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Dose response and risk assessment: Evolutionary foundations.

Edward J Calabrese1, Dima Yazji Shamoun1, Evgenios Agathokleous2

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Summary

The linear no-threshold (LNT) model for radiation risk assessment originated from a flawed understanding of evolutionary repair mechanisms. Modern research shows LNT

Keywords:
DNA repairEnvironmental risk assessmentEvolutionHormesisLinear non-thresholdMutation

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Area of Science:

  • Radiation Biology
  • Evolutionary Biology
  • Genetics

Background:

  • The linear no-threshold (LNT) model for radiation risk assessment is rooted in an early, incomplete understanding of evolutionary principles.
  • This historical context precluded the recognition of genetic repair mechanisms, influencing radiation protection standards.

Purpose of the Study:

  • To critically examine the evolutionary basis of the LNT concept for ionizing radiation.
  • To highlight how a lack of understanding regarding gene mutation repair influenced radiation risk assessment models.

Main Methods:

  • Historical analysis of the development of the LNT model in radiation genetics.
  • Review of research on genetic and cellular repair processes from the late 1950s onwards.
  • Examination of the role of evolutionary mechanisms in understanding radiation dose-response relationships.

Main Results:

  • The LNT model's foundation in the denial of mutation repair processes is scientifically inaccurate.
  • Research since the late 1950s has confirmed the existence and efficacy of genetic and cellular repair.
  • Current risk assessment policies, particularly by regulatory agencies, have not fully integrated modern evolutionary and repair mechanisms.

Conclusions:

  • The historical origins of the LNT dose-response model are flawed due to an insufficient grasp of evolutionary repair.
  • A correct understanding of evolution, incorporating adaptive and repair mechanisms, is crucial for accurate low-dose radiation risk assessment.
  • Modern biological insights necessitate a re-evaluation of radiation risk assessment policies to align with evolutionary principles.