1.Vascular endothelial growth factor 165 promotes proliferation of human adipose-derived mesenchymal stem cells
Yu WANG ; Zhitu ZHU ; Junjiang CHEN
Chinese Journal of Tissue Engineering Research 2015;(28):4485-4492
BACKGROUND:Autologous fat transplantation has been widely used in soft tissue defect repair and cosmetic surgery, and the 1-year transplant survival rate is 20%-80%. Therefore, the establishment of timely and adequate blood supply at early period after transplantation is very important for the survival of transplanted fat tissues.
OBJECTIVE:To observe the proliferation of human adipose-derived mesenchymal stem cel s transfected with vascular endothelial growth factor 165.
METHODS:Human adipose-derived mesenchymal stem cel s were subcultured in vitro. Recombinant adenovirus carrying vascular endothelial growth factor 165 and blank virus were respectively transferred into adipose-derived mesenchymal stem cel s. Cel s cultured normal y served as blank group.
RESULTS AND CONCLUSION:Compared with the control and blank groups, the expressions of vascular endothelial growth factor 165 mRNA and protein were higher in the experimental group (P<0.05). Experimental findings suggest that the recombinant adenovirus carrying vascular endothelial growth factor 165 transferred into adipose-derived mesenchymal stem cel s cannot only maintain the expression of target protein but also obviously promote the proliferation of adipose-derived mesenchymal stem cel s.
2.Clinical efficacy and influencing factors of the laparoscopic Roux-en-Y gastric bypass and metformin in the treatment of obese patients with type 2 diabetes mellitus
Jie ZHAO ; Junjiang LI ; Yunhai ZHU ; Wen LI
Chinese Journal of Digestive Surgery 2017;16(6):575-581
Objective To investigate the clinical efficacy of the laparoscopic Roux-en-Y gastric bypass (LRYGB) and metformin in the treatment of obese patients with type 2 diabetes mellitus,and influencing factors of remission rate of diabetes.Methods The case-control study was conducted.The clinical data of 172 obese patients with type 2 diabetes mellitus who were admitted to the First People's Hospital of Shangqiu (43 patients) and the First Affiliated Hospital of Sun Yat-sen University (129 patients) from June 2010 to June 2015 were collected.Of 172 patients,82 undergoing LRYGB were allocated into the group A and 90 taking oral metformin were allocated into the group B.Observation indicators:(1) follow-up situations;(2) comparison of metabolic indices after treatment between the 2 groups;(3) influencing factors analysis of remission rate of diabetes in patients undergoing LRYGB;(4) influencing factors analysis of remission rate of diabetes in patients taking oral metformin.Follow-up using outpatient examination and telephone interview was performed to detect occurrence of treatment-related complications up to January 2017,and metabolic indices were measured regularly.Measurement data with normal distribution were represented as ±s and comparison between groups was analyzed using the independent-sample t test.Repeated measurement data were analyzed by the repeated measures ANOVA.Comparisons of count data were evaluated by the chi-square test.The univariate analysis and multivariate analysis were respectively done using the chi-square test and Logistic regression model.Results (1) Follow-up situations:172 patients were followed up after treatment for 19-43 months,with a median time of 28 months.During the follow-up,5 patients complicated with mild diarrhea and 1 complicated with iron deficiency anemia at 1 year postoperatively were improved by symptomatic treatment in the group A,and there was no treatment-related complications in the group B.(2) Comparison of metabolic indices after treatment between 2 groups:body mass,BMI,2-hour postprandial blood glucose (2HPBG),2-hour postprandial serum C-peptide,glycosylated hemoglobin (GHb),fasting insulin,2-hour postprandial insulin (2HPI),low-density lipoprotein (LDL) and cases with hypertension in the group A were (89±6) kg,(31.5±2.0) kg/m2,(19.4±3.9) mmol/L,(3.52± 0.32) μg/L,15.7% ±5.3%,(8.0± 1.4) uIU/L,(20.6± 2.5) uIU/L,(3.7 ± 1.3) mmol/L,24 before LRYGB and(77±16)kg,(24.2±2.9)kg/m2,(10.6±2.6) mmol/L,(7.19± 2.23) μg/L,5.3%±4.5%,(9.2± 4.3)uIU/L,(28.3±2.9)uIU/L,(2.2±2.1)mmol/L,9 after LRYGB,respectively,with statistically significant differences between preoperative and postoperative indicators (F=2.112,3.026,1.253,2.107,1.257,3.473,1.223,2.584,x2 =8.540,P < 