Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
This narrative review explores the applied correlations between Vāta Doṣa and Agni, two fundamental Ayurvedic principles and modern concepts of cellular receptor physiology. Drawing from classical Ayurvedic texts (Charaka Saṃhitā, Suśruta Saṃhitā, Aṣṭāṅga Hṛdaya) and contemporary biomedical literature, the study establishes conceptual parallels between Ayurvedic models of motion and transformation and molecular mechanisms of signalling and metabolism. Bhūtāgni and Dhātvāgni are interpreted as elemental and tissue-level metabolic regulators analogous to enzymatic and intracellular metabolic processes, while Vāta represents the kinetic and communicative principle comparable to neural conduction and receptor-mediated signalling. The integrated functioning of these entities reflects a sophisticated regulatory network that aligns with the coordination between signal transduction and metabolic adaptation in modern physiology. Understanding Vāta–Agni interdependence thus provides a holistic framework for interpreting cellular communication, receptor responsiveness, and homeostatic regulation from an Ayurvedic–biomedical perspective.
Keywords:
Vāta Doṣa, Agni, Bhūtāgni, Dhātvāgni, Cellular Receptor Physiology, Integrative Medicine
Cite Article:
"Applied Correlations of Vāta Doṣa and Agni with Cellular Receptor Physiology: A Narrative Review", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.11, Issue 1, page no.a591-a595, January-2026, Available :http://www.ijrti.org/papers/IJRTI2601086.pdf
Downloads:
00083
ISSN:
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