JOURNAL ARTICLE
Extraction and Isolation of Active Phytochemical Constituents from Garcinia cambogia for Anti-Obesity Activity.
Published In: International Journal of Pharma Research, 2024, v. 15, n. 1. P. 18 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: A., Mohamed Afsal; Subramani, Supraja; Jeevanesh; Elango, Hemnath 3 of 3
Abstract
Obesity is a major health concern worldwide, and it is leading to worsening disease morbidity and mortality. Herbal supplements and diet-based therapies have attracted interest in the treatment of obesity. Even though many supplements are available, this study is focused on Garcinia cambogia (GC), also called Malabar tamarind, which contains polyphenols that have anti-obesity activity. Food supplements of plant origin for weight control are being demanded by the population globally as a way to promote good health. Among them, those based on Garcinia cambogia are widely commercialized considering their bioactive properties, mainly due to (-) hydroxycitric acid (-HCA). However, recently, controversy has arisen over their safety; thus, further research and continuous monitoring of their composition are required. Hence, in this work, a multi-analytical approach has been performed for the extraction and isolation of not only (-)-HCA but also other active phytochemical constituents for anti-obesity activity. Moreover, many studies paved the way for the detection of different compounds present in G. cambogia fruits. This multi-analytical methodology is shown to be advantageous in addressing different fraudulent practices affecting the quality of these supplements. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of Pharma Research. 2024/01, Vol. 15, Issue 1, p18
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2024
- ISSN:0975-3532
- Accession Number:183119591
- Copyright Statement:Copyright of International Journal of Pharma Research is the property of PSG College of Pharmacy and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Looking to go deeper into this topic? Look for more articles on EBSCOhost.