Matches in SemOpenAlex for { <https://semopenalex.org/work/W3093296940> ?p ?o ?g. }
- W3093296940 endingPage "113469" @default.
- W3093296940 startingPage "113469" @default.
- W3093296940 abstract "Withania somnifera L. (Solanaceae), commonly known as Ashwagandha or Indian ginseng, is used in Ayurveda (Indian system of traditional medicine) for vitality, cardio-protection and treating other ailments, such as neurological disorders, gout, and skin diseases. We present a critical overview of the information on the metabolomics of W. somnifera and highlight the significance of the technique for use in quality control of medicinal products. We have also pointed out the use of metabolomics to distinguish varieties and to identify best methods of cultivation, collection, as well as extraction. The relevant information on medicinal value, phytochemical studies, metabolomics of W. somnifera, and their applications were collected from a rigorous electronic search through scientific databases, including Scopus, PubMed, Web of Science and Google Scholar. Structures of selected metabolites were from the PubChem. The pharmacological activities of W. somnifera were well documented. Roots are the most important parts of the plant used in Ayurvedic preparations. Stem and leaves also have a rich content of bioactive phytochemicals like steroidal lactones, alkaloids, and phenolic acids. Metabolomic studies revealed that metabolite profiles of W. somnifera depended on plant parts collected and the developmental stage of the plant, besides the season of sample collection and geographical location. The levels of withanolides were variable, depending on the morpho/chemotypes within the species of W. somnifera. Although studies on W. somnifera were initiated several years ago, the complexity of secondary metabolites was not realized due to the lack of adequate and fool-proof technology for phytochemical fingerprinting. Sophistications in chromatography coupled to mass spectrometry facilitated the discovery of several new metabolites. Mutually complementary techniques like LC-MS, GC-MS, HPTLC, and NMR were employed to obtain a comprehensive metabolomic profile. Subsequent data analyses and searches against spectral databases enabled the annotation of signals and dereplication of metabolites in several numbers without isolating them individually. The present review provides a critical update of metabolomic data and the diverse application of the technique. The identification of parameters for standardization and quality control of herbal products is essential to facilitate mandatory checks for the purity of formulation. Such studies would enable us to identify the best geographical location of plants and the time of collection. We recommend the use of metabolomic analysis of herbal products based on W. somnifera for quality control as well as the discovery of novel bioactive compounds." @default.
- W3093296940 created "2020-10-22" @default.
- W3093296940 creator A5009856441 @default.
- W3093296940 creator A5026204180 @default.
- W3093296940 creator A5028480059 @default.
- W3093296940 creator A5029012151 @default.
- W3093296940 creator A5052842206 @default.
- W3093296940 date "2021-03-01" @default.
- W3093296940 modified "2023-10-06" @default.
- W3093296940 title "Metabolomics of Withania somnifera (L.) Dunal: Advances and applications" @default.
- W3093296940 cites W1481006175 @default.
- W3093296940 cites W1571035420 @default.
- W3093296940 cites W1755369401 @default.
- W3093296940 cites W1776667840 @default.
- W3093296940 cites W1815965285 @default.
- W3093296940 cites W1849944123 @default.
- W3093296940 cites W1890836171 @default.
- W3093296940 cites W1964727001 @default.
- W3093296940 cites W1967396225 @default.
- W3093296940 cites W1972430929 @default.
- W3093296940 cites W1985658900 @default.
- W3093296940 cites W1985941861 @default.
- W3093296940 cites W1989078481 @default.
- W3093296940 cites W1993326805 @default.
- W3093296940 cites W1993689059 @default.
- W3093296940 cites W2003142721 @default.
- W3093296940 cites W2003658163 @default.
- W3093296940 cites W2006270701 @default.
- W3093296940 cites W2006411577 @default.
- W3093296940 cites W2013529346 @default.
- W3093296940 cites W2015650819 @default.
- W3093296940 cites W2016553764 @default.
- W3093296940 cites W2017522220 @default.
- W3093296940 cites W2021778576 @default.
- W3093296940 cites W2022363920 @default.
- W3093296940 cites W2024880968 @default.
- W3093296940 cites W2038230222 @default.
- W3093296940 cites W2041418448 @default.
- W3093296940 cites W2044583789 @default.
- W3093296940 cites W2057722574 @default.
- W3093296940 cites W2068900672 @default.
- W3093296940 cites W2077581164 @default.
- W3093296940 cites W2079770700 @default.
- W3093296940 cites W2082552678 @default.
- W3093296940 cites W2087129770 @default.
- W3093296940 cites W2090184308 @default.
- W3093296940 cites W2098946890 @default.
- W3093296940 cites W2103582509 @default.
- W3093296940 cites W2108763926 @default.
- W3093296940 cites W2137388847 @default.
- W3093296940 cites W2147923911 @default.
- W3093296940 cites W2162939977 @default.
- W3093296940 cites W2165810298 @default.
- W3093296940 cites W2167967613 @default.
- W3093296940 cites W2181204878 @default.
- W3093296940 cites W2285608359 @default.
- W3093296940 cites W2314061557 @default.
- W3093296940 cites W2338010118 @default.
- W3093296940 cites W2395027512 @default.
- W3093296940 cites W2442839603 @default.
- W3093296940 cites W2461081458 @default.
- W3093296940 cites W2494042983 @default.
- W3093296940 cites W2530739643 @default.
- W3093296940 cites W2552917793 @default.
- W3093296940 cites W2576471852 @default.
- W3093296940 cites W2580327311 @default.
- W3093296940 cites W2604858218 @default.
- W3093296940 cites W2607391074 @default.
- W3093296940 cites W2753074284 @default.
- W3093296940 cites W2760788253 @default.
- W3093296940 cites W2765108388 @default.
- W3093296940 cites W2778712085 @default.
- W3093296940 cites W2793410156 @default.
- W3093296940 cites W2795679690 @default.
- W3093296940 cites W2810343603 @default.
- W3093296940 cites W2909313627 @default.
- W3093296940 cites W2912465277 @default.
- W3093296940 cites W2913336198 @default.
- W3093296940 cites W2952527284 @default.
- W3093296940 cites W2968471757 @default.
- W3093296940 cites W2969120993 @default.
- W3093296940 cites W4249300457 @default.
- W3093296940 doi "https://doi.org/10.1016/j.jep.2020.113469" @default.
- W3093296940 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33075439" @default.
- W3093296940 hasPublicationYear "2021" @default.
- W3093296940 type Work @default.
- W3093296940 sameAs 3093296940 @default.
- W3093296940 citedByCount "16" @default.
- W3093296940 countsByYear W30932969402021 @default.
- W3093296940 countsByYear W30932969402022 @default.
- W3093296940 countsByYear W30932969402023 @default.
- W3093296940 crossrefType "journal-article" @default.
- W3093296940 hasAuthorship W3093296940A5009856441 @default.
- W3093296940 hasAuthorship W3093296940A5026204180 @default.
- W3093296940 hasAuthorship W3093296940A5028480059 @default.
- W3093296940 hasAuthorship W3093296940A5029012151 @default.
- W3093296940 hasAuthorship W3093296940A5052842206 @default.
- W3093296940 hasConcept C142724271 @default.