1.Preparation of the polyclonal antibodies of CDPK 5 gene from toxoplasma gondii and the identification of its functions
Liangyin ZHONG ; Simin LIU ; Zhihua ZENG ; Xiaosong XU ; Hanwei LU ; Wenchao ZHOU ; Yanting HUANG ; Jinghui LU ; Sicong CHEN
Chongqing Medicine 2016;45(16):2182-2185
Objective Screening the immune polypeptide sequence of toxoplasma (Tg) CDPK5 gene ,which were synthesized and then immunized the New Zealand white rabbit to prepare antiserum ,and identification its function .Methods Bioinformatics a‐nalysis was used to determine the immune peptide of Tg CDPK5 sequence ,which were artificially synthesized to immune white rab‐bit to prepare antiserum .The titers of antibodies were determined by ELISA and the polyclonal antibodies were verified with CD‐KP5 antigen by Western blot .The sub‐cellular localization of Tg CDPK 5 were obtained by immunofluorescence assay .Results 17 bp peptide sequence from the Tg CDPK5 N‐terminal were chosen as immune polypeptide by bioinformatics analysis .Synthetic pep‐tide were used to immune rabbit to obtain polyclonal antiserum .The result showed that the titer of the obtained ployantibody were 1∶640 000 ;Western blot demonstrated that the antiserum could specifically recognize Tg CDPK 5(75 .4 × 103 );Immunofluores‐cence assay revealed this antibody could specifically recognize the endogenous Tg CDPK 5 of Toxoplasma gondii .Conclusion Ac‐cording to the analysis of Tg CDPK5 sequence information ,this study successful obtained Tg CDPK5 polyclonal antibody .
2.Mechanism of Aurora-A to promote chemoresistance in nasopharyngeal carcinoma
Xiaoqin FAN ; Jian SONG ; Yujie WANG ; Hanwei WU ; Lu LU ; Guohui NIE
Chinese Archives of Otolaryngology-Head and Neck Surgery 2019;26(1):5-8
OBJECTIVE To explore the mechanism of Aurora kinase A (Aurora-A) promoting cancer cell chemotherapy resistance in nasopharyngeal carcinoma. METHODS The expression of Aurora-A in nasopharyngeal carcinoma tissues and adjacent tissues were detected by Western bolt and Q-PCR. The highexpressing Aurora A cell line CNE2 was used to detected the cell apoptosis and the expression of key pathway marker protein after Aurora-A inhibitor VX680 and cisplatin treatment by using Flow cytometry and WB. RESULTS The expression of Aurora-A in nasopharyngeal carcinoma tissues was significantly higher than that in adjacent tissues. Comparing to normal nasopharyngeal cells NP69, Aurora-A was significantly highly expressed in all of nasopharyngeal carcinoma cells and was highest in CNE2. Inhibiton of Aurora-A increased the cell apoptosis and the expression of p-AKT, p21 and Cleaved-Caspase-3 after using cisplatin or the Aurora-A inhibitor VX680 treatment. CONCLUSION The results shown that Aurora-A confer chemoresistance to cisplatin treatment through p-AKT/p21/Cleaved-Caspase-3 pathway.
3.Diagnosis of nasopharyngeal carcinoma with convolutional neural network on narrowband imaging.
Jingjin WENG ; Jiazhang WEI ; Yunzhong WEI ; Zhi GUI ; Hanwei WANG ; Jinlong LU ; Huashuang OU ; He JIANG ; Min LI ; Shenhong QU
Journal of Clinical Otorhinolaryngology Head and Neck Surgery 2023;37(6):483-486
Objective:To evaluate the diagnostic accuracy of the convolutional neural network(CNN) in diagnosing nasopharyngeal carcinoma using endoscopic narrowband imaging. Methods:A total of 834 cases with nasopharyngeal lesions were collected from the People's Hospital of Guangxi Zhuang Autonomous Region between 2014 and 2016. We trained the DenseNet201 model to classify the endoscopic images, evaluated its performance using the test dataset, and compared the results with those of two independent endoscopic experts. Results:The area under the ROC curve of the CNN in diagnosing nasopharyngeal carcinoma was 0.98. The sensitivity and specificity of the CNN were 91.90% and 94.69%, respectively. The sensitivity of the two expert-based assessment was 92.08% and 91.06%, respectively, and the specificity was 95.58% and 92.79%, respectively. There was no significant difference between the diagnostic accuracy of CNN and the expert-based assessment (P=0.282, P=0.085). Moreover, there was no significant difference in the accuracy in discriminating early-stage and late-stage nasopharyngeal carcinoma(P=0.382). The CNN model could rapidly distinguish nasopharyngeal carcinoma from benign lesions, with an image recognition time of 0.1 s/piece. Conclusion:The CNN model can quickly distinguish nasopharyngeal carcinoma from benign nasopharyngeal lesions, which can aid endoscopists in diagnosing nasopharyngeal lesions and reduce the rate of nasopharyngeal biopsy.
Humans
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Nasopharyngeal Carcinoma
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Narrow Band Imaging
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China
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Neural Networks, Computer
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Nasopharyngeal Neoplasms/diagnostic imaging*