JOURNAL ARTICLE

Pharmacological and phytochemical potential of Rubus ellipticus: a wild edible with multiple health benefits.

  • Published In: Journal of Pharmacy & Pharmacology, 2023, v. 75, n. 2. P. 143 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Kewlani, Pushpa; Tiwari, Deepti; Rawat, Sandeep; Bhatt, Indra D 3 of 3

Abstract

The article reviews the pharmacological, phytochemical, nutritional, traditional, and genomic aspects of Rubus ellipticus (family Rosaceae), a wild edible fruit native to the Himalayan region and parts of South and Southeast Asia. It highlights the species’ rich content of bioactive compounds—including phenolics, flavonoids, anthocyanins, terpenoids, and carotenoids—and its diverse pharmacological activities such as anti-diabetic, nephroprotective, anti-inflammatory, analgesic, anti-pyretic, anti-cancer, wound healing, anti-fertility, anti-plasmodial, antimicrobial, and antioxidant effects, many of which support its traditional medicinal uses. The review also notes significant genetic variability within R. ellipticus, suggesting potential for breeding and domestication, and discusses its economic importance through various value-added products and market potential. It concludes by emphasizing the need for further detailed phytochemical characterization, molecular mechanism studies, clinical validation, and development of nutraceutical and therapeutic applications to fully harness the species’ potential.

Additional Information

  • Source:Journal of Pharmacy & Pharmacology. 2023/02, Vol. 75, Issue 2, p143
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2023
  • ISSN:0022-3573
  • DOI:10.1093/jpp/rgac053
  • Accession Number:162356308
  • Copyright Statement:Copyright of Journal of Pharmacy & Pharmacology is the property of Oxford University Press / USA 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.