Lev/MSNs/n-HA/PU has been proved to be a novel scaffold material to treat bone defect caused by chronic osteomyelitis. We have previously identified that this material can effectively treat chronic osteomyelitis caused by Staphylococcus aureus in vivo . However, the potential mechanisms of antibacterial and osteogenic induction properties remain unclear. Thus, for osteogenesis property, immunohistochemistry, PCR, and Western blot were performed to detect the expression of osteogenic markers. Furthermore, flow cytometry and TUNEL were applied to analyze MC3T3-E1 proliferation and apoptosis. For antibacterial property, the material was co-cultivated with bacteria, bacterial colony forming units was counted and the release time of the effective levofloxacin was assayed by agar disc-diffusion test. Moreover, scanning electron microscope was applied to observe adhesion of bacteria. In terms of osteogenic induction, we found BMSCs adherently grew more prominently on Lev/MSNs/n-HA/PU. Lev/MSNs/n-HA/PU also enhanced the expression of osteogenic markers including OCN and COL1α1, as well as effectively promoted the transition from G1 phase to G2 phase. Furthermore, Lev/MSNs/n-HA/PU could reduce apoptosis of MC3T3-E1. Besides, both Lev/MSNs/n-HA/PU and n-HA/PU materials could inhibit bacterial colonies, while Lev/MSNs/n-HA/PU possessed a stronger antibacterial activities, and lower bacterial adhesion than n-HA/PU. These results illustrated that Lev/MSNs/n-HA/PU composite scaffold possess favorable compatibility in vitro , which induce osteogenic differentiation of MSCs, promote proliferation and differentiation of MC3T3-E1, and inhibit apoptosis. Moreover, clear in vitro antibacterial effect of Lev/MSNs/n-HA/PU was also observed. In summary, this study replenishes the potential of Lev/MSNs/n-HA/PU composite scaffold possess dual functions of anti-infection and enhanced osteogenesis for future clinical application.
The China–Africa Community with Shared Benefits is the cornerstone of the China-Africa Community with Shared Future. Since the beginning of the twenty-first century, through economic and trade cooperation, China and Africa have promoted the common economic and social development of both sides, and consolidated the material foundation of the China–Africa Community with Shared Benefits. The economic and trade cooperation between China and Africa has developed rapidly with remarkable achievements and great influence. This article fully affirms and reviews the great achievements of China–Africa trade and economic cooperation, points out that the China–Africa economic and trade cooperation still faces some challenges, but overall, the China–Africa economic and trade cooperation has an absolutely bright future and will become a persistence engine to build the Community with Shared Benefits. China's investment will further promote economic and social development in Africa, and the China–Africa Community with Shared Benefits will have a huge demonstration effect internationally.
In order to build an aeroengine on-board model with full envelope, full state, high accuracy and high real-time, a modeling method based on flight data is proposed. This method builds state variable model based on component level model; Considering the influence of Reynolds number, power extraction, air bleed and other factors, the steady state model of the on-board model is modified based on regression analysis using flight data to reduce the modeling error caused by individual engine differences; At the same time, in order to compensate the residual steady-state error, a steady-state error model based on Gaussian mixture model neural network (GMM-NN) is established; Considering the need to reconstruct the speed sensor, the speed signal can not be used as the scheduling variable to build a new scheduling variable, which has less dynamic error compared to taking fuel as the scheduling variable. Compared with the traditional model, the input of this model is only control variables and flight conditions, and it can reconstruct the signals of speed, pressure, temperature and other sensors. At the same time, it has the advantages of simple structure, no iterative calculation and high accuracy. Compared with flight data, the maximum dynamic error of compressor outlet total pressure of the new scheduling variable model is 3.564%, which is 4.13 times higher than the maximum relative error of 14.735% of the fuel scheduling model; In the verification of multi flight data, the average errors of LP rotor speed, HP rotor speed, compressor outlet total pressure and LP turbine outlet total temperature are 0.52%, 0.39%, 0.53% and 0.9% respectively, meeting the accuracy requirements of the project.
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