No-threshold Research Articles

Radiation adaptive response for constant dose-rate irradiation in high background radiation areas

AbstractThe presented paper describes the problem of human health in regions with high level of natural ionizing radiation in various places in the world. The radiation adaptive response biophysical model was presented and calibrated for the special case of constant dose-rate irradiation. The calibration was performed for the data of residents of several high background radiation areas, like Ramsar in Iran, Kerala in India or Yangjiang in China. Studied end-points were: chromosomal aberrations, cancer incidence and cancer mortality. For the case of aberrations, among collected publications about 45% have shown the existence of adaptive response. Average reduction of chromosomal aberrations was ∼ 10%, while for the case of cancer incidence it was ∼ 15% and ∼ 17% for cancer mortality (each taking into account only results showing adaptive response). Results of the other 55% of data regarding chromosomal aberrations have been tested with the LNT (linear no-threshold) hypothesis, but results were inconsistent with the linear model. The conditions for adaptive response occurrence are still unknown, but it is postulated to correlate with the distribution of individual radiosensitivity among members of surveyed populations.

Cardiac Radiation Exposure and Incident Cancer: challenges and opportunities.

Use of radiological procedures has enormously advanced cardiology. People with heart disease are exposed to ionizing radiation. Exposure to ionizing radiation increases lifetime cancer risk with a dose-proportional hazard according to the linear no-threshold model adopted for radioprotection purposes. In the United States, the average citizen accumulates a median annual medical radiation exposure of 2.29 millisievert (mSv) per year per capita as of the radiologic year 2016, corresponding to the dose exposure of 115 chest X-rays. Cardiology studies often involve high exposures per procedure accounting for approximately 30% to 50% of cumulative medical radiation exposures. Malignancy is more incident in the most radiosensitive organs receiving the largest organ dose from cardiac interventions and cardiovascular imaging testing, such as the lung, bone marrow, and female breast. The latency period between radiation exposure and cancer is thought to be at least 2 years for leukemia and 5 years for all solid cancers, and differences are more likely to emerge in cardiology studies with longer follow-up and inclusion of non-cardiovascular endpoints such as cancer incidence. In cardiological studies, excess cancers are observed 3 to 12 years following exposure, with longer follow-up times showing greater differences in cancer incidence. The presumed associated excess cancer risk needs greater study. These exposures provide a unique opportunity to expand our knowledge of the relationship between exposure to ionizing radiation and cancer risk. Future trials comparing interventional fluoroscopy versus optimal medical therapy or open surgery should include a cancer incidence endpoint.

Random Threshold Model: A Low-Dose Radiation-Induced Risk Assessment Approach Considering Individual Susceptibility to Cancer.

Objectives: The linear no-threshold (LNT) model, which has been used for radiation protection purposes, was developed based on the assumption that exposure to even a small amount of radiation may cause cancer. However, although it is known in carcinogenesis that there is variation in radiation sensitivity among individuals, the LNT model does not adequately consider radiosensitive subgroups. In this paper, we represent susceptibility to contract cancer by radiation exposure by means of the threshold of a dose-response function, introduce an assumption that the thresholds are random to represent the variation of the radiosensitivity among individuals in a susceptible subgroup. We propose a novel method, the random threshold (RT) model, for determining the safe dose limit for the subgroup to protect cancer-susceptible individuals from radiation exposure. Conclusion: The proposed method is illustrated by targeting ATM gene (a cancer-susceptible gene) mutation carriers as a radiosensitive subgroup. For cancer risk associated with low-dose radiation exposure, the contribution of radiosensitivity cannot be ignored, thus the RT model would be more suitable for risk protection for radiosensitive subgroups instead of the LNT model. We also notice that it could be widely applicable for risk protection of not only low-dose radiation but also environmental pollutants.

The scientific nature of the linear no-threshold (LNT) model used in the system of radiological protection.

During the first half of the 20th century, it was commonly assumed that radiation-induced health effects occur only when the dose exceeds a certain threshold. This idea was discarded for stochastic effects when more knowledge was gained about the mechanisms of radiation-induced cancer. Currently, a key tenet of the international system of radiological protection is the linear no-threshold (LNT) model where the risk of radiation-induced cancer is believed to be directly proportional to the dose received, even at dose levels where the effects cannot be proven directly. The validity of the LNT approach has been questioned on the basis of a claim that only conclusions that can be verified experimentally or epidemiologically are scientific and LNT should, thus, be discarded because the system of radiological protection must be based on solid science. The aim of this publication is to demonstrate that the LNT concept can be tested in principle and fulfils the criteria of a scientific hypothesis. The fact that the system of radiological protection is also based on ethics does not render it unscientific either. One of the fundamental ethical concepts underlying the LNT model is the precautionary principle. We explain why it is the best approach, based on science and ethics (as well as practical experience), in situations of prevailing uncertainty.

Overt Scientific Bias and Clandestine Acts by Trusted Scientists: The Flawed Application of the Linear No-threshold Model.

