The model of SD rats ligated at the proximate left anterior descend (LAD) of coronary was used. The number and dissociation constant of β receptor were studied by using receptor autoradiography to observe the changes...The model of SD rats ligated at the proximate left anterior descend (LAD) of coronary was used. The number and dissociation constant of β receptor were studied by using receptor autoradiography to observe the changes in β receptor and the effects of Radix Ginseng Rubra on cAMP in experimental ischemic myocardium. The result showed that the number of binding site in simple ligation group (B max =0.279) was obviously higher than that in sham operation group (B max =0.093) and the dissociation constant of simple ligation group (Kd=12.431) was higher than that of sham operation group (k d=1.319). There was a significant difference between the two groups ( P <0.05). It proved that the number of β receptor was increased and the activity was elevated in myocardial cell membranes after ligation of LAD. The myocardial cAMP level in simple ligation group (1293.96±519.36)×10 -3 nmol/g was much higher than that in sham operation group (774.44±210.55)×10 -3 nmol/g ; but the level of cAMP in ligation group after receiving Radix Ginseng Rubra treatment (805.02±362.48 pm/g) was obviously lower than that in simple ligation group ( P <0.01), which was close to the result of sham operation. The results indicated that Radix Ginseng Rubra could decrease the cAMP level in ischemic myocardium.展开更多
Objective:To establish a deep-learning architecture based on faster region-based convolutional neural networks(Faster R-CNN)algorithm for detection and sorting of red ginseng(Ginseng Radix et Rhizoma Rubra)with intern...Objective:To establish a deep-learning architecture based on faster region-based convolutional neural networks(Faster R-CNN)algorithm for detection and sorting of red ginseng(Ginseng Radix et Rhizoma Rubra)with internal defects automatically on an online X-ray machine vision system.Methods:A Faster R-CNN based classifier was trained with around 20000 samples with mean average precision value(mAP)of 0.95.A traditional image processing method based on feedforward neural network(FNN)obtained a bad performance with the accuracy,recall and specificity of 69.0%,68.0%,and70.0%,respectively.Therefore,the Faster R-CNN model was saved to evaluate the model performance on the defective red ginseng online sorting system.Results:An independent set of 2000 red ginsengs were used to validate the performance of the Faster RCNN based online sorting system in three parallel tests,achieving accuracy of 95.8%,95.2%and 96.2%,respectively.Conclusion:The overall results indicated that the proposed Faster R-CNN based classification model has great potential for non-destructive detection of red ginseng with internal defects.展开更多
文摘The model of SD rats ligated at the proximate left anterior descend (LAD) of coronary was used. The number and dissociation constant of β receptor were studied by using receptor autoradiography to observe the changes in β receptor and the effects of Radix Ginseng Rubra on cAMP in experimental ischemic myocardium. The result showed that the number of binding site in simple ligation group (B max =0.279) was obviously higher than that in sham operation group (B max =0.093) and the dissociation constant of simple ligation group (Kd=12.431) was higher than that of sham operation group (k d=1.319). There was a significant difference between the two groups ( P <0.05). It proved that the number of β receptor was increased and the activity was elevated in myocardial cell membranes after ligation of LAD. The myocardial cAMP level in simple ligation group (1293.96±519.36)×10 -3 nmol/g was much higher than that in sham operation group (774.44±210.55)×10 -3 nmol/g ; but the level of cAMP in ligation group after receiving Radix Ginseng Rubra treatment (805.02±362.48 pm/g) was obviously lower than that in simple ligation group ( P <0.01), which was close to the result of sham operation. The results indicated that Radix Ginseng Rubra could decrease the cAMP level in ischemic myocardium.
基金funded by National Natural Science Foundation of China(Grant No.82074276)Projects of International Cooperation of Traditional Chinese Medicine(Grant No.06102040NF020928)+1 种基金National S&T Major Project of China(Grant No.2018ZX09201011)Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine.(No.ZYYCXTD-D-202002)。
文摘Objective:To establish a deep-learning architecture based on faster region-based convolutional neural networks(Faster R-CNN)algorithm for detection and sorting of red ginseng(Ginseng Radix et Rhizoma Rubra)with internal defects automatically on an online X-ray machine vision system.Methods:A Faster R-CNN based classifier was trained with around 20000 samples with mean average precision value(mAP)of 0.95.A traditional image processing method based on feedforward neural network(FNN)obtained a bad performance with the accuracy,recall and specificity of 69.0%,68.0%,and70.0%,respectively.Therefore,the Faster R-CNN model was saved to evaluate the model performance on the defective red ginseng online sorting system.Results:An independent set of 2000 red ginsengs were used to validate the performance of the Faster RCNN based online sorting system in three parallel tests,achieving accuracy of 95.8%,95.2%and 96.2%,respectively.Conclusion:The overall results indicated that the proposed Faster R-CNN based classification model has great potential for non-destructive detection of red ginseng with internal defects.
