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Dispersive Modeling of Normal and Cancerous Cervical Cell Responses to Nanosecond Electric Fields in Reversible
Mayank Kumar1, Sachin Kumar2, Shubhro Chakrabartty3
1Technical Research Analyst (TRA), Electronics/Biomedical Engineering, Aranca, Mumbai 400076, Maharastra, India.
Micromachines
|December 23, 2023
Summary
This study models cervical cells and their response to electric pulses, revealing differences between normal and cancerous cells for potential diagnostic and therapeutic applications.
Area of Science:
- Biophysics
- Cell Biology
- Computational Modeling
Background:
- Understanding cellular responses to electric fields is crucial for developing novel diagnostic and therapeutic strategies.
- Investigating the mechanical and electrical properties of normal versus cancerous cervical cells provides insights into disease mechanisms.
Purpose of the Study:
- To develop a 3D computational model of normal and cancerous cervical cells.
- To analyze cellular responses, including transmembrane potential and pore dynamics, to low-frequency and nanosecond pulsed electric fields.
- To investigate cytoskeleton integrity and electrodeformation under electric stress.
Main Methods:
- Image processing and computer-aided design (CAD) for 3D cell modeling.
- Simulation of low-frequency and nanosecond pulsed electric fields.
- Calculation of transmembrane potential, pore density/radius, Maxwell stress tensor, and solid displacement.
- Thermal analysis to confirm non-thermal effects.
Main Results:
- Validated computational models against experimental data for low-frequency pulses.
- Observed distinct responses of normal and cancerous cervical cells to electric pulses.
- Demonstrated that nanosecond pulsed electric fields induce non-thermal effects.
- Quantified cellular deformation and strain energy under electric stress.
Conclusions:
- The developed 3D cell models accurately predict cellular responses to electric fields.
- Differences in cellular morphology and properties lead to varied responses between normal and cancerous cells.
- The model-driven microdosimetry approach shows promise for diagnostic and therapeutic applications in oncology.

