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Identification of epididymis-specific transcripts in the mouse and rat by transcriptional profiling 认领 引用 被引量：9
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作者 Daniel S. Johnston Terry T. Turner +3 位作者 Joshua N. Finger Tracy L. Owtscharuk Gregory S. Kopf Scott A. Jelinsky 《Asian Journal of Andrology》 SCIE CAS 2007年第4期522-527,共6页
As part of our efforts to identify novel contraceptive targets in the epididymis we performed transcriptional profiling on each of the 10 and 19 segments of the mouse and rat epididymidis, respectively, using Affymetr... As part of our efforts to identify novel contraceptive targets in the epididymis we performed transcriptional profiling on each of the 10 and 19 segments of the mouse and rat epididymidis, respectively, using Affymetrix whole genome microarrays. A total of 17 096 and 16 360 probe sets representing transcripts were identified as being expressed in the segmented mouse and rat epididymal transcriptomes, respectively. Comparison of the expressed murine transcripts against a mouse transcriptional profiling database derived from 22 other mouse tissues identified 77 transcripts that were expressed uniquely in the epididymis. The expression of these genes was further evaluated by reverse transcription polymerase chain reaction （RT-PCR） analysis of RNA from 21 mouse tissues. RT-PCR analysis confirmed epididymis-specific expression of Defensin Beta 13 and identified two additional genes with expression restricted only to the epididymis and testis. Comparison of the 16 360 expressed transcripts in the rat epididymis with data of 21 other tissues from a rat transcriptional profiling database identified 110 transcripts specific for the epididymis. Sixty-two of these transcripts were further investigated by qPCR analysis. Only Defensin 22 （E3 epididymal protein） was shown to be completely specific for the epididymis. In addition, 14 transcripts showed more than 100-fold selective expression in the epididymis. The products of these genes might play important roles in epididymal and/or sperm function and further investigation and validation as contraceptive targets are warranted. The results of the studies described in this report are available at the Mammalian Reproductive Genetics （MRG） Database （http：//mrg. genetics.washington.edu/）. （Asian J Androl 2007July; 9： 522-527） 展开更多
关键词 mouse rat epididymis transcriptional profiling contraception microarray epididymis-specific epididymis-selective
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Ultrasound Features Improve Diagnostic Performance of Ovarian Cancer Predictors in Distinguishing Benign and Malignant Ovarian Tumors 认领 引用 被引量：6
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作者 Yong-ning CHEN Fei MA +3 位作者 Ya-di ZHANG Li CHEN Chan-yuan LI Shi-peng GONG 《Current Medical Science》 SCIE CAS 2020年第1期184-191,共8页
To determine whether ultrasound features can improve the diagnostic performance of tumor markers in distinguishing ovarian tumors,we enrolled 719 patients diagnosed as having ovarian tumors at Nanfang Hospital from Se... To determine whether ultrasound features can improve the diagnostic performance of tumor markers in distinguishing ovarian tumors,we enrolled 719 patients diagnosed as having ovarian tumors at Nanfang Hospital from September 2014 to November 2016.Age,menopausal status,histopathology,the International Federation of Gynecology and Obstetrics(FIGO)stages,tumor biomarker levels,and detailed ultrasound reports of patients were collected.The area under the curve(AUC),sensitivity,and specificity of the bellow-mentioned predictors were analyzed using the receiver operating characteristic curve.Of the 719 patients,531 had benign lesions,119 had epithelial ovarian cancers(EOC),44 had borderline ovarian tumors(BOT),and 25 had non-EOC.AUCs and the sensitivity of cancer antigen 125(CAI25),human epididymis-specific protein 4(HE4),Risk of Ovarian Malignancy Algorithm(ROMA),Risk of Malignancy Index(RMI1),HE4 model,and Rajavithi-Ovarian Cancer Predictive Score(R-OPS)in the overall population were 0.792,0.854,0.856,0.872,0.893,0.852,and 70.2%,56.9%,69.1%,60.6%,77.1%,71.3%,respectively.For distinguishing EOC from benign tumors,the AUCs and sensitivity of the above mentioned predictors were 0.888,0.946,0.947,0.949,0.967,0.966,and 84.0%,79.8%,87.4%,84.9%,90.8%,89.1%,respectively.Their specificity in predicting benign diseases was 72.9%,94.4%,87.6%,95.9%,86.3%,90.8%,respectively.Therefore,we consider biomarkers in combination with ultrasound features may improve the diagnostic performance in distinguishing malignant from benign ovarian tumors. 展开更多
关键词 cancer antigen 125 human epididymis-specific protein 4 Risk of Ovarian Malignancy Algorithm Risk of Malignancy Index Risk of Malignancy Index model Rajavithi-Ovarian Cancer Predictive Score ovarian masses
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