Generation of mouse anti-human urate anion exchanger antibody by genetic immunization and its identification

Background Human urate anion exchanger (hURAT1) as a major urate transporter expressed on renal tubular epithelial cells regulates blood urate level by reabsorbing uric acid. Antibody is an important tool to study hURAT1. This study aimed, by genetic immunization, to produce mouse anti-hURAT1 polyclonal antibody with high throughput and high specificity and to detect the location of hURAT1 in human kidney.Methods Human renal total RNA was isolated and the entire cDNA of hURAT1 was amplified by RT-PCR. The sequence of intracellular high antigenicity fragment (A280 to R349) was chosen by prediction software of protein antigenicity, and its cDNA was amplified from cDNA of hURAT1, and then cloned into pBQAP-TT vector to construct recombinant plasmid pBQAP-TT-hURAT1-210 for genetic immunization. Mice were inoculated with this recombinant plasmid and two other adjuvant plasmids, pCMVi-GMCSF and pCMVi-Flt3L, which helped to enhance the antibody’s generation. After four weeks, the mice were sacrificed to obtain the anti-hURAT1 antibody from serum. The antibody was identified by western blot analysis and immunohistochemistry. At the same time, rabbit anti-hURAT1 antibody was produced by protein immunization. The specificity and efficiency between the rabbit and mouse anti-hURAT1 antibody were compared by western blot analysis and immunohistochemistry. Results The entire cDNA of hURAT1 and cDNA of its intracellular high immunogenic fragment were amplified successfully. Recombinant plasmid pBQAP-TT-hURAT1-210 for genetic immunization was confirmed by restriction digestion and sequencing. Both!the mouse anti-hURAT1 antibody and rabbit anti-hURAT1 antibody recognized 58kD hURAT1 and 64kD glycosylated hURAT1 protein bands in western blot. Immunohistochemically, hURAT1 was located at the brush border membrane of renal proximal tubular cells. In addition, the throughput and specificity of the mouse anti-hURAT1 antibody were higher than those of the rabbit anti-hURAT1 antibody.Conclusion Genetic immunization can generate anti-hURAT1 polyclonal antibody of high throughput and specificity.

Optimization of Submarine Hydrodynamic Coefficients Based on Immune Genetic Algorithm

Aiming at the demand for optimization of hydrodynamic coefficients in submarine's motion equations,an adaptive weight immune genetic algorithm was proposed to optimize hydrodynamic coefficients in motion equations.Some hydrodynamic coefficients of high sensitivity to control and maneuver were chosen as the optimization objects in the algorithm.By using adaptive weight method to determine the weight and target function,the multi-objective optimization could be translated into single-objective optimization.For a certain kind of submarine,three typical maneuvers were chosen to be the objects of study:overshoot maneuver in horizontal plane,overshoot maneuver in vertical plane and turning circle maneuver in horizontal plane.From the results of computer simulations using primal hydrodynamic coefficient and optimized hydrodynamic coefficient,the efficiency of proposed method is proved.

Intelligent optimization of the structure of the large section highway tunnel based on improved immune genetic algorithm

As in the building of deep buried long tunnels,there are complicated conditions such as great deformation,high stress,multi-variables,high non-linearity and so on,the algorithm for structure optimization and its application in tunnel engineering are still in the starting stage. Along with the rapid development of highways across the country,it has become a very urgent task to be tackled to carry out the optimization design of the structure of the section of the tunnel to lessen excavation workload and to reinforce the support. Artificial intelligence demonstrates an extremely strong capability of identifying,expressing and disposing such kind of multiple variables and complicated non-linear relations. In this paper,a comprehensive consideration of the strategy of the selection and updating of the concentration and adaptability of the immune algorithm is made to replace the selection mode in the original genetic algorithm which depends simply on the adaptability value. Such an algorithm has the advantages of both the immune algorithm and the genetic algorithm,thus serving the purpose of not only enhancing the individual adaptability but maintaining the individual diversity as well. By use of the identifying function of the antigen memory,the global search capability of the immune genetic algorithm is raised,thereby avoiding the occurrence of the premature phenomenon. By optimizing the structure of the section of the Huayuan tunnel,the current excavation area and support design are adjusted. A conclusion with applicable value is arrived at. At a higher computational speed and a higher efficiency,the current method is verified to have advantages in the optimization computation of the tunnel project. This also suggests that the application of the immune genetic algorithm has a practical significance to the stability assessment and informationization design of the wall rock of the tunnel.

A novel immune genetic algorithm based on quasi secondary response

Combining the advantages of a genetic algorithm and an artificial immune system, a novel genetic algorithm named immune genetic algorithm based on quasi secondary response （IGA QSR） is proposed. IGA QSR employs a database to simulate the standard secondary response and the quasi secondary response. Elitist strategy, automatic extinction, clonal propagation, diversity guarantee, and selection based on comprehensive fitness are also used in the process of IGA QSR. Theoretical analysis, numerical examples of three benchmark mathematical optimization problems and a trave ling salesman problem all demonstrate that IGA-QSR is more effective not only on convergence speed but also on convergence probability than a simple genetic algorithm with the elitist strategy （ SGA ES）. Besides, IGA QSR allows the designers to stop and restart the optimization process freely with out losing the best results that have already been obtained. These properties make IGA QSR be a fea sible, effective and robust search algorithm for complex engineering problems.

An Improved Immune Genetic Algorithm for Solving the Optimization Problems of Computer Communication Networks

Obtaining the average delay and selecting a route in a communication networkare multi-constrained nonlinear optimization problems . In this paper, based on the immune geneticalgorithm, a new fuzzy self-adaptive mutation operator and a new upside-down code operator areproposed. This improved IGA is further successfully applied to solve optimal problems of computercommunication nets.

Generalized Shape and Gauge Decoupling Load Distribution Optimization Based on IGA for Tandem Cold Mill

Load distribution is the foundation of shape control and gauge control, in which it is necessary to take into account the shape control ability of TCM （tandem cold mill） for strip shape and gauge quality. First, the objective function of generalized shape and gauge decoupling load distribution optimization was established, which considered the rolling force characteristics of the first and last stands in TCM, the relative power, and the TCM shape control ability. Then, IGA （immune genetic algorithm） was used to accomplish this multi-objective load distribution optimization for TCM. After simulation and comparison with the practical load distribution strategy in one tandem cold mill, general- ized shape and gauge decoupling load distribution optimization on the basis of IGA approved good ability of optimizing shape control and gauge control simultaneously.