Objective To explore the herpes virus Ⅱ(HSV-2) infection and Ki-67 expression for the cervical carcinoma and cervical intraepithelial neoplasia(CN).Methods The polymerase chain reaction(PCR) and immunohistochemistry were applied to detect the HSV-2 and Ki-67 expressions in cancerous tissues of uterine cervix in 84 cases (67 scaly cell carcinoma,3 scaly adenocarcinoma,and 14 adenocarcinoma cases),CN in 35 cases,and normal cervical tissues in 13 cases.Results (1)The positive rote of HSV-2 is 40.2% (53/132),and the rate in cervical cancerous tissues,CN and normal cervical tissues were 48.8% (41/48) ,28.5% (10/35) and 15.4% (2/13) respectively.HSV-2 DNA expressions in cancerous tissue and CN were much higher than that of normal cervical tissues (P<0.01).(2)The Ki-67 positive cells were progressive increasing in the normal cervical tissues,CN and cervical cancerous tissues,thus showing that there were relations between the Ki-67 expression degree and tissue types.The HSV-2 and Ki-67 expressions were remarkably connected(P < 0.01).Conclusion There are HSV-2 infection ,close related between HSV-2 infection and Ki-67 expression in the tissues of cervical carcinoma and CN.And the cooperation of them may play an important role in the development of cervical carcinoma.

Objective To investigate the relationship between herpes simplex virus(HSV) and spontaneous abortion. Methods 40 aborted material and 16 post-aborted curettings were tested for the presence of HSVDNA with in situ hybridization.In addition 20 normal endometria and 20 induced abortive placentas were used as controls. Results 56.3 %(9/16)post-abortion curettings were demonstrated the presence of HSVDNA.It was higher than that of the control group( P

Objective To investigate the expression of insulin-like growth factor Ⅱ mRNA-binding protein 3( IMP3 ) in transitional cell carcinoma of bladder( TCCB ) and its clinical significance. Methods The IMP3 expressions in 6 normal bladder tissues and 48 TCCB tissues were determined by immunohistochemistry staining, and the relationships between IMP3 expression and gender, age, pathological grading and staging were analyzed statistically. Results The positive expression rate of IMP3 was 62.5% ( 30/48 ) in bladder cancer,which were significantly higher than that in normal control ( 0/6 ) ( P ＜ 0. 05 ). The positive rate of IMP3 expression were significantly lower in superficial TCCB ( 46. 15%, 12/22 ) or early TCCB [ Grade Ⅰ 12. 5%(1/8) ,Grade Ⅱ 60. 0% (12/20) ] than that in invasive TCCB [T2 or above,81.8% (18/22) ] or advanced TCCB [ Grade Ⅲ ,85% ( 17/20 ) ] ( Ps ＜ 0. 05 ). Conclusion IMP3 is a promising biomarker for eraly detection and assessment of the malignancy degree in TCCB.

Objective To explore the three ultrasonic technologies of two -dimensional ultrasound(2D -US),ultrasonic elastography(UE) and contrast -enhanced ultrasound(CEUS) for the measurement error in breast cancer and the correlation with the expression of ER,PR,VEGF.Methods 50 patients with breast cancer were meas-ured by 2D -US,UE,CEUS preoperatively,and the pathological specimen were measured postoperatively.Then used the immunohistochemistry to detect the expression of ER,PR,VEGF in tumor,and analyzed the correlation with the measurement errors.Results The results of differences between 2D -US,UE,CEUS and pathology were respectively as follows:( -0.59 ±-0.34)cm,( -0.20 ±-0.14)cm,( -0.40 ±-0.31)cm,and the differences were statistically significant(F =20.497,P <0.001).The positive expression rate of ER and PR was high if the difference between UE and 2D -US was less than or equal to 0.44cm.And the positive expression rate of VEGF was low if the difference between CEUS and 2D -US was less than or equal to 0.19cm.Three ultrasonic technologies in the measurement of breast cancer were different,the trend of difference between UE and 2D -US was smaller if the ER and PR were positively expression,and the trend of difference between CEUS and 2D -US was bigger if the VEGF was positively expression.Conclusion There is correlation between different immunohistochemical expression of breast cancer with measurement error in three different ultrasonic imaging technologies.The results suggest that the molecular pathology difference of breast cancer can impact on ultrasonic imaging,which contributes to know the reason and regulation of measurement error in different ultrasonic imaging technology.

Background/Aims: The accuracy of endosonographers in diagnosing gastric subepithelial lesions (SELs) using endoscopic ultrasonography (EUS) is influenced by experience and subjectivity. Artificial intelligence (AI) has achieved remarkable development in this field. This study aimed to develop an AI-based EUS diagnostic model for the diagnosis of SELs, and evaluated its efficacy with external validation. Methods: We developed the EUS-AI model with ResNeSt50 using EUS images from two hospitals to predict the histopathology of the gastric SELs originating from muscularis propria. The diagnostic performance of the model was also validated using EUS images obtained from four other hospitals. Results: A total of 2,057 images from 367 patients (375 SELs) were chosen to build the models, and 914 images from 106 patients (108 SELs) were chosen for external validation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the model for differentiating gastrointestinal stromal tumors (GISTs) and non-GISTs in the external validation sets by images were 82.01%, 68.22%, 86.77%, 59.86%, and 78.12%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in the external validation set by tumors were 83.75%, 71.43%, 89.33%, 60.61%, and 80.56%, respectively. The EUS-AI model showed better performance (especially specificity) than some endosonographers.The model helped improve the sensitivity, specificity, and accuracy of certain endosonographers. Conclusions We developed an EUS-AI model to classify gastric SELs originating from muscularis propria into GISTs and non-GISTs with good accuracy. The model may help improve the diagnostic performance of endosonographers. Further work is required to develop a multi-modal EUS-AI system.