Electromagnetic Biology and Medicine最新文献

The aim of this study is to investigate the potential synergistic effects of agomelatine(AGM) and 2600 MHz radiofrequency(RF) field exposure on inflammation induced by chronic lipopolysaccharide(LPS) administration in rats. A total of 49 female Wistar albino rats were randomly divided into 7 groups(n = 7 per group): Control, Sham, LPS, LPS+AGM,LPS+RF,AGM+RF, and LPS+AGM+RF. Animals in the RF groups were exposed to a 2600 MHz field (1 h/day for 15 days). The whole-body averaged SAR was calculated to be 0.637 W/kg, while the localized SAR values were found to be 1.27 W/kg for 1 g and 0.91 W/kg for 10 g of brain tissue at a frequency of 2600 MHz. Chronic LPS administration(1 mg/kg/day for 15 days) successfully induced a systemic inflammatory state. The most significant finding was observed in plasma IL-6 levels. While AGM or RF exposure alone did not significantly alter IL-6 levels in LPS-treated animals, the combined treatment of LPS+AGM+RF resulted in a substantial and statistically significant decrease in plasma IL-6 compared to the sham group(p < 0.001). This represents a large-magnitude effect (Cohen's d = 1.59), suggesting a potent anti-inflammatory action of the combined therapy. In contrast, plasma IL-1β and TNF-α levels showed no statistically significant differences among any of the groups. In the hypothalamus, chronic LPS exposure was associated with a downregulation of MAP kinase signaling pathways (ERK, JNK), indicative of endotoxin tolerance, and with reduced NF-κB level. This study provides novel evidence that 2600 MHz RF, when combined with AGM, may exert a powerful anti-inflammatory effect, highlighting a potential therapeutic interaction that warrants further investigation.

This work investigates the electroosmotic peristaltic transport of a Casson (blood)-based hybrid nanofluid $\left(F{e}_2{O}_3-\mathrm{Cu}\right)$ via an asymmetric channel embedded inside a porous medium. The model takes into consideration electric and magnetic field effects, Ohmic heating, as well as velocity and thermal slip conditions. The governing equations are simplified and solved by employing unsupervised sigmoid-based neural networks (SNNs), Fibonacci-based neural networks (FNNs), and their hybrid model (FSNNs) under the assumptions of low Reynolds number and long wavelength. Furthermore, a comparative analysis is conducted among SNNs, FNNs, and FSNNs to evaluate their performance. The results reveal that the FSNNs demonstrate superior accuracy and stability compared to the other models. The results show that the temperature rises with larger values of the Grashof number, Brinkman number, and heat source/sink parameter, while lowers with higher values of Casson parameter, porosity factor, and velocity slip parameter. The pressure gradient grows with increasing $\mathrm{Gr}$, $\varrho$, and $U_{\mathrm{hs}},$ but decreases as Hartmann number increases. This study sheds light on the design of efficient microfluidic, biomedical, and thermal management systems, emphasizing the role of electromagnetic modulation and hybrid nanofluids in improving performance and control.

The purpose of this study was to investigate the effects of a 900 megahertz (MHz) electromagnetic field (EMF) applied in the prenatal period on rat peripheral nerve morphology, nerve conduction velocity, and locomotor activity. Nine pregnant Sprague Dawley rats were assigned into three groups. No procedure was applied to the first group (control). The second (sham) group was placed inside an EMF cage for 1 h a day throughout the experiment (days 1-21 of pregnancy), but was not exposed to EMF. The third group (EMF) was placed inside the EMF cage for 1 h a day throughout the experiment (days 1-21 of pregnancy) and exposed to a 900 MHz EMF. No procedure was applied to the newborn pups until postnatal (PN) day 21, and new groups were constituted from among these. All the newly established groups were subjected to the open field and rotarod tests on PN days 21 and 60, after which electrophysiological measurements were performed on the groups in line with the study protocol. Sciatic nerves obtained from the animals sacrificed on PN day 60 were subjected to histopathological, histomorphometric, immunohistochemical, and biochemical analyses. In light of the study results, we concluded that prenatal application of a 900 MHz EMF adversely affects rat peripheral nerve development, and that these effects persist up to adulthood such as to be detectable in the sciatic nerve morphology, but that these morphological changes are not sufficiently severe to affect functional associated with the sciatic nerve.

