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Manganese superoxide dismutase (MnSOD) is a latent tumor suppressor gene. To investigate the therapeutic effect of MnSOD and its mechanisms, a replication-competent recombinant adenovirus with E1B 55-kDa gene deletion (ZD55) was constructed, and human MnSOD and tumor necrosis factor– related apoptosis-inducing ligand (TRAIL) genes were inserted to form(More)
The influence of inoculum size on the growth kinetics of Clostridium botulinum 56A and percentage of growth-positive samples was studied in a complete factorial design with factors of inoculum size (1, 100, or 10,000 spores), pH, and sodium-chloride concentration. Growth was followed hourly as change in A 620. Polynomial regression was used to analyze the(More)
Ghrelin, a novel gastric hormone, regulates food intake and energy metabolism via central mechanisms. The peripheral effect of ghrelin on adiposity is poorly understood. We established a stable 3T3-L1 cell line expressing ghrelin to study the direct effect of ghrelin on adipogenesis. Cells overexpressing ghrelin demonstrate significantly attenuated(More)
Slice-parallel video coding with a fixed number of slices and uniformly allocated coding regions would cause extra waiting time among slice threads, especially when the encoding machine is also busy running other applications. In this paper, we propose to adaptively decide the number of slices before encoding each frame by computing the expected value of(More)
MicroRNAs (miRNAs or miRs) are involved in phenotype modulation of neural cells after peripheral nerve injury. The effects of miRNAs on the survival of dorsal root ganglion (DRG) neurons, however, have not yet been well understood. In this study, microarray profiling indicated that 13 miRNAs were differentially expressed in rat DRGs (L4-L6) during the(More)
Recommender systems, especially the newly launched ones, have to deal with the data-sparsity issue, where little existing rating information is available. Recently, transfer learning has been proposed to address this problem by leveraging the knowledge from related recom-mender systems where rich collaborative data are available. However, most previous(More)
Collaborative filtering (CF) aims to predict users' ratings on items according to historical user-item preference data. In many real-world applications, preference data are usually sparse, which would make models overfit and fail to give accurate predictions. Recently, several research works show that by transferring knowledge from some manually selected(More)