C21 steroidal glycosides have been extensively reported for treating several types of cancer and are widely found in Marsdenia tenacissima. In this study, a C21 fraction was synthesized from M. tenacissima, and its anti-cancer potency was assessed against in vitro gastric cell lines BGC-823, SGC-7901, and AGS. Significant growth inhibition and cell cycle arrest were observed in C21 fraction-treated gastric cancer cells. The results of apoptotic staining techniques in C21 fraction-treated gastric cells were confirmed with excess reactive oxygen species generation. Moreover, SOD and H2O2 levels were increased by C21 fraction, especially when combined with chloroquine (CQ). The apoptotic inducing potential of C21 fraction was also evidenced by upregulation of proapoptotic proteins cleaved-PARP and BAX and downregulation of antiapoptotic proteins Bcl-2 and p-AKT by western blot, especially in the presence of the autophagy inhibitor CQ. The results showed that the apoptosis of gastric cancer cells caused by C21 fraction was enhanced by inhibiting autophagy. The current findings reveal a new mechanism for the antitumor activity of C21 fraction on gastric cancer.
A Stackelberg congestion game (SCG) is a bilevel program in which a leader aims to maximize their own gain by anticipating and manipulating the equilibrium state at which followers settle by playing a congestion game. Large-scale SCGs are well known for their intractability and complexity. This study approaches SCGs through differentiable programming, which marries the latest developments in machine learning with conventional methodologies. The core idea centers on representing the lower-level equilibrium problem using an evolution path formed by the imitative logit dynamics. It enables the use of automatic differentiation over the evolution path towards equilibrium, leading to a double-loop gradient descent algorithm. We further show the fixation on the lower-level equilibrium may be a self-imposed computational obstacle. Instead, the leader may only look ahead along the followers' evolution path for a few steps, while updating their decisions in sync with the followers through a co-evolution process. The revelation gives rise to a single-loop algorithm that is more efficient in terms of both memory consumption and computation time. Through numerical experiments that cover a wide range of benchmark problems, we find the single-loop algorithm consistently strikes a good balance between solution quality and efficiency, outperforming not only the standard double-loop implementation but also other methods from the literature. Importantly, our results highlight both the wastefulness of "full anticipation" and the peril of "zero anticipation". If a quick-and-dirty heuristic is needed for solving a really large SCG, the proposed single-loop algorithm with a one-step look-ahead makes an ideal candidate.
Thin-walled structures subjected to internal or external pressure usually need to be reinforced with ribs. The design of ribs is generally based on experiences in engineering, and the results are often very conservative. In this paper, an approach for the rational design of reinforced ribs on thin-walled structures is proposed based on the limit load analysis method, maximizing the limit load of the reinforced thin-walled structure or minimizing the weight of the reinforced ribs. Firstly, the limit load numerical analysis was conducted to study rib forms at the continuous and discontinuous regions of the structure and find the rational ribs which provide the most effective reinforcement for the structure. Then, using the proposed rib forms, an engine test cabin was re-designed based on the limit load analysis to verify the feasibility and effects of the rib design. The engine test cabin after the redesign of the rib plate can reach 98% of the limit load of the original test cabin while the weight of reinforcing ribs is only 62% of the weight of the original ones, which means that the reinforcement design approach based on the limit load analysis method and the rib forms proposed in this paper is effective and feasible, and can achieve a structural lightweight design.
Glioma is the most common malignant tumor of the nervous system, which accounts for more than 45% of central nervous system tumors and seriously threatens our health. Because of high mortality rate, limitations, and many complications of traditional treatment methods, new treatment methods are urgently needed. β-Mangostin is a natural compound derived from the fruit of Garcinia mangostana L. and it has anticancer activity in several types of cancer cells. However, the antitumor effect of β-mangostin in glioma has not been clarified. Hence, this study aimed to investigate its therapeutic effects on gliomas.To study the effect of β-mangostin on glioma cells, cell viability assay, reactive oxygen species production, cell cycle, apoptosis, and mitochondrial membrane potential were evaluated in the C6 cell line in vitro. Immunofluorescence and Western blotting were used to analyze protein expression and phosphorylation to study its mechanism of action. A subcutaneous xenograft model was used to investigate the effect of β-mangostin on tumorigenesis in vivo.We found that β-mangostin can inhibit glioma cell growth and induce oxidative damage in vitro. In addition, it reduces the phosphorylated form levels of PI3K, AKT and mTOR. Furthermore, the phosphorylated form levels of PI3K, AKT and mTOR were increased after the PI3K inhibitor was added. In vivo experiments showed that β-mangostin can inhibit tumor growth as shown by its reduced size and weight.This study suggests that β-mangostin can inhibit cell proliferation and induce oxidative damage in cells. It is the first study to demonstrate that β-mangostin induces oxidative damage in glioma cells by inhibiting the PI3K/AKT/mTOR signaling pathway.
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