1.Study on chiral recognition for the glimepiride and glimepiride-cis-isomer by applying three amino acid (D-Lysine, L-Glutamine and L-Tyrosine) as chiral probes based on electrospray ionization mass spectrometry
Ying GENG ; Caiyu ZHANG ; Tianxing DAI ; Lan HE
Drug Evaluation Research 2017;40(6):792-796
Objective Chiral recognition for the glimepiride and glimepiride-cis-isomer by applying three amino acid (D-Lysine,L-Glutamine and L-Tyrosine) as chiral probes based on electrospray ionization mass spectrometry (ESI-MS) was achieved.Methods glimepiride/glimepiride-cis-isomer solutions were mixed with three amino acid solutions.The complex was extracted by ESI-MS and then the fragmentation abundance was investigated applying collision induced dissociation (CID) by MS/MS,which is the basis of chiral recognition for glimepiride and glimepiride-cis-isomer.Results Chiral recognition effect was achieved with the recognition rate (R) 1.61,2.92 and 2.17 for D-Lysine,L-Glutamine and L-Tyrosine respectively.Conclusion 3 kinds ofchiral amino acids were used as probes to distinguish between stereoisomers,and rapid identification of glimepiride and glimepiride cis isomer by mass spectrometry come true for the first time.
2.Prediction of Microvascular Complications in Type 2 Diabetes Mellitus Based on Deep Belief Network
Ruiyao LI ; Jingyi XU ; Haoyu DAI ; Huiwen SUN ; Ying BAO ; Lvchun HUA ; Tianxing WU
Journal of Medical Informatics 2024;45(7):68-73
Purpose/Significance A prediction model is constructed based on real-world data to achieve prediction and early screening of type 2 diabetic microvascular complications.Method/Process Based on the real world data of Nanjing Drum Tower Hospital in the past 10 years,a particle swarm optimization based deep belief network(PSO-DBN)prediction model for microvascular complica-tions in type 2 diabetes mellitus is constructed by taking test results and medical record documents into consideration.Result/Conclusion The PSO-DBN model can predict diabetic microvascular complications,and the performance is better than that of random forest and sup-port vector machine(SVM)benchmark models,it provides references for the research of disease prediction model of real-world data.
3.Establishment of a non-venous bypass orthotopic liver transplantation model in Bama miniature pigs
Qiao SU ; Zhenyu YU ; Wenwen LI ; Linsen YE ; Tianxing DAI ; Rongpu LIANG ; Rongqiang LIU ; Guozhen LIN ; Guangyin ZHAO ; Wuguo LI ; Guoying WANG ; Guihua CHEN
Organ Transplantation 2019;10(1):55-
Objective To establish a non-venous bypass orthotopic liver transplantation model in Bama miniature pigs with high repeatability and stability. Methods Twelve Bama miniature pigs were randomly divided into the donor group (
4.Effect of different liver function Child-Pugh classification on clinical prognosis of hepatocellular carcinoma recipients after liver transplantation
Guozhen LIN ; Tianxing DAI ; Rongqiang LIU ; Mingbin DENG ; Guoying WANG ; Shuhong YI ; Hua LI ; Yang YANG ; Guihua CHEN
Organ Transplantation 2019;10(3):308-
Objective To evaluate the effect of the different Child-Pugh classification on the recurrence and survival of hepatocellular carcinoma (HCC) recipients after liver transplantation. Methods Clinical data of 125 HCC recipients undergoing liver transplantation were retrospectively analyzed. The 3-year disease-free survival (DFS) and overall survival (OS) rates were calculated by Kaplan-Meier survival curve. The independent risk factors probably affecting the recurrence and survival of HCC recipients after liver transplantation were identified by using Cox's proportional hazards regression model. Results The median follow-up time was 25.6 months. The 3-year DFS and OS rates were 68.4% and 65.7% for all patients. The 3-year DFS and OS rates in 113 patients with Child-Pugh class A/B HCC were 68.6% and 66.2%, whereas 66.7% and 65.6% for 12 patients with Child-Pugh class C HCC with no statistical significance (all
5.Clinical significance of apolipoprotein F in prognosis of patients with hepatocellular carcinoma
Boxuan ZHOU ; Zhicheng YAO ; Zhiyong XIONG ; Ruixi LI ; Tianxing DAI ; Mingxing XU ; Weiming FAN ; Zheng ZHOU ; Hao LIANG ; Meihai DENG ; Yunbiao LING
Chinese Journal of Hepatic Surgery(Electronic Edition) 2018;7(1):73-76
Objective To investigate the expression of apolipoprotein (Apo) F in hepatocellular carcinoma (HCC) and its application value in the prognosis of patients with HCC. Methods 50 HCC samples were procured from patients undergoing surgical resection in the Third Affiliated Hospital of Sun Yat-sen University between September 2015 and September 2016, and all the samples were confirmed by postoperative pathological examination. The informed consents of all patients were obtained and the local ethical committee approval was received. There were 37 males and 13 females, aged from 31-67 with a median age of 53 years old. The expression of ApoF mRNA in HCC tissues was detected by RT-PCR. The expression profile was analyzed by using data from the Gene Expression Omnibus (GEO). The expression of ApoF between two groups were compared by t test. Correlation analysis of clinical related parameter was conducted by Chi-square test, and survival prognosis was analyzed by Kaplan-Meier test and Log rank test. Results The average relative expression of ApoF mRNA in HCC tissues was 0.15±0.07, significantly lower than 0.55±0.09 in the adjacent tissues (t=-6.26, P<0.05). GEO online analysis showed that expression of ApoF was significantly correlated with the status of liver cirrhosis, and most HCC patients with liver cirrhosis presented low expression of ApoF (χ2=4.626, P<0.05). The 5-year disease-free survival was respectively 55.9% and 32.0% in ApoF high expression group and low expression group, where significant difference was observed (χ2=3.939, P<0.05). Conclusions Low expression of ApoF exists in HCC tissues, and it is related to the liver cirrhosis status of patients. Patients with low ApoF expression present poorer prognosis. ApoF plays a role in inhibiting the cancer.