OBJECTIVE: Exploring the effect of Optimized New Shengmai powder(优化新生脉散方, ONSMP) on myocardial fibrosis in heart failure(HF) based on rat sarcoma(RAS)/rapidly accelerated fibrosarcoma(RAF)/mitogen-activated pro...OBJECTIVE: Exploring the effect of Optimized New Shengmai powder(优化新生脉散方, ONSMP) on myocardial fibrosis in heart failure(HF) based on rat sarcoma(RAS)/rapidly accelerated fibrosarcoma(RAF)/mitogen-activated protein kinase kinase(MEK)/extracellular regulated protein kinases(ERK) signaling pathway. METHODS: Randomized 70 Sprague-Dawley rats into sham(n = 10) and operation(n = 60) groups, then established the HF rat by ligating the left anterior descending branch of the coronary artery. We randomly divided the operation group rats into the model, ONSMP [including low(L), medium(M), and high(H) dose], and enalapril groups. After the 4-week drug intervention, echocardiography examines the cardiac function and calculates the ratios of the whole/left heart to the rat's body weight. Finally, we observed the degree of myocardial fibrosis by pathological sections, determined myocardium collagen(COL) Ⅰ and COL Ⅲ content by enzyme-linked immunosorbent assay, detected the m RNA levels of COL Ⅰ, COL Ⅲ, α-smooth muscle actin(α-SMA), and c-Fos proto-oncogene(c-Fos) by universal real-time, and detected the protein expression of p-RAS, p-RAF, p-MEK1/2, p-ERK1/2, p-ETS-like-1 transcription factor(p-ELK1), p-c-Fos, α-SMA, COL Ⅰ, and COL Ⅲ by Western blot. RESULTS: ONSMP can effectively improve HF rat's cardiac function, decrease cardiac organ coefficient, COL volume fraction, and COL Ⅰ/Ⅲ content, down-regulate the m RNA of COL Ⅰ/Ⅲ, α-SMA and c-Fos, and the protein of p-RAS, p-RAF, p-MEK1/2, p-ERK1/2, p-ELK1, c-Fos, COL Ⅰ/Ⅲ, and α-SMA. CONCLUSIONS: ONSMP can effectively reduce myocardial fibrosis in HF rats, and the mechanism may be related to the inhibition of the RAS/RAF/MEK/ERK signaling pathway.展开更多
Additives are widely employed to regulate the morphology,size,and agglomeration degree of crystalline materials during crystallization to enhance their functional,physical,and powder properties.However,the existing me...Additives are widely employed to regulate the morphology,size,and agglomeration degree of crystalline materials during crystallization to enhance their functional,physical,and powder properties.However,the existing methods for screening and validating target additives require a large quantity of materials and involve tedious molecular simulation/crystallization experiments,making them time-consuming,resource-intensive,and reliant on the operator’s experience level.To overcome these challenges,we proposed a computer vision-assisted high-throughput additive screening system(CV-HTPASS)which comprises a high-throughput additive screening device,in situ imaging equipment,and an artificial intelligence(AI)-assisted image-analysis algorithm.Using the CV-HTPASS,we performed high-throughput screening experiments on additives to regulate the succinic acid crystal properties,generating thousands of crystal images with diverse crystal morphologies.To extract valuable crystal information from the massive data and improve the analysis accuracy and efficiency,the AI-based image-analysis algorithm was implemented innovatively for the segmentation,classification,and data mining of crystals with four morphologies to further screen the target additive.Subsequently,scale-up crystallization experiments conducted under optimized conditions demonstrated that succinic acid products exhibited a preferred cubic morphology,reduced agglomeration degree,narrowed crystal size distribution,and improved powder properties.The proposed CV-HTPASS offers a highly efficient approach for scale-up experiments.Further,it provides a platform for the screening of additives and the optimization of the powder properties of crystal products in industrial-scale crystallization processes.展开更多
基金Innovation Team Development Program of the Ministry of Education:Research on the Prevention and Treatment of Cardiovascular Diseases with Traditional Chinese Medicine (IRT-16R54)。
文摘OBJECTIVE: Exploring the effect of Optimized New Shengmai powder(优化新生脉散方, ONSMP) on myocardial fibrosis in heart failure(HF) based on rat sarcoma(RAS)/rapidly accelerated fibrosarcoma(RAF)/mitogen-activated protein kinase kinase(MEK)/extracellular regulated protein kinases(ERK) signaling pathway. METHODS: Randomized 70 Sprague-Dawley rats into sham(n = 10) and operation(n = 60) groups, then established the HF rat by ligating the left anterior descending branch of the coronary artery. We randomly divided the operation group rats into the model, ONSMP [including low(L), medium(M), and high(H) dose], and enalapril groups. After the 4-week drug intervention, echocardiography examines the cardiac function and calculates the ratios of the whole/left heart to the rat's body weight. Finally, we observed the degree of myocardial fibrosis by pathological sections, determined myocardium collagen(COL) Ⅰ and COL Ⅲ content by enzyme-linked immunosorbent assay, detected the m RNA levels of COL Ⅰ, COL Ⅲ, α-smooth muscle actin(α-SMA), and c-Fos proto-oncogene(c-Fos) by universal real-time, and detected the protein expression of p-RAS, p-RAF, p-MEK1/2, p-ERK1/2, p-ETS-like-1 transcription factor(p-ELK1), p-c-Fos, α-SMA, COL Ⅰ, and COL Ⅲ by Western blot. RESULTS: ONSMP can effectively improve HF rat's cardiac function, decrease cardiac organ coefficient, COL volume fraction, and COL Ⅰ/Ⅲ content, down-regulate the m RNA of COL Ⅰ/Ⅲ, α-SMA and c-Fos, and the protein of p-RAS, p-RAF, p-MEK1/2, p-ERK1/2, p-ELK1, c-Fos, COL Ⅰ/Ⅲ, and α-SMA. CONCLUSIONS: ONSMP can effectively reduce myocardial fibrosis in HF rats, and the mechanism may be related to the inhibition of the RAS/RAF/MEK/ERK signaling pathway.
基金supported by the Shandong Provincial Key Research and Development Program(Major Key Technology Project)(2021CXGC010514)the National Natural Science Foundation of China(22008173).
文摘Additives are widely employed to regulate the morphology,size,and agglomeration degree of crystalline materials during crystallization to enhance their functional,physical,and powder properties.However,the existing methods for screening and validating target additives require a large quantity of materials and involve tedious molecular simulation/crystallization experiments,making them time-consuming,resource-intensive,and reliant on the operator’s experience level.To overcome these challenges,we proposed a computer vision-assisted high-throughput additive screening system(CV-HTPASS)which comprises a high-throughput additive screening device,in situ imaging equipment,and an artificial intelligence(AI)-assisted image-analysis algorithm.Using the CV-HTPASS,we performed high-throughput screening experiments on additives to regulate the succinic acid crystal properties,generating thousands of crystal images with diverse crystal morphologies.To extract valuable crystal information from the massive data and improve the analysis accuracy and efficiency,the AI-based image-analysis algorithm was implemented innovatively for the segmentation,classification,and data mining of crystals with four morphologies to further screen the target additive.Subsequently,scale-up crystallization experiments conducted under optimized conditions demonstrated that succinic acid products exhibited a preferred cubic morphology,reduced agglomeration degree,narrowed crystal size distribution,and improved powder properties.The proposed CV-HTPASS offers a highly efficient approach for scale-up experiments.Further,it provides a platform for the screening of additives and the optimization of the powder properties of crystal products in industrial-scale crystallization processes.
