Biology subjects

Goliaei, B.

Publications and source records attributed to Goliaei, B..

4 recordsLinked to original sources

bioRxiv2026

Crosstalk Between Calcium Dynamics and ROS Levels in U87 Glioblastoma Cells Exposed to Extremely Low Frequency Pulsed Electromagnetic Fields

Extremely low-frequency pulsed electromagnetic fields (ELF-PEMFs) have been proposed to modulate intracellular signaling in cancer cells, however, the primary mediators and their temporal sequence remain incompletely understood. In this study, U87 glioblastoma cells were exposed to ELF-PEMF at varying frequencies and amplitudes, and intracellular calcium (Ca2+) dynamics, reactive oxygen species (ROS) levels, and mitochondrial membrane potential ({Delta}{Psi}m) were monitored. Exposure likely led to rapid ROS elevation and a decrease in {Delta}{Psi}m, indicating early mitochondrial involvement in ELF-PEMF responses. Fast Fourier transform (FFT) analysis of Ca2+ oscillations suggested that low-frequency exposures produced higher spectral power and amplitude compared with controls, consistent with enhanced Ca2+ signaling activity. Parallel pharmacological experiments demonstrated that ROS elevation may occur independently of IPL-dependent endoplasmic reticulum (ER) Ca2+ release, as 2-Aminoethoxydiphenyl borate (2-APB) inhibition did not prevent ROS increase. In contrast, treatment with the antioxidant N-acetylcysteine (NAC) effectively suppressed ROS without significantly altering basal cytosolic Ca2+ levels. These observations indicate that ROS likely acts as an early mediator of cellular responses to ELF-PEMF exposure, with downstream modulation of calcium signaling pathways. The magnitude of ROS elevation and Ca2+ modulation was strongly dependent on field frequency and amplitude, consistent with a frequency-dependent biological window. Overall, ROS likely acts as a primary mediator of ELF-PEMF bioeffects, highlighting its potential relevance for glioblastoma therapy, and future studies are warranted to assess other glioma lines to confirm generalizability.

cell biology↗

bioRxiv2025

A Dynamic Model of Calcium Frequency Modulation by Mitochondrial Superoxide

Numerous studies have highlighted the crucial roles of cytosolic calcium transients mediated by inositol 1,4,5-trisphosphate receptor (IP3R) channels in intracellular signaling, as well as the significant modulatory effects of cytosolic redox state on these dynamics. Accordingly, developing a mathematical model that captures the core dynamics by which redox state of IP3Rs influence calcium signaling would provide a valuable foundation for simulating and predicting experimental observations. In this study, we developed a dynamic system, based on ordinary differential equations that incorporates a kinetic model for the redox dynamic of the IP3R and the role of this dynamic on the channels gating parameters. Using this framework, we simulated both the static and dynamic effects of mitochondria-derived superoxide fluctuations on local calcium oscillations in non-excitable cells. Numerical solutions demonstrated that the model quantitatively reproduced experimentally observed changes in local calcium oscillation frequency in response to mitochondria-derived superoxide variations. Overall, the proposed model offers a predictive tool for exploring how redox perturbations in non-excitable cells affect cellular signaling pathways through calcium frequency modulation.

cell biology↗

bioRxiv2025

Unlocking Precision Diagnostics: A Multimodal Framework Integrating Metabolomics with Advanced Machine Learning Techniques

Integrating multiple omics modalities is a crucial strategy in cancer research, particularly in metabolomics, enabling early detection and detailed exploration of cancer biomarker signatures. This study evaluates five strategies for integrating metabolomics data from liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and nuclear magnetic resonance. Deep Transfer Learning and Multiple Kernel Learning demonstrated superior performance, significantly improving classification accuracy, sensitivity, and robustness compared to single-modality analyses. Deep Transfer Learning employed a custom autoencoder for feature extraction followed by artificial neural network classification, while Multiple Kernel Learning optimized kernel matrices across different modalities. Feature extraction in the Deep Transfer Learning approach, combined with the selection of important features and subsequent analysis, revealed elevated levels of monounsaturated phospholipids such as phosphatidylcholine 30:1, phosphatidylethanolamine 32:1, and sphingomyelin 32:1 in HER2-positive cases. Additionally, {beta}-alanine, gluconic acid, and N-acetylaspartic acid were increased, whereas 5-deoxy-5-methylthioadenosine and nicotinamide were decreased. These methods advance cancer detection, biomarker discovery, and the development of precise diagnostic and therapeutic tools while offering robust and adaptable strategies for multi-omics data integration across diverse biological datasets.

bioinformatics↗

bioRxiv2024

An Amplification Mechanism for Weak ELF Magnetic Fields Quantum-Bio Effects in Cancer Cells

Observing quantum mechanical characteristics in biological processes is a surprising and important discovery. One example, which is gaining more experimental evidence and practical applications, is the effect of weak magnetic fields with extremely low frequencies on cells, especially cancerous ones. In this study, we use a mathematical model of ROS dynamics in cancer cells to show how ROS oscillatory patterns can act as a resonator to amplify the small effects of the magnetic fields on the radical pair dynamics in mitochondrial Complex III. We suggest such a resonator can act in two modes for distinct states in cancer cells: 1) cells at the edge of mitochondrial oscillation and 2) cells with local oscillatory patches. When exposed to magnetic fields, the first group exhibits high-amplitude oscillations, while the second group synchronizes to reach a whole-cell oscillation. Both types of amplification are frequency-dependent in the range of hertz and sub-hertz. We use UV radiation as a positive control to observe the two states of cells in DU and HELA cell lines. Application of magnetic fields shows frequency-dependent results on both the ROS and mitochondrial potential which agree with the model for both type of cells. We also observe the oscillatory behavior in the time-lapse fluorescence microscopy for 0.02 Hz magnetic fields. Finally, we investigate the dependence of the results on the field strength and propose a quantum spin-forbidden mechanism for the effect of magnetic fields on superoxide production in QO site of mitochondrial Complex III.

biophysics↗