SUMOylation plays an essential role in diverse physiological and pathological processes. Identification of wild‐type SUMO1‐modification sites by mass spectrometry is still challenging. In this study, we produced a monoclonal SUMO1C‐K antibody recognizing SUMOylated peptides and proposed an efficient streamline for identification of SUMOylation sites. We identified 471 SUMOylation sites in 325 proteins from five raw data. These identified sites exhibit a high positive rate when evaluated by mutation‐verified SUMOylation sites. We identified many SUMOylated proteins involved in mitochondrial metabolism and non‐membrane‐bounded organelles formation. We proposed a SUMOylation motif, ΨKXD/EP, where proline is required for efficient SUMOylation. We further revealed SUMOylation of TFII‐I was stimulated by growth signals and was required for nucleus‐localization of p‐ERK1/2. Mutation of SUMOylation sites of TFII‐I suppressed tumor cell growth in vitro and in vivo. Taken together, we provided a strategy for personalized identification of wild‐type SUMO1‐modification sites and revealed the physiological significance of TFII‐I SUMOylation in this study.
An electromagnetic acoustic transducer (EMAT) is suitable for measuring the propagation time more accurately without causing abrasion to the transducer during testing due to the principle of its excitation. This work designs a flux-concentrating EMAT with a radial-flux-focusing permanent magnet to significantly enhance static magnetic field strength. Through theoretical analysis and finite element simulation, two kinds of coils are designed according to the concentration areas of the horizontal and vertical components of the magnetic field. One is used to generate pure longitudinal waves, and the other is used to generate both longitudinal waves and shear waves. The experimental comparison shows that the amplitudes of the pure longitudinal wave and the dual-mode wave excited by the two kinds of coils with the radial-flux-focusing magnet are more than two times higher than those with the ordinary magnet. Therefore, the flux-concentrating EMAT with the appropriate coil provides an insight into realizing more accurate detection where longitudinal wave detection is required.
A improved genetic algorithm is proposed based on a new fitness function in allusion to the problem that the traditional genetic algorithm is not fully consider the knowledge of the problem itself.The improved genetic algorithm is used to analyze the fault feature , to extract the fault and remove redundant characteristic parameters for the fault classification and calculation.The diagnosis example shows that the method has faster convergence speed and can be effective for fault identification.
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