Objective To examine the sensitivity of human colorectal carcinoma cells to 5-fluorouracil treatment by stable transfection of extrinsic Fas-associated death domain protein(FADD) gene，both in vitro and in vivo，so as to investigate the feasibility of combination therapy of FADD gene and 5-fluorouracil in human colorectal carcinoma.Methods①RT-PCR and Western blotting were used to detect the expressions of both mRNA and protein of FADD gene in SW480／FADD (stably transfected with FADD)，SW480／neo and SW480 cells.②After treatment with 5-fluorouracil as an apoptotic inducer，in vitro cell growth activities were investigated by MTT assay.Cell apoptosis and its rates were determined by terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling(TUNEL)assay and flow cytometry of annexin V-FITC／PI staining.The expressions of caspase-8 and caspase-3 were examined by Western blotting.③To examine the inhibitory effect of FADD gene combined with 5-fluorouracil, tumor xenograft model was prepared for in vivo study.Results ① Compared with SW480 and SW480/neo cells, FADD mRNA and protein levels of SW480/FADD cells were higher (P<0.05). ② Inhibitory rate of SW480/FADD cells was remarkably higher than SW480 and SW480/neo cells (P＜0.05 ). ③ Forty-eight hours after treatment with 5-fluorouracil (10 mg/L), the apoptotic rate of SW480/FADD cells was (33.3 ± 4.5)%, which was higher than SW480 [(13. 9 ± 3. 2)%3 and SW480/neo [(14. 1 ± 3. 4)%], with significant difference (P< 0.05).④ Forty-eight hours after treatment with 5-fluorouracil (10 mg/L),procaspase-8 and procaspase-3 expressions of SW480 and SW480/neo cells were higher than SW480/FADD cells, whereas their cleaved caspase-8 and cleaved caspase-3 expressions were lower than SW480/FADD cells (P＜0. 05).⑤ In in vivo study, SW480/FADD cells increased the efficacy of fluorouracil-induced inhibition of tumor growth in nude mice. ConclusionsStable overexpression of FADD increases sensitivity of the cells to 5-fluorouracil and combination of FADD with 5-fluorouracil will he a promising alternative in colorectal cancer treatment.

In order to express and purify the catalytic domain of SHP-1/SHP-2 (named as D1C and D2C respectively) and determine their kinetics, the constructed D1C and D2C plasmids were transformed into Escherichia coli BL21 and the expression was induced with IPTG. The harvested cells were suspended in extraction buffer. After sonication, the solution was applied to HPLC and the results were confirmed by SDS-PAGE. The purified peptides were further subjected to kinetic specificity study using synthetic phosphotyrosine (pY) as substrate by malachite green method and analyzed by Lineweaver-Burk plot calculation. From this study, we found D1C and D2C were expressed successfully in soluble state in Escherichia coli BL21 and purified efficiently with HPLC system. The molecular weight of D1C was 34.6 kD, and its Michaelis constant (K(m)) was 2.04 mmol catalytic constant (K(cat)) was 44.98 s(-1), specific constant (K(cat)/K(m)) was 22.05 L/(mmol x s); the molecular weigh of D2C was 35.3 kD, and its Michaelis constant (K(m)) was 2.47 mmol, catalytic constant (K(cat)) was 27.45 s(-1), specific constant (K(cat)/K(m)) was L/(mmol x s). The enzyme activity of D1C is stronger than that of D2C.
Catalytic Domain ; Chromatography, High Pressure Liquid ; Escherichia coli ; genetics ; metabolism ; Kinetics ; Plasmids ; Protein Tyrosine Phosphatase, Non-Receptor Type 11 ; genetics ; metabolism ; Protein Tyrosine Phosphatase, Non-Receptor Type 6 ; genetics ; metabolism ; Recombinant Proteins ; genetics ; metabolism

