Cookies

We use cookies to ensure that we give you the best experience on our website. By continuing to browse this repository, you give consent for essential cookies to be used. You can read more about our Privacy and Cookie Policy.


Durham Research Online
You are in:

A statistical framework for radiation dose estimation with uncertainty quantification from the γ-H2AX assay.

Einbeck, Jochen and Ainsbury, Elizabeth A. and Sales, Rachel and Barnard, Stephen and Kaestle, Felix and Higueras, Manuel (2018) 'A statistical framework for radiation dose estimation with uncertainty quantification from the γ-H2AX assay.', PLoS ONE., 13 (11). e0207464.

Abstract

Over the last decade, the γ–H2AX focus assay, which exploits the phosphorylation of the H2AX histone following DNA double–strand–breaks, has made considerable progress towards acceptance as a reliable biomarker for exposure to ionizing radiation. While the existing literature has convincingly demonstrated a dose–response effect, and also presented approaches to dose estimation based on appropriately defined calibration curves, a more widespread practical use is still hampered by a certain lack of discussion and agreement on the specific dose–response modelling and uncertainty quantification strategies, as well as by the unavailability of implementations. This manuscript intends to fill these gaps, by stating explicitly the statistical models and techniques required for calibration curve estimation and subsequent dose estimation. Accompanying this article, a web applet has been produced which implements the discussed methods.

Item Type:Article
Full text:(VoR) Version of Record
Available under License - Creative Commons Attribution.
Download PDF
(2237Kb)
Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1371/journal.pone.0207464
Publisher statement:Copyright: © 2018 Einbeck et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Date accepted:31 October 2018
Date deposited:13 December 2018
Date of first online publication:28 November 2018
Date first made open access:13 December 2018

Save or Share this output

Export:
Export
Look up in GoogleScholar