A Regenerative RF Sensing System for Improved Detection of Microwave Emission From Staphylococcus aureus Biofilms
IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology（2022）
摘要
Electromagnetic (EM) radiation from
Staphylococcus aure
us (
S. aureus
) biofilms has been recently detected in the 3.16 – 3.2 GHz frequency range. In this work, a regenerative RF sensing system is designed and implemented to enhance the detection of signals generated by biofilms. The system utilizes the concept of regeneration (also known as positive feedback) for the amplification of emitted signals at a desired frequency (3.18 GHz). Comparative experiments were conducted, where the power measured from peptone-NaCl-glucose (PNG) media with biofilms (biofilm samples) was compared with that measured from fresh PNG media void of biofilms (PNG samples). The measured power level differences between the biofilm samples and the PNG samples are many orders of magnitude higher than what was previously reported using the wideband near-zone radiative system. Furthermore, illumination experiments were conducted to examine biofilms’ response to external EM stimuli. A sinusoidal signal at the emission frequency of 3.18 GHz was used to illuminate the biofilms. It is shown that biofilm samples exhibited stronger radiation behavior after being exposed to the external 3.18 GHz signal. For comparison, a similar setup was constructed at a different frequency (6.3 GHz), and the same experiments were carried out. No radiation is identified in the other band for both illuminated and unilluminated biofilm samples, which is consistent with the results reported in previous studies. This work not only confirms the existence of EM radiation generated by biofilms, but also demonstrates that cells actively respond to external EM signals at the same frequency as the signal they generate. This discovery is a major step toward understanding cell communications.
更多查看译文
关键词
Bioelectromagnetic,EM signaling,regeneration,positive feedback,amplification,biofilms
AI 理解论文
溯源树
样例
生成溯源树，研究论文发展脉络
Chat Paper
正在生成论文摘要