Chondrosarcoma is the second most common form of bone cancer and is characterized by its ability to produce an extracellular matrix of the cartilage. High-grade chondrosarcoma is highly aggressive and can metastasize to other parts of the body. Chondrosarcoma is resistant to both conventional chemotherapy and radiotherapy; hence, the current main treatment is still surgical resection. Doxorubicin (Dox) has been shown to significantly improve patient survival compared with untreated chondrosarcoma. However, for patients with metastasis, surgical resection alone can hardly treat them. In addition, drug resistance is one of the leading causes of death in patients with chondrosarcoma. Secreted proteins can mediate cell-cell interactions in the cancer microenvironment, which may be associated with the development of drug resistance. In the present study, chondrosarcoma cells were treated with Dox, the conditioned medium was then collected and changes in secreted proteins were analyzed using the antibody array. Results showed that the Dox-treated group had the highest secretion of basic fibroblast growth factor (bFGF), indicating the effect of bFGF on Dox sensitivity in chondrosarcoma. Furthermore, lentiviral-mediated knockdown and treatment of exogenous recombinant protein were employed to further investigate the effect of bFGF on Dox resistance. Results demonstrated that bFGF can promote the expression of X-ray repair cross-complementing protein 5 (XRCC5), leading to Dox resistance. Secreted bFGF is likely to be detected in serum, in addition to being a biomarker for predicting Dox resistance, the combination of Dox and bFGF/XRCC5 blockers may be a new therapeutic strategy to improve the efficacy of Dox in future. 相似文献
Aim of the study: Parkinson’s disease (PD) is a neurodegenerative disorder. It is caused by the degeneration of dopaminergic neurons and the dopamine (DA) deletion in the substantia nigra pars compacta (SNpc). Morphine elevates the level of dopamine in the mesolimbic dopamine system and plays a role in alleviating PD symptoms. However, the molecular mechanism is still unclear. The aim of the study is to investigate the mechanism on morphine alleviating PD symptoms.
Materials and methods: The viability of PC12 cells was measured by using MTT assay. The expressions of tyrosine hydroxylase (TH), thioredoxin-1 (Trx-1), CyclinD1 and Cyclin-dependent kinase5 (Cdk5) were detected by Western Blot.
Results: In present study, we found that morphine increased the cell viability in PC12 cells. 1-methyl-4-phenylpyridi-nium (MPP+) reduced the cell viability and TH expression, which were reversed by morphine. MPP+ decreased the expressions of Trx-1, CyclinD1, Cdk5, which were restored by morphine. Moreover, the role of morphine in restoring the expressions of Trx-1, CyclinD1 and Cdk5 decreased by MPP+ was abolished by LY294002, phosphatidylinositol-3-kinase (PI3K)/Akt inhibitor.
Conclusions: These results suggest that morphine reverses effects induced by MPP þ through activating PI3K/Akt pathway. 相似文献
Resident and inflammatory macrophages are essential effectors of the innate immune system. These cells provide innate immune defenses and regulate tissue and organ homeostasis. In addition to their roles in diseases such as cancer, obesity and osteoarthritis, they play vital roles in tissue repair and disease rehabilitation. Macrophages and other inflammatory cells are recruited to tissue injury sites where they promote changes in the microenvironment. Among the inflammatory cell types, only macrophages have both pro-inflammatory(M1) and anti-inflammatory(M2) actions, and M2 macrophages have four subtypes. The co-action of M1 and M2 subtypes can create a favorable microenvironment, releasing cytokines for damaged tissue repair. In this review, we discuss the activation of macrophages and their roles in severe peripheral nerve injury. We also describe the therapeutic potential of macrophages in nerve tissue engineering treatment and highlight approaches for enhancing M2 cell-mediated nerve repair and regeneration. 相似文献
In the area of large-scale graph data representation and semi-supervised learning, deep graph-based convolutional neural networks have been widely applied. However, typical graph convolutional network (GCN) aggregates information of neighbor nodes based on binary neighborhood similarity (adjacency matrix). It treats all neighbor nodes of one node equally, which does not suppress the influence of dissimilar neighbor nodes. In this paper, we investigate GCN based on similarity matrix instead of adjacency matrix of graph nodes. Gaussian heat kernel similarity in Euclidean space is first adopted, which is named EGCN. Then biologically inspired manifold similarity is trained in reproducing kernel Hilbert space (RKHS), based on which a manifold GCN (named MGCN) is proposed for graph data representation and semi-supervised learning with four different kernel types. The proposed method is evaluated with extensive experiments on four benchmark document citation network datasets. The objective function of manifold similarity learning converges very quickly on different datasets using various kernel functions. Compared with state-of-the-art methods, our method is very competitive in terms of graph node recognition accuracy. In particular, the recognition rates of MGCN (Gaussian kernel) and MGCN (Polynomial Kernel) outperform that of typical GCN about 3.8% on Cora dataset, 3.5% on Citeseer dataset, 1.3% on Pubmed dataset and 4% on Cora_ML dataset, respectively. Although the proposed MGCN is relatively simple and easy to implement, it can discover local manifold structure by manifold similarity learning and suppress the influence of dissimilar neighbor nodes, which shows the effectiveness of the proposed MGCN.
