Objective To observe the impact of ultrasonic image quality on the consistency of artificial intelligence(Al)assisted diagnosis system and manual measurements of biological indicators of developmental dysplasia of hip(DDH).Methods Hip ultrasonic data of 75 DDH and 345 non-DDH children were retrospectively analyzed,and the quality of ultrasonic images were subjectively scored.An evaluation model of ultrasonic image quality was constructed based on 140 ultrasonic images acquired from 140 cases(group A,containing 25 DDH and 115 non-DDH)using entropy weighting method,the weight of anatomic structures and impact factors related to DDH were obtained.The comprehensive image quality scores of other ultrasonic images acquired from 280 cases(group B,including 50 DDH and 230 non-DDH)were calculated,and the images in group B were classified into grade A,B and C in descending order.The consistency of AI and manual measurements of DDH biological indicators in group B was assessed.Results The weight of each anatomic structure and impact factors of DDH obtained with the model were as follows:The lower edge of iliac branch＞ilium＞glenoid labrum＞bony margin＞femoral head＞motion artifacts.In group B,grade A was observed in 67(9 DDH and 58 non-DDH),grade B was found in 160(26 DDH and 134 non-DDH),while grade C was noticed in 53(15 DDH and 38 non DDH)images.Except for β,femoral head coverage(FHC)and femoral head length diameter,the consistencies between AI and manual measurements of other indicators of DDH were grade A＞B＞C.In group B,AI and manual measurements were more consistent in DDH than in non-DDH cases.Conclusion Ultrasonic image quality affected the consistency between AI and manual measurements of biological indicators of DDH.When image quality was not good enough,further attention should be paid to measurement of FHC and sizes of femoral head.

Lung cancers are the leading cause of cancer deaths worldwide and pose a grave threat to human life and health. Non-small cell lung cancer (NSCLC) is the most frequent malignancy occupying 80% of all lung cancer subtypes. Except for other mutations (

Objective To identify the best cell line for Pneumocystis carinii(Pc) proliferation Methods Specimens containing 5?10 5 Pc cysts were inoculated onto 8 kinds of cell lines separately. At the same time, Pc were inoculated in different amounts on HepG-2 cell line to identify the most suitable number of Pc needed for Pc proliferation in vitro within seven days. Results On HepG-2 cell line, Pc increased by 7-fold in trophozoite forms with a peak increasing rate between 4～5 days with the optimal growth at the cyst number of 5?10 5 .Conclusions HepG-2 cell line is found to be the most suitable cell line for Pc culture and the best inoculation number of Pc is 5?10 5.