Re‐Examining the Applicability of the Linear No‐Threshold ( LNT ) Theory in Radiation Protection for Very Low Doses

ABSTRACT

Integrating recent biological and epidemiological insights, this analysis re‐examines the Linear No‐Threshold (LNT) model—the current basis for radiological protection—which assumes that cancer risk increases proportionally with any dose of ionizing radiation (IR). Empirical data from a cross‐sectional study of 5156 radiation workers indicated a lower frequency of micronuclei in lymphocytes at very low cumulative doses (< 1 mSv) compared to a pre‐employment control group. This observation is suggestive of, but does not directly prove, an adaptive cellular response; importantly, micronuclei are downstream cytogenetic endpoints that do not directly measure DNA repair capacity or carcinogenic risk, and thus this finding cannot, by itself, be taken as evidence for enhanced repair or reduced cancer risk. Meanwhile, ecological studies in high‐background radiation areas (Yangjiang, Kerala, Ramsar) have reported nonlinear dose–response patterns, although these ecological studies are subject to confounding and should be interpreted with caution. These findings raise the hypothesis that chronic, near‐background exposures (~2–3 mSv/year) could trigger adaptive responses (radiation hormesis), a hypothesis that remains to be rigorously tested. Plausible mechanisms, which are speculative at this stage, include upregulated DNA repair (e.g., PARP1) and antioxidant systems (e.g., SOD), potentially enhancing radical scavenging and epigenetic adaptation, which could reduce genomic instability. However, the existence of a universal “practical threshold” cannot be concluded from the present observational data alone, and further mechanistic and prospective studies are needed. Therefore, it is possible that the low‐dose regime follows a “practical threshold” or a J‐shaped curve rather than a strictly linear relationship, although this remains an open scientific question. Future efforts should link the processing of complex damage to organism‐level effects, including genomic instability and immune responses, in order to advance biologically grounded risk models.