Electromagnetic Biology and Medicine最新文献

In this study, we investigated the inhibitory effects of radiofrequency exposure on RANKL-induced osteoclast differentiation in RAW264.7 cells, along with the underlying mechanisms. RAW264.7 cells were subjected to radiofrequency exposure at three distinct power densities: 50 µW/cm², 150 µW/cm², and 450 µW/cm². The results showed that, among the three dosage levels, exposure to 150 µW/cm² of radiofrequency radiation significantly reduced the proliferation capacity of RAW264.7 cells. RF exposure at three power densities resulted in significant increases in the level of osteoclast apoptosis and notable decreases in osteoclast differentiation. Notably, the most pronounced effects on apoptosis, differentiation in RAW 264.7 cells were observed at the 150 µW/cm² power density. These effects were accompanied by concurrent decreases in mRNA and protein levels of osteoclast-specific genes, including RANK, NFATc1, and TRACP. Furthermore, radiofrequency exposure at power density of 150 µW/cm² induced a significant decrease in cytoplasmic NF-κB protein levels while increasing its nuclear fraction, thereby counteracting the effects of RANKL-induced NF-κB activation. These data suggest that radiofrequency exerts inhibitory properties on RANKL-induced NF-κB transcriptional activity, subsequently indirectly suppressing the expression of downstream NF-κB target genes, such as NFATc1 and TRACP. In conclusion, our study demonstrates that radiofrequency radiation effectively inhibits osteoclast differentiation by modulating the NF-κB signaling pathway. These findings have important implications for potential therapeutic interventions in osteoporosis.

The brain is a crucial organ that controls the body's neural system. The tumor develops and spreads across the brain as a result of irregular cell generation. The provision of substantial treatment to patients requires the early diagnosis of malignancies. However, timely diagnosis and accurate classification were difficult in the conventional models. Thus, the Taylor Fire Hawk optimization (TFHO) is implemented here for effective segmentation and classification. The TFHO is the merging of the Taylor series and Fire Hawk Optimizer (FHO). The de-noising is accomplished by the adaptive median filter, and the segmentation is carried out using M-Net, which has been trained by TFHO. Subsequently, image augmentation is performed to increase the image dimension, followed by the extraction of effective features. Finally, DenseNet is used for the classification, and the training is done by TFHO. The introduced method obtained 94.86% accuracy, 92.83% Negative Predictive Values, 89.33% Positive Predictive Values (PPV), 95.91% True Positive Rate (TPR), 4.37% False Negative Rate (FNR), and 90.98% F1-score.

Brain tumors present a formidable diagnostic challenge due to their aberrant cell growth. Accurate determination of tumor location and size is paramount for effective diagnosis. Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) are pivotal tools in clinical diagnosis, yet tumor segmentation within their images remains challenging, particularly at boundary pixels, owing to limited sensitivity. Recent endeavors have introduced fusion-based strategies to refine segmentation accuracy, yet these methods often prove inadequate. In response, we introduce the Parallel-Way framework to surmount these obstacles. Our approach integrates MRI and PET data for a holistic analysis. Initially, we enhance image quality by employing noise reduction, bias field correction, and adaptive thresholding, leveraging Improved Kalman Filter (IKF), Expectation Maximization (EM), and Improved Vibe Algorithm (IVib), respectively. Subsequently, we conduct multi-modality image fusion through the Dual-Tree Complex Wavelet Transform (DTWCT) to amalgamate data from both modalities. Following fusion, we extract pertinent features using the Advanced Capsule Network (ACN) and reduce feature dimensionality via Multi-objective Diverse Evolution-based selection. Tumor segmentation is then executed utilizing the Twin Vision Transformer with dual attention mechanism. Implemented our Parallel-Way framework which exhibits heightened model performance. Evaluation across multiple metrics, including accuracy, sensitivity, specificity, F1-Score, and AUC, underscores its superiority over existing methodologies.

