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Tanshinone IIA (Tan II A) is widely used in the treatment of cardiovascular diseases as an active component of Salvia miltiorrhiza Bunge. It has been demonstrated to have pleiotropic effects for atherosclerosis. From the anti-inflammatory and immunomodulatory mechanism perspective, this paper reviewed major progresses of Tan IIA in antiatherosclerosis research, including immune cells, antigens, cytokines, and cell signaling pathways. [ABSTRACT FROM AUTHOR]

The dendritic cell ( DC) lineage is remarkably heterogeneous. It has been postulated that specialized DC subsets have evolved in order to select and support the multitude of possible T cell differentiation pathways. However, defining the function of individual DC subsets has proven remarkably difficult, and DC subset control of key T cell fates such as tolerance, T helper cell commitment and regulatory T cell induction is still not well understood. While the difficulty in assigning unique functions to particular DC subsets may be due to sharing of functions, it may also reflect a lack of appropriate physiological in-vivo models for studying DC function. In this paper we review the limitations associated with many of the current DC models and highlight some of the underlying difficulties involved in studying the function of murine DC subsets. [ABSTRACT FROM AUTHOR]

Simple Summary: Osteosarcoma is the most common primary bone tumor and has a poor prognosis. Therefore, it is important to understand the mechanism of the development of osteosarcoma to overcome therapy resistance. Several mathematical models have been developed to study the initiation and progression of many cancer types. However, there are currently no mathematical models for the progression of osteosarcoma, to the best of our knowledge. In this work, we develop a data-driven mathematical model to analyze the impact of the immune cell interactions on the growth of osteosarcoma tumors that have distinct immune patterns. Our model provides a foundation for investigating the effect of various treatments on the dynamics of key players in the primary tumor, including immune cells and cytokines, and ultimately the whole tumor. As the immune system has a significant role in tumor progression, in this paper, we develop a data-driven mathematical model to study the interactions between immune cells and the osteosarcoma microenvironment. Osteosarcoma tumors are divided into three clusters based on their relative abundance of immune cells as estimated from their gene expression profiles. We then analyze the tumor progression and effects of the immune system on cancer growth in each cluster. Cluster 3, which had approximately the same number of naive and M2 macrophages, had the slowest tumor growth, and cluster 2, with the highest population of naive macrophages, had the highest cancer population at the steady states. We also found that the fastest growth of cancer occurred when the anti-tumor immune cells and cytokines, including dendritic cells, helper T cells, cytotoxic cells, and IFN- γ , switched from increasing to decreasing, while the dynamics of regulatory T cells switched from decreasing to increasing. Importantly, the most impactful immune parameters on the number of cancer and total cells were the activation and decay rates of the macrophages and regulatory T cells for all clusters. This work presents the first osteosarcoma progression model, which can be later extended to investigate the effectiveness of various osteosarcoma treatments. [ABSTRACT FROM AUTHOR]