The Health Physics Society (HPS) released a video documentary on the history of the linear no-threshold (LNT) model in April 2022. It exposed many scientific and ethical failings of many leaders, influential scientists, and organizations that have resulted in the current system of radiological protection. Since then, the society received many comments; most were supportive, while a few criticized the video documentary as delivering an anti-LNT message. Shortly thereafter, many emails discovered via an independent Freedom of Information Act request revealed multiple layers of coordination between prominent people in the field of radiation protection to coopt the leadership within the HPS and suppress information they perceived or assumed to be contrary to a pro-LNT message. Many of these emails were published by JunkScience.com, an independent organization that exposes faulty scientific data and analyses used to advance special interests and hidden agendas. This Forum article is intended to document in the peer-reviewed literature the JunkScience.com findings of clandestine acts by trusted scientists within the radiation protection community. The emails exposed strong personal biases, actions taken by leaders within the National Commission on Radiation Protection and Measurements (NCRP) to "save the Society" from its "downward spiral," and actions taken by NCRP and HPS members serving on a National Academies of Sciences committee to suppress scientific information relevant to the debate about health effects in low-dose environments. These anti-science actions harm our entire profession and the trust that Congress bestows on our scientific organizations expecting to receive objective recommendations based on sound science. It is important that these events are recorded in the scientific literature from a historical perspective. The radiation protection community will be judged not by what is revealed in this article but by what actions are taken from here.

The Linear No-Threshold Model in Epidemiological Studies: An Example of Radiation Exposure

The Linear No-Threshold Model in Epidemiological Studies: An Example of Radiation Exposure

Replace the Linear No-threshold Model with a Risk-informed Targeted Approach to Radiation Protection.

The linear no-threshold (LNT) model may be useful as a simple basis for developing radiation protection regulations and standards, but it bears little resemblance to scientific reality and is probably overly conservative at low doses and low dose rates. This paper is an appeal for a broader view of radiation protection that involves more than just optimization of radiation dose. It is suggested that the LNT model should be replaced with a risk-informed, targeted approach to limitation of overall risks, which include radiation and other types of risks and accidents/incidents. The focus should be on protection of the individual. Limitation of overall risk does not necessarily always equate to minimization of individual or collective doses, but in some cases it might. Instead, risk assessment (hazards analysis) should be performed for each facility/and or specific job or operation (straightforward for specialized work such as radiography), and this should guide how limited resources are used to protect workers and the public. A graded approach could be used to prioritize the most significant risks and identify exposure scenarios that are unlikely or non-existent. The dose limits would then represent an acceptable level of risk, below which no further reduction in dose would be needed. Less resources should be spent on ALARA and tracking small individual and collective doses. Present dose limits are thought to be conservative and should suffice in general. Two exceptions are possibly the need for a lower (lifetime) dose limit for lens of the eye for astronauts and raising the public limit to 5 mSv y -1 from 1 mSv y -1 . This would harmonize the public limit with the current limit for the embryo fetus of the declared pregnant worker. Eight case studies are presented that emphasize how diverse and complex radiation risks can be, and in some cases, chemical and industrial risks outweigh radiation risks. More focus is needed on prevention of accidents and incidents involving a variety of types of risks. A targeted approach is needed, and commitments should be complied with until they are changed or exemptions are granted. No criticism of regulators or nuclear industry personnel is intended here. Protection of workers and the public is everyone's goal. The question is how best to accomplish that.

A Review of Recent Low-dose Research and Recommendations for Moving Forward.

The linear no-threshold (LNT) model has been the regulatory "law of the land" for decades. Despite the long-standing use of LNT, there is significant ongoing scientific disagreement on the applicability of LNT to low-dose radiation risk. A review of the low-dose risk literature of the last 10 y does not provide a clear answer, but rather the body of literature seems to be split between LNT, non-linear risk functions (e.g., supra- or sub-linear), and hormetic models. Furthermore, recent studies have started to explore whether radiation can play a role in the development of several non-cancer effects, such as heart disease, Parkinson's disease, and diabetes, the mechanisms of which are still being explored. Based on this review, there is insufficient evidence to replace LNT as the regulatory model despite the fact that it contributes to public radiophobia, unpreparedness in radiation emergency response, and extreme cleanup costs both following radiological or nuclear incidents and for routine decommissioning of nuclear power plants. Rather, additional research is needed to further understand the implications of low doses of radiation. The authors present an approach to meaningfully contribute to the science of low-dose research that incorporates machine learning and Edisonian approaches to data analysis.

The Impact of the Linear No-threshold Hypothesis on Litigation.

As the basis of radiation safety practice and regulations worldwide, the linear no-threshold (LNT) hypothesis exerts enormous influence throughout society. This includes our judicial system, where frivolous lawsuits are filed alleging radiation-induced health effects caused by negligent companies who subject unwitting victims to enormous financial and physical harm. Typically, despite the lack of any supporting scientific basis, these cases result in enormous costs to organizations, insurance companies, and consumers.

A Revised System of Radiological Protection Is Needed.

The system of radiological protection has been based on linear no-threshold theory and related dose-response models for health detriment (in part related to cancer induction) by ionizing radiation exposure for almost 70 y. The indicated system unintentionally promotes radiation phobia, which has harmed many in relationship to the Fukushima nuclear accident evacuations and led to some abortions following the Chernobyl nuclear accident. Linear no-threshold model users (mainly epidemiologists) imply that they can reliably assess the cancer excess relative risk (likely none) associated with tens or hundreds of nanogray (nGy) radiation doses to an organ (e.g., bone marrow); for 1,000 nGy, the excess relative risk is 1,000 times larger than that for 1 nGy. They are currently permitted this unscientific view (ignoring evolution-related natural defenses) because of the misinforming procedures used in data analyses of which many radiation experts are not aware. One such procedure is the intentional and unscientific vanishing of the excess relative risk uncertainty as radiation dose decreases toward assigned dose zero (for natural background radiation exposure). The main focus of this forum article is on correcting the serious error of discarding risk uncertainty and the impact of the correction. The result is that the last defense of the current system of radiological protection relying on linear no-threshold theory (i.e., epidemiologic studies implied findings of harm from very low doses) goes away. A revised system is therefore needed.

If You Torture Your Data Long Enough, It Will Confess to Anything: On the Epidemiological Basis of the LNT Model.

This note deals with epidemiological data interpretation supporting the linear no-threshold model, as opposed to emerging evidence of adaptive response and hormesis from molecular biology in vitro and animal models. Particularly, the US-Japan Radiation Effects Research Foundation's lifespan study of atomic bomb survivors is scrutinized. We stress the years-long lag of the data processing after data gathering and evolving statistical models and methodologies across publications. The necessity of cautious interpretation of radiation epidemiology results is emphasized.

Влияние облучения на заболевания крови среди участников ликвидации последствий аварии на Чернобыльской атомной электростанции с учётом мультиморбидности состояний пациентов

The statistical relationships between radiation doses and blood diseases with the account of the multimorbidity factor in the Russian cohort of workers involved in mitigation of the consequences of the accident at the Chernobyl NPP have been investigated. For analysis observation data accumulated from 1986 over 2022 kept in the National Radiation Epidemiological Register were used. The size of the liquidators cohort was 89,578 men. During the follow-up period 6,013 blood disorders (D50-D89 ICD-10) were detected for the first time. The average radiation dose in the cohort was 0.13 Gy, and the average age at the first exposure was 33.6 years. Common approaches to data mining (Data Mining) were used to identify statistical relationships between blood diseases and other diseases; for radiation risk assessment, logistic regression models were used to link disease probability to radiation dose. The effect of low-dose radiation (less than 0.3 Gy) on blood diseases is statistically significant and is characterized by a multiplicative linear no-threshold model, the dose-response model with ERR/Gy=0.59 at 95% CI (0.23; 0.99). When considering multimorbidity in patients, the blood diseases radiation risk change was not statistically significant. Radiation risks several times higher than risks of malignant neoplasms, were found in three groups of diseases: 1) blood and haemopoietic organs other than anaemia and hemorrhages (D70-D77), with ERR/Gy=2.25; 2) immunodeficiency states (D80-D89), with ERR/Gr=2.01; 3) aplastic anemias (D60-D61), with ERR/Gy=5.56. The inclusion of aplastic anaemia in the officially approved list of diseases caused by exposure to ionizing radiation in Russia should be considered as scientifically justified document. The list may need to be supplemented by diseases of blood and haemorrhagic organs other than anaemia and hemorrhage, as well as immunodeficiency conditions. The radiation risk coefficients (ERR/Gy) for the main groups of blood diseases estimated for the first time will make it possible to establish radiation dependence in exposed people with the use of a dose and radiation-epidemiological approach, estimating the attributive fraction of radiation in the etiology of each specific disease case.

Modern universal standardised trends in worker and public exposure monitoring and control in 21st century by Sohrabi URPS-based hypothesis

Abstract The Universal Radiation Protection System (URPS) was recently hypothesised by Sohrabi in order to address the many deficiencies of current radiation protection system. The ICRP system is currently practiced worldwide based on the linear no-threshold (LNT) model with no supporting health risk data at low effective doses. The ICRP only considers worker occupational doses and sets dose limits only on one portion of doses a worker or public receives. The URPS hypothesis equals human heath-effect risks per unit dose either from natural or man-made sources; formulates dose limits on all integrated doses an individual receives; considers worker also a member of public; conserves ‘cause-effect principle’ for epidemiology risk estimation; introduces dose fractionation concept in radiation protection; introduces the ‘URPS Model’ for bridging LNT, hormesis and threshold models; recommends establishing ‘National Patient Dose Registering System’; and defines modified/new exposure terms and definitions commensurate with URPS hypothesis, as advanced since 2014.

The challenges of defining hormesis in epidemiological studies: The case of radiation hormesis

In the current radiation protection system, preventive measures and occupational exposure limits for controlling occupational exposure to ionizing radiation are based on the linear no-threshold extrapolation model. However, currently an increasing body of evidence indicates that this paradigm predicts very poorly biological responses in the low-dose exposure region. In addition, several in vitro and in vivo studies demonstrated the presence of hormetic dose response curves correlated to ionizing radiation low exposure. In this regard, it is noