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Prediction of the Exposure to 1763MHz Radiofrequency Radiation Based on Gene Expression Patterns
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  • Prediction of the Exposure to 1763MHz Radiofrequency Radiation Based on Gene Expression Patterns
  • Prediction of the Exposure to 1763MHz Radiofrequency Radiation Based on Gene Expression Patterns
저자명
Lee. Min-Su,Huang. Tai-Qin,Seo. Jeong-Sun,Park. Woong-Yang
간행물명
Genomics & informatics
권/호정보
2007년|5권 3호|pp.102-106 (5 pages)
발행정보
한국유전체학회
파일정보
정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
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기타언어초록

Radiofrequency (RF) radiation at the frequency of mobile phones has been not reported to induce cellular responses in in vitro and in vivo models. We exposed HEI-OC1, conditionally-immortalized mouse auditory cells, to RF radiation to characterize cellular responses to 1763 MHz RF radiation. While we could not detect any differences upon RF exposure, whole-genome expression profiling might provide the most sensitive method to find the molecular responses to RF radiation. HEI-OC1 cells were exposed to 1763 MHz RF radiation at an average specific absorption rate (SAR) of 20 W/kg for 24 hr and harvested after 5 hr of recovery (R5), alongside sham-exposed samples (S5). From the whole-genome profiles of mouse neurons, we selected 9 differentially-expressed genes between the S5 and R5 groups using information gain-based recursive feature elimination procedure. Based on support vector machine (SVM), we designed a prediction model using the 9 genes to discriminate the two groups. Our prediction model could predict the target class without any error. From these results, we developed a prediction model using biomarkers to determine the RF radiation exposure in mouse auditory cells with perfect accuracy, which may need validation in in vivo RF-exposure models.