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Nigella sativa Linn., commonly known as black seed or black cumin, is a widely used medicinal plant in traditional systems of medicine across Asia, the Middle East, and Africa. Its seeds possess a rich pharmacological profile attributed primarily to its bioactive constituent, thymoquinone. Thymoquinone has been reported to exhibit diverse biological activities, including antioxidant, anti-inflammatory, anticancer, antimicrobial, and immunomodulatory. Given the growing interest in natural immunomodulators for managing immune-related disorders and enhancing immune defense, thymoquinone has emerged as a promising phytochemical candidate. However, scientific validation of its therapeutic efficacy requires accurate standardization and quantification in herbal formulations. High-Performance Thin Layer Chromatography (HPTLC) has proven to be a reliable, reproducible, and cost-effective method for the qualitative and quantitative analysis of phytoconstituents. This study aims to develop and validate an HPTLC method for the quantitative estimation of thymoquinone in Nigella sativa seeds and to correlate its content with potential immunomodulatory applications. The establishment of such a method not only supports quality control of herbal preparations containing Nigella sativa but also provides a scientific basis for further pharmacological and clinical investigations into its immune-regulating potential.
"QUANTITATIVE ESTIMATION OF THYMOQUINONE IN NIGELLA SATIVA LINN. VIA HPTLC: IMPLICATIONS FOR IMMUNOMODULATORY POTENTIAL", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 6, page no.c1-c10, June-2025, Available :http://www.ijrti.org/papers/IJRTI2506201.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator