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Objectives: The most common cause of osteosarcoma (OS) death is lung metastasis. Currently, doxorubicin is the primary chemotherapy drug used to treat OS, however, it is not effective in inhibiting metastasis, and it has obvious cardiotoxicity. The anticancer activity of ginsenoside Rg3 has been demonstrated in a variety of malignant tumours. The aim of this study was to determine the potential role of ginsenoside Rg3 and doxorubicin in OS and the possible mechanism. Methods: The potential synergistic effects of ginsenoside Rg3 and doxorubicin on human osteosarcoma cells 143B and U2OS, human umbilical vein endothelial cells, and mice receiving 143B xenografts and lung metastases were investigated. Key findings: Our study demonstrated that the combination of ginsenoside Rg3 and doxorubicin significantly inhibited cell proliferation, metastasis and angiogenesis in vitro. Mechanically, the anti-tumour activity of ginsenoside Rg3 and doxorubicin by modulating mTOR/HIF-1α/VEGF and EMT signalling pathways. Furthermore, ginsenoside Rg3 combined with doxorubicin inhibits tumour growth and lung metastasis in 143B-derived murine osteosarcoma models. More importantly, ginsenoside Rg3 can effectively ameliorate doxorubicin-induced weight loss and cardiotoxicity in mice. Conclusions: Consequently, we concluded that the combination of ginsenoside Rg3 and doxorubicin displayed an evidently synergistic effect, which has the potential to be used as an effective and safe therapeutic approach for OS treatment. [ABSTRACT FROM AUTHOR]

Microkinetic modeling has drawn increasing attention for quantitatively analyzing catalytic networks in recent decades, in which the speed and stability of the solver play a crucial role. However, for the multi-step complex systems with a wide variation of rate constants, the often encountered stiff problem leads to the low success rate and high computational cost in the numerical solution. Here, we report a new efficient sensitivity-supervised interlock algorithm (SSIA), which enables us to solve the steady state of heterogeneous catalytic systems in the microkinetic modeling with a 100% success rate. In SSIA, we introduce the coverage sensitivity of surface intermediates to monitor the low-precision time-integration of ordinary differential equations, through which a quasi-steady-state is located. Further optimized by the high-precision damped Newton's method, this quasi-steady-state can converge with a low computational cost. Besides, to simulate the large differences (usually by orders of magnitude) among the practical coverages of different intermediates, we propose the initial coverages in SSIA to be generated in exponential space, which allows a larger and more realistic search scope. On examining three representative catalytic models, we demonstrate that SSIA is superior in both speed and robustness compared with its traditional counterparts. This efficient algorithm can be promisingly applied in existing microkinetic solvers to achieve large-scale modeling of stiff catalytic networks. [ABSTRACT FROM AUTHOR]

As an effective method to analyze complex catalytic reaction networks, microkinetic modeling is gaining increasing popularity in the catalytic activity evaluation and rational design of heterogeneous catalysts. An automated simulator with stable and reliable performance is especially useful and in great request. Here we introduce the CATKINAS package developed for large‐scale microkinetic modeling and analysis. Featuring with a multilevel solver and a multifunctional analyzer, CATKINAS can provide both accurate solutions and various quantitative and automatic analysis for a wide range of catalytic systems. The structure and the basic workflow are overviewed with the multilevel solver particularly illustrated. Also, we take the CO methanation reaction as an example to illustrate the application and efficiency of the CATKINAS package. [ABSTRACT FROM AUTHOR]

Understanding the reconstruction kinetics of solid surfaces involving an ensemble of atomic movements is practically important but challenging due to the complexity of high-dimensional potential energy surfaces. Herein, we develop a step-deciding technique incorporated with the nudged elastic band method, which enables multidirection pathway sampling and ensures the capture of a minimum energy path (MEP). Using this approach, the (2×1) reconstruction mechanism of a rutile-TiO 2 (011) surface, a classic and long-standing open problem in the fields of surface science and heterogeneous catalysis, is quantified, and the MEP is explicitly identified and explained. Following the least-bond-breaking rule, it gives a stepwise Ti-O bond cleavage mechanism with a collection of decoupled local structural relaxation modes at an overall barrier of 1.25 eV critically affected by initial Ti-O bond opening, which is much lower than the common synergy mechanism. Moreover, the adsorption-induced reconstruction is rationalized considering practical reaction conditions, where H atom adsorbate is shown to effectively stabilize the labile one-fold O 1c intermediate and promote the reconstruction kinetics. This work reveals the reconstruction mechanism regarding multiatom movements and provides a general method for the structural exploration of other complicated systems.