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Updated: Jan 31, 2026

Electric and Magnetic Field Devices for Stimulation of Biological Tissues
Published on: May 15, 2021
Activation of the intracellular temperature and ROS sensor membrane protein STIM1 as a mechanism underpinning
Myrtill Simkó1, Mats-Olof Mattsson1
1SciProof International AB, Östersund, Sweden.
Abstract:
The biological effects of low frequency magnetic fields (LF MF) at high flux densities are well known and the underlying mechanism is established. In contrast, health associated effects at lower flux densities, which can be found in the human environment, are controversial, and no accepted interaction mechanism has been presented. Here we present a hypothesis regarding the biological aspect of interaction between LF MF and cells. We suggest that the endoplasmic reticulum (ER) membrane protein STIM1, which functions as a sensor for several cellular conditions (low Ca2+ levels, temperature increase, increased levels of oxygen radicals, hypoxia), is a candidate LF MF sensor. Such a sensor function can be either direct (via local temperature increase caused by intracellularly induced electric fields), or indirect due to responses to increased reactive oxygen species (ROS) levels. Activated STIM1 leads to downstream effects by activation of signal transduction processes and changes in gene expression leading to secondary events. The nature of these changes would be dependent on both cell type and the particular physiological state the cell displays at the time of STIM1 activation. Results from testing of this hypothesis, as suggested in this paper, would greatly assist in understanding of the possible health-related effects of low-level LF MF. This would benefit both safety assessments regarding MF exposure as well as possible use of MF in medicine. A better understanding of the biological mechanisms underpinning MF exposure effects of living matter allows the targeted use of the fields in medical applications. There are several examples already in use based on empiric and not on mechanistic knowledge. Knowledge generated from our hypothesis testing makes it possible for MF based medical applications to be optimized.
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