Extraction and Analysis of Coronal High-temperature Components Based on Outlier Detection

The extraction of high-temperature regions in active regions(ARs)is an important means to help understand the mechanism of coronal heating.The important observational means of high-temperature radiation in ARs is the main emission line of Fe XVⅢin the 94?of the Atmospheric Imaging Assembly.However,the diagnostic algorithms for Fe XVⅢ,including the differential emission measure(DEM)and linear diagnostics proposed by Del based on the DEM,have been greatly limited for a long time,and the results obtained are different from the predictions.In this paper,we use the outlier detection method to establish the nonlinear correlation between 94?and 171,193,211?based on the former researches by others.A neural network based on 171,193,211?is constructed to replace the low-temperature emission lines in the ARs of 94?.The predicted results are regarded as the low-temperature components of 94?,and then the predicted results are subtracted from 94?to obtain the outlier component of 94?,or Fe XVⅢ.Then,the outlier components obtained by neural network are compared with the Fe XVⅢobtained by DEM and Del's method,and a high similarity is found,which proves the reliability of neural network to obtain the high-temperature components of ARs,but there are still many differences.In order to analyze the differences between the Fe XVⅢobtained by the three methods,we subtract the Fe XVⅢobtained by the DEM and Del's method from the Fe XVⅢobtained by the neural network to obtain the residual value,and compare it with the results of Fe XIV in the temperature range of 6.1-6.45 MK.It is found that there is a great similarity,which also shows that the Fe XVⅢobtained by DEM and Del's method still has a large low-temperature component dominated by Fe XIV,and the Fe XVⅢobtained by neural network is relatively pure.

HPV16 E6 gene mutation promotes the proliferation of cervical cancer cells by regulating the expression of BDNF/TrKB

Objective:Study on the mechanism of HPV16 E6 gene mutation promoting the proliferation of cervical cancer cells by influencing the expression of BDNF/TrkB.Methods:The expression levels of HPV16 E6 T350G,BDNF,TrkB and p53 mRNA in cervical cancer tissue samples and CINII cervical tissues were detected by Real-time PCR.HPV16 E6 T350G lentivirus(pLV5-HPV16 E6 T350G)and empty vector(pLV5-vector)were designed and constructed,and transfected with HCerEpiC cells,the expression levels of HPV16 E6 T350G,BDNF,TrKB and p53 mRNA were detected by Real-time PCR,and the expression levels of BDNF,TrKB,PI3K,pPI3K,AKT and pAKT protein were detected by western blot;cell proliferation was detected by MTT experiments.Results:Compared with cinii cervical tissue,HPV16 E6 T350G,BDNF and TrkB mRNA expression levels were all positive,while p53 mRNA expression was negative.After overexpression of HPV16 E6 T350G in HCerEpiC cells,it can up-regulate the expression levels of BDNF and TrKB protein and mRNA,and activate the PI3K/AKT signaling pathway which is the downstream of BDNF/TrKB,and reduce p53 protein expression levels;HPV16 E6 T350G overexpression can enhance the proliferation capacity of HCerEpiC cells.Conclusion:Overexpression of HPV16 E6 T350G can promote the proliferation of cervical cancer cells,which may be related to the upregulation of BDNF/TrKB expression,the activation of PI3K/AKT signaling pathway,and the decrease of p53 expression.