Discovery of the ammonium substrate site on glutamine synthetase, a third cation binding site

Glutamine synthetase (GS) catalyzes the ATP-dependent condensation of ammonia and glutamate to yield glutamine, ADP, and inorganic phosphate in the presence of divalent cations. Bacterial GS is an enzyme of 12 identical subunits, arranged in two rings of 6, with the active site between each pair of subunits in a ring. In earlier work, we have reported the locations within the funnel-shaped active site of the substrates glutamate and ATP and of the two divalent cations, but the site for ammonia (or ammonium) has remained elusive. Here we report the discovery by X-ray crystallography of a binding site on GS for monovalent cations, Tl+ and Cs+, which is probably the binding site for the substrate ammonium ion. Fourier difference maps show the following. (1) Tl+ and Cs+ bind at essentially the same site, with ligands being Glu 212, Tyr 179, Asp 50', Ser 53' of the adjacent subunit, and the substrate glutamate. From its position adjacent to the substrate glutamate and the cofactor ADP, we propose that this monovalent cation site is the substrate ammonium ion binding site. This proposal is supported by enzyme kinetics. Our kinetic measurements show that Tl+, Cs+, and NH4+ are competitive inhibitors to NH2OH in the gamma-glutamyl transfer reaction. (2) GS is a trimetallic enzyme containing two divalent cation sites (n1, n2) and one monovalent cation site per subunit. These three closely spaced ions are all at the active site: the distance between n1 and n2 is 6 A, between n1 and Tl+ is 4 A, and between n2 and Tl+ is 7 A. Glu 212 and the substrate glutamate are bridging ligands for the n1 ion and Tl+. (3) The presence of a monovalent cation in this site may enhance the structural stability of GS, because of its effect of balancing the negative charges of the substrate glutamate and its ligands and because of strengthening the "side-to-side" intersubunit interaction through the cation-protein bonding. (4) The presence of the cofactor ADP increases the Tl+ binding to GS because ADP binding induces movement of Asp 50' toward this monovalent cation site, essentially forming the site. This observation supports a two-step mechanism with ordered substrate binding: ATP first binds to GS, then Glu binds and attacks ATP to form gamma-glutamyl phosphate and ADP, which complete the ammonium binding site. The third substrate, an ammonium ion, then binds to GS, and then loses a proton to form the more active species ammonia, which attacks the gamma-glutamyl phosphate to yield Gln. (5) Because the products (Glu or Gln) of the reactions catalyzed by GS are determined by the molecule (water or ammonium) attacking the intermediate gamma-glutamyl phosphate, this negatively charged ammonium binding pocket has been designed naturally for high affinity of ammonium to GS, permitting glutamine synthesis to proceed in aqueous solution.     

Noninvasive glucose monitoring in vivo with an optical heterodyne polarimeter

An amplitude-sensitive optical heterodyne polarimeter was set up to monitor noninvasively the aqueous glucose concentration in a rabbit's eye. A Zeeman laser in conjunction with a Glan-Thompson analyzer was used to generate an optical heterodyne signal. The amplitude of the heterodyne signal linearly related to the optical rotation angle of the aqueous glucose. The concentration of the aqueous glucose in a rabbit's eyeball was measured in vivo. There was a 30-min time delay between observations of aqueous glucose and blood glucose. The detection capability and the reproducibility of the experiment are demonstrated and discussed.     

Ho:CaF(2) solid-state saturable-absorber Q switch for the 2-µm Tm,Cr:Y(3)Al(5)O(12) laser

The holmium-doped calcium fluoride (Ho:CaF(2)) crystal was shown to be an effective solid-state saturable-absorber Q-switch for a flash-lamp-pumped Tm,Cr:Y(3)Al(5)O(12) laser at 2.017 μm. With a 1-cm-thick Ho(0.5%),Er(5%):CaP(2) saturable absorber and a 6.3% output coupler, a single Q-switched laser pulse of 51 mJ in energy and 60 ns in duration was obtained at a flash-lamp input energy of 85 J. With a 14.6% output coupler, a typical Q-switched laser pulse of 84 mJ and 82 ns was observed.     