0.05).Fasting blood glucose,2HPBG,fasting serum C-peptide,2-hour postprandial serum C-peptide,GHb,fasting insulin and 2HPI in the group B were (11.3±2.5)mmol/L,(18.5± 4.4) mmol/L,(1.54±0.33) μg/L,(3.57±0.91) μg/L,17.5% ±8.0%,(8.2± 1.3) uIU/L,(21.2±2.6) uIU/L before taking oral metformin and (6.6 ± 1.1) mmol/L,(10.2 ± 2.8) mmol/L,(3.52 ± 1.34) μg/L,(7.68 ± 1.94) μg/L,5.4% ±2.1%,(9.6± 3.9) uIU/L,(30.3± 3.1) uIU/L after taking oral metformin,respectively,with statistically significant differences between before and after taking oral metformin (F=1.245,3.224,3.127,2.064,3.672,2.074,1.137,P<0.05).Remission rate of diabetes and excess weight loss (EWL) in patients after treatment were 14.6%,80% ± 15% in the group A and 11.1%,60% ± 10% in the group B,respectively.There were statistically significant differences in body mass,BMI and EWL after treatment between the 2 groups (t=1.973,2.326,2.347,P<0.05),and no statistically significant difference in remission rate of diabetes between the 2 groups (x2 =0.477,P>0.05).(3) Influencing factors analysis of remission rate of diabetes in patients undergoing LRYGB:the results of univariate analysis showed that BMI,diabetes duration and LDL were factors affecting remission rate of diabetes in patients undergoing LRYGB,with statistically significant differences (x2=11.267,9.519,5.567,P<0.05).The results of multivariate analysis showed that diabetes duration < 10 years was an independent factor affecting good remission rate of diabetes in patients undergoing LRYGB,with statistically significant differences [OR=2.202,95% confidence interval (CI):1.418-3.420,P<0.05].(4) Influencing factors analysis of remission rate of diabetes in patients taking oral metformin:the results of univariate analysis showed that diabetes duration,GHb and LDL were factors affecting remission rate of diabetes in patients taking oral metformin,with statistically significant differences (x2 =6.306,7.758,4.652,P<0.05).The results of multivariate analysis showed that GHb < 15.0% was an independent factor affecting good remission rate of diabetes in patients taking oral metformin,with statistically significant differences (OR=3.167,95%CI:1.586-6.325,P<0.05).Conclusions LRYGB and oral metformin in the treatment of obese patients with type 2 diabetes mellitus are safe and effective,showing an equivalent remission rate of diabetes,and LRYGB had an advantage of weight loss.Diabetes duration < 10 years and GHb < 15.0% are respectively independent factors affecting good remission rate of diabetes in patients undergoing LRYGB and taking oral metformin.
3.Atrial fibrillation diagnosis algorithm based on improved convolutional neural network.
Yu PU ; Junjiang ZHU ; Detao ZHANG ; Tianhong YAN
Journal of Biomedical Engineering 2021;38(4):686-694
Atrial fibrillation (AF) is a common arrhythmia, which can lead to thrombosis and increase the risk of a stroke or even death. In order to meet the need for a low false-negative rate (FNR) of the screening test in clinical application, a convolutional neural network with a low false-negative rate (LFNR-CNN) was proposed. Regularization coefficients were added to the cross-entropy loss function which could make the cost of positive and negative samples different, and the penalty for false negatives could be increased during network training. The inter-patient clinical database of 21 077 patients (CD-21077) collected from the large general hospital was used to verify the effectiveness of the proposed method. For the convolutional neural network (CNN) with the same structure, the improved loss function could reduce the FNR from 2.22% to 0.97% compared with the traditional cross-entropy loss function. The selected regularization coefficient could increase the sensitivity (SE) from 97.78% to 98.35%, and the accuracy (ACC) was 96.62%, which was an increase from 96.49%. The proposed algorithm can reduce the FNR without losing ACC, and reduce the possibility of missed diagnosis to avoid missing the best treatment period. Meanwhile, it provides a universal loss function for the clinical auxiliary diagnosis of other diseases.
Algorithms
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Atrial Fibrillation/diagnosis*
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Electrocardiography
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Humans
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Neural Networks, Computer
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Stroke