Determination of Sensitive Frequency Bands for Cytotoxicity Analysis Using Microwave Dielectric Measurements

This study presents a comprehensive frequency-resolution analysis framework to identify biologically significant frequency bands for cancer cell monitoring in the 10–20 GHz range. By integrating statistical significance, effect size, dielectric deviation magnitude, and temporal stability analysis, the spectral response of cell cultures exposed to cytotoxic agents was systematically evaluated. The results revealed a dual-optimization environment: the 13.9–14.2 GHz range showed a statistically significant global maximum for signal coherence, while higher frequencies demonstrated superior dielectric contrast due to γ-dispersion mechanisms. To resolve this balance, a composite sensitivity score and band-averaged analysis were used. The evaluation identified the 16–18 GHz band as the optimum working region, offering significantly enhanced physical contrast and temporal robustness while maintaining a composite score almost identical to the statistical peak (<0.7% difference). This study demonstrates that data-driven, multi-criteria frequency selection provides a robust foundation for sensor design and paves the way for the development of highly sensitive, frequency-selective microwave biosensors for toxicological screening.

Authors

Institutions

Publication Details

Journal
International Journal of Applied Methods in Electronics and Computers
Published
2025-12-30
DOI
https://doi.org/10.58190/ijamec.2025.148
Primary Topic
Microwave and Dielectric Measurement Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Determination of Sensitive Frequency Bands for Cytotoxicity Analysis Using Microwave Dielectric Measurements

Taha Fatih Ateş, Ali Osman ÖZKAN
International Journal of Applied Methods in Electronics and Computers
Microwave and Dielectric Measurement Techniques
article

Determination of Sensitive Frequency Bands for Cytotoxicity Analysis Using Microwave Dielectric Measurements

Taha Fatih Ateş, Ali Osman ÖZKAN
article en

Abstract

This study presents a comprehensive frequency-resolution analysis framework to identify biologically significant frequency bands for cancer cell monitoring in the 10–20 GHz range. By integrating statistical significance, effect size, dielectric deviation magnitude, and temporal stability analysis, the spectral response of cell cultures exposed to cytotoxic agents was systematically evaluated. The results revealed a dual-optimization environment: the 13.9–14.2 GHz range showed a statistically significant global maximum for signal coherence, while higher frequencies demonstrated superior dielectric contrast due to γ-dispersion mechanisms. To resolve this balance, a composite sensitivity score and band-averaged analysis were used. The evaluation identified the 16–18 GHz band as the optimum working region, offering significantly enhanced physical contrast and temporal robustness while maintaining a composite score almost identical to the statistical peak (<0.7% difference). This study demonstrates that data-driven, multi-criteria frequency selection provides a robust foundation for sensor design and paves the way for the development of highly sensitive, frequency-selective microwave biosensors for toxicological screening.

International Journal of Applied Methods in Electronics and Computers
Necmettin Erbakan University (TR), KTO Karatay University (TR)
Necmettin Erbakan Üniversitesi
Openalex Percentile: Top 41%
Microwave and Dielectric Measurement Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.