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Roles of MT-ND1 in Cancer
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作者 yi-chun xu Jun SU +2 位作者 Jia-jing ZHOU Qing YUAN Jun-song HAN 《Current Medical Science》 SCIE CAS 2023年第5期869-878,共10页
The energy shift toward glycolysis is one of the hallmarks of cancer.Complex I is a vital enzyme complex necessary for oxidative phosphorylation.The mitochondrially encoded NADH:ubiquinone oxidoreductase core subunit ... The energy shift toward glycolysis is one of the hallmarks of cancer.Complex I is a vital enzyme complex necessary for oxidative phosphorylation.The mitochondrially encoded NADH:ubiquinone oxidoreductase core subunit 1(MT-ND1)is the largest subunit coded by mitochondria of complex I.The present study summarizes the structure and biological function of MT-ND1.From databases and literature,the expressions and mutations of MT-ND1 in a variety of cancers have been reviewed.MT-ND1 may be a biomarker for cancer diagnosis and prognosis.It is also a potential target for cancer therapy. 展开更多
关键词 mitochondrially encoded NADH:ubiquinone oxidoreductase core subunit 1 CANCER BIOMARKER MUTATION
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A deep learning interatomic potential suitable for simulating radiation damage in bulk tungsten
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作者 Chang-Jie Ding Ya-Wei Lei +6 位作者 Xiao-Yang Wang Xiao-Lin Li Xiang-Yan Li Yan-Ge Zhang yi-chun xu Chang-Song Liu xue-Bang Wu 《Tungsten》 EI CSCD 2024年第2期304-322,共19页
So far, it has been a challenge for existing interatomic potentials to accurately describe a wide range of physical properties and maintain reasonable efficiency. In this work, we develop an interatomic potential for ... So far, it has been a challenge for existing interatomic potentials to accurately describe a wide range of physical properties and maintain reasonable efficiency. In this work, we develop an interatomic potential for simulating radiation damage in body-centered cubic tungsten by employing deep potential, a neural network-based deep learning model for representing the potential energy surface. The resulting potential predicts a variety of physical properties consistent with first-principles calculations, including phonon spectrum, thermal expansion, generalized stacking fault energies, energetics of free surfaces, point defects, vacancy clusters, and prismatic dislocation loops. Specifically, we investigated the elasticity-related properties of prismatic dislocation loops, i.e., their dipole tensors, relaxation volumes, and elastic interaction energies. This potential is found to predict the maximal elastic interaction energy between two 1/2 <1 1 1> loops better than previous potentials, with a relative error of only 7.6%. The predicted threshold displacement energies are in reasonable agreement with experimental results, with an average of 128 eV. The efficiency of the present potential is also comparable to the tabulated gaussian approximation potentials and modified embedded atom method potentials, meanwhile, can be further accelerated by graphical processing units. Extensive benchmark tests indicate that this potential has a relatively good balance between accuracy, transferability, and efficiency. 展开更多
关键词 Machine learning Deep learning Interatomic potential Radiation damage TUNGSTEN
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