Bibliometrics ; China ; Occupational Health ; statistics & numerical data ; Periodicals as Topic ; statistics & numerical data

Objective To assess the safety, tolerability and efficacy of preoperative low dose intravenous amiodarone in the prevention of atrial fibrillation (AF) after off-pump coronary artery bypass grafting (OPCAB). Methods Two hundred patients with coronary atheroselerotic heart disease underwent selected OPCAB and were randomly divided into two groups: control group (100 cases) and experimental group (100 cases). Patients in control group were given conventional medicines and placebo, and patients in experimental group were treated with low dose intravenous amiodarone daily for 4 days before surgery. They were given conventional medicines after surgery. Results After the off-pump coronary artery bypass grafting, the incidence of AF, ventricular rate and the duration of AF in the experimental group were lower than those in control group [15% vs. 41%, χ2=16.766, P=0.000; (126.0±20.8) times/ min vs. (150.0±25.6) times/ min, t=0.478, P =0. 017; (8. 0±8. 6) h vs. (12.0±9.6) h, t=0. 439, P=0. 019]. No significant difference were found in the incidence of side effect between low close amiodarone group and the control group. Conclusions Prophylactic application of low dose intravenous arniodarone before off-pump coronary artery bypass grafting can safely and effectively reduce the postoperative ventricular rate and the incidence of AF, shorten the duration of AF, promote the rehabilitation and slightly improve the clinical symptoms.

Pattern recognition of thermophilic and mesophilic proteins were studied through principle component analysis, partial least-square regression and BP neural network. The results showed that the fitting accuracy of the three methods was 92%, 95% and 98%, respectively. And the forecasting accuracy was 60%, 72.5% and 72.5%, respectively. The best forecasting accuracy for thermophilic proteins was 75%, and for mesophilic proteins was 85%. A mathematical model was established and the biological meaning of it was expatiated on, a new method to discriminate the thermophilic and mesophilic proteins based on their sequences was established here.
Amino Acids ; chemistry ; metabolism ; Discriminant Analysis ; Hot Temperature ; Least-Squares Analysis ; Models, Theoretical ; Neural Networks (Computer) ; Pattern Recognition, Automated ; Principal Component Analysis ; Proteins ; chemistry ; genetics

In this paper, a prediction model for amino acid composition and optimum pH of xylanase in G/11 family was established in terms of an artificial neural networks based on uniform design. Results showed that the calculated and predicted pHs fitted the optimum pHs of xylanase very well and the MAPEs (Mean mean Absolute Percent Error) were 3.02% and 4.06%, the MSEs (Mean Square Error) were 0.19 and 0.19 pH unit, the MAE (Mean Absolute Error) were 0.11 and 0.19 pH unit, respectively. It was better in fittings and predictions compared with the reported model based on stepwise regression.
Amino Acids ; chemistry ; Hydrogen-Ion Concentration ; Models, Chemical ; Neural Networks (Computer) ; Xylan Endo-1,3-beta-Xylosidase ; chemistry ; isolation & purification

In this work, the dipeptide composition of 3216 thermophilic and 4007 mesophilic protein sequences was systematically analyzed. We found that the thermophilic proteins contained more dipeptides such as EE, EK, KE, VE, EI, KI, EV, KK, VK and IE, whereas less dipeptides such as AA, LL, LA, AL, QA, QL, AQ, LT, TL and EQ. Based on this information, a statistical method for discriminating thermophilic and mesophilic proteins was developed. Our approach correctly picked up the thermophilic proteins with the accuracy of 94.0% and 89%, respectively, for the testing sets of 382 and 73 thermophilic proteins. And for the testing 325 and 73 mesophilic proteins, the accuracy was 85.2% and 89%, respectively. The influence of specific dipeptides on discrimination was also discussed.
Amino Acids ; chemistry ; Bacteria ; chemistry ; Bacterial Proteins ; chemistry ; Dipeptides ; chemistry ; Discriminant Analysis ; Hot Temperature ; Sequence Analysis, Protein ; Thermodynamics

Objective To assess temporary filter in the inferior vena cava (IVC) for trapping thrombus and preventing pulmonary embolism in patients with deep vein thrombosis. Methods In 58 cases of deep vein thrombus in single lower extremity, Antheor temporary filter (ATF) was introduced into IVC prior to anticoagulation and/or vascular intraluminal procedures. Results All IVC filters were successfully introduced. No symptomatic pulmonary embolism was documented. ATF was removed after a mean of 12.0?2.0 days. Thrombus was trapped in 46 cases (79.3%). Thrombus more than 1 cm in size was trapped in 2 cases. Conclusion Temporary filter was safe and effective in prevention of pulmonary embolism.

Objective To investigate the effect of interleukin 6 (IL-6) on the growth and proliferation of human pancreatic cancer cell line Capan-2 and the signal transduction pathway. Methods MTr method was used to detect the effect of IL-6 of different concentrations on the growth and proliferation of Capan - 2 cells; cell apoptosis was detected by flow cytometry; the intracellular localization of phosphorylated STAT3 (P-STAT3) was determined by immunocytochemistry and western blot were used to detect P-STAT3, bcl-xl and Cyclin D1 in Capan-2 cells stimulated by IL-6. Results IL-6 (100 ng/ml) could remarkably promote the growth of Capan-2 cells from 1 to 4. 965 ± 0. 18 (P < 0. 05) ; the percentage of apoptosis decreased significantly from (3.21 ±0.23)% to (1.98 ±0.67)% (P <0.05) ; the expressions of P-STAT3, bcl-xl, Cyelin D1 increased significantly (P < 0.05), and the expressions of bcl-xl was positively correlated with that of P-STAT3 (r =0.985, P =0.015) ; the expressions of Cyclin DI was also positively correlated with that of P-STAT3(r=0.914,P=0.036),Conclusions IL-6 activate JAK/STAT signal transduction pathway,which played an important role in the growth and proliferation of Capan-2 cells in the presence of IL-6.

In order to isolate genes related with the osmoadaptation and glycerol metabolism of Candida glycerinogenes, a transformation system based on the dominant selectable marker Zeocin and restriction enzyme-mediated integration (REMI) was established. Effects of seven restriction enzymes on transformation efficiency of C.glycerinogenes were tested. Transformation conditions were optimized in the presence of Hind III. Under the optimal conditions of OD_ 600 ≈1.3, voltage of 1.5 kV, 2.0?10~9 competent cells/mL, 100 units of Hind III added, the transformation efficiency was up to 129 trnaformants/?g DNA. 58% of transformants were stable on nonselective medium. These results suggest that REMI technique would be beneficial to the genetic transformation of C.glycerinogenes.

In this paper, the Boosting-based decision tree ensemble classifiers were applied to discriminate thermophilic and mesophilic proteins. Three methods, namely, self-consistency test, 5-fold cross-validation and independent testing with other dataset, were used to evaluate the performance and robust of the models. Logitboost, as a novel classifier in Boosting algorithm, performed better than Adaboost. The overall accuracy of the three methods was 100%, 88.4% and 89.5%, respectively. It was demonstrated that LogitBoost performed comparably or even better than that of neural network, a very powerful classifier widely used in biological literatures. The influence of protein size on discrimination was addressed. It is anticipated that the power in predicting many bio-macromolecular attributes will be further strengthened if the Boosting and some other existing algorithms can be effectively complemented with each other.
Algorithms ; Decision Trees ; Molecular Weight ; Neural Networks (Computer) ; Proteins ; chemistry ; classification