0.05). Conclusion Peaks of serum gonadotropin and sex hormone concentrations are reached at 2~4 months of age and sexual dimorphism is shown, suggesting that in boy and girl infants, different mechanisms may be involved in regulating the development of gonads.

Objective To set up the technology for adsorbing and separating total flavone in Sarcandra glabra with macroporous adsorption resin,11 types of macroporous adsorption resins were investigated.Methods The static adsorption and separation were used in investigation of macroporous adsorption resin;the dynamic adsorption and separation were used in studying the condition of adsorption and separation.The total flavone adsorption capacity,total flavone content,and total flavone recovery rate were used as the evaluation criteria.The UV spectrophotometric method was used in the determination of total flavone content.Results The results showed that among 11 types of macroporous adsorption resins,the HPD400 was the best for adsorbing and separating the total flavone in S.glabra in the following technological condition: the concentration of S.glabra sample extract was 10 mg/mL;the maximum adsorbing capacity for total flavone in S.glabra was 9.5 mg/mL;the current velocity was 2.5 mL/min;the eluting reagent was 70% ethanol(three times as the volume of the resin);and the HPD400 resin could be used three times,repeatedly.Conclusion It is a simple and efficient to separate the total flavone in S.glabra under the technological conditions,and a total flavone recovery rate is about 85%.

Objective To investigate the causes of misdiagnosis and improve the level of diagnosis and treatment for endocrine myopathy,through the study the clinical data of 20 patients with endocrine myopathy who were misdiagnosed as polymyositis were analyzed.Methods 20 cases were retrospectively analyzed who suffered from proximal weakness as the main performance and misdiagnosed as polymyositis,through the method of supervision to track,review of the observation and methods of medical record information query.Results The main types of diseases which were misdiagnosed including 18 patients of thyroid diseases(13 patients of hypothyroidism,5 patients of hyper-thyroidism),2 patients of parathyroid disease(1 patient of hyperparathyroidism,1 patient of hypoparathyroidism). Conclusion Mastering polymyositis and endocrine myopathy in the identification of main points,improving the ability of differential diagnosis,so that doctor can avoid misdiagnosis.

Objective To investigate the changes of serum soluble factor-related apoptosis (sFas) and soluble Fas ligand (sFasL) and their relations with cognition disorders in the patients with vascular dementia (VaD). Methods Serum concentrations of sFas and sFasl were detected by enzyme-linked immunosorbent assay (ELISA) and compared between 70 patients with VaD aged (72.5± 7.5)years and 50 healthy elderly people aged(72.5 ± 7.5)years.The VaD patient's cognitive functions were evaluated by activity of daily living scale (ADL),mini mental state examination (MMSE) and hachinski ischemia score (Hachinski). Results The serum levels of sFas and sFasL in VaD patients were (228.0±60.7)μg/L and (146.8±30.1)μg/L,and in the healthy elderly were (62.4±22.6)μg/L and (82.3 ± 18.7)μg/L,respectively.The serum levels of apoptosis factors in VaD patients were significantly higher than in the healthy controls (t=20.883,14.453,P＜0.01).sFas level was negatively correlated with age,the scores of ADL and Hachiuski while positively with the scores of MMSE (r=-0.956,-0.943,-0.950 and 0.904,all P＜0.01). sFasL level was negatively correlated with the scores of MMSE while positively with age,the scores of ADL and Hachinski (r=-0.899,0.963,0.948 and 0.939,a11 P＜0.01). Conclusions Apoptosis may be involved in the pathological change during VaD and the serum levels of sFas and sFasL might be related with cognition disorders.

