Humans ; Indicators and Reagents ; supply & distribution ; Occupational Health

0.05).3.IL-8-251A and 781C were lingkaged(D′=0.348?0.019,r2=0.114 P

Objective To evaluate the effectiveness of regional electrocardiographic consultation network for primary medical institutions.Methods A distance electrocardiographic ( ECG ) consultation center was established in Yuyao People′s Hospital in September 2012, which was connected to 56 regional primary medical through internet.The online consultation was provided by ECG specialists in the center for general practitioners in regional primary health care institutions.Additionally, the ECG training course was also conducted monthly for general practitioners.The 2-year data of ECG consultation were retrospectively reviewed and the effectiveness of the consultation network was evaluated.Results During the past two years, 86 593 electrocardiograms were uploaded by primary medical institutions, in which 3 976 were required for consultation. The monthly number of electrocardiograms sent by general practitioners was increased from 3 269 ±290 in the first year to 3 947 ±376 in the second year ( P<0.01 ) .However, the requirements of ECG consultation were not significantly different between two years.Compared to the first year, the rates of consultation requirements, misdiagnosis and missed diagnosis for ECGs of atrial and ventricular premature beats, atrial fibrillation, supraventricular tachycardia, left and right bundle branch blocks,ⅠandⅡdegree atrioventricular blocks and myocardial infarction were significantly decreased ( all P<0.05) in the second year;meanwhile there was a tendency towards the reduction for ECGs of atrial flutter and Ⅲ degree atrioventricular block in the second year.Conclusion The regional electrocardiographic consultation network is effective to improve the capability of primary medical institutions in electrocardiographic diagnosis.

Objective To summarize and analyze the epidemiological and clinical characteristics of COVID-19 Omicron variant cases in makeshift hospital, and the influence of age, sex and vaccination status on the disease duration, so as to provide reference for the prevention and control of the COVID-19 epidemic. Methods The epidemiological and clinical characteristics of COVID-19 cases admitted to makeshift hospital of National Convention and Exhibition Center (Shanghai) from April 9 to May 31, 2022 were retrospectively described and analyzed, and further cohort analysis was conducted to determine the influence of age, sex and vaccination status on the disease duration of COVID-19 cases in the author's branch hospital. Results Among the 174 466 COVID-19 cases in makeshift hospital, most of them were male, accounting for 59.38%. The infected cases were mainly young and middle-aged people aged 18-59 years old, accounting for 83.50%, followed by 12.30% of the elderly group over 60 years old; the average hospital stay was 7.40 days; the proportion of patients with fever was less than 27.79%; 15.37% (26 817/174 466) of the patients complicated with underlying diseases, and the top three were hypertension, diabetes and coronary heart disease. The proportion of people who received COVID-19 vaccine accounted for 79.56% (13 799/17 956), of which the highest proportion of three doses was 44.09%. The disease duration of 17 956 COVID-19 cases in the author's branch of makeshift hospital was 10.18 (7.34, 13.05) days. The disease duration in the elderly group was the longest with 11.34 (8.35, 14.37) days, followed by 11.17 (9.07, 14.33) days in the preschool group, 10.37 (8.14, 13.34)· days in the middle-aged group, 10.07 (7.37, 12.37) days in the school-age group, and 9.34 (7.05, 12.16) days in the young group. There was significant difference in the overall distribution of disease duration among the five groups (H=550.479 P<0.01). The disease duration in each age group basically showed a V-shaped distribution. The disease duration was 10.27 (7.34, 12.57) days in males and 10.10 (7.25, 13.09) days in females, and there was no significant difference (Z=-1.505 P>0.05). The disease duration of vaccinated patients was 10.24 (7.35, 13.05) days, and that of unvaccinated patients was 9.47 (7.09, 12.47) days. There was significant difference between the two groups (Z=-4.338 P<0.01). Conclusions COVID-19 Omicron variant cases have a high proportion of males, mainly young and middle-aged, and the proportion of fever patients is less than 30%. The disease duration is significantly lower than that of the original strain in Wuhan, and shows "V" distribution with each age group. Sex had no effect on the disease duration. COVID-19 vaccination did not have a clinical effect on the disease duration.

Female ; Humans ; Neoplasms ; physiopathology ; Thoracic Neoplasms ; pathology ; physiopathology ; Thoracic Wall ; pathology ; Young Adult

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

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

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