For the characteristics including minimal invasion,low incidence of complication and better postoperative prognosis,endoscopic therapy is widely accepted to be the first line therapy for most biliary strictures.At present,repeated progressive dilation combined with multiple plastic stents placement is the main therapy for benign biliary strictures.The long-term effective rate is relatively high in surgery related strictures,but in the non-surgery related strictures,its long-term effective rate is limited and the optimal therapy should be chosen cautiously according to patients' condition.In malignent biliary stricutes,dilation combined with metallic stents placement is recommended to treat both of preoperative long-term drainage in patients with resectable tumor and palliative treatment in patients with unresectable tumor,while nosobiliary drainage is recommended in preoperative short-term drainage. The choice of unilateral or bilateral drainage depends on patients' conditons in malignent hilar biliary strictures.The merits and demerits of stents should be mastered before they are placed in stricture sections.Recently,a lot of new endoscopic technologies and methods are applied in clinical practice,but their curative effect should be tested.Therefore,accumulative evidence-based data are needed to make them more rational and more standard.

Objective To establish an artificial intelligence deep learning model using clinical colonoscopy images and video to assist the diagnosis by colonoscopy. Methods More than 600000 colonoscopy images were collected in endoscopic center of the Second Affiliated Hospital of Zhejiang University School of Medicine from 2014 to 2018, and endoscopic experts recorded a large number of high-quality operation video of colonoscopy as analysis data. After repeated discussion by six experts, the classified intestinal sites and pathological features were determined, and fuzzy and confusable images were deleted. The final selection result was approximately 1 out of 4. And then the features of images were marked using an independently developed software. The deep learning algorithm was developed using TensorFlow platform of Google. Results After repeated comparison and analysis of the results of machine training and judgment results combined with pathology from endoscopic experts, the sensitivity of the model for some diseases ( such as colon polyps) was 99％ under laboratory conditions. In the clinical colonoscopy test, the sensitivity, specificity, and overall accuracy of this model for diagnosis of colon polyps were 98. 30％(4187/4259), 88. 10％ (17620/20000), and 92. 92％ [2×98. 30％×88. 10％/(98. 30％+88. 10％)], respectively. The sensitivity and specificity for ulcerative colitis were 78. 32％ ( 2671/3410) , and 67. 06％(13412/20000), respectively. The diagnosis time spent on a single image was 0. 5±0. 03 s, and it was the real time for application, including system recognition, text prompt in video image, background record and storage. Conclusion The artificial intelligence assisted diagnosis model developed by our team can identify colonic polyps, colorectal cancer, colorectal eminence, colonic diverticulum, ulcerative colitis, etc. The auxiliary diagnosis model of colon disease can guide beginners to carry out colonoscopy, and can improve lesion detection rate, reduce misdiagnosis rate, and improve the overall operating efficiency of endoscopic center, which is conducive to the quality control of colonoscopy.

Objective:To systematically evaluate the clinical efficacy of compound α-ketoacid tablets in the treatment of diabetic kidney disease (DKD).Methods:CNKI, Wanfang database, EMBASE, PubMed and Cochrane Library database were searched for eligible records published from the establishment of individual database to November 13 th, 2022. The quality of the included studies were assessed, data were extracted, and meta-analysis was conducted using RevMan5.3. Results:A total of 26 randomized controlled trials were included, with a total of 2 790 DKD patients (1 465 in the experimental group and 1 325 in the control group). Multiple parameters were significantly improved in the experimental group compared with the control group, including 24-hour urinary protein, blood creatinine, urea nitrogen, nutritional index, oxidative stress level, fasting blood glucose, glycated hemoglobin, homocysteine, HGF, VEGF, TGF-β1, and systolic blood pressure.Conclusions:Limited low-quality evidence showed that compound α-ketoacid tablets combined with low-protein diet may be related to the improved 24-hour urinary protein, renal function, and glucose metabolism in patients with DKD. Due to the lack of randomized controlled trials designed for respective stages of DKD, the inclusion criteria of our study were relatively general, possibly leading to the lack of pertinence of the results. Some indicators showed apparent heterogeneity among different groups, and more high-quality multi-center studies with large sample sizes are still needed to verify our findings.

ObjectiveTo investigate the characteristics of electromyography (EMG) and postural stability of lower limb muscles during Y-balance test (YBT) and their relationship. MethodsFrom October to November, 2021, a total of 26 female students aged 18 to 22 years were recruited from Binzhou Medical University to complete YBT; while the EMG of rectus femoris, biceps femoris, tibialis anterior and gastrocnemius of supporting legs were collected synchronously to measure root mean square (RMS), integral electromyography (iEMG), and muscle contribution rate; and the postural stabilities were measured with three-dimensional force platform, to record total, antero-posterior (A/P) and medio-lateral (M/L) path length of center of pressure (COP). ResultsIn three directions of YBT, the RMS of rectus femoris was the most (χ² > 56.952, P < 0.001), and the iEMG and contribution rate of the tibialis anterior were the most (χ² > 38.507, P < 0.001). All the path length of COP was the shortest in the anterior (P < 0.05). In the anterior, the total path length of COP correlated with iEMG of biceps femoris (r = 0.452, P = 0.02) and gastrocnemius (r = 0.397, P = 0.045); in the postero-medial, the total path length of COP correlated with iEMG of gastrocnemius (r = 0.478, P = 0.014); and in the postero-lateral, the total path length of COP correlated with iEMG of tibialis anterior (r = 0.437, P = 0.026). ConclusionFor YBT, the activation of rectus femoris, tibialis anterior and gastrocnemius muscles of supporting legs are significant, and different with the indicators of EMG. Postural stability is the best in the posterolateral. The joint extensors or flexors play a different role for dynamic postural stability in the different directions.