Literature DB >> 22951470

High potential for methodical improvements of FISH-based translocation analysis for retrospective radiation biodosimetry.

Christina Beinke1, Viktor Meineke.   

Abstract

Due to their high stability and accumulation over time, translocations are currently the cytogenetic marker of choice for radiation dose estimation following protracted radiation overexposures or overexposures that occurred up to several decades in the past (environmental/occupational/medical exposures). In the course of this, particular intention is focused on the quantification of low doses (≪ 1.0 Gy) for the purpose of evaluating potential associations between different radiation-induced chromosomal aberrations and future health impairments, usually cancer. However, existing limitations of FISH-based translocation analysis give occasion to further optimize this method. In particular, the practical and technical aspects of the method offer a great scope for potential improvements considerably facilitating the performance of extensive studies. On the one hand, huge studies encompassing a considerable number of different collectives aiming at the determination of spontaneous translocation frequencies due to several already determined and potentially not yet known confounders are essential for improved individual dosimetry in the very low dose range. An accurate and reliable individual dosimetry and the methodical feasibility of extensive FISH-based studies are prerequisites to further elucidate the characteristics of radiation induced cancer; e.g., radiation and radiation quality specificity or total dose and dose rate dependencies. This paper focuses on the practical and technical limitations of FISH-based translocation analysis, in fact the tremendous workload and costs of huge approaches, and points out how this could be overcome by method optimization, namely standardizing and automating translocation scoring to allow sharing of future work and planning of more extensive studies.

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Year:  2012        PMID: 22951470     DOI: 10.1097/HP.0b013e31824645fb

Source DB:  PubMed          Journal:  Health Phys        ISSN: 0017-9078            Impact factor:   1.316


  6 in total

1.  Radiation Dose-Rate Effects on Gene Expression in a Mouse Biodosimetry Model.

Authors:  Sunirmal Paul; Lubomir B Smilenov; Carl D Elliston; Sally A Amundson
Journal:  Radiat Res       Date:  2015-06-26       Impact factor: 2.841

2.  Retrospective biodosimetry using translocation frequency in a stable cell of occupationally exposed to ionizing radiation.

Authors:  Min Su Cho; Jin Kyung Lee; Keum Seok Bae; Eun-Ae Han; Seong Jae Jang; Wi-Ho Ha; Seung-Sook Lee; Joan Francesc Barquinero; Wan Tae Kim
Journal:  J Radiat Res       Date:  2015-04-28       Impact factor: 2.724

3.  Medical management of acute responses to radiation.

Authors:  Nelson J Chao; Cullen Case; Dennis Confer
Journal:  Hemasphere       Date:  2019-06-30

4.  Comparison of Individual Radiosensitivity to γ-Rays and Carbon Ions.

Authors:  Grace Shim; Marie Delna Normil; Isabelle Testard; William M Hempel; Michelle Ricoul; Laure Sabatier
Journal:  Front Oncol       Date:  2016-06-13       Impact factor: 6.244

5.  Consecutive results of blood cell count and retrospective biodosimetry: useful tools of health protection regulation for radiation workers.

Authors:  Seongjae Jang; Jin Kyung Lee; Minsu Cho; Su San Yang; Seung Hyun Kim; Wan Tae Kim
Journal:  Occup Environ Med       Date:  2016-07-26       Impact factor: 4.402

6.  Occupational radiation exposure and its health effects on interventional medical workers: study protocol for a prospective cohort study.

Authors:  Seulki Ko; Hwan Hoon Chung; Sung Bum Cho; Young Woo Jin; Kwang Pyo Kim; Mina Ha; Ye Jin Bang; Yae Won Ha; Won Jin Lee
Journal:  BMJ Open       Date:  2017-12-15       Impact factor: 2.692

  6 in total

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