Literature DB >> 21428733

Fractal immunology and immune patterning: potential tools for immune protection and optimization.

Rodney R Dietert1.   

Abstract

Fractals are self-similar geometric patterns that are inherently embedded throughout nature. Their discovery and application have produced significant benefits across a wide variety of biomedical applications. Recently, complex physiological systems (e.g., neurological, respiratory, cardiovascular) have been shown to exhibit fractal dimensions that are capable of distinguishing among physiologic function versus dysfunction and, in turn, health versus disease. Additionally, fractal data suggest that the immune system operates under similar patterned relationships, and this is in keeping with the recent findings that immune-based diseases are organized according to specific patterns. This review considers the potential benefits of using fractal analysis along with considerations of nonlinearity, scaling, and chaos as calibration tools to obtain holistic information on immune-environment interactions. The potential uses of both synthetic and artificial immune systems for improved protection of the biological immune system are also discussed. The addition of holistic measures of immune status to currently collected biomarkers of immunotoxicity has the potential to increase the effectiveness of health risk assessment. The objective of extending fractal physiology analyses to the immune system would be to promote immune optimization as a public health benefit, which would include improved: (1) immunotoxicity testing and effective health risk reduction and (2) measures of effective immune management for children, adults, and aged individuals.

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Year:  2011        PMID: 21428733     DOI: 10.3109/1547691X.2011.559951

Source DB:  PubMed          Journal:  J Immunotoxicol        ISSN: 1547-691X            Impact factor:   3.000


  2 in total

Review 1.  A pharmacologic perspective on newly emerging T-cell manipulation technologies.

Authors:  Dominic Smethurst
Journal:  Br J Clin Pharmacol       Date:  2013-08       Impact factor: 4.335

Review 2.  Scaling in Colloidal and Biological Networks.

Authors:  Michael Nosonovsky; Prosun Roy
Journal:  Entropy (Basel)       Date:  2020-06-04       Impact factor: 2.524

  2 in total

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