The ever-expanding use of a large number of electrical appliances and mobile communication systems, which outnumber the global population, emit electromagnetic radiation through mobile telephones, power stations, transmission lines, radar, microwave ovens, televisions, refrigerators, therapeutic and other electronic devices. Electromagnetic radiation has been classified by the International Agency for Research on Cancer (IARC) as possibly carcinogenic to humans (Group 2B). A large number of research results show that short-term and long-term exposure to electromagnetic radiation can lead to anxiety, depression, decreased learning ability, memory loss, sleep rhythm disorders and other adverse effects. Sleep rhythm disorders affect many people worldwide and may be associated with psychiatric disorders such as anxiety and depression. In this review, we summarise key experiments related to the effects of electric field exposure on mood and rhythms in animal and cellular studies over the past decade, describe the effects of electromagnetic radiation on emotional behaviors and circadian rhythms in humans and mammals, and explore the relationship between electromagnetic radiation，mood and rhythms as well as its underlying mechanisms of action. Most animal studies suggest that electromagnetic radiation may affect the physiological organization and functioning of the brain, influence neurotransmitters and receptors, interfere with neuronal formation and structure, or alter associated endocrine hormones and free radicals, which may lead to the unfavorable development of psychiatric disorders and sleep rhythm disorders. This summary may provide researchers with better clues and ideas to develop therapeutic solutions with sleep disorders and depressive psychiatric disorders.

The use of mobile phones, one of the popular recent sources of radio-frequency fields (RFF), is increasing. It has been shown thatRFF exposure can increase free radical levels and oxidative stress.Obesity is an important risk factor for many diseases such as cancer, cardiovascular diseases, and diabetes, and has been shown to increase oxidative stress. In this study, rats were exposed to 2100 MHz RFF(electric field 15 V/m) for 15 minutes daily and 4 hours daily for 3 weeks. It aims to investigate the effects of 2100 MHz RFF on brain tissue and plasma of normal and obese rats. The rats were divided into eight groups (n = 6):control, Sham1, Sham2, RFF1, RFF2, High Fat Diet (HFD), Sham+HFD, andHFD+RFF. The inflammatory and oxidative effects on brain tissue and plasma were analyzed using the GraphPad 9 macOS package program. WhenTOS levels in brain tissue were compared between Sham2 and RFF1 andall groups, a significant difference was found in the RFF2 group. TASlevel was significantly different in the HDF+RFF group compared to the control group, Sham and all groups. When pro-inflammatory and anti-inflammatory parameters were evaluated in brain tissue, significant differences were found in different exposure groups. Inplasma, TOS levels were significantly different in the RFF2 groupcompared to Sham2 and RFF1, but TAS levels were not different.According to the data obtained, obesity may be protective against the oxidative and inflammatory effects of RFF.

High power microwaves (HPMs), characterized by frequencies spanning from 1 GHz to 300 GHz and peak power exceeding 100 MW, have numerous applications but also pose considerable health hazards. This review discusses the biological effects of HPMs on various human and animal cells, tissues, organs, and systems. Notably, HPMs can damage brain structures, particularly the hippocampus, causing oxidative stress and DNA damage, which in turn contribute to cognitive impairment. The immune system is subject to dual effects from HPMs, exhibiting both stimulatory and suppressive immune responses contingent on the specifics of exposure details. In the reproductive system, HPMs are observe to diminish male fertility by interfering with spermatogenesis and semen quality, although antioxidants may mitigate these effects. Furthermore, HPMs may exacerbate skin conditions, such as atopic dermatitis, and potentially accelerate the onset of skin cancer. With regard to cardiovascular health, these effects are usually transient, mainly affecting blood pressure and heart rate, but ultimately not impairing them. Furthermore, HPMs in agricultural production, sterilization and other beneficial effects have been found. This review provides valuable references for the investigation of the biological effects and the underlying mechanisms of HPM, as well as for the revision of related standards and guidelines.

In cardiovascular research, electromagnetic fields (EMFs) induced by Riga plates are applied to study and potentially manipulate blood flow dynamics, offering insights for therapies against arterial plaque deposition and for understanding varied blood flow behaviors. This research focuses on predicting the flow patterns of blood infused with gold and maghemite nanoparticles (gold-maghemite/blood) inside an EM microchannel under these electromagnetic influences and abruptly change in pressure gradient. The study models these flows by considering radiation heat emission and Darcy drag forces within porous media. Mathematical representation involves time-variant partial differential equations, resolved through Laplace transform (LT) to yield compact-form expressions for the model variables. The outcomes, including shear stress (SS) and rate of heat transfer (RHT) across the microchannel, are analyzed and displayed graphically, highlighting the effects of modified Hartmann number and electrode width on these parameters. Hybrid nano-blood (HNB) and nano-blood (NB) exhibit distinct thermal characteristics, with HNB transferring more heat within the blood flow. These study implements a cutting-edge AI-powered approach for high-fidelity evaluation of critical flow parameters, achieving unprecedented prediction accuracy. Validation results confirm the algorithm's excellence, with SS predictions reaching 99.552% (testing) and 97.019% (cross-validation) accuracy, while RHT predictions show 100% testing accuracy and 97.987% cross-validation reliability. This convergence of nanotechnology with advanced machine learning paves the way for transformative clinical applications that could redefine standards of care in surgical oncology, interventional cardiology, and therapeutic radiology. This model underpins potential applications such as controlled drug release and magnetic fluid hyperthermia, enhancing procedures like cardiopulmonary bypass, vascular surgery, and diagnostic imaging.

