RESUMO
Three new phenolic glycosides, named as glycopentosides A-C (1-3), along with nine known compounds were isolated from the n-BuOH extract of stems of Glycosmis pentaphylla. Their structures were determined by using spectroscopic and chemical methods. Bioassay showed that compound 10 (tachioside) could inhibit nitric oxide production in lipopolysaccharides-stimulated RAW 264.7 cells with IC50 value of 12.14 µM.
Assuntos
Anti-Inflamatórios não Esteroides/isolamento & purificação , Medicamentos de Ervas Chinesas/isolamento & purificação , Glicosídeos/isolamento & purificação , Fenóis/isolamento & purificação , Rutaceae/química , Animais , Anti-Inflamatórios não Esteroides/química , Anti-Inflamatórios não Esteroides/farmacologia , Medicamentos de Ervas Chinesas/química , Medicamentos de Ervas Chinesas/farmacologia , Glicosídeos/química , Glicosídeos/farmacologia , Concentração Inibidora 50 , Lipopolissacarídeos/farmacologia , Camundongos , Estrutura Molecular , Óxido Nítrico/biossíntese , Fenóis/química , Fenóis/farmacologia , Caules de Planta/químicaRESUMO
Objective: To explore the genotyping characteristics of human fecal Escherichia coli( E. coli) and the relationships between antibiotic resistance genes (ARGs) and multidrug resistance (MDR) of E. coli in Miyun District, Beijing, an area with high incidence of infectious diarrheal cases but no related data. Methods: Over a period of 3 years, 94 E. coli strains were isolated from fecal samples collected from Miyun District Hospital, a surveillance hospital of the National Pathogen Identification Network. The antibiotic susceptibility of the isolates was determined by the broth microdilution method. ARGs, multilocus sequence typing (MLST), and polymorphism trees were analyzed using whole-genome sequencing data (WGS). Results: This study revealed that 68.09% of the isolates had MDR, prevalent and distributed in different clades, with a relatively high rate and low pathogenicity. There was no difference in MDR between the diarrheal (49/70) and healthy groups (15/24). Conclusion: We developed a random forest (RF) prediction model of TEM.1 + baeR + mphA + mphB + QnrS1 + AAC.3-IId to identify MDR status, highlighting its potential for early resistance identification. The causes of MDR are likely mobile units transmitting the ARGs. In the future, we will continue to strengthen the monitoring of ARGs and MDR, and increase the number of strains to further verify the accuracy of the MDR markers.