Objective To observe the effect of saxagliptin combined insulin four times to strengthen the vola-tility on blood glucose variability in patients with type 1 diabetes.Methods According to random number table meth-od,60 patients with type 1 diabetes were divided into DPP4 group(28 cases)and the control group(32 cases).The control group was given insulin four times to strengthen the volatility(insulin aspart/insulin lispro +insulin glargine /insulin detemir),the DPP4 group on the basis of insulin four times to strengthen the volatility plus the saxagliptin 5mg/d,all patients into the group after1 -3D and 13 -15D using CGMS(Medtronic)continuously monitor the blood glucose.Results (1)Within the group comparison:the DPP4 group:1 -3d after treatment:MAGE and SDBG,MBG, LAGE,PT10.0,PT3.9 were lower than before treatment,including MAGE [(6.91 ±1.63)mmol/L vs.(6.31 ± 1.42)mmol/L,t =0.993],SDBG[(2.63 ±0.81)mmol/L vs.(2.41 ±0.51)mmol/L,t =0.751],MBG[(11.51 ± 1.24)mmol/L vs.(10.87 ±2.01)mmol/L,t =1.077],LAGE[(9.43 ±1.73)mmol/L vs.(8.56 ±1.97)mmol/L, t =1.125],PT10.0[(12.99 ±5.61)% vs.(9.66 ±5.03)%,t =1.427],PT3.9[(5.51 ±2.43)% vs.(5.07 ± 2.44)%,t =1.141],there were statistically significant differences compared with before treatment(all P <0.05), 1 -3d after treatment,SDBG[(2.77 ±0.73)mmol/L vs.(2.14 ±0.69)mmol/L,t =1.547],MBG[(11.67 ± 1.46)mmol/L vs.(9.76 ±1.58)mmol/L,t =1.1.326]were decreased,but there were no statistically significant differences compared with before treatment(all P >0.05);13 -15d after treatment:MAGE[(6.88 ±1.49)mmol/L vs.(2.97 ±0.86)mmol/L,t =3.021],SDBG[(2.77 ±0.73)mmol/L vs.(1.12 ±0.43)mmol/L,t =1.964],MBG [(11.67 ±1.46)mmol/L vs.(7.44 ±0.93)mmol/L,t =2.760],LAGE[(9.55 ±1.77)mmol/L vs.(6.53 ±1.21)mmol/L, t =2.409],PT10.0[(13.58 ±5.14)% vs.(4.72 ±2.37)%,t =2.657],PT3.9[(5.36 ±2.05)% vs.(3.05 ± 2.60)%,t =1.840]were decreased,there were statistically significant differences compared with before treatment (P <0.05 or P <0.01 );the control group:1 -3d after treatment:MAGE [(6.91 ±1.63)mmol/L vs.(6.31 ± 1.42)mmol/L,t =0.993],SDBG[(2.63 ±0.81)mmol/L vs.(2.41 ±0.51)mmol/L,t =0.751],MBG[(11.51 ± 1.24)mmol/L vs.(10.87 ±2.01)mmol/L,t =1.077],LAGE[(9.43 ±1.73)mmol/L vs.(8.56 ±1.97)mmol/L, t =1.125],PT10.0[(12.99 ±5.61)% vs.(9.66 ±5.03)%,t =1.427],PT3.9[(5.51 ±2.43)% vs.(5.07 ± 2.44)%,t =1.141]were lower than before treatment,but compared with before treatment,there were no statistically significant differences(all P >0.05 );13 -15d after treatment:MAGE [(6.91 ±1.63 )mmol/L vs.(6.07 ± 1.36)mmol/L,t =1.223],SDBG[(2.63 ±0.81)mmol/L vs.(1.91 ±0.93)mmol/L,t =0.984],MBG[(11.51 ± 1.24)mmol/L vs.(8.82 ±1.13)mmol/L,t =1.808],LAGE[(9.43 ±1.73)mmol/L vs.(7.06 ±1.57)mmol/L, t =1.963],PT10.0[(12.99 ±5.61)% vs.(6.74 ±3.35)%,t =2.012],PT3.9[(5.51 ±2.43)% vs.(4.73 ± 2.57)%,t =1.541]were decreased,there were statistically significant differences in MBG,LAGE,PT10.0 compared with before treatment(all P <0.05).Group comparision:1 -3d after treatment:the DPP4 group:MAGE[(4.81 ± 1.15)mmol/L vs.(6.31 ±1.42)mmol/L,t =2.351],SDBG[(2.14 ±0.69)mmol/L vs.(2.41 ±0.51)mmol/L, t =1.332],MBG[(9.76 ±1.58)mmol/L vs.(10.87 ±2.01)mmol/L,t =0.856],LAGE[(7.74 ±1.88)mmol/L vs.(8.56 ±1.97)mmol/L,t =2.102],PT10.0 [(7.47 ±4.96)% vs.(9.66 ±5.03)%,t =2.667],PT3.9 [(4.64 ±2.14)% vs.(5.07 ±2.44)%,t =1.890]were all significantly lower than the control group,there were statistically significant differences in MAGE,LAGE,PT10.0 between the two groups(all P <0.05).13 -15d after treatment:the above indictors,the DPP 4 group was decreased obviously compared with the control group,MAGE [(2.97 ±0.86)mmol/L vs.(6.07 ±1.36)mmol/L,t =2.854],SDBG[(1.12 ±0.43)mmol/L vs.(1.91 ± 0.93)mmol/L,t =2.328],MBG[(7.44 ±0.93)mmol/L vs.(8.82 ±1.13)mmol/L,t =2.125],LAGE[(6.53 ± 1.21)mmol/L vs.(7.06 ±1.57)mmol/L,t =2.111],PT10.0[(4.72 ±2.37)% vs.(6.74 ±3.35)%,t =2.312] and PT3.9 [(3.05 ±2.60)% vs.(4.73 ±2.57)%,t =2.237],there were statistically significant differences between the two groups (P <0.05 or P <0.01).Conclusion The combination of DPP4 inhibitors and insulin four renforcement can improve blood glucose fluctuation in patients with type 1 diabetes,reduce the dosage of insulin and not increase incidence of hypoglycemic events.

