{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T17:31:03Z","timestamp":1790357463546,"version":"4.1.0"},"reference-count":74,"publisher":"Oxford University Press (OUP)","issue":"14","license":[{"start":{"date-parts":[[2023,9,18]],"date-time":"2023-09-18T00:00:00Z","timestamp":1694995200000},"content-version":"vor","delay-in-days":17,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,9,18]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Biomarkers for ionising radiation exposure have great utility in scenarios where there has been a potential exposure and physical dosimetry is missing or in dispute, such as for occupational and accidental exposures. Biomarkers that respond as a function of dose are particularly useful as biodosemeters to determine the dose of radiation to which an individual has been exposed. These dose measurements can also be used in medical scenarios to track doses from medical exposures and even have the potential to identify an individual\u2019s response to radiation exposure that could help tailor treatments. The measurement of biomarkers of exposure in medicine and for accidents, where a larger number of samples would be required, is limited by the throughput of analysis (i.e. the number of samples that could be processed and analysed), particularly for microscope-based methods, which tend to be labour-intensive. Rapid analysis in an emergency scenario, such as a large-scale accident, would provide dose estimates to medical practitioners, allowing timely administration of the appropriate medical countermeasures to help mitigate the effects of radiation exposure. In order to improve sample throughput for biomarker analysis, much effort has been devoted to automating the process from sample preparation through automated image analysis. This paper will focus mainly on biological endpoints traditionally analysed by microscopy, specifically dicentric chromosomes, micronuclei and gamma-H2AX. These endpoints provide examples where sample throughput has been improved through automated image acquisition, analysis of images acquired by microscopy, as well as methods that have been developed for analysis using imaging flow cytometry.<\/jats:p>","DOI":"10.1093\/rpd\/ncad060","type":"journal-article","created":{"date-parts":[[2023,3,18]],"date-time":"2023-03-18T03:54:59Z","timestamp":1679111699000},"page":"1477-1484","source":"Crossref","is-referenced-by-count":7,"title":["Development of high-throughput systems for biodosimetry"],"prefix":"10.1093","volume":"199","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9621-477X","authenticated-orcid":false,"given":"Ruth C","family":"Wilkins","sequence":"first","affiliation":[{"name":"Consumer and Clinical Radiation Protection Bureau, Health Canada , Ottawa K1A 1C1 , Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lindsay A","family":"Beaton-Green","sequence":"additional","affiliation":[{"name":"Consumer and Clinical Radiation Protection Bureau, Health Canada , Ottawa K1A 1C1 , Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2023,9,18]]},"reference":[{"key":"2023121516261528500_ref1","doi-asserted-by":"crossref","DOI":"10.1016\/j.mrrev.2019.108287","article-title":"Retrospective biodosimetry techniques: focus on cytogenetics assays for individuals exposed to ionizing radiation","volume":"783","author":"Herate","year":"2020","journal-title":"Mutat. 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