Artificial intelligence (AI) has emerged as a transformative technology in accelerating drug discovery and development within natural medicines research. Natural medicines, characterized by their complex chemical compositions and multifaceted pharmacological mechanisms, demonstrate widespread application in treating diverse diseases. However, research and development face significant challenges, including component complexity, extraction difficulties, and efficacy validation. AI technology, particularly through deep learning (DL) and machine learning (ML) approaches, enables efficient analysis of extensive datasets, facilitating drug screening, component analysis, and pharmacological mechanism elucidation. The implementation of AI technology demonstrates considerable potential in virtual screening, compound optimization, and synthetic pathway design, thereby enhancing natural medicines' bioavailability and safety profiles. Nevertheless, current applications encounter limitations regarding data quality, model interpretability, and ethical considerations. As AI technologies continue to evolve, natural medicines research and development will achieve greater efficiency and precision, advancing both personalized medicine and contemporary drug development approaches.
Biological Products/pharmacology* ; Artificial Intelligence ; Humans ; Drug Discovery/methods* ; Machine Learning ; Deep Learning

OBJECTIVE To analyze the differences in chemical composition of mussels from Shengsi,Zhoushan in different har-vest months,and to compare the differences in the composition of mussels from different origins,so as to provide ideas for the compre-hensive utilization of its resources.METHODS Ultra-high performance liquid chromatography-triple quadrupole mass spectrometry(UHPLC-QqQ-MS)and spectrophotometry were used to analyze and evaluate the contents of nucleosides,amino acids,water-soluble proteins,total sugars and polysaccharides in mussels from Shengsi,Zhoushan in 12 months of the year and from 5 different origins;principal component analysis(PCA),partial least squares discriminant method(PLS-DA)and TOPSIS method were used to compre-hensively evaluate mussels.RESULTS A total of 16 amino acids and 11 nucleosides were detected in mussels.The average content of total amino acids in Shengsi mussels throughout the year was 4 851.74 μg·g-1,the average content of total nucleosides was 921.40 μg·g-1,and the average contents of water-soluble protein,polysaccharides,and total sugars were 51.32 mg·g-1,74.39 μg·g-1,and 417.22 mg·g-1,respectively.The nucleosides of Shengsi mussels were the highest in March and April,the ami-no acids and water-soluble proteins were the highest in April and May,and the polysaccharides and total sugars were the highest in Oc-tober and November.The PCA and PLS-DA results of the chemical components of different resources showed that there were great differences in Shengsi mussel samples harvested in different seasons.The entropy weight TOPSIS analysis showed that the comprehen-sive scores of Shengsi mussels in March and April(S7 and S8)were better than those in other areas,and the comprehensive score of Shengsi mussels in April(S8)was the highest,which was determined to be the best harvesting month.CONCLUSION The comparison results of multi-type resource chemistry show that there are great differences in the chemical compo-sition of Shengsi mussels in different harvesting seasons;the quality of Shengsi mussels is better than that of other areas;April is the best harvesting season,providing a reference for the quality evaluation and comprehensive development and utilization of mussels.

OBJECTIVE To analyze the differences in chemical composition of mussels from Shengsi,Zhoushan in different har-vest months,and to compare the differences in the composition of mussels from different origins,so as to provide ideas for the compre-hensive utilization of its resources.METHODS Ultra-high performance liquid chromatography-triple quadrupole mass spectrometry(UHPLC-QqQ-MS)and spectrophotometry were used to analyze and evaluate the contents of nucleosides,amino acids,water-soluble proteins,total sugars and polysaccharides in mussels from Shengsi,Zhoushan in 12 months of the year and from 5 different origins;principal component analysis(PCA),partial least squares discriminant method(PLS-DA)and TOPSIS method were used to compre-hensively evaluate mussels.RESULTS A total of 16 amino acids and 11 nucleosides were detected in mussels.The average content of total amino acids in Shengsi mussels throughout the year was 4 851.74 μg·g-1,the average content of total nucleosides was 921.40 μg·g-1,and the average contents of water-soluble protein,polysaccharides,and total sugars were 51.32 mg·g-1,74.39 μg·g-1,and 417.22 mg·g-1,respectively.The nucleosides of Shengsi mussels were the highest in March and April,the ami-no acids and water-soluble proteins were the highest in April and May,and the polysaccharides and total sugars were the highest in Oc-tober and November.The PCA and PLS-DA results of the chemical components of different resources showed that there were great differences in Shengsi mussel samples harvested in different seasons.The entropy weight TOPSIS analysis showed that the comprehen-sive scores of Shengsi mussels in March and April(S7 and S8)were better than those in other areas,and the comprehensive score of Shengsi mussels in April(S8)was the highest,which was determined to be the best harvesting month.CONCLUSION The comparison results of multi-type resource chemistry show that there are great differences in the chemical compo-sition of Shengsi mussels in different harvesting seasons;the quality of Shengsi mussels is better than that of other areas;April is the best harvesting season,providing a reference for the quality evaluation and comprehensive development and utilization of mussels.