A template-based baseball video scene classification using efficient playfield segmentation

In this paper, we present an effective and efficient framework for baseball video scene classification. The results of scene classification can be able to provide the ground for baseball video abstraction and high-level event extraction. In general, most conventional approaches are shot-based, which shot change detection and key-frame extraction are necessary prerequisite procedures. On the contrary, we propose a frame-based approach. In our scene classification framework, an efficient playfield segmentation technique is proposed, and then the reduced field maps are utilized as scene templates. Because the shot change detection and the key-frame extraction are not required in proposed method, the new framework is very simple and efficient. The experimental results have demonstrated that the effectiveness of our proposed framework for baseball videos scene classification, and it can be easily extended the template-based approach to other kinds of sports videos.     

Simulation optimization using particle swarm optimization algorithm with application to assembly line design

Assembly line design is an important part of production system. Some processes need to undergo changes in order to increase in efficiency. Computer simulation has been applied on process design for many decades. Traditionally, simulation had to run all possible alternatives of assembly line and was not considered as an optimization technique. Thus, this study employs particle swarm optimization (PSO) algorithm which is with mutation based on similarity for simulation optimization in order to optimize the managerial parameters in production system. Through experimentation designs and statistics tests, the simulation results show that the proposed method is better than other algorithms, like genetic algorithm and conventional PSO algorithm for solving assembly line design problem.     

An econometric analysis of SARS and Avian Flu on international tourist arrivals to Asia

This paper compares the impacts of SARS and human deaths arising from Avian Flu on international tourist arrivals to Asia. The effects of SARS and human deaths from Avian Flu are compared directly according to the number of human deaths. The nature of the short run and long run relationship is examined empirically by estimating a static line fixed effect model and a difference transformation dynamic model, respectively. Empirical results from the static fixed effect and difference transformation dynamic models are consistent, and indicate that both the short run and long run SARS effect have a more significant impact on international tourist arrivals than does Avian Flu. In addition, the effects of deaths arising from both SARS and Avian Flu suggest that SARS is more important to international tourist arrivals than is Avian Flu. Thus, while Avian Flu is here to stay, its effect is currently not as significant as that of SARS.     

Gene selection and sample classification on microarray data based on adaptive genetic algorithm/k-nearest neighbor method

Recently, microarray technology has widely used on the study of gene expression in cancer diagnosis. The main distinguishing feature of microarray technology is that can measure thousands of genes at the same time. In the past, researchers always used parametric statistical methods to find the significant genes. However, microarray data often cannot obey some of the assumptions of parametric statistical methods, or type I error may be over expanded. Therefore, our aim is to establish a gene selection method without assumption restriction to reduce the dimension of the data set. In our study, adaptive genetic algorithm/k-nearest neighbor (AGA/KNN) was used to evolve gene subsets. We find that AGA/KNN can reduce the dimension of the data set, and all test samples can be classified correctly. In addition, the accuracy of AGA/KNN is higher than that of GA/KNN, and it only takes half the CPU time of GA/KNN. After using the proposed method, biologists can identify the relevant genes efficiently from the sub-gene set and classify the test samples correctly.     

Modeling analysis of a triaxial microaccelerometer with piezoelectric thin-film sensing using energy method

This study applies energy method to derive the system modeling of a triaxial microaccelerometer that consists of a quadri-beam suspension, a seismic mass, and displacement transducers using piezoelectric thin films. Two suspension beams support both ends of the seismic mass, which is fabricated by anisotropic etching of silicon. An out-of-plane acceleration will result in a symmetric bend, and in-plane accelerations will produce asymmetric bend and torsion of the suspension beams. Two piezoelectric thin-film transducers are arranged at both ends of each suspension beam. Eight transducers in total are interconnected such that triaxial accelerations can be measured selectively. The structure stiffness of the suspension beams considers both the silicon beams and piezoelectric films by the use of the laminated beam theory. Therefore, the analytical model is applicable to the accelerometers with thick piezoelectric films. The model is based on the anisotropic material properties of Silicon and PZT and Euler’s beam equation with the assumptions that smaller strains and stresses are negligible. The analytical results of the resonant frequencies and sensor sensitivities to triaxial accelerations are presented and confirmed by finite element analysis.     

The adaptive fuzzy time series model with an application to Taiwan’s tourism demand

In this study, an adaptive fuzzy time series model for forecasting Taiwan’s tourism demand is proposed to further enhance the predicted accuracy. We first transfer fuzzy time series data to the fuzzy logic group, assign weights to each period, and then use the proposed adaptive fuzzy time series model for forecasting in which an enrollment forecasting values is applied to obtain the smallest forecasting error. Finally, an illustrated example for forecasting Taiwan’s tourism demand is used to verify the effectiveness of proposed model and confirmed the potential benefits of the proposed approach with a very small forecasting error MAPE and RMSE.