BackgroundCordycepin, the main active ingredient of a traditional Chinese herbal remedy – extracted from Cordyceps sinensis – has been demonstrated as a very effective anti-inflammatory and antitumor drug. The present study investigated its antitumor effect on pancreatic cancer, a highly aggressive cancer with extremely poor prognosis due to malignancy, and clarified its underlying mechanism both in vitro and in vivo.MethodsThe antitumor viability of cordycepin on human pancreatic cancer MIAPaCa-2 and Capan-1 cells was determined by colony formation assays. Annexin V/PI double staining and flow cytometry assay were used to investigate whether cordycepin induced apoptosis and cell cycle arrest. The mitochondrial membrane potential (ΔΨm) was analyzed by Rhodamine 123 staining, and expression of related proteins evaluated by Western blot and immunohistochemistry, both on pancreatic cancer cells and tumor xenografts to reveal the potential mechanism for the effect of cordycepin. Furthermore, the in vivo efficacy was examined on nude mice bearing MIAPaCa-2 cell tumors treated by intraperitoneal injection of cordycepin (0, 15, and 50 mg/kg/d) for 28 days.ResultsCordycepin inhibited cell viability, proliferation and colony formation ability and induced cell cycle arrest and early apoptosis of human pancreatic cancer cells (MIAPaCa-2 and Capan-1) in a dose- and time-dependent manner. The same effect was also observed in vivo. Decrease of ΔΨm and upregulation of Bax, cleaved caspase-3, cleaved caspase-9, and cleaved PARP as well as downregulation of Bcl-2 both in vitro and in vivo indicated that the mitochondria-mediated intrinsic pathway was involved in cordycepin’s antitumor effect.ConclusionOur data showed that cordycepin inhibited the activity of pancreatic cancer both in vitro and in vivo by regulating apoptosis-related protein expression through the mitochondrial pathway and suggest that cordycepin may be a promising therapeutic option for pancreatic cancer.

This paper proposes a new approach to the multi-robot map fusion algorithm that enables a team of robots to build a joint map without initial knowledge of their relative pose. First, the relative distance and bearing measurements between two robots are fused together by the covariance intersection method after they detect each other. Second, the transformation equations among multi robots coordinates are derived based on their relative distance and bearing measurements. Third, all the multi robots local maps are merged into one global map by unscented transform based on the transformation equations. Fourth, the possible duplicate features are filtered out by the robots maximal detection area and the features coordinate range, then the Mahalanobis distance is computed to decide the duplicate features correspondence through unscented transform, and the Kalman Filter is used while fusing the duplicate features information. As a means of validation for the proposed method, experimental results obtained from the two robots are presented.