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https://www.selleckchem.com/ The results were consistent with those in GES-1 and SGC-7901 cell lines. Meanwhile, we found that hsa-miR-328-3p can bind to the 3'-UTR of the potential target gene STAT3. Furthermore, propofol significantly inhibited the proliferation of gastric cancer cell line SGC-7901, where hsa-miR-328-3p was up-regulated and the expression of STAT3 and downstream proliferation-related target genes were down-regulated. However, the growth inhibition of propofol on SGC-7901 cell was significantly reversed after the inhibition of hsa-miR-328-3p. To sum up, propofol suppressed the STAT3 pathway via up-regulating hsa-miR-328-3p to inhibit gastric cancer proliferation. To sum up, propofol suppressed the STAT3 pathway via up-regulating hsa-miR-328-3p to inhibit gastric cancer proliferation.Essential proteins are assumed to be an indispensable element in sustaining normal physiological function and crucial to drug design and disease diagnosis. The discovery of essential proteins is of great importance in revealing the molecular mechanisms and biological processes. Owing to the tedious biological experiment, many numerical methods have been developed to discover key proteins by mining the features of the high throughput data. Appropriate integration of differential biological information based on protein-protein interaction (PPI) network has been proven useful in predicting essential proteins. The main intention of this research is to provide a comprehensive study and a review on identifying essential proteins by integrating multi-source data and provide guidance for researchers. Detailed analysis and comparison of current essential protein prediction algorithms have been carried out and tested on benchmark PPI networks. In addition, based on the previous method TEGS (short for the network Topology, gene Expression, Gene ontology, and Subcellular localization), we improve the performance of predicting essential proteins by incorporating known protein comple

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