Evaluates Dsup-based radioprotection in chronically exposed nuclear workers, suggesting a new preventive approach.
This preprint identifies and frames a critical unaddressed gap in occupational radiation protection research. Nuclear power plant workers and other chronically exposed occupational populations face documented health risks — including elevated cancer, cardiovascular, and neurodegenerative outcomes — that current regulatory frameworks, calibrated exclusively to cancer endpoints, fail to adequately address. The only FDA-approved prophylactic radioprotective agent, amifostine, carries a toxicity profile that renders it unsuitable for routine occupational deployment. Simultaneously, a revolution in extremophile biology has produced a candidate solution: the Damage Suppressor protein (Dsup) of the tardigrade Ramazzottius varieornatus, which physically shields DNA from ionizing radiation by binding to nucleosomes and has been shown to reduce radiation-induced strand breaks by approximately 40–50% when expressed in human cells. Recent advances in mRNA nanoparticle delivery have demonstrated tissue-targeted, transient Dsup expression in living animal models without genomic integration risk. Despite this convergence of occupational health need and emerging biotechnology, no published research has proposed, modeled, or tested Dsup-based prophylaxis for chronic low-dose occupational radiation exposure. This preprint applies the Presignal Subtraction Framework to isolate this gap as a Category I signal and proposes a five-priority research agenda for translating tardigrade-inspired radioprotection into worker protection. The research agenda addresses chronic low-dose efficacy profiling, systemic delivery optimization, dosing schedule modeling, long-term safety characterization, and integration with existing occupational biomarker frameworks. This work originates in the Niagara Region of Ontario, Canada, and is informed by the Canadian National Dose Registry cohort literature documenting Ontario nuclear power plant worker outcomes.
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John Carter (2026) studied this question.
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