Objective: Coronary artery was ligated to study the characteristics of myocardial ischemia in rats. Methods: The left anterior descending artery was ligated to establish the rat model of acute myocardial ischemia. All...Objective: Coronary artery was ligated to study the characteristics of myocardial ischemia in rats. Methods: The left anterior descending artery was ligated to establish the rat model of acute myocardial ischemia. All animals were divided into normal control group, sham operation group and model group. 1, 2 and 4 weeks after modeling, ECG (II lead) was recorded, the weight of whole heart and left ventricle were recorded and organ indexes were calculated;myocardial infarct size was determined by TTC;CK, CK-MB, LDH, AST contents of serum were detected;cardiac function was determined by left ventricular intubation via carotid artery and left ventricular was taken to perform pathological observation. Results: 1 week after modeling, compared with the sham operation group, the ECG and heart function index of rats model had significant change, but the myocardial enzymes did not change significantly;4 weeks after modeling, the ECG and cardiac function of animal models had a recovery trend, but the myocardial enzymes, including CK, CK-MB, LDH, AST, were significantly increased;1 week after modeling, the left ventricular indexes of model rats were increased;the infarct size was about 30%, myocardial cell necrosis and granulation tissue hyperplasia could be observed in infarction area;with the modeling time extended, from 2 to 4 weeks, the left ventricular and heart indexes of model group were significantly increased;the infarct size was relatively constant, left ventricular became thickly, and fibrous or granulation tissue was significantly proliferated in infarction area under microscope. Conclusion: The indexes of myocardial ischemia induced by coronary artery ligation in rats are different at different time points. The results suggest that the time point should be selected to observe the anti-myocardial ischemia effect of the subjects from different aspects.展开更多
In cancer patients, especially terminal patients, the family members of the patients will develop more serious sadness and find it difficult to face death rationally, which affects the quality of life and activities. ...In cancer patients, especially terminal patients, the family members of the patients will develop more serious sadness and find it difficult to face death rationally, which affects the quality of life and activities. Because of this, in the clinical treatment of oncology patients, strengthening hospice care for family members, doing a good job of death education, assisting them to face and participate in the clinical treatment of oncology in a positive way, and avoiding excessive grief can simultaneously improve the quality of life of patients and their families.展开更多
By using the numerical renormalization group(NRG)method,we construct a large dataset with about one million spectral functions of the Anderson quantum impurity model.The dataset contains the density of states(DOS)of t...By using the numerical renormalization group(NRG)method,we construct a large dataset with about one million spectral functions of the Anderson quantum impurity model.The dataset contains the density of states(DOS)of the host material,the strength of Coulomb interaction between on-site electrons(U),and the hybridization between the host material and the impurity site(Γ).The continued DOS and spectral functions are stored with Chebyshev coefficients and wavelet functions,respectively.From this dataset,we build seven different machine learning networks to predict the spectral function from the input data,DOS,U,andΓ.Three different evaluation indexes,mean absolute error(MAE),relative error(RE)and root mean square error(RMSE),are used to analyze the prediction abilities of different network models.Detailed analysis shows that,for the two kinds of widely used recurrent neural networks(RNNs),gate recurrent unit(GRU)has better performance than the long short term memory(LSTM)network.A combination of bidirectional GRU(BiGRU)and GRU has the best performance among GRU,BiGRU,LSTM,and BiLSTM.The MAE peak of BiGRU+GRU reaches 0.00037.We have also tested a one-dimensional convolutional neural network(1DCNN)with 20 hidden layers and a residual neural network(ResNet),we find that the 1DCNN has almost the same performance of the BiGRU+GRU network for the original dataset,while the robustness testing seems to be a little weak than BiGRU+GRU when we test all these models on two other independent datasets.The ResNet has the worst performance among all the seven network models.The datasets presented in this paper,including the large data set of the spectral function of Anderson quantum impurity model,are openly available at https://doi.org/10.57760/sciencedb.j00113.00192.展开更多
