three distinct crystal forms. A cooling crystallization experiment was performed, and nucleation of each polymorph upon ultrasonication was observed. In addition, the nucleation was analyzed using the nucleation probability theory. The results indicate that ultrasonic irradiation would significantly induce the nucleation of a particular polymorph.