Objective To analyze the clinical curative effect of retroperitoneoscopy combined with inguen small incision surgery in treatment of urothelium carcinoma.Methods Ninety-eight urothelium carcinoma patients were divided into observation group (56 cases) and control group (42 cases) according to the surgery method.The patients in observation group were treated with retroperitoneoscopy combined with inguen small incision surgery,and the patients in control group were treated with open surgery.The operation time,intraoperative bleeding volume,postoperative drainage volume,postoperative gastrointestinal function recovery time,postoperative ambulation time,drainage tube removal time,hospitalization time,incision fat liquefaction,incision hernia,incision prolapse,incision pain and discomfort,postoperative analgesia,postoperative 3 months incision satisfaction and postoperative 36 months tumor recurrence were observed.Results The operation time,intraoperative bleeding volume,postoperative gastrointestinal function recovery time,postoperative ambulation time and hospitalization time in observation group were significantly lower than those in control group:(135.23 ±32.18) min vs.(177.58 ±57.29) min,(119.33 ±35.02) ml vs.(161.29 ± 72.06) ml,(2.03 ± 0.73) d vs.(2.79 ± 0.79) d,(20.68 ± 9.75) h vs.(32.41 ± 11.12) h,(8.51 ± 0.93) d vs.(9.81 ± 2.21) d,and there were statistical differences (P ＜ 0.05 or ＜ 0.01).There were no statistical differences in postoperative drainage volume and drainage tube removal time between 2 groups (P ＞ 0.05).The rates of incision fat liquefaction,incision hernia,incision prolapse,incision pain and discomfort and postoperative analgesia in observation group were significantly lower than those in control group:1.79％ (1/56) vs.26.19％ (11/42),0 vs.11.90％ (5/42),0 vs.7.14％ (3/42),1.79％ (1/56) vs.11.90％ (5/42),1.79％ (1/56)vs.11.90％ (5/42),the rate of postoperative 3 months incision satisfaction in observation group (92.86％,52/56) was significantly higher than that in control group (78.57％,33/42),and there were statistical differences (P ＜ 0.01 or ＜ 0.05).The rate of tumor recurrence in observation group (14.29％,8/56) was significantly lower than that in control group (47.62％,20/42),and there was statistical difference (P ＜ 0.01).Conclusions Retroperitoneoscopy combined with inguen small incision surgery in treatment of urothelium carcinoma can significantly reduce the patients' treatment and recovery time,improve the beauty of incision and patients' satisfaction degree,and reduce the postoperative tumor recurrence rate.

AIM:Chronic heart failure (CHF), caused by ischemic cardiomyopathy (ICM) and nonischemic cardiomyopathy (NICM), is among the leading causes of mortality and morbidity worldwide .Low-density lipoprotein receptor-related protein 6 (LRP6) plays a criti-cal role in regulating Wnt signaling .Dysregulated Wnt signaling contributes to high incidence of arrhythmias .Thus, there might be an association between genetic variations of LRP6 and sudden cardiac death ( SCD) .The objective of the study was to examine the associ-ation between common variants of LRP6 and prognosis of CHF patients .METHODS:From July 2005 to December 2009, patients with CHF referred from 10 hospitals and participants without structural heart disease in China were undergone a prospective study .The sin-gle-nucleotide polymorphism rs 2302684 was selected to evaluate the effect of LRP6 polymorphisms on the survival of the patients .RE-SULTS:A total of 1 887 patients (1 437 with CHF and 450 in the control group)were finally enrolled for the analysis.During a medi-an follow-up of 61 months, a total of 546 (38.00%) patients died, including 201(36.81%) cases with SCD and 345 (63.19%) ca-ses with NSCD.No end point event occurred in the control group .Patients carrying A allele of rs2302684 had increased risks of all-cause death (P<0.01) and SCD (P<0.01).After adjusted for the other risk factors , the associations remained significant in all-cause death (P<0.01) and SCD (P<0.01).In patients with CHF caused by ICM , those carrying A allele of rs2302684 also had in-creased risks of all-cause death (P<0.01) and SCD (P<0.01).After adjusted for the other risk factors , the associations remained significant in all-cause death (P<0.01) and SCD (P<0.01).However, there was no association between A allele of rs 2302684 and prognosis in patients with CHF caused by NICM .CONCLUSION:The SNP rs2302684 T>A in LRP6 is associated with an increased risk of all-cause death and SCD in patients with CHF in Chinese Han population , and the association is more prevalent in patients with CHF caused by ICM.Thus, LRP6 might be added as a novel predictor of SCD and could provide an attractive and direct therapeutic target in SCD prevention .

