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Exosomes are indispensable for intercellular communications. Tumor microenvironment (TME) is the living environment of tumor cells, which is composed of various components, including immune cells. Based on TME, immunotherapy has been recently developed for eradicating cancer cells by reactivating antitumor effect of immune cells. The communications between tumor cells and TME are crucial for tumor development, metastasis, and drug resistance. Exosomes play an important role in mediating these communications and regulating the reprogramming of TME, which affects the sensitivity of immunotherapy. Therefore, it is imperative to investigate the role of exosomes in TME reprogramming and the impact of exosomes on immunotherapy. Here, we review the communication role of exosomes in regulating TME remodeling and the efficacy of immunotherapy, as well as summarize the underlying mechanisms. Furthermore, we also introduce the potential application of the artificially modified exosomes as the delivery systems of antitumor drugs. Further efforts in this field will provide new insights on the roles of exosomes in intercellular communications of TME and cancer progression, thus helping us to uncover effective strategies for cancer treatment. [ABSTRACT FROM AUTHOR]

This article discusses the coordinated control problem of multiple high-speed trains operating under the virtual coupling mode. The study proposes a novel distributed model predictive control (DMPC) algorithm to address safety inter-train distance constraints and other independent constraints affecting train dynamics. The algorithm decomposes the centralized control problem into a sequence of local problems and considers potential hypothetical control policies among neighboring trains. The feasibility and effectiveness of the proposed algorithm are confirmed through theoretical analysis and numerical experiments. The article also discusses the modeling and control of high-speed trains operating under the virtual coupling mode, with a focus on designing control strategies that ensure speed consensus, maintain inter-train distances, and avoid collisions. A distributed model predictive control framework is proposed to handle the multiple constraints involved in the cooperative operation of the trains. The article presents a distributed model predictive control problem for coordinating the operation of high-speed trains in a virtual coupling mode. The problem is solved using a distributed serial iterative architecture to reduce communication requirements and increase robustness. The problem is converted into a series of smaller optimization problems that can be solved cooperatively based on information from adjacent trains. The feasibility of the optimization problems is proven, and the proposed approach is more practical for implementation. The article discusses a distributed control protocol for high-speed trains operating under the virtual coupling mode, aiming to achieve speed consensus and maintain safe distances between trains. The effectiveness of the control protocol is supported by a theorem and proof, and numerical simulations comparing the proposed protocol with other control policies are conducted. The simulations consider parameters [Extracted from the article]