ABSTRACT
Fourteen new geranyl phenyl ethers (1-14) along with three known compounds (15-17) were isolated from Illicium micranthum, and their structures were elucidated by comprehensive spectroscopic methods. Illimicranins A-H (1-8) were characterized as geranyl vanillin ethers, while 9 and 10 were dimethyl acetal derivatives. Illimicranins I and J (11 and 12) were rare geranyl isoeugenol ethers. Illimicranins K and L (13 and 14) represented the first example of geranyl guaiacylacetone ether and geranyl zingerone ether, respectively. Compounds 1, 2 and 15 exhibited anti-HBV (hepatitis B virus) activity against HBsAg (hepatitis B surface antigen) and HBeAg (hepatitis B e antigen) secretion, and HBV DNA replication.
Subject(s)
Antiviral Agents/pharmacology , Hepatitis B Surface Antigens , Hepatitis B e Antigens , Illicium/chemistry , Phenyl EthersABSTRACT
Objective To investigate the oral health status and awareness of urban children in Lhasa,aiming to provide a data basis for the prevention and treatment of children's caries and the promotion of oral health education. Methods A total of 504 Tibetan students were selected by cluster sampling from 2 primary schools in Chengguan District of Lhasa.All the participants were required to take oral health examination and complete a questionnaire about oral health awareness and behavior. Results The caries prevalence rate and mean decayed-missing-filled tooth(DMFT)of permanent teeth were 75.00% and 2.18±1.91,respectively.The rates of pit and fissure sealant and filling of permanent teeth were 3.77% and 6.81%,respectively.The caries prevalence rate of first permanent molars was 47.62%.The mean DMFT of permanent teeth and caries prevalence rate of first permanent molar were significantly higher in female group(
Subject(s)
Child , Female , Humans , DMF Index , Dental Caries/epidemiology , Oral Health , Oral Hygiene , Prevalence , Schools , Students , Surveys and QuestionnairesABSTRACT
The application of artificial intelligence in medicine has gradually received attention along with its development. Many studies have shown that machine learning has a wide range of applications in stomatology, especially in the clinical diagnosis and treatment of maxillofacial cysts and tumors. This article reviews the application of machine learning in maxillofacial cyst and tumor to provide a new method for the diagnosis of oral and maxillofacial diseases.