Fig 2 - uploaded by Jan Beyea
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Four measurements of radiation-induced, mutation frequency by the Stern group at 50-r. Data from Uphoff and Stern (1949). 95% confidence limits are based on twoproportion count statistics (NCSS, 2016). The points at 21 days duration have been dithered for clarity.
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There are both statistically valid and invalid reasons why scientists with differing default hypotheses can disagree in high-profile situations. Examples can be found in recent correspondence in this journal, which may offer lessons for resolving challenges to mainstream science, particularly when adherents of a minority view attempt to elevate the...
Citations
... The history of how LNT moved from being a "theory" to a "hypothesis" and finally a "model" is interesting and mirrors the developments in our understanding of low dose radiobiology and the roles of genetics, epigenetics and environmental factors in determining outcomes. Even this history is controversial as the three selected review papers [129][130][131] demonstrate! ...
The role of signalling in initiating and perpetuating effects triggered by deposition of ionising radiation energy in parts of a system is very clear. Less clear are the very early steps involved in converting energy to chemical and biological effects in non-targeted parts of the system. The paper aims to present a new model, which could aid our understanding of the role of low dose effects in determining ultimate disease outcomes. We propose a key role for electromagnetic signals resulting from physico-chemical processes such as excitation decay, and acoustic waves. These lead to the initiation of damage response pathways such as elevation of reactive oxygen species and membrane associated changes in key ion channels. Critically, these signalling pathways allow coordination of responses across system levels. For example, depending on how these perturbations are transduced, adverse or beneficial outcomes may predominate. We suggest that by appreciating the importance of signalling and communication between multiple levels of organisation, a unified theory could emerge. This would allow the development of models incorporating time, space and system level to position data in appropriate areas of a multidimensional domain. We propose the use of the term “infosome” to capture the nature of radiation-induced communication systems which include physical as well as chemical signals. We have named our model “the variable response model” or “VRM” which allows for multiple outcomes following exposure to low doses or to signals from low dose irradiated cells, tissues or organisms. We suggest that the use of both dose and infosome in radiation protection might open up new conceptual avenues that could allow intrinsic uncertainty to be embraced within a holistic protection framework.
... However, unrepaired damages caused a mutation that may lead to either cancer or killing of irradiated cells. [16][17][18] It is now well accepted that the long-term effects of acute radiation doses induce cancer. However, even before understanding the underlying mechanisms, physicians were quick to utilize the ability of radiation to kill cancer cells which allowed establishing cancer radiotherapy departments in hospitals. ...
Biological responses to low‑dose and high‑dose radiations are markedly different;
the former produce beneficial effects and the latter at acute doses cause detrimental
health effects such as cancer induction. High‑dose radiations (>2 Gy) of low linear
energy transfer are widely used in the treatment of cancer, but limitations are
imposed due to normal tissue adverse reactions. Low‑dose radiations (LDRs), such
as X‑rays (a few mGy), have been widely used in diagnosis of many diseases
without any known adverse health effects. LDR preexposures have been known to
suppress cancer induction by acute doses of radiation. This article briefly reviews
the possible applications of LDR in cancer therapy and delineates the underlying
radiobiological mechanisms in suppressing high‑dose‑induced cancer. It is further
argued to develop LDR technology in preventing and for palliative outcomes in
fighting COVID‑19 pandemic infection among the populations. Furthermore, it is
suggested to examine the average number of people living in high background
radiation areas for susceptibility to COVID‑19 infection and compare with the
average infection rate in the general public for gaining new knowledge on the
response of LDR‑exposed population.
Keywords: Anti COVID‑19 infection, anticancer, high‑dose radiotherapy, low
dose radiation therapy, radiation anti‑inflammation, radiation‑immunostimulation
... However, unrepaired damages caused a mutation that may lead to either cancer or killing of irradiated cells. [16][17][18] It is now well accepted that the long-term effects of acute radiation doses induce cancer. However, even before understanding the underlying mechanisms, physicians were quick to utilize the ability of radiation to kill cancer cells which allowed establishing cancer radiotherapy departments in hospitals. ...
Low dose radiobiology
... The abovementioned LNT model assumes de facto that an organism's ability to repair damage caused by ionizing irradiation (including genome integrity and cellular viability) is affected only slightly by radiation dose and dose rate and that complete repair is impossible. As already mentioned, the LNT concept is the subject of active debate (see, eg, recent discussion by Beyea 16 and Calabrese 17 in the Environmental Research Journal). This debate was triggered during the past decades following the accumulation of biological findings that contradict the aforementioned hypothesis, showing that damage repair ability actually does depend on the irradiation dose and dose rate. ...
Health impacts of low-dose ionizing radiation are significant in important fields such as X-ray imaging, radiation therapy, nuclear power, and others. However, all existing and potential applications are currently challenged by public concerns and regulatory restrictions. We aimed to assess the validity of the linear no-threshold (LNT) model of radiation damage, which is the basis of current regulation, and to assess the justification for this regulation. We have conducted an extensive search in PubMed. Special attention has been given to papers cited in comprehensive reviews of the United States (2006) and French (2005) Academies of Sciences and in the United Nations Scientific Committee on Atomic Radiation 2016 report. Epidemiological data provide essentially no evidence for detrimental health effects below 100 mSv, and several studies suggest beneficial (hormetic) effects. Equally significant, many studies with in vitro and in animal models demonstrate that several mechanisms initiated by low-dose radiation have beneficial effects. Overall, although probably not yet proven to be untrue, LNT has certainly not been proven to be true. At this point, taking into account the high price tag (in both economic and human terms) borne by the LNT-inspired regulation, there is little doubt that the present regulatory burden should be reduced.
... 75 This recommendation was made in spite of the fact that radiation-induced genetic effects in the offspring of irradiated parents have never been observed in humans. Recent historical research has revealed that this recommendation was made under questionable circumstances ( 76-80 but see also [81][82][83]. Even so, the LNT model was later expanded and applied to radiation-induced cancer risks. ...
The US Environmental Protection Agency (USEPA) is the primary federal agency responsible for promulgating regulations and policies to protect people and the environment from ionizing radiation. Currently, the USEPA uses the linear no-threshold (LNT) model to estimate cancer risks and determine cleanup levels in radiologically contaminated environments. The LNT model implies that there is no safe dose of ionizing radiation; however, adverse effects from low dose, low-dose rate (LDDR) exposures are not detectable. This article (1) provides the scientific basis for discontinuing use of the LNT model in LDDR radiation environments, (2) shows that there is no scientific consensus for using the LNT model, (3) identifies USEPA reliance on outdated scientific information, and (4) identifies regulatory reliance on incomplete evaluations of recent data contradicting the LNT. It is the time to reconsider the use of the LNT model in LDDR radiation environments. Incorporating the latest science into the regulatory process for risk assessment will (1) ensure science remains the foundation for decision making, (2) reduce unnecessary burdens of costly cleanups, (3) educate the public on the real effects of LDDR radiation exposures, and (4) harmonize government policies with the rest of the radiation scientific community.
... 1 U.S. EPA [1] states that linear extrapolation should be used for 'agents that are DNA-reactive and have direct mutagenic activity'. However, the concept of linear responses/linear MOAs for mutagenic agents is controversial [17,18] and efforts are ongoing to define thresholds for such agents [19,20]. ...
The determination of whether a chemical induces a specific cancer through a mutagenic or non-mutagenic mode of action (MOA) plays an important role in choosing between linear and nonlinear low-dose extrapolation to derive toxicity criteria. There is no formal framework from the U.S. EPA for determining whether environmental chemicals act through a mutagenic or non-mutagenic MOA; consequently, most such determinations are made on an ad hoc basis. Eastmond [Mutat Res 751 (2012)] recently conducted a systematic investigation of MOA determinations by U.S. and international regulatory agencies and organizations, and identified ten major factors that influence them, including toxicokinetics, in vivo genotoxicity in target organs, data quality, and evidence for alternative MOAs. We have used these ten factors to evaluate mutagenic vs. non-mutagenic MOA for gastrointestinal tumors induced by oral exposure to hexavalent chromium [Cr(VI)]. We also highlight similarities between Cr(VI) and other intestinal carcinogens previously determined to have non-genotoxic MOAs. Based on these analyses, we conclude that the MOA for Cr(VI) induced gastrointestinal tumors is non-mutagenic and that threshold risk assessment approaches are appropriate.
The linear no-threshold (linear-non-threshold) model is a dose-response model that has long served as the foundation of the international radiation protection framework, which includes the Canadian regulatory framework. Its purpose is to inform the choice of appropriate dose limits and subsequent as low as reasonably achievable requirements, social and economic factors taken into account. The linear no-threshold model assumes that the risk of developing cancer increases proportionately with increasing radiation dose. The linear no-threshold model has historically been applied by extrapolating the risk of cancer at high doses (>1,000 mSv) down to low doses in a linear manner. As the health effects of radiation exposure at low doses remain ambiguous, reducing uncertainties found in cancer risk dose-response models can be achieved through in vitro and animal-based studies. The purpose of this critical review is to analyze whether the linear no-threshold model is still applicable for use by modern nuclear regulators for radiation protection purposes, or if there is sufficient scientific evidence supporting an alternate model from which to derive regulatory dose limits.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the Journal.
Purpose: This reflection aims to look at the evolution of thinking about radiation dose response relationships from the early years of the journal when target theory prevailed to the present day when dose response is seen as a more holistic process involving multiple levels of organisation and communication. The review is structured to consider how the old ideas evolved leading to apparently abrupt paradigm shifts. The odd data leading to these conceptual shifts are reviewed. Topics, which are currently still not mainstream are considered with a view to how they may change the future of radiobiology. Finally some personal reflections on the insights gained during the writing of the review are presented.
Conclusions: The major conclusion from this study is that ideas concerning survival curves and radiation dose responses evolved and (epi)mutated gradually, driven in a large part by the techniques available for studying radiobiological processes. The illusion of abrupt paradigm shifts is not really borne out by the history when primary references are studied rather than textbooks or reviews. The textbooks necessarily simplify and distil complex data to provide a “take-home message” while reviews are usually very personal collations selected among the vast amount of scientific literature. Primary references reveal the context of the discussion and the caveats and uncertainties of the authors.