AIM: To compare the fingerprints difference between total flavonoids and coumarins of Sarcandra glabra extract separated by macroporous adsorption resin. METHODS: To establish HPLC fingerprint chromatogram of Sarcandra glabra extract and to evaluate the constituents. RESULTS: The difference fingerprint was showed in total flavonoid part and coumarin part. CONCLUSION: Drug action part could be separated by macroporous adsorption resin and exosyndromed by Spectrogram fingerprints.

Objective:To investigate the prognosis and influencing factors of liver transplantation (LT) for hepatocellular carcinoma (HCC) using steatotic donor liver.Methods:The retrospective cohort study was conducted. The clinicopathological data of 152 pairs of donors and the corresponding recipients undergoing LT for HCC in the two medical centers [89 pairs in Shulan (Hangzhou) Hospital and 63 pairs in the First Affiliated Hospital of Zhejiang University School of Medicine] from January 2015 to December 2019 were collected. Of 152 donors, there were 131 males and 21 females, aged (48±12)years, and there were 130 cases with liver mild steatosis and 22 cases with liver moderate steatosis. Of 152 recipients, there were 138 males and 14 females, aged (52±9)years. Observation indicators: (1) follow-up, overall survival and tumor recurrence free survival of recipients; (2) influencing factors for overall survival and tumor recurrence free survival of recipients; (3) construction and validation of nomogram prediction model for overall survival and tumor recurrence free survival of recipients. Follow-up was conducted using outpatient examination and telephone interview to detect survival and tumor recurrence of recipients up to December 2020. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M( IQR). Count data were described as absolute numbers. The Kaplan-Meier method was used to calculate the survival time and draw survival curve, and the Log-Rank test was used for survival analysis. The COX regression model was used for univariate and multivariate analysis. The independent risk factors were brought into the R 3.6.2 software to construct nomogram prediction model and draw the receiver operating characteristic (ROC) curve. The accuracy and discrimination of the nomogram prediction model were evaluated using the area under curve (AUC) and the calibration curve. Results:(1) Follow-up, overall survival and tumor recurrence free survival of recipients. All the 152 recipients undergoing LT for HCC using steatotic donor liver were followed up for 45.8(27.6)months, with the overall survival time and tumor recurrence free survival time of 36.5(32.3)months and 30.4(34.6)months. The 1-year, 3-year overall survival rates and tumor recurrence free rates of the 152 recipients were 73.4%, 55.8% and 62.2%, 43.4%, respectively. (2) Influencing factors for overall survival and tumor recurrence free survival of recipients. Results of univariate analysis showed that the donor liver cold ischemia time (CIT), the donor liver warm ischemia time (WIT), graft-to-recipient weight ratio (GRWR), ABO compatibility, recipient body mass index (BMI), recipient tumor diameter, recipient tumor number, recipient tumor differentiation degree, recipient preoperative alpha fetoprotein (AFP) were related factors influencing the overall survival of recipients ( hazard ratio=6.26, 1.90, 2.47, 4.08, 0.55, 5.16, 3.62, 5.28, 2.65, 95% confidence interval as 3.01?13.03, 1.07?3.38, 1.36?4.49, 2.07?8.03, 0.31?0.98, 2.56?10.42, 1.95?6.72, 1.60?17.42, 1.48?5.01, P<0.05) and the donor liver CIT, GRWR, ABO compatibility, recipient tumor diameter, recipient tumor number, recipient tumor differentiation degree, recipient preoperative AFP were related factors influencing the tumor recurrence free survival of recipients ( hazard ratio=4.24, 2.53, 4.05, 3.39, 3.10, 5.19, 2.63, 95% confidence interval as 2.50?7.21, 1.54?4.17, 2.12?7.72, 2.04?5.62, 1.91?5.03, 2.04?13.18, 1.61?4.30, P<0.05). Results of multivariate analysis showed that donor liver CIT ≥8 hours, GRWR ≥2.5%, recipient tumor diameter ≥8 cm and recipient preoperative AFP ≥400 μg/L were independent risk factors influencing the overall survival of recipients ( hazard ratio=4.21, 2.58, 4.10, 2.27, 95% confidence interval as 1.98?8.96, 1.24?5.35, 1.35?12.43, 1.13?4.56, P<0.05) and donor liver CIT ≥8 hours, GRWR ≥2.5%, recipient tumor diameter ≥8 cm, recipient tumor number ≥3 and recipient preoperative AFP ≥400 μg/L were independent risk factors influencing the tumor recurrence free survival of recipients ( hazard ratio=3.37, 2.63, 2.42, 2.12, 2.22, 95% confidence interval as 1.70?6.67, 1.40?4.96, 1.04?5.66, 1.08?4.18, 1.26?3.90, P<0.05). (3) Construction and validation of nomogram prediction model for overall survival and tumor recurrence free survival of recipients. The donor live CIT, GRWR, recipient tumor diameter, recipient preoperative AFP were used to construct nomogram prediction model for overall survival of recipients and the donor liver CIT, GRWR, recipient tumor diameter, recipient tumor number, recipient preoperative AFP were used to construct nomogram prediction model for tumor recurrence free survival of recipients. The ROC curve showed that the AUC of the nomogram prediction model for overall survival of recipients was 0.84 (95% confidence interval as 0.76?0.92, P<0.05), with the optimal diagnostic value as 7.3 and the specificity and sensitivity as 87.6% and 70.0%. The AUC of the nomogram prediction model for tumor recurrence free survival of recipients was 0.79 (95% confidence interval as 0.71?0.87, P<0.05), with the optimal diagnostic value as 5.8 and the specificity and sensitivity as 97.4% and 52.5%. The calibration curve showed that the nomogram prediction model had good distinction for high risk recipients in overall survival and tumor recurrence free survival. Conclusion:Donor liver CIT ≥8 hours, GRWR ≥2.5%, recipient tumor diameter ≥8 cm and recipient preoperative AFP ≥400 μg/L are independent risk factors influencing the overall survival of recipients who underwent LT for HCC using steatotic donor liver and donor liver CIT ≥8 hours, GRWR ≥2.5%, recipient tumor diameter ≥8 cm, recipient tumor number ≥ 3 and recipient preoperative AFP ≥400 μg/L are independent risk factors influencing the tumor recurrence free survival of recipients.

