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HPLC-Fingerprints and Antioxidant Constituents of Phyla nodiflora

Phyla nodiflora is a creeping perennial herb, widely distributed in the most tropical and subtropical regions. It has been used as a folk medicine, herbal beverage, or folk cosmetic. For these usages, the development of a chemical quality control method of this plant is necessary. In the present stu...

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Detalles Bibliográficos
Autores principales: Lin, Fang-Ju, Yen, Feng-Lin, Chen, Pei-Chun, Wang, Moo-Chin, Lin, Chun-Nan, Lee, Chiang-Wen, Ko, Horng-Huey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4129175/
https://www.ncbi.nlm.nih.gov/pubmed/25140335
http://dx.doi.org/10.1155/2014/528653
Descripción
Sumario:Phyla nodiflora is a creeping perennial herb, widely distributed in the most tropical and subtropical regions. It has been used as a folk medicine, herbal beverage, or folk cosmetic. For these usages, the development of a chemical quality control method of this plant is necessary. In the present study, ten compounds, namely, 3,7,4′,5′-tetrahydroxy-3′-methoxyflavone (1), nodifloretin (2), 4′-hydroxywogonin (3), onopordin (4), cirsiliol (5), 5,7,8,4′-tetrahydroxy-3′-methoxyflavone (6), eupafolin (7), hispidulin (8), larycitrin (9), and β-sitosterol were isolated from the methanolic extract of the aerial part of P. nodiflora (PNM) and their structures were identified by 1D-NMR comparing their spectra with the literature. The antioxidant activities of these compounds were evaluated by free radical scavenging activity and tyrosinase inhibitory effect in cell-free systems. Compounds 4, 5, and 7 showed strong antioxidant activity. To control the quality of P. nodiflora, a simple and reliable method of high-performance liquid chromatography combined with ultraviolet detector (HPLC-UV) was established for both the fingerprint analysis and the quantitative determination of two selected active compounds, onopordin (4) and eupafolin (7). Statistical analysis of the obtained data demonstrated that our method achieved the desired linearity, precision, and accuracy. The results indicated that the developed method can be used as a quality evaluation method for PNM.