Interaction between pancreatic β cell and electromagnetic fields: A systematic study toward finding the natural frequency spectrum of β cell system.

Author: Farashi S1
Author Information:
1a Faculty of Medicine , Shahid Beheshti University of Medical Sciences , Tehran , Iran.
Conference/Journal: Electromagn Biol Med.
Date published: 2017 Oct 31
Other: Volume ID: 1-16 , Special Notes: doi: 10.1080/15368378.2017.1389751. [Epub ahead of print] , Word Count: 232


Interaction between biological systems and environmental electric or magnetic fields has gained attention during the past few decades. Although there are a lot of studies that have been conducted for investigating such interaction, the reported results are considerably inconsistent. Besides the complexity of biological systems, the important reason for such inconsistent results may arise due to different excitation protocols that have been applied in different experiments. In order to investigate carefully the way that external electric or magnetic fields interact with a biological system, the parameters of excitation, such as intensity or frequency, should be selected purposefully due to the influence of these parameters on the system response. In this study, pancreatic β cell, the main player of blood glucose regulating system, is considered and the study is focused on finding the natural frequency spectrum of the system using modeling approach. Natural frequencies of a system are important characteristics of the system when external excitation is applied. The result of this study can help researchers to select proper frequency parameter for electrical excitation of β cell system. The results show that there are two distinct frequency ranges for natural frequency of β cell system, which consist of extremely low (or near zero) and 100-750 kHz frequency ranges. There are experimental works on β cell exposure to electromagnetic fields that support such finding.

KEYWORDS: Electromagnetic exposure; modeling approach; natural frequency spectrum; pancreatic β cell; systematic analysis

PMID: 29087732 DOI: 10.1080/15368378.2017.1389751

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