Case Studies supporting PEMF benefits for Non-Drug Option
Effect of electromagnetic field on cyclic adenosine monophosphate (cAMP) in a human mu-opioid receptor cell model
During the cell communication process, endogenous and exogenous signaling affect normal as well as pathological developmental conditions. Exogenous influences such as extra-low-frequency electromagnetic field (EMF) have been shown to effect pain and inflammation by modulating Gprotein receptors, down-regulating cyclooxygenase-2 activity, and affecting the calcium/calmodulin/nitric oxide pathway. Investigators have reported changes in opioid receptors and second messengers, such as cyclic adenosine monophosphate (cAMP), in opiate tolerance and dependence by showing how repeated exposure to morphine decreases adenylate cyclase activity causing cAMP to return to control levels in the tolerant state, and increase above control levels during withdrawal. Resonance responses to biological systems using exogenous EMF signals suggest that frequency response characteristics of the target can determine the EMF biological response. In our past research we found significant down regulation of inflammatory markers tumor necrosis factor alpha (TNF-α) and nuclear factor kappa B (NFκB) using 5 Hz EMF frequency. In this study cAMP was stimulated in Chinese Hamster Ovary (CHO) cells transfected with human mu-opioid receptors, then exposed to 5 Hz EMF, and outcomes were compared with morphine treatment. Results showed a 23% greater inhibition of cAMP-treating cells with EMF than with morphine. In order to test our results for frequency specific effects, we ran identical experiments using 13 Hz EMF, which produced results similar to controls. This study suggests the use of EMF as a complementary or alternative treatment to morphine that could both reduce pain and enhance patient quality of life without the side-effects of opiates.
Case Study Reference Source:
1. Effect of electromagnetic field on cyclic adenosine monophosphate (cAMP) in a human mu-opioid receptor cell model
(Authors: Christina L. Rossa,b, Thaleia Telia, and Benjamin S. Harrisona)