Abstract

The linear no-threshold (LNT) theory describes the linear relationship between a radiation dose and its effects. However, whether the linear relationship is maintained at low radiation doses has yet to be determined. Many previous studies support the radiation hormesis theory, which states that radiation has beneficial effects on health. In this viewpoint, we propose a mathematical function fitted to a model consistent with both the LNT at ≥100 mSv and radiation hormesis theories at <100 mSv, and the model requires a factor whose amount or activity takes a mountain-like shape versus the radiation dose and have one maximum value at 40.9 mSv. We searched a wide range of factors with these features based on searches on PubMed, and then evaluated whether these factors were suitable candidates consistent with both the LNT and radiation hormesis theories. Our consideration indicated that these factors did not completely follow the equation suggested at this time. Of course, other theories do not deny that these factors are involved in hormesis. However, based on our theory, still unknown factors may be involved in radiation hormesis, and then such unknown factors which are activated at <100 mSv should be searched.

Highlights

  • The linear no-threshold (LNT) hypothesis [1] has been proposed for the management of radiation risks

  • The radiation dose at which R(x) reaches a maximum is defined as x1, the value of x for the local minimum of D(x) as x2, the value of x for the local maximum of D(x) as x3, and the other value of x where D has the same value as D(x3 ) as x4

  • We identified the following factors: superoxide dismutase (SOD), catalase, glutathione peroxidase, heat shock protein 70, tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), interleukin-10 (IL-10), interleukin-12 (IL-12), c-Raf, ERK1/2, MEK, 3-phosphoinositidedependent protein kinase (PDK), AKT, p38, JNK, caspase-3, caspase-7, caspase-9, cAMP

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Summary

Introduction

The LNT hypothesis for radiation doses

Objectives
Methods
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Discussion
Conclusion
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