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Exosomes derived from 3D-cultured MSCs improve therapeutic effects in periodontitis and experimental colitis and restore the Th17 cell/Treg balance in inflamed periodontium 被引量:25
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作者 Yong Zhang Jiayao Chen +7 位作者 haijun fu Shuhong Kuang Feng He Min Zhang Zongshan Shen Wei Qin Zhengmei Lin Shuheng Huang 《International Journal of Oral Science》 SCIE CAS CSCD 2021年第4期448-462,共15页
Although mesenchymal stem cell-derived exosomes(MSC-exos)have been shown to have therapeutic effects in experimental periodontitis,their drawbacks,such as low yield and limited efficacy,have hampered their clinical ap... Although mesenchymal stem cell-derived exosomes(MSC-exos)have been shown to have therapeutic effects in experimental periodontitis,their drawbacks,such as low yield and limited efficacy,have hampered their clinical application.These drawbacks can be largely reduced by replacing the traditional 2D culture system with a 3D system.However,the potential function of MSC-exos produced by 3D culture(3D-exos)in periodontitis remains elusive.This study showed that compared with MSC-exos generated via 2D culture(2D-exos),3D-exos showed enhanced anti-inflammatory effects in a ligature-induced model of periodontitis by restoring the reactive T helper 17(Th17)cell/Treg balance in inflamed periodontal tissues.Mechanistically,3D-exos exhibited greater enrichment of miR-1246,which can suppress the expression of Nfat5,a key factor that mediates Th17 cell polarization in a sequence-dependent manner.Furthermore,we found that recovery of the Th17 cell/Treg balance in the inflamed periodontium by the local injection of 3D-exos attenuated experimental colitis.Our study not only showed that by restoring the Th17 cell/Treg balance through the miR-1246/Nfat5 axis,the 3D culture system improved the function of MSC-exos in the treatment of periodontitis,but also it provided a basis for treating inflammatory bowel disease(IBD)by restoring immune responses in the inflamed periodontium. 展开更多
关键词 period culture injection
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The coupling of carbon non-stoichiometry and short-range order in governing mechanical properties of high-entropy ceramics
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作者 Wenyu Lu Jingru Xu +7 位作者 Shasha Huang Xuepeng Xiang haijun fu Xinlei Gu Baichuan Xu Ailin Yang Zhenggang Wu Shijun Zhao 《npj Computational Materials》 2025年第1期650-662,共13页
High-entropy carbide ceramics(HECCs)commonly exhibit non-stoichiometric compositions and short-range order(SRO)arising from diverse elemental mixing.In this study,taking(TiZrHfNb)C as a representative HECC,we explore ... High-entropy carbide ceramics(HECCs)commonly exhibit non-stoichiometric compositions and short-range order(SRO)arising from diverse elemental mixing.In this study,taking(TiZrHfNb)C as a representative HECC,we explore the coupling effects of SRO and carbon non-stoichiometry based on density-functional theory(DFT)and machine learning(ML).DFT results indicate that carbon non-stoichiometry is favored in Ti and Nb environments due to enhanced local atomic relaxation and charge transfer,which contribute to improved d-d bonding interactions.DFT-based Monte Carlo(MC)simulations further reveal a clustering tendency of Ti and Nb elements that compete with carbon non-stoichiometry formation.These local features are effectively captured by ML models,enabling rapid assessment of the interplay among carbon deficiency,SRO,and their influences on the mechanical properties of HECCs.This work elucidates the microscopic local properties responsible for the macroscopic behavior,offering key insights for designing HECCs through careful element selection and local chemistry control. 展开更多
关键词 machine learning ml dft ti nb environments short range order local atomic relaxation carbon non stoichiometry coupling effects high entropy carbide ceramics high entropy ceramics
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Local-distortion-informed exceptional multicomponent transition-metal carbides uncovered by machine learning
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作者 Jun Zhang Liu He +8 位作者 Yaoxu Xiong Shasha Huang Biao Xu Shihua Ma Xuepeng Xiang haijun fu Jijung Kai Zhenggang Wu Shijun Zhao 《npj Computational Materials》 CSCD 2024年第1期1576-1585,共10页
Developing high-performance multicomponent ceramics,which are promising in solving challenges posed by emerging technologies,shows grand difficulties because of the immense compositional space and complex local distor... Developing high-performance multicomponent ceramics,which are promising in solving challenges posed by emerging technologies,shows grand difficulties because of the immense compositional space and complex local distortions.In this work,an accurate machine learning(ML)model built upon an ab initio database is developed to predict the mechanical properties and structural distortions of multicomponent transition metal carbides(MTMCs). 展开更多
关键词 carbides DISTORTION MULTICOMPONENT
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