Objective:To explore the value of aspartate aminotransferase(AST)and platelet (PLT)ratio index(APRI)in the prognosis of liver transplantation(LT)for hepatocellular carcinoma and establish a nomogram model for evaluating its clinical application potential.Methods:From January 2015 to December 2019, retrospective review was conducted for clinical data of LT for hepatocellular carcinoma(HCC)at First Affiliated Hospital of Zhejiang University School of Medicine and Shulan(Hangzhou)Hospital(601 cases). They were randomized into two groups of modeling (399 cases)and validation(202 cases)and then divided into low and high APRI groups according to the APRI value at Month 1 post-transplantation. The independent risk factors of recurrence and prognosis post-LT were screened in modeling group using univariate and multivariate Cox regression analyses and were further used for constructing a nomogram prediction model. The receiver operating characteristic curve(ROC)and survival curve were utilized for verifying the accuracy of nomogram prediction model.Results:Univariate and multivariate Cox regression analyses revealed that independent risk factors for the prognosis of HCC-LT included cold ischemic time(CIT) >8 h, beyond Hangzhou criteria, surgical bleeding volume >1 000 ml and APRI >1.5. The AUC of HCC-LT recurrence prediction model was 0.734(95%CI: 0.681~0.787)and 0.749(95%CI: 0.671~0.817)in modeling and validation groups; the AUC of HCC-LT mortality prediction model was 0.735(95%CI: 0.679~0.790)and 0.758(95%CI: 0.682~0.834)in modeling and validation groups.Conclusions:APRI>1.5 is an independent risk factor for postoperative recurrence and mortality after HCC-LT. The nomogram prediction model based upon CIT, Hangzhou criteria, intraoperative bleeding volume and APRI can effectively predict the recurrence and overall survival of LT for HCC.