This study demonstrated that LPA levels in plasma and ascites may be useful diagnostic biomarkers for PC of gastric cancer and that higher levels are associated with poor prognosis.
Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a heterogeneous disease with different clinical characteristics and different treatment responsiveness. The aims of this study were to compare the nasal fluid cytology and cytokines between eosinophilic CRSwNP (eCRSwNP) and non-eosinophilic CRSwNP (neCRSwNP) and establish a new multivariate model to predict eCRSwNP before surgery to improve personalized treatment for CRSwNP patients.Methods: Eighty-six consecutive patients with CRSwNP and sixteen healthy controls were recruited in this study. Nasal fluid (NF) was collected from all subjects and nasal polyp tissue was collected during the surgery. The differential cell counts and concentrations of IL-6, IL-8, TNF-α and IL-10 in NF were measured. Univariate and multivariate logistic regression were used to identify predictors for eCRSwNP.Results: There were more inflammatory cells in NF of CRSwNP than controls. The eosinophil percentage was significantly higher in eCRSwNP than neCRSwNP and controls. The level of IL-8 was significantly higher in neCRSwNP than in eCRSwNP and controls.Blood eosinophilia, nasal fluid eosinophilia, higher total ethmoid score / total maxillary score (E/M ratio) and higher visual analogue scale (VAS) score of CRS were associated with eCRSwNP, the area under receiver operating characteristic curve (AUC) was 0.800, 0.755, 0.703 and 0.648, respectively. Using the coefficients of multivariate regression, we set up a scoring system to predict eCRSwNP with three of the variates and the AUC was 0.883.
Conclusion:ECRSwNP, neCRSwNP and healthy controls demonstrated different cytology and cytokine profiles in NF. A new preoperational multivariate prediction model for eCRSwNP with NF eosinophilia, blood eosinophilia and higher E/M ratio was established.
Purpose. Dioscorea nipponica Makino (DNM) is a traditional herb with multiple medicinal functions. This study is aimed at exploring the therapeutic effects of DNM on asthma and the underlying mechanisms involving RKIP-mediated MAPK signaling pathway. Methods. An ovalbumin-induced asthma model was established in mice, which was further administrated with DNM and/or locostatin (RKIP inhibitor). ELISA was performed to detect the serum titers of OVA-IgE and OVA-IgG1, bronchoalveolar lavage fluid (BALF) levels of inflammation-related biomarkers, and tissue levels of oxidative stress-related biomarkers. The expression of RKIP was measured by quantitative real-time PCR, Western blot, immunohistochemistry, and immunofluorescence. HE staining was used to observe the pathological morphology of lung tissues. The protein expression of MAPK pathway-related proteins was detected by Western blot. Results. Compared with the controls, the model mice exhibited significantly higher serum titers of OVA-IgE and OVA-IgG1, BALF levels of IL-6, IL-8, IL-13, TGF-β1, and MCP-1, tissue levels of MDA and ROS, lower BALF levels of IL-10 and IFN-γ, and tissue level of GSH. DNM relieved the allergic inflammatory response and oxidative stress in the model mice. DNM also recovered the downregulation of RKIP and the pathological injury of lung tissues in asthma mice. In addition, the Raf-1/MEK/MAPK/ERK pathway in the model mice was blocked by DNM. Silencing of RKIP by locostatin weakened the relieving effects of DNM on asthma through activating the Raf-1/MEK/MAPK/ERK pathway. Conclusion. DNM relieves asthma via blocking the Raf-1/MEK/MAPK/ERK pathway that mediated by RKIP upregulation.
Background. In this study, network pharmacological methods were used to analyze the targets of Rhizoma Dioscoreae Nipponicae (RDN) and investigate the potential underlying mechanism of RDN in the treatment of asthma. Methods. Asthma-related targets were obtained from the GeneCards and DisGeNET databases. The bioactive components of RDN were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database, and the targets of these compounds were predicted using the BATMAN-TCM database. The network of RDN component targets was constructed using Cytoscape. A protein-protein interaction (PPI) network was constructed in Cytoscape to determine the potential targets of RDN for the treatment of asthma. The hub genes of RDN in the treatment of asthma were screened using network topological parameters. Gene ontology (GO) and the KEGG pathways were analyzed. Molecular docking and in vivo experiments were performed to validate the network pharmacology results. Results. A total of four bioactive components and 55 targets were identified. The results of the enrichment analysis suggested that the treatment of asthma with RDN involved signaling pathways, such as those related to systemic lupus erythematosus, alcoholism, viral carcinogenesis, the cell cycle, prostate cancer, transcriptional misregulation in cancer, hepatitis B, thyroid hormone signaling, and PI3K-AKT signaling, as well as other signaling pathways. Molecular docking showed that the active components of RDN could stably bind to the predicted target. In vivo experiments showed that RDN could regulate the expression of target genes and inhibit the activation of the PI3K-AKT signaling pathway. Conclusion. To a certain extent, this study reveals the potential bioactive components and molecular mechanisms of RDN in the treatment of asthma and provides new insights for the development of new drugs for asthma.
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