Multidrug-resistant Pseudomonas aeruginosa is one of the most life-threatening pathogens for global health. In this regard, phage encoded lytic proteins, including endolysins and virion-associated peptidoglycan hydrolases (VAPGH), have been proposed as promising antimicrobial agents to treat P. aeruginosa. Most dsDNA phages use VAPGH to degrade peptidoglycan (PG) during infection, and endolysin to lyse the host cells at the end of lytic cycle. By contrast, dsRNA phage encodes only one lytic protein, which is located in the viral membrane to digest the PG during penetration, and also serves as an endolysin to release the phage. Currently, there are only seven sequenced dsRNA phages, and phiYY is the only one that infects human pathogen P. aeruginosa. In this study, dsRNA phage phiYY encoded lysin, named Ply17, was cloned and purified. Ply17 contains a PG-binding domain and a lysozyme-like-family domain. Ply17 exhibited a broad antibacterial activity against the outer membrane permeabilizer treated Gram-negative bacteria. The best lytic activity was achieved at 37°C, pH 7.5, in the presence of 0.5 mM EDTA. Moreover, it could effectively lyse Gram-positive bacteria directly, including Staphylococcus aureus. Therefore, dsRNA phage encoded Ply17 might be a promising new agent for treating multidrug-resistant pathogens.

Image fusion is process which combine relevant information from two or more images into a single image. The aim of fusion is to extract relevant information for research. According to different application and characteristic of algorithm, image fusion algorithm could be used to improve quality of image. This paper complete compare analyze of image fusion algorithm based on wavelet transform and Laplacian pyramid. In this paper, principle, operation, steps and characteristic of fusion algorithm are summarized, advantage and disadvantage of different algorithm are compared. The fusion effects of different fusion algorithm are given by MATLAB. Experimental results shows that quality of fused image would be improve obviously.

Contrast pyramid algorithm is put forward in this paper. The human visual system is sensitive to contrast information of image, so contrast pyramid algorithm would outstanding the contrast of image. The algorithm consists of creation process of Gauss Pyramid, the process of creating contrast Pyramid and reconstruction process of clear image. Simulation by MATLAB was completed in multi-focus image, multi-modality image and color image. Objective evaluation index such as mean, standard deviation, entropy and average gradient was calculated Simulation results and index show that the contrast pyramid algorithm has advantage of projecting the contrast of image, especially in color image fusion.

Thresholding is one of the critical steps in pattern recognition and has a significant effect on the upcoming steps of image application, the important objectives of thresholding are as follows, and separating objects from background, decreasing the capacity of data consequently increases speed. Various threshold segmentation methods are studied. These methods are compared by using MATLAB7.0. The qualities of image segmentation are elaborated. The results show that iterative threshold segmentation method is better than others.

Image fusion algorithm based on gradient pyramid is one of the multi-scale, multi-resolution decomposition algorithms. Original image was decomposed into Gauss pyramid, after that, gradient decomposition was completed on each layer in four directions, and fusion effect was evaluated by taking using of entropy, average gradient, mean and standard deviation. Simulation results show that gradient pyramid algorithm is effective to multi-focus image and color image.