Objective:To develop early gastric cancer (EGC) detection system of magnifying blue laser imaging (ME-BLI) model and magnifying narrow-band imaging (ME-NBI) model based on deep convolutional neural network, to compare the performance differences of the two models and to explore the effects of training methods on the accuracy.Methods:The images of benign gastric lesions and EGC under ME-BLI and ME-NBI were respectively collected. A total of five data sets and three test sets were collected. Data set 1 included 2 024 noncancerous lesions and 452 EGC images under ME-BLI. Data set 2 included 2 024 noncancerous lesions and 452 EGC images under ME-NBI. Data set 3 was the combination of data set 1 and 2 (a total of 4 048 noncancerous lesions and 904 EGC images under ME-BLI and ME-NBI). Data set 4: on the basis of data set 2, another 62 noncancerous lesions and 2 305 EGC images under ME-NBI were added (2 086 noncancerous lesions and 2 757 EGC images under ME-NBI). Data set 5: on the basis of data set 3, another 62 noncancerous lesions and 2 305 EGC images under ME-NBI were added(4 110 noncancerous lesions and 3 209 EGC images under ME-NBI and ME-BLI). Test set A included 422 noncancerous lesions and 197 EGC images under ME-BLI. Test set B included 422 noncancerous lesions and 197 EGC images under ME-NBI. Test set C was the combination of test set A and B (844 noncancerous and 394 EGC images under ME-BLI and ME-NBI). Five models were constructed according to these five data sets respectively and their performance was evaluated in the three test sets. Per-lesion video was collected and used to compare the performance of deep convolutional neural network models under ME-BLI and ME-NBI for the detection of EGC in clinical environment, and compared with four senior endoscopy doctors. The primary endpoint was the diagnostic accuracy of EGG, sensitivity and specificity. Chi-square test was used for statistical analysis.Results:The performance of model 1 was the best in test set A with the accuracy, sensitivity and specificity of 76.90% (476/619), 63.96% (126/197) and 82.94% (350/422), respectively. The performance of model 2 was the best in test set B with the accuracy, sensitivity and specificity of 86.75% (537/619), 92.89% (183/197) and 83.89% (354/422), respectively. The performance of model 3 was the best in test set B with the accuracy, sensitivity and specificity of 86.91% (538/619), 84.26% (166/197) and 88.15% (372/422), respectively. The performance of model 4 was the best in test set B with the accuracy, sensitivity and specificity of 85.46% (529/619), 95.43% (188/197) and 80.81% (341/422), respectively. The performance of model 5 was the best in test set B, with the accuracy, sensitivity and specificity of 83.52% (517/619), 96.95% (191/197) and 77.25% (326/422), respectively. In terms of image recognition of EGC, the accuracy of models 2 to 5 was higher than that of model 1, and the differences were statistically significant ( χ2=147.90, 149.67, 134.20 and 115.30, all P<0.01). The sensitivity and specificity of models 2 and 3 were higher than those of model 1, the specificity of model 2 was lower than that of model 3, and the differences were statistically significant ( χ2=131.65, 64.15, 207.60, 262.03 and 96.73, all P < 0.01). The sensitivity of models 4 and 5 was higher than those of models 1 to 3, and the specificity of models 4 and 5 was lower than those of models 1 to 3, and the differences were statistically significant ( χ2=151.16, 165.49, 71.35, 112.47, 132.62, 153.14, 176.93, 74.62, 14.09, 15.47, 6.02 and 5.80, all P<0.05). The results of video test based on lesion showed that the average accuracy of doctors 1 to 4 was 68.16%. And the accuracy of models 1 to 5 was 69.47% (66/95), 69.47% (66/95), 70.53% (67/95), 76.84% (73/95) and 80.00% (76/95), respectively. There were no significant differences in the accuracy among models 1 to 5 and between models 1 to 5 and doctors 1 to 4 (all P>0.05). Conclusions:ME-BLI EGC recognition model based on deep learning has good accuracy, but the diagnostic effecacy is sligntly worse than that of ME-NBI model. The effects of EGC recognition model of ME-NBI combined with ME-BLI is better than that of a single model. A more sensitive ME-NBI model can be obtained by increasing the number of ME-NBI images, especially the images of EGG, but the specificity is worse.

Objective To discuss primary experience the clinical use of "All-seeing needle set" combined with Holmium laser to treat the single renal stone lesser than 2 cm in diameter through a super minimal tract (F12).Methods From January 2015 to December 2016,43 patients were enrolled into this retrospective study.There were 23 males and 20 females who were diagnosed as single renal stone less than 2 cm in diameter(age range from 23-65 years).There were 8 upper pole renal stones,13 lower pole renal stones and 22 renal pelvis stones.The mean stone size was (1.63 ± 0.32) cm in diameter (range from 1.2 cm to 2.0 cm)."All-seeing needle system" was applied during percutaneous puncture.After building a F12 minimal tract by fascia dilator,all patients received lithotripsy with Holmium laser.Indwelling catheters for 3 days and an F6 double-J tube was left for 2 weeks without a tube in the percutaneous tract after operation.Finally,KUB and/or urinary CT were used to check the results on day 1.Result All operations were completed successfully.The operation time was 23-65min [averaged (31.0 ±9.2) min].41 cases' renal stones were store free,and the 2 stone residues was clear with later extracorporeal shock wave lithotripsy.No severe complications occurred.Conclusion As an alternative to standard procedures for treatment of renal stones less than 2 cm in diameter,adopting "All-seeing needle set" with Holmium laser through a super minimal tract (F12) is safe,minimally invasive,fast and effective with a low complication rate.