[Progress in antitumor activity of diterpenoid alkaloids in plants of Aconitum].

Small-molecule compounds with rich sources have diverse structures and activities. The active ingredients in traditional Chinese medicine(TCM) provide new sources for the discovery of new antitumor drugs. Aconitum plants as Chinese medicinal plants have the effects of dispelling wind, removing dampness, warming meridian, and relieving pain. They are mainly used to treat inflammation, pain, rheumatism, and tumors, improve heart function, and dilate blood vessels in clinical practice. Diterpenoid alkaloids are the main active components of Aconitum plants, including C20-, C19-, C18-diterpenoid alkaloids and bis-diterpenoid alkaloids. Stu-dies have demonstrated that diterpenoid alkaloids can effectively treat lung cancer, liver cancer, breast cancer, colon cancer and other cancers. Diterpenoid alkaloids are considered as the most promising natural compounds against cancers. In this review, we summarized the chemical structures and antitumor activities of C20-, C19-, C18-diterpenoid alkaloids and bis-diterpenoid alkaloids extracted from plants of Aconitum, aiming to provide reference for further development of diterpenoid alkaloids from Aconitum as antitumor drugs.

[Association of liver damage with coronary artery lesion and no response to intravenous immunoglobulin in the acute stage of Kawasaki disease]. / å·å´Žç— æ€¥æ€§æœŸè‚æŸå®³ä¸Žå† çŠ¶åŠ¨è„‰æŸä¼¤å’Œå ç–«çƒè›‹ç™½æ— ååº”çš„å ³ç³».

OBJECTIVES: To summarize the clinical features of liver damage in children in the acute stage of Kawasaki disease (KD), and to investigate the clinical value of liver damage in predicting coronary artery lesion and no response to intravenous immunoglobulin (IVIG) in children with KD. METHODS: The medical data were collected from 925 children who were diagnosed with KD for the first time in Beijing Children's Hospital from January 1, 2016 to December 31, 2017. According to the presence or absence of abnormal alanine aminotransferase (ALT) level on admission, the children were divided into a liver damage group (n=284) and a non-liver damage group (n=641). A logistic regression analysis was used to investigate the clinical value of the indicators including liver damage in predicting coronary artery lesion and no response to IVIG in children with KD. RESULTS: Compared with the non-liver damage group, the liver damage group had a significantly earlier admission time and significantly higher serum levels of inflammatory indicators (P<0.05). The liver damage group had a significantly higher incidence rate of coronary artery lesion on admission than the non-liver damage group (P=0.034). After initial IVIG therapy, the liver damage group had a significantly higher proportion of children with no response to IVIG than the non-liver damage group (P<0.001). In children with KD, coronary artery lesion was associated with the reduction in the hemoglobin level and the increases in platelet count, C-reactive protein, and ALT (P<0.05), and no response to IVIG was associated with limb changes, the reduction in the hemoglobin level, the increases in platelet count, C-reactive protein, and ALT, and coronary artery lesion (P<0.05). CONCLUSIONS: Compared with those without liver damage, the children in the early stage of KD with liver damage tend to develop clinical symptoms early and have higher levels of inflammatory indicators, and they are more likely to have coronary artery lesion and show no response to IVIG treatment.

Performance analysis of adaptive optics with a phase retrieval algorithm in orbital-angular-momentum-based oceanic turbulence links.

Recently, orbital angular momentum (OAM) beams have been applied in underwater optical communication (UWOC) to build a high-capacity communication link. However, a wave-front-sensitive OAM beam suffers significant distortion due to oceanic turbulence (OT), resulting in considerable intermodal crosstalk that degrades the UWOC performance. Herein, we propose and demonstrate an adaptive optics (AO)-based correction approach with a phase retrieval algorithm (PRA) to compensate for the distorted OAM beams induced by OT. In a simulation, an OT model with the random phase screen method is utilized. Two PRAs, the Gerchberg-Saxton algorithm (GSA) and the hybrid input-output algorithm (HIOA), are utilized to reconstruct the distorted phase-front of the OAM beam. The simulation results illustrate that the PRA-based AO approach can effectively compensate for the distorted OAM beam and improve the bit error rate performance in an oceanic channel. Additionally, the compensation performance of HIOA-based AO is superior to that of GSA-based AO in terms of convergence performance. This work verifies the feasibility and validity of a PRA-based AO approach in underwater turbulence optical communication and provides new insights into the OAM underwater communication system.

Prediction of lung cancer based on serum biomarkers by gene expression programming methods.

In diagnosis of lung cancer, rapid distinction between small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) tumors is very important. Serum markers, including lactate dehydrogenase (LDH), C-reactive protein (CRP), carcino-embryonic antigen (CEA), neurone specific enolase (NSE) and Cyfra21-1, are reported to reflect lung cancer characteristics. In this study classification of lung tumors was made based on biomarkers (measured in 120 NSCLC and 60 SCLC patients) by setting up optimal biomarker joint models with a powerful computerized tool - gene expression programming (GEP). GEP is a learning algorithm that combines the advantages of genetic programming (GP) and genetic algorithms (GA). It specifically focuses on relationships between variables in sets of data and then builds models to explain these relationships, and has been successfully used in formula finding and function mining. As a basis for defining a GEP environment for SCLC and NSCLC prediction, three explicit predictive models were constructed. CEA and NSE are frequently- used lung cancer markers in clinical trials, CRP, LDH and Cyfra21-1 have significant meaning in lung cancer, basis on CEA and NSE we set up three GEP models-GEP 1(CEA, NSE, Cyfra21-1), GEP2 (CEA, NSE, LDH), GEP3 (CEA, NSE, CRP). The best classification result of GEP gained when CEA, NSE and Cyfra21-1 were combined: 128 of 135 subjects in the training set and 40 of 45 subjects in the test set were classified correctly, the accuracy rate is 94.8% in training set; on collection of samples for testing, the accuracy rate is 88.9%. With GEP2, the accuracy was significantly decreased by 1.5% and 6.6% in training set and test set, in GEP3 was 0.82% and 4.45% respectively. Serum Cyfra21-1 is a useful and sensitive serum biomarker in discriminating between NSCLC and SCLC. GEP modeling is a promising and excellent tool in diagnosis of lung cancer.