Objective To study effect of Radix Angelica Sinensis (RAS) on Alzhemier's Disease (AD)-like lesions in rats with chronic cerebral hypoperfusion (CCH).Methods rats were randomly divided into sham group,bilateral vascular occlusion (model group),low RAS dose treatment group and high RAS dose treatment group.Cognitive function was assessed by Morris Water Maze and Object Recognition Test.Aβ was detected by ELISA while brain-derived neurotrophic factor (BDNF)、β secretory enzyme 1 (BACE1)、phosphorylated Tau and phosphorylation of Akt/ GSK3β was detected by Western blot.Results There were shorter target quadrant exploration time (TQET),lower priority index (PI) 、phosphorylated Akt/GSK3β expression、BDNF and high-er Aβ1 40 、Aβ1-42 、p-Tau and BACE1 in model group than insham group (P＜0.05,P＜0.01).Low and high RAS dose treatment lengthened TQET,improved PI、phosphorylated Akt/GSK3β expression and BDNF while decreased Aβ1-40 、Aβ1-42 、p-Tau and BACE1 compared with model group.BDNF was higher after high dose RAS treatment than model group (P＜0.01).Conclusion RAS inhibits AD-like lesions in rats with CCH by downregulating the Akt/GSK3β pathway and BACE1 activity,thus improving the cognitive impairment.

Objective To evaluate the diagnosis and surgical treatment of primary retroperitoneal extraadrenal pheochromocytoma(PREAP). Methods Clinical data of 17 cases with PREAP from 1976 to 2006 were analyzed retrospectively. Results It was not difficult for the diagnosis of PREAP based on the primary symptoms, including paroxysmal hypertension or persistent hypertension. PREAP is usually deep, large and invading on adjacent organs. B-uhrasound was used for preliminary screening. CT and MRI with high soft tissue resolution and multi directional imaging are of great value for correct diagnosis and determination of exact extent of the tumor in diagnosis of PREAP. 24 h urinary VMA output imcreased in 12 cases (92. 3%) and urinary catecholamine level was up to 526. 1 μg- Precise location of PREAP by 123I-MIBG is superior to that by 131I-MIBG. The diagnosis was tentative in 4 cases and definite in 13 cases. Complete tumor resection was achieved in 15 cases, among them 2 cases died on table due to inadequate preparation before surgery in 1970's. In the remaining 2 cases with huge tumors partial resection, silver clips were put in during operation to locate the extent of the tumors for further management after operation. Conclusions Locating and qualitative diagnosis before operation are valuable and once the patients are diagnosed as PREAP, they should receive exploratory laparotomy after an adequate preparation.

Objective To evaluate the diagnosis and surgical treatment of adult congenital choledochal cyst(ACCC). Methods Clinical data of 345 ACCC cases from 1974 to 2007 were analyzed retrospectively. Results There were only 110 patients (31.9%) with typical triad (abdominal pain, palpable mass and jaundice). B-ultrasound, CT, ERCP, PTC and MRCP were methods for diagnosis. Cancer arising from choledochal cysts was found in 19 cases who had undergone internal drainage and its incidence of cholangiocarcinoma is much higher than in the general population. All cases underwent surgical treatment, in which total excision of choledochal cyst and Roux-en-Y hepaticojejunostomy was main operation, 337 cases recovered well and 8 (2. 3%) died. C..ondusions Accurate diagnosis of ACCC was difficult depending on clinical symptoms only. B-ultrasound was the choice of atraumatic diagnosis. All patients with an established diagnosis of ACCC should undergo exploratory laparotomy. Total excision of eholedochal cyst and Roux-en-Y hepaticojejunostomy is most effective treatment for ACCC.

AIM: To investigate the role of N-cadherin in the delamination of neural crest cells. METHODS: The normal expression of N-cadherin in neural tube was identified using in situ hybridization. The cells with N-cadherin over expression were obtained by transfection of wild-type N-cadherin (wt-N-cadherin) ,and the cells with N-cadherin silencing expression were obtained by transfection of dominant-negative N-cadherin (dn-N-cadherin). The migration of cranial neural crest cells was determined by the technique of immunohistochemistry. RESULTS: Either overexpression or down-regulation of N-cadherin significantly affected the migration of cranial neural crest cells. CONCLUSION: Delamination and migration of the cranial neural crest cells rely on the relative N-cadherin expression in the neural tube during neurulation.

