No abstract

Stromal cell-derived factor 1alpha (SDF-1alpha) (CXCL12) has been observed to enhance tumor angiogenesis. However, the comprehensive role of SDF-1alpha (CXCL12)-CXCR4 interaction, exerted during angiogenesis, has not been well understood. We have previously demonstrated that human basal cell carcinoma (BCC) tissues and a BCC cell line (BCC-1/KMC) had significant expression of CXCR4, whose level was higher in invasive than in the non-invasive BCC types. Here, we observed that human BCC tissues with high expression levels of CXCR4 had higher vascularity. Further, among the 71 BCCs diagnosed between the years 2004-2005, BCCs with high CXCR4 expression had concomitantly higher microvessel density, as compared with those with low CXCR4 expression (P < 0.001). We found that SDF-1alpha induced angiogenic activity in human BCC cells, both in vitro and in vivo. SDF-1alpha significantly upregulated several angiogenesis-associated genes such as interferon-alpha-inducible protein 27, interleukin (IL)-6, bone morphogenetic protein (BMP)-6, SOCS2 and cyclooxygenase 2 (COX)-2 in human BCC cells. Among them, IL-6 was the earliest and highest upregulated gene whose induction was observed within 6 h of the commencement of SDF-1alpha-CXCR4 interaction. The mechanisms behind the SDF-1alpha-induced time and dose-dependent upregulation of messenger RNA expression and protein secretion of IL-6 were investigated. The transcriptional regulation of IL-6 by SDF-1alpha was mediated by phosphorylation of extracellular signal-related kinase 1/2 and activation of the nuclear factor-kappaB complex. The identification of the angiogenic profiles induced through SDF-1alpha-CXCR4 interactions in human BCC cells may contribute further insights into the mechanisms involved in the angiogenic potential of SDF-1alpha (CXCL12).

We explored the potential association rules within acupoints in treating diabetic gastroparesis (DGP) using Apriori algorithm complemented with another partition-based algorithm, a frequent pattern growth algorithm. Apriori algorithm is a data mining-based analysis that is widely applied in various fields, such as business and medicine, to mine frequent patterns in datasets. To search for effective acupoint combinations in the treatment of DGP, we implemented Apriori algorithm to investigate the association rules of acupoints among 17 randomized controlled trials (RCTs). The acupoints were extracted from the 17 included RCTs. In total, 29 distinct acupoints were observed in the RCTs. The top 10 frequently selected acupoints were CV12, ST36, PC6, ST25, BL21, BL20, BL23, SP6, BL18, and ST21. The frequency pattern of acupoints achieved by using a frequent pattern growth algorithm also confirms the result. The results showed that the most associated rules were {BL23, BL18} ≥ {SP6}, {BL20, BL18} ≥ {PC6}, {PC6, BL18} ≥ {BL20}, and {SP6, BL18} ≥ {BL23} in the database. Acupoints, including BL23, BL18, SP6, BL20, and PC6, can be deemed as core elements of acupoint combinations for treating DGP.