文摘Objective: Coronary artery was ligated to study the characteristics of myocardial ischemia in rats. Methods: The left anterior descending artery was ligated to establish the rat model of acute myocardial ischemia. All animals were divided into normal control group, sham operation group and model group. 1, 2 and 4 weeks after modeling, ECG (II lead) was recorded, the weight of whole heart and left ventricle were recorded and organ indexes were calculated;myocardial infarct size was determined by TTC;CK, CK-MB, LDH, AST contents of serum were detected;cardiac function was determined by left ventricular intubation via carotid artery and left ventricular was taken to perform pathological observation. Results: 1 week after modeling, compared with the sham operation group, the ECG and heart function index of rats model had significant change, but the myocardial enzymes did not change significantly;4 weeks after modeling, the ECG and cardiac function of animal models had a recovery trend, but the myocardial enzymes, including CK, CK-MB, LDH, AST, were significantly increased;1 week after modeling, the left ventricular indexes of model rats were increased;the infarct size was about 30%, myocardial cell necrosis and granulation tissue hyperplasia could be observed in infarction area;with the modeling time extended, from 2 to 4 weeks, the left ventricular and heart indexes of model group were significantly increased;the infarct size was relatively constant, left ventricular became thickly, and fibrous or granulation tissue was significantly proliferated in infarction area under microscope. Conclusion: The indexes of myocardial ischemia induced by coronary artery ligation in rats are different at different time points. The results suggest that the time point should be selected to observe the anti-myocardial ischemia effect of the subjects from different aspects.
文摘In cancer patients, especially terminal patients, the family members of the patients will develop more serious sadness and find it difficult to face death rationally, which affects the quality of life and activities. Because of this, in the clinical treatment of oncology patients, strengthening hospice care for family members, doing a good job of death education, assisting them to face and participate in the clinical treatment of oncology in a positive way, and avoiding excessive grief can simultaneously improve the quality of life of patients and their families.
基金Project supported by the National Natural Science Foundation of China(Grant No.12174101)the Fundamental Research Funds for the Central Universities(Grant No.2022MS051)。
文摘By using the numerical renormalization group(NRG)method,we construct a large dataset with about one million spectral functions of the Anderson quantum impurity model.The dataset contains the density of states(DOS)of the host material,the strength of Coulomb interaction between on-site electrons(U),and the hybridization between the host material and the impurity site(Γ).The continued DOS and spectral functions are stored with Chebyshev coefficients and wavelet functions,respectively.From this dataset,we build seven different machine learning networks to predict the spectral function from the input data,DOS,U,andΓ.Three different evaluation indexes,mean absolute error(MAE),relative error(RE)and root mean square error(RMSE),are used to analyze the prediction abilities of different network models.Detailed analysis shows that,for the two kinds of widely used recurrent neural networks(RNNs),gate recurrent unit(GRU)has better performance than the long short term memory(LSTM)network.A combination of bidirectional GRU(BiGRU)and GRU has the best performance among GRU,BiGRU,LSTM,and BiLSTM.The MAE peak of BiGRU+GRU reaches 0.00037.We have also tested a one-dimensional convolutional neural network(1DCNN)with 20 hidden layers and a residual neural network(ResNet),we find that the 1DCNN has almost the same performance of the BiGRU+GRU network for the original dataset,while the robustness testing seems to be a little weak than BiGRU+GRU when we test all these models on two other independent datasets.The ResNet has the worst performance among all the seven network models.The datasets presented in this paper,including the large data set of the spectral function of Anderson quantum impurity model,are openly available at https://doi.org/10.57760/sciencedb.j00113.00192.
基金supported by the National Natural Science Foundation of China(61874007,12074028,and 52102152)Shandong Provincial Major Scientific and Technological Innovation Project(2019JZZY010209)+2 种基金the Key-area Research and Development Program of Guangdong Province(2020B010172001)the Fundamental Research Funds for the Central Universities(buctrc201802,buctrc201830,and buctrc202127)Beijing Outstanding Young Scientist Program(BJJWZYJH01201910010024)。
