ABSTRACT
Objective: To investigate and analyze anticomplement and antitussive activities and the active ingredients of the extract of Chimonanthus nitens leaf. Methods: The classical anti-complement pathway and the concentrated ammonia-induced cough model was used to compare the activity of the different polar parts of C. nitens leaf, and the polar parts with anti-complement and antitussive activity were determined. A preliminary analysis of the chemical composition in activity extract was identified by high performance liquid chromatography-mass spectrometry. The main chemical components in the C. nitens leaf of antitussive and antibody activity were also evaluated. Results: The ethyl acetate extract of C. nitens leaf had both anti-complement and antitussive effects. A total of 28 compounds were initially identified through mass spectrometry analysis. Kaempferol-3-O-rutinoside and kaempferol had both antitussive and anti-complement activities. Conclusion: The ethyl acetate extract of C. nitens leaf has good anti-complement and antitussive activities, and the mainly active ingredients in it were kaempferol-3-O-rutinoside and kaempferol that could be used as quality-controlling chemical markers.
ABSTRACT
Objective::To establish an ultra-high-performance liquid chromatography (UHPLC) method for simultaneous determination of seven components(chlorogenic acid, 3, 5-dicaffeoylquinic acid, 1, 5-dicaffeoylquinic acid, kaempferol-3-O-rutinoside, quercetin, kaempferol and thymol) in blossoms of Inula nervosa, and provide references for its quality control. Method::The separation was performed on an Agilent Poroshell 120 C18 column (3.0 mm×100 mm, 2.7 μm) with 0.1% formic acid(A) and methyl (B)as mobile phase for gradient elution(0-4 min, 2%B; 4-6 min, 2%-5%B; 6-10 min, 5%-10%B; 10-20 min, 10%-20%B; 20-30 min, 20%-27%B; 30-37 min, 27%-25%B, 37-45 min, 25%-32%B; 45-68 min, 32%-58%B; 68-75 min, 58%-25%B; 75-82 min, 25%-2%B; 82-90 min, 2%B). The flow rate was 0.3 mL·min-1 and the detection wavelength was 254 nm. Result::There was a good linear relationship between the concentration and peak area of all the seven components in the investigated concentration range (r>0.999). The average recoveries ranged from 97.80% to 101.28% with RSD≤3.0%. Cluster analysis of SPSS software and principal component analysis of SIMCA software can be used to intuitively classify samples from four different origins. Conclusion::The established method is simple and fast with high precision, which can be used to compare the differences of blossoms of Inula nervosa from different origins and efficiently control its quality.