Objective To establish and validate a prediction model for gastric cancer lymph node metastasis based on four machine learning(ML)algorithms.Methods A retrospective analysis was conducted on clinical data of 531 patients who underwent radical gastrectomy.The patients were ran-domly divided into training set(399 patients)and test set(132 patients)in a ratio of 3 to 1.Univari-ate analysis was used to screen for variables associated with gastric cancer lymph node metastasis,and Logistic regression,random forest,K-nearest neighbor algorithm,and support vector machine algo-rithm models were established to rank the importance of variables.All ML algorithm models were vali-dated in the test set,and receiver operating characteristic(ROC)curves were plotted.The optimal ML algorithm model was determined based on the area under the curve(AUC),sensitivity,specifici-ty,and accuracy.A nomogram model was constructed based on the variable importance ranking of the optimal ML algorithm model.The discrimination,calibration,and clinical applicability of the nomo-gram model were evaluated using ROC curves,calibration curves,and decision curves.Results The results of the comparison of the four ML algorithm models showed that the random forest model was the optimal algorithm model.The accuracy,sensitivity,and specificity of the random forest model in the training set were 72.7％,69.9％,and 75.0％,respectively,with an AUC of 0.803.The accuracy,sensitivity,and specificity of the random forest model in the test set were 64.4％,66.7％,and 62.5％,respectively,with an AUC of 0.751.A nomogram model was constructed based on the variables of the random forest algorithm model.The ROC curve showed that the AUCs of the nomogram model in the training set and test set were 0.721 and 0.776,respectively.Calibration curves and decision curves showed that the nomogram model had good calibration and clinical applicability in both the training set and test set.Conclusion The random forest model is the optimal algorithm model a-mong the four ML algorithm models.The nomogram model based on the random forest model can ac-curately predict the risk of gastric cancer lymph node metastasis,thereby better guiding clinical di-agnosis and treatment decisions.

Objective To establish and validate a prediction model for gastric cancer lymph node metastasis based on four machine learning(ML)algorithms.Methods A retrospective analysis was conducted on clinical data of 531 patients who underwent radical gastrectomy.The patients were ran-domly divided into training set(399 patients)and test set(132 patients)in a ratio of 3 to 1.Univari-ate analysis was used to screen for variables associated with gastric cancer lymph node metastasis,and Logistic regression,random forest,K-nearest neighbor algorithm,and support vector machine algo-rithm models were established to rank the importance of variables.All ML algorithm models were vali-dated in the test set,and receiver operating characteristic(ROC)curves were plotted.The optimal ML algorithm model was determined based on the area under the curve(AUC),sensitivity,specifici-ty,and accuracy.A nomogram model was constructed based on the variable importance ranking of the optimal ML algorithm model.The discrimination,calibration,and clinical applicability of the nomo-gram model were evaluated using ROC curves,calibration curves,and decision curves.Results The results of the comparison of the four ML algorithm models showed that the random forest model was the optimal algorithm model.The accuracy,sensitivity,and specificity of the random forest model in the training set were 72.7％,69.9％,and 75.0％,respectively,with an AUC of 0.803.The accuracy,sensitivity,and specificity of the random forest model in the test set were 64.4％,66.7％,and 62.5％,respectively,with an AUC of 0.751.A nomogram model was constructed based on the variables of the random forest algorithm model.The ROC curve showed that the AUCs of the nomogram model in the training set and test set were 0.721 and 0.776,respectively.Calibration curves and decision curves showed that the nomogram model had good calibration and clinical applicability in both the training set and test set.Conclusion The random forest model is the optimal algorithm model a-mong the four ML algorithm models.The nomogram model based on the random forest model can ac-curately predict the risk of gastric cancer lymph node metastasis,thereby better guiding clinical di-agnosis and treatment decisions.

Objective To monitor the antifungal resistance of clinical isolates of Candida spp.in the East China region.Methods MALDI-TOF MS or molecular methods were used to re-identify the strains collected from January 2018 to December 2022.Antifungal susceptibility testing was performed using the broth microdilution method.The susceptibility test results were interpreted according to the breakpoints of 2022 Clinical and Laboratory Standards Institute(CLSI)documents M27 M44s-Ed3 and M57s-Ed4.Results A total of 3 026 strains of Candida were collected,65.33％of which were isolated from sterile body sites,mainly from blood(38.86％)and pleural effusion/ascites(10.21％).The predominant species of Candida were Candida albicans(44.51％),followed by Candida parapsilosis complex(19.46％),Candida tropicalis(13.98％),Candida glabrata(10.34％),and other Candida species(0.79％).Candida albicans showed overall high susceptibility rates to the 10 antifungal drugs tested(the lowest rate being 93.62％).Only 2.97％of the strains showed dose-dependent susceptibility(SDD)to fluconazole.Candida parapsilosis complex had a SDD rate of 2.61％and a resistance rate of 9.42％to fluconazole,and susceptibility rates above 90％to other drugs.Candida glabrata had a SDD rate of 92.01％and a resistance rate of 7.99％to fluconazole,resistance rates of 32.27％and 48.24％to posaconazole and voriconazole non-wild-type strains(NWT),respectively,and susceptibility rates above 90％to other drugs.Candida tropicalis had resistance rates of 29.55％and 26.24％to fluconazole and voriconazole,respectively,resistance rates of 76.60％and 21.99％to posaconazole and echinocandins non-wild-type strains(NWT),and a resistance rate of 2.36％to echinocandins.Conclusions The prevalence and species distribution of Candida spp.in the East China region are consistent with previous domestic and international reports.Candida glabrata exhibits certain degree of resistance to fluconazole,while Candida tropicalis demonstrates higher resistance to triazole drugs.Additionally,echinocandins resistance has emerged in Candida albicans,Candida glabrata,Candida tropicalis,and Candida parapsilosis.