Brain tumors can cause difficulties in normal brain function and are capable of developing in various regions of the brain. Malignant tumours can develop quickly, pass through neighboring tissues, and extend to further brain regions or the central nervous system. In contrast, healthy tumors typically develop slowly and do not invade surrounding tissues. Individuals frequently struggle with sensory abnormalities, motor deficiencies affecting coordination, and cognitive impairments affecting memory and focus. In this research, Utilizing Phase-aware Composite Deep Neural Network Optimized with Coati Optimized Algorithm for Brain Tumor Identification Based on Magnetic resonance imaging (PACDNN-COA-BTI-MRI) is proposed. First, input images are taken from the brain tumour Dataset. To execute this, the input image is pre-processed using Multivariate Fast Iterative Filtering (MFIF) and it reduces the occurrence of over-fitting from the collected dataset; then feature extraction using Self-Supervised Nonlinear Transform (SSNT) to extract essential features like model, shape, and intensity. Then, the proposed PACDNN-COA-BTI-MRI is implemented in Matlab and the performance metrics Recall, Accuracy, F1-Score, Precision Specificity and ROC are analysed. Performance of the PACDNN-COA-BTI-MRI approach attains 16.7%, 20.6% and 30.5% higher accuracy; 19.9%, 22.2% and 30.1% higher recall and 16.7%, 21.9% and 30.8% higher precision when analysed through existing techniques brain tumor identification using MRI-Based Deep Learning Approach for Efficient Classification of Brain Tumor (MRI-DLA-ECBT), MRI-Based Brain Tumor Detection using Convolutional Deep Learning Methods and Chosen Machine Learning Techniques (MRI-BTD-CDMLT) and MRI-Based Brain Tumor Image Detection using CNN-Based Deep Learning Method (MRI-BTID-CNN) methods, respectively.

In this study, the genotoxic and histopathological effects of 6 GHz (0.065 W/kg) Radiofrequency-Electromagnetic Radiation (RF-EMR) on rat liver tissue were investigated. Sham (control) and Radiofrequency Radiation (RFR) groups were formed with 10 adult male rats in each group. Rats in the sham group received no treatment. Rats in the RFR group were exposed to 6 GHz RF-EMR for 4 h/day for 42 days. Immediately after the completion of the exposure, the rats in both groups were sacrificed and liver tissues were removed. Comet Test was performed to determine the genotoxic effect in the samples. Masson Trichrome and Hematoxylin Eosin staining methods were applied histopathologically. According to the Comet Analysis results, the genetic damage index (GDI) and damaged cell percentage (DCP) of the RFR group were higher than the sham group, but this difference was not statistically significant (p > 0.05). In histopathologic examinations, portal inflammation, single cell necrosis, vascularity and congestion were more prominent in the RFR group compared to the sham group. In our study, it was shown that 6 GHz RF-EMR can cause histopathologic and DNA level changes in rat liver tissue. As a result of the literature review, no prior studies have specifically examined the genotoxic and histopathological effects of 6 GHz RF-EMR. This makes our study important as it addresses the biological impacts of the 6 GHz frequency band.

The present research concentrates on examining entropy generation during the flow phenomenon of a three-dimensional peristaltic motion of a magnetized tri-hybrid nanofluid within a curved rectangular duct using a machine learning technique called backpropagated Levenberg-Marquardt (BLMT). The Carreau constitutive model is used for base liquid (blood). To obtain the most accurate solutions for the governing equations, an analytical tool called the Homotopy Perturbation Method (HPM) is utilized along with a machine learning methodology ANN-BLMT method on MatLab. The data of HPM and machine learning are also compared to assess how the framework of partial differential equations (PDEs) occurring in the problem can be improved. It shows the highest correlations between output and prediction of ANN-BLMT method. The convergence analysis reveals that for two scenarios, velocity exhibits the best validation performance values around $7.3117\times {10}^{-11}$ and $1.0082\times {10}^{-10}$. A detailed comparison between blood and nanofluid has been presented graphically to enhance the benefits of ternary hybrid nanoparticles in a simple base fluid. It is also found that the velocity of the blood can be slowed by the curvature increase and because of the increment of tri-hybrid nanoparticles in pure blood. It is also noted that the rate of heat transfer for ternary hybrid nanofluids is greater than that of a simple blood. Research findings have obvious implications for comprehending and enhancing peristaltic dynamics in biological processes such as the intestinal tract.