{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T22:57:34Z","timestamp":1791241054140,"version":"4.1.0"},"reference-count":97,"publisher":"Radiation Research Society","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Radiation Research"],"published-print":{"date-parts":[[2025,9,19]]},"abstract":"<jats:p>The issue of determining likely outcomes after low dose exposure to radiation is complex and controversial. Currently, the linear no-threshold (LNT) model is used to justify the linear extrapolation of (adverse) outcomes from high doses, where effects are clearly seen, to low doses, where effects are very difficult to detect and even more difficult to ascribe to the measured radiation exposure. Among the factors hindering the development of a more precise system are the lack of reliable predictors of system health. While biomarkers indicating the health of individual cells or organisms exist, they fail at low doses due to the complexity of cause-effect relationships and the multiple factors contributing stress to the system as a whole (whether whole is a whole organism, a population or an ecosystem). Approaches to capture this complexity include adverse outcome pathway (AOP) analysis, which looks at multiple levels of organization from gene to ecosystem. In this commentary, we discuss the role of non-targeted effects (NTE) such as genomic instability and bystander effects. These mechanisms involve transmission of information between different levels of organization. In the case of BE, signals from exposed to unexposed cells or organisms coordinate response at higher levels of organization, permitting population responses to radiation to be identified and, potentially, mitigated. Genomic instability is more complex as it involves not only signaling but also trans-generational transmission of genetic or epigenetic changes and may lead to long-term adaptive evolution. GI may also be involved in memory or legacy effects, which contribute a further component to the dose effect measured in legacy sites. Our recent analysis of the contributions of memory and legacy effects to the total effect using data sets from Chernobyl and Fukushima (voles, birds and butterflies) suggests this type of analysis may help reduce uncertainties over laboratory-to-field extrapolations. A focus on novel but widespread NTE mechanistic pathways may open the way to successful prophylaxis and development of new biomarkers for better risk assessment after low dose exposures.<\/jats:p>","DOI":"10.1667\/rade-25-00032.1","type":"journal-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T15:01:50Z","timestamp":1758294110000},"page":"517-528","source":"Crossref","is-referenced-by-count":2,"title":["Development of Low Radiation Dose Biomarkers: A Commentary on Whether Non-targeted Effects Need to Be Considered"],"prefix":"10.1667","volume":"204","author":[{"given":"Carmel","family":"Mothersill","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Colin","family":"Seymour","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1243","reference":[{"key":"1","doi-asserted-by":"crossref","unstructured":"D. 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