Biological Effects of Magnetic Storms and ELF Magnetic Fields

Magnetic fields are a constant and essential part of our environment. The main components of ambient magnetic fields are the constant part of the geomagnetic field, its fluctuations caused by magnetic storms, and man-made magnetic fields. These fields refer to extremely-low-frequency (<1 kHz) magnetic fields (ELF-MFs). Since the 1980s, a huge amount of data has been accumulated on the biological effects of magnetic fields, in particular ELF-MFs. However, a unified picture of the patterns of action of magnetic fields has not been formed. Even though a unified mechanism has not yet been generally accepted, several theories have been proposed. In this review, we attempted to take a new approach to analyzing the quantitative data on the effects of ELF-MFs to identify new potential areas for research. This review provides general descriptions of the main effects of magnetic storms and anthropogenic fields on living organisms (molecular-cellular level and whole organism) and a brief description of the main mechanisms of magnetic field effects on living organisms. This review may be of interest to specialists in the fields of biology, physics, medicine, and other interdisciplinary areas.

Melatonin Levels and Low-Frequency Magnetic Fields in Humans and Rats: New Insights From a Bayesian Logistic Regression

The present analysis revisits the impact of extremely low-frequency magnetic fields (ELF-MF) on melatonin (MLT) levels in human and rat subjects using both a parametric and non-parametric approach. In this analysis, we use 62 studies from review articles. The parametric approach consists of a Bayesian logistic regression (LR) analysis and the non-parametric approach consists of a Support Vector analysis, both of which are robust against spurious/false results. Both approaches reveal a unique well-ordered pattern, and show that human and rat studies are consistent with each other once the MF strength is restricted to cover the same range (with B ≲ 50 μT). In addition, the data reveal that chronic exposure (longer than ∼22 days) to ELF-MF appears to decrease MLT levels only when the MF strength is below a threshold of ~30 μT ( log B thr [ μ T ] = 1 . 4 - 0 . 4 + 0 . 7 ), i.e., when the man-made ELF-MF intensity is below that of the static geomagnetic field. Studies reporting an association between ELF-MF and changes to MLT levels and the opposite (no association with ELF-MF) can be reconciled under a single framework. Bioelectromagnetics. 2019;40:539-552. © 2019 Bioelectromagnetics Society.

Pineal melatonin level disruption in humans due to electromagnetic fields and ICNIRP limits

The International Agency for Research on Cancer (IARC) classifies electromagnetic fields (EMFs) as 'possibly carcinogenic' to humans that might transform normal cells into cancer cells. Owing to high utilisation of electricity in day-to-day life, exposure to power-frequency (50 or 60 Hz) EMFs is unavoidable. Melatonin is a natural hormone produced by pineal gland activity in the brain that regulates the body's sleep-wake cycle. How man-made EMFs may influence the pineal gland is still unsolved. The pineal gland is likely to sense EMFs as light but, as a consequence, may decrease the melatonin production. In this study, more than one hundred experimental data of human and animal studies of changes in melatonin levels due to power-frequency electric and magnetic fields exposure were analysed. Then, the results of this study were compared with the International Committee of Non-Ionizing Radiation Protection (ICNIRP) limit and also with the existing experimental results in the literature for the biological effect of magnetic fields, in order to quantify the effects. The results show that this comparison does not seem to be consistent despite the fact that it offers an advantage of drawing attention to the importance of the exposure limits to weak EMFs. In addition to those inconsistent results, the following were also observedfrom this work: (i) the ICNIRP recommendations are meant for the well-known acute effects, because effects of the exposure duration cannot be considered and (ii) the significance of not replicating the existing experimental studies is another limitation in the power-frequency EMFs. Regardless of these issues, the above observation agrees with our earlier study in which it was confirmed that it is not a reliable method to characterise biological effects by observing only the ratio of AC magnetic field strength to frequency. This is because exposure duration does not include the ICNIRP limit. Furthermore, the results show the significance of disruption of melatonin due to exposure to weak EMFs, which may possibly lead to long-term health effects in humans.

Antagonistic effects of a 50 Hz magnetic field and melatonin in the proliferation and differentiation of hepatocarcinoma cells

BACKGROUND/AIMS

Epidemiological and experimental evidence exists indicating that exposure to weak, extremely low frequency magnetic fields (ELF - MF) could affect cancer progression. It has been proposed that such hypothetical action could be mediated by MF-induced effects on the cellular response to melatonin (MEL), a potentially oncostatic neurohormone. The present study investigates the response of HepG2 cells to intermittent exposure to a 50 Hz, 10 µT MF, in the presence or absence of MEL at physiological (10 nM) or pharmacological doses (1 µM).

METHODS

The Trypan blue cell exclusion test, BrdU incorporation and PCNA expression assays were carried out to assess the cellular response in terms of viability and proliferation. In addition, albumin and alpha-fetoprotein, were analyzed as specific hepatocellular differentiation markers.

RESULTS

The results indicate that the MF exerts significant cytoproliferative and dedifferentiating effects that can be prevented by 10 nM MEL. Conversely, MEL exerts cytostatic and differentiating effects on HepG2 that are abolished by simultaneous exposure to MF.

CONCLUSION

As a whole, these results support the hypothesis that ELF - MF and MEL exert opposite, mutually counteracting effects on cell proliferation and differentiation.

Comparing performances of logistic regression and neural networks for predicting melatonin excretion patterns in the rat exposed to ELF magnetic fields

Various studies have been reported on the bioeffects of magnetic field exposure; however, no consensus or guideline is available for experimental designs relating to exposure conditions as yet. In this study, logistic regression (LR) and artificial neural networks (ANNs) were used in order to analyze and predict the melatonin excretion patterns in the rat exposed to extremely low frequency magnetic fields (ELF-MF). Subsequently, on a database containing 33 experiments, performances of LR and ANNs were compared through resubstitution and jackknife tests. Predictor variables were more effective parameters and included frequency, polarization, exposure duration, and strength of magnetic fields. Also, five performance measures including accuracy, sensitivity, specificity, Matthew's Correlation Coefficient (MCC) and normalized percentage, better than random (S) were used to evaluate the performance of models. The LR as a conventional model obtained poor prediction performance. Nonetheless, LR distinguished the duration of magnetic fields as a statistically significant parameter. Also, horizontal polarization of magnetic fields with the highest logit coefficient (or parameter estimate) with negative sign was found to be the strongest indicator for experimental designs relating to exposure conditions. This means that each experiment with horizontal polarization of magnetic fields has a higher probability to result in "not changed melatonin level" pattern. On the other hand, ANNs, a more powerful model which has not been introduced in predicting melatonin excretion patterns in the rat exposed to ELF-MF, showed high performance measure values and higher reliability, especially obtaining 0.55 value of MCC through jackknife tests. Obtained results showed that such predictor models are promising and may play a useful role in defining guidelines for experimental designs relating to exposure conditions. In conclusion, analysis of the bioelectromagnetic data could result in finding a relationship between electromagnetic fields and different biological processes.