Objective To investigate correlation between aspirin resistance(AR) and inflammatory factors. Methods One hundred and ten patients with coronary heart disease took aspirin 0.1 mg/d for 14 days.It was detected platelet aggregation function induced with adenosine disphosphate (ADP) and arachidonic acid (AA), and investigated correlation between AR and inflammatory factors. Interleukin-1? (IL-1?),interleukin-6 (IL-6) and high sensitive C-reaction protein (hs-CRP) levels. Results IL-6 level of patients with AR was significantly higher than that of aspirin sensitive (AS) patients. The other two index were not different between the two groups. Conclusion IL-6 levels could be used as predictor.

s] Objective To detect the feasibility and efficiency of bone age(BA) artificial intelligence(AI) estimation based on deep learning features from traditional regions of interest(ROI) in hand digital radiographs(DR). Methods BA dataset of left hand DR with 11 858 subjects aged from 0 to 18 years in Children′s Hospital of Shanghai were split to training(80.0%) and validation (20.0%) set in this study. An improved regression convolutional neural networks and extreme gradient boosting decision tree method were utilized for the BA analysis based on traditional ROIs in the images. Another set of BA data with 1 229 subjects also in the hospital was adopted for test. Mean average precision(mAP) and mean absolute error(MAE) were used to assess model accuracy of detection and BA prediction, respectively. Results The mAP of ROIs detection of the model was 0.91,and MAE of all male and female subjects was 0.461 and 0.431 years respectively in validation and test sets. The difference less than 1 year in test accounted for 90.07% between BA assessment of the model and of the peadiatric radiologists, with an accuracy rate of 96.67%.The difference over 1 year was 9.03% (with underestimation of 6.43% and overestimation of 2.60%), in which corresponding age data was of being less in training set or sesamoid nearby adductor pollicis or fusion of epiphysis appeared in test set. Conclusion An AI model based on deep learning of traditional ROIs′features in hand DR images is initially achieved to automatically predict BA rapidly and effectively, yet it still needs further optimization.

Objective: To detect the feasibility and efficiency of bone age(BA) artificial intelligence(AI) estimation based on deep learning features from traditional regions of interest(ROI) in hand digital radiographs(DR). Methods: BA dataset of left hand DR with 11 858 subjects aged from 0 to 18 years in Children′s Hospital of Shanghai were split to training(80.0%) and validation (20.0%) set in this study. An improved regression convolutional neural networks and extreme gradient boosting decision tree method were utilized for the BA analysis based on traditional ROIs in the images. Another set of BA data with 1 229 subjects also in the hospital was adopted for test. Mean average precision(mAP) and mean absolute error(MAE) were used to assess model accuracy of detection and BA prediction, respectively. Results: The mAP of ROIs detection of the model was 0.91,and MAE of all male and female subjects was 0.461 and 0.431 years respectively in validation and test sets. The difference less than 1 year in test accounted for 90.07% between BA assessment of the model and of the peadiatric radiologists, with an accuracy rate of 96.67%.The difference over 1 year was 9.03% (with underestimation of 6.43% and overestimation of 2.60%), in which corresponding age data was of being less in training set or sesamoid nearby adductor pollicis or fusion of epiphysis appeared in test set. Conclusion An AI model based on deep learning of traditional ROIs′ features in hand DR images is initially achieved to automatically predict BA rapidly and effectively, yet it still needs further optimization.