Objective To investigate the role of estrogen in spontaneous repair of osteochondral defect,so as to provide guidance for the application of estrogen in tissue engineering.Methods Seventytwo healthy adult female SD rats (4-month-old) were assigned to negative control group (group A,n =24),ovariectomized group (group B,n =24) and ovariectomized + estrogen treatment group (group C,n =24) according to the random number table.Rats in group C were intraperitoneally injected 0.1 mg/kg estradiol benzoate once per week after operation.An osteochondral defect model (diameter:2 mm,height:1.5 mm) was established in femoral trochlea of rats 4 weeks after operation.At 2,10 and 20 weeks after the modeling,8 rats from each group were sacrificed.Femoral condyles were collected to measure bone volume fraction (BVF),number of bone trabeculae (Tb.N),trabecular thickness (Tb.Th) and trabecular spacing (Tb.Sp) in the osteochondral defect area by micro-CT scanning.Morphological changes were observed by HE staining,histomorphological changes and cartilage regeneration by safranine O-fast green staining,osteoclast count by tartrate-resistant acid phosphatase (TRAP) staining,distribution of matrix metalloproteinase-9 (MMP-9) by immunohistochemistry and expressions of osteoprotegerin (OPG),receptor activator of nuclear factor-κB ligand (RANKL) and MMP-9 by real-time-PCR.Results Compared to group B,increased BVF and Tb.N and decreased Tb.Sp were observed in groups A and C at each time point.More bone matrix formations were observed in groups A and C than in group B at 2 weeks,cysts (also known as cystic cavities) in regenerated subchondral bone and cracks in subchondral bone plate were observed in group B at 10 and 20 weeks,and proliferation of osteoclasts was active within lesions in group B at 10 and 20 weeks.Compared to group B,lowered levels of RANKL and MMP-9 (P ＜ 0.05) and significantly increased level of OPG (P ＜ 0.01) were observed in groups A and C at each time point,and osteoclast count in groups A and C was lowered at 10 and 20 weeks (P＜0.05).No regeneration of cartilage layer was observed in all groups.Conclusions Excessive proliferation of osteoclasts results in formation of cystic cavities and cracks.Estrogen improves the speed and quality of bone repair by regulating activities of osteoblasts and osteoclasts,so it can be used to treat osteochondral defect in tissue engineering.

Objective To investigate the correlation among mammographic features、pathology and molecu-lar biology markers of breast infitrating ductal carcinoma(IDC) tissues.Methods The mammographic features of 93 cases with IDC confirmed by surgery and histopathology were analyzed retrospectively.The mastectomy specimens of the IDC were stained with immunohistochemistry,and the expression of ER、PR、C-erbB-2 were measured.The rela-tionship between the immunohistochemical pathologic results and mammographic features was analyzed.Results A-mong the 93 cases of IDC,ER positive expression was positively correlated with the spiculate margin of breast cancer (P<0.05);C-erbB-2 positive expression was positively correlated(P<0.05).Moreover,ER and PR positive expres-sion showed a significant inverse correlation with the calcifying of breast cancer(P>0.05);ER and PR positive ex-pression was positively correlated with the transfer of lymph(P<0.05);there existed correlation between the positive expression of C-erbB-2 and lymphatic metastasis and pathohistology grade(P<0.05).Conclusion There was a pos-itive correlation among IDC mammography、pathology and the abnormal value of ER、PR and C-erbB-2.The X-ray mammography could reflect the diagnosis value of ER、PR and C-erbB-2 roughly,and thadpractical value in determi-ning prognoses and endocrinotherapy.