Efficient and accurate classification of brain tumor categories remains a critical challenge in medical imaging. While existing techniques have made strides, their reliance on generic features often leads to suboptimal results. To overcome these issues, Multimodal Contrastive Domain Sharing Generative Adversarial Network for Improved Brain Tumor Classification Based on Efficient Invariant Feature Centric Growth Analysis (MCDS-GNN-IBTC-CGA) is proposed in this manuscript.Here, the input imagesare amassed from brain tumor dataset. Then the input images are preprocesssed using Range - Doppler Matched Filter (RDMF) for improving the quality of the image. Then Ternary Pattern and Discrete Wavelet Transforms (TPDWT) is employed for feature extraction and focusing on white, gray mass, edge correlation, and depth features. The proposed method leverages Multimodal Contrastive Domain Sharing Generative Adversarial Network (MCDS-GNN) to categorize brain tumor images into Glioma, Meningioma, and Pituitary tumors. Finally, Coati Optimization Algorithm (COA) optimizes MCDS-GNN's weight parameters. The proposed MCDS-GNN-IBTC-CGA is empirically evaluated utilizing accuracy, specificity, sensitivity, Precision, F1-score,Mean Square Error (MSE). Here, MCDS-GNN-IBTC-CGA attains 12.75%, 11.39%, 13.35%, 11.42% and 12.98% greater accuracy comparing to the existingstate-of-the-arts techniques, likeMRI brain tumor categorization utilizing parallel deep convolutional neural networks (PDCNN-BTC), attention-guided convolutional neural network for the categorization of braintumor (AGCNN-BTC), intelligent driven deep residual learning method for the categorization of braintumor (DCRN-BTC),fully convolutional neural networks method for the classification of braintumor (FCNN-BTC), Convolutional Neural Network and Multi-Layer Perceptron based brain tumor classification (CNN-MLP-BTC) respectively.

Results from clinical trials show that serotonergic psychedelics have efficacy in treating psychiatric disorders, where currently approved pharmacotherapies are inadequate. Developing psychedelic medicines, however, comes with unique challenges, such as tempering heightened anxiety associated with the psychedelic experience. We conceived a new strategy to potentially mitigate psychedelic effects with defined electromagnetic signals (ES). We recorded the electromagnetic fields emitted by the serotonin 2 receptor (5-HT₂R) agonist (±)-2,5-dimethoxy-4-iodoamphetamine (DOI) and converted them to a playable WAV file. We then exposed the DOI WAV ES to mice to assess its effects on the DOI-elicited, 5-HT_2AR dependent head-twitch response (HTR). The DOI WAV signal significantly attenuated the HTR in mice elicited by 0.1 and 0.3 mg/kg subcutaneous DOI (p < 0.05 and p < 0.01, respectively). A scrambled WAV signal did not affect the DOI-elicited HTR, suggesting specificity of the DOI WAV signal. These results provide evidence that defined ES could modulate the psychoactive effects of serotonergic psychedelics. We discuss putative explanations for the distinct effects of the DOI WAV signal in the context of previous studies that demonstrate ES's efficacy for treating other conditions, including pain and cancer.

Breast cancer has been recognized as the most common cancer affecting women. Extremely low-frequency electromagnetic field (ELF-EMF) exposure can influence cellular activities such as cell-cell junctions and metastasis. However, more research is required to determine these fields' underlying mechanisms of action. Since cadherin switching is an important process during EMT (epithelial-mesenchymal transition), in this study, cadherin switching was regarded as one of the probable mechanisms of the effect of ELF-EMFs on metastasis suppression. For five days, breast cells received a 1 Hz, 100mT ELF-EMF (2 h/day). Cell invasion and migration were assessed in vitro by the Scratch wound healing assay and Transwell culture chambers. The expression of E- and N-cadherin was assessed using real-time PCR, western blotting, and Immunocytochemistry. ELF-EMF dramatically reduced the migration and invasion of MDA-MB 231 malignant cells compared to sham exposure, according to the results of the scratch test and the Transwell invasion test. The mRNA and protein expression levels of E-cadherin showed an increase, while the N-cadherin expression was found with a decrease, in MDA-MB231 cells receiving 1 Hz EMF compared to sham exposure. E-cadherin's mRNA and protein expression levels were enhanced in MCF10A cells receiving 1 Hz EMF compared to sham exposure. ELF-EMF can be used as a method for the multifaceted treatments of invasive breast cancer.

The effect of non-ionizing millimeter range electromagnetic waves (MM EMW) (30-300 GHz) on the bovine serum albumin (BSA) interaction peculiarities with acridine orange (AO) has been studied in vitro. The frequencies 41.8 and 50.3 GHz were chosen, since the first one is nonresonant frequency for the water, while the second one is resonant for water. The binding constant and number of binding sites were calculated at both irradiation presence and absence. AO was revealed to bind to BSA, while after the protein irradiation the interaction force strengthens. However, it was also shown that there are differences of the interaction parameters while irradiating by 41.8 or 50.3 GHz. AO binds to BSA, irradiated by MM EMW with the frequency 41.8 GHz much more weaker, than to that, irradiated by MM EMW with the frequency 50.3 GHz.

Background: Oncological systemic treatments such as cytotoxic chemotherapy, radiation therapy or treatment with biological response modifiers can alter the quality of life (QoL) of cancer patients.The aim of this study is to assess the effects of cardiologic magnetic and optical stimulation (CMOS) on QoL in patients with advanced cancer receiving systemic treatment. For this purpose, we designed a non-invasive device that can reproduce and dynamically modulate stimulations of the same nature as the biological electromagnetic emissions specific to the body (cardiac). These crafted emissions were sent back to the body in perfect synchronization with the Electrocardiogram (ECG) in order to foster resonance mechanisms.

Methodology: In the phase pilot EPHEME, the experimental group received sessions of exposure to CMOS and control group without exposure to CMOS.This study was conducted on hospitalized patients suffering from anxiety and depression. The improvement of the global Hospital Anxiety and Depression (HAD) score being the primary end-point, was completed before and after 3 sessions of CMOS treatment over a period of 10 days. The secondary objective is to evaluate the quality of life, by using the EQ-5D questionnaire which covers mobility, autonomy, usual activities, pain/discomfort, and anxiety/depression. Additionally, patient satisfaction was measured for the two groups.

Results: The patient outcomes in the experimental group treated with CMOS demonstrated notable improvements. The variation in the Hospital Anxiety and Depression (HAD) scores before and after treatment showed a significant decrease (p < 0.001). Similarly, the quality of life, as measured by the EQ-5D questionnaire, exhibited significant enhancement (p = 0.004). Conversely, in the control group, no significant improvement in either anxiety and depression symptoms or quality of life. Throughout the study, sessions were well tolerated, and there were no reports of serious side effects in either group.

Conclusions: The cardiologic magnetic and optical emissions provided by the CMOS device subjectively improved the quality of life in cancer patients receiving systemic treatment compared to those receiving sham stimulation. A prospective randomized study using a larger patient sample could bring more robust results. More research is needed to understand potential positives effects of low frequencies/heart-like electromagnetic waves in treatment of cancer-related fatigue.

The size of the pores created by external electrical pulses is important for molecule delivery into the cell. The size of pores and their distribution on the cell membrane determine the efficiency of molecule transport into the cell. There are very few studies visualizing the presence of electropores. In this study, we aimed to investigate the size distribution of electropores that were created by high intensity and short duration electrical pulses on MCF-7 cell membrane. Scanning Electron Microscopy (SEM) was used to visualize and characterize the membrane pores created by the external electric field. Structural changes on the surface of the electroporated cell membrane was observed by Atomic Force Microscopy (AFM). The size distribution of pore sizes was obtained by measuring the radius of 500 electropores. SEM imaging showed non-uniform patterning. The average radius of the electropores was 12 nm, 51.60% of pores were distributed within the range of 5 to 10 nm, and 81% of pores had radius below 15 nm. These results showed that microsecond (µs) high intensity electrical pulses cause the creation of heterogeneous nanopores on the cell membrane.