In-vitro assessment of Jurkat T-cells response to 1966 MHz electromagnetic fields in a GTEM cell

Nektarios Moraitis, Maria Christopoulou, Konstantina S. Nikita, Georgia Persephoni Voulgaridou, Ioannis Anestopoulos, Mihalis I Panagiotidis, Aglaia Pappa

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    2 Citations (Scopus)

    Abstract

    This paper presents the experimental configuration and procedure as well as the in-vitro assessment of Jurkat T-cells response to 1966 MHz exposure of modulated and unmodulated electromagnetic signals within a Gigahertz Transverse Electro-Magnetic (GTEM) cell. Different combinations of electric field intensity, exposure duration and modulation schemes were applied. Exposures at continuous wave (CW) signal at low intensity levels (3 V/m) did not induce any significant DNA damage, but a slight increase was observed for extreme stress levels (76.4 V/m). On the other hand, the results indicate that, at both, low and high electric field intensity UMTS (Universal Mobile Telecommunications System) signal could be statistically related to DNA damage invitro. Nevertheless, further experiments are required, increasing the statistical number of samples and recruiting more DNA damage endpoints before conclusive statements are drawn.

    Original languageEnglish
    Title of host publication37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015
    PublisherIEEE
    Pages2592-2595
    Number of pages4
    ISBN (Print)9781424492718
    DOIs
    Publication statusPublished - Nov 2015
    Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2015 - Milan, Italy
    Duration: 25 Aug 201529 Aug 2015

    Conference

    Conference37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2015
    Abbreviated titleEMBC 2015
    Country/TerritoryItaly
    CityMilan
    Period25/08/1529/08/15

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition
    • Signal Processing
    • Biomedical Engineering
    • Health Informatics

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