ArticleScientific reports2022
Radiation dose estimation with time-since-exposure uncertainty using the [Formula: see text]-H2AX biomarker.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Potential biomarkers of chronic low-dose radiation exposure for nuclear medicine technologists.International journal of radiation biology · 2025Review
- Current Status and Developments in Biodosimetry Research in India.Journal of medical physicsReview
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6 authors.
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Abstract
To predict the health effects of accidental or therapeutic radiation exposure, one must estimate the radiation dose that person received. A well-known ionising radiation biomarker, phosphorylated [Formula: see text]-H2AX protein, is used to evaluate cell damage and is thus suitable for the dose estimation process. In this paper, we present new Bayesian methods that, in contrast to approaches where estimation is carried out at predetermined post-irradiation times, allow for uncertainty regarding the time since radiation exposure and, as a result, produce more precise results. We also use the Laplace approximation method, which drastically cuts down on the time needed to get results. Real data are used to illustrate the methods, and analyses indicate that the models might be a practical choice for the [Formula: see text]-H2AX biomarker dose estimation process.
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