Coenzyme Q (CoQ or ubiquinone) is a lipid-soluble component of virtually all types of cell membranes and has been shown to play multiple metabolic functions. Several clinical diseases including encephalomyopathy, cerebellar ataxia and isolated myopathy were shown to be associated with CoQ deficiency. However, the role of CoQ in immunity has not been defined. In the present study, we showed that flies defective in CoQ biosynthetic gene coq2 were more susceptible to bacterial and fungal infections, while were more resistant to viruses. We found that Drosophila contained both CoQ9 and CoQ10, and food supplement of CoQ10 could partially rescue the impaired immune functions of coq2 mutants. Surprisingly, wild-type flies fed CoQ10 became more susceptible to viral infection, which suggested that extra caution should be taken when using CoQ10 as a food supplement. We further showed that CoQ was essential for normal induction of anti-microbial peptides and amplification of viruses. Our work determined CoQ content in Drosophila and described its function in immunity for the first time.
<p><strong>Abstract.</strong> The traditional fast marching algorithm for segmentation of the liver is suitable for processing on the central processing unit (CPU) platform, however, it is not suitable for implementation on Graphics Processing Unit (GPU). The fuzzy connection algorithm is used to extract the blood vessels in the liver, but there is a calculation error. The refinement algorithm is very time consuming when extracting the target skeleton line from the 3D image. In this paper, the fast-marching algorithm and the thinning algorithm are improved, which can be applied to the GPU computing, The fuzzy algorithm is also improved, and the calculation error of the algorithm is solved, making it more suitable for medical image processing. The computing speed of GPU is far faster than CPU. Medical image processing is one of the earliest applications where the computing performance is improved by GPU. These three segmentation methods, fast marching method, fuzzy connecting method and refinement algorithm are very common in medical image segmentation. Because the increment of medical image data results in the extension of computing time for medical image processing, it is necessary to apply the high parallelism of the GPU to speed up these algorithms. The experiment results demonstrate the feasibility of our accelerating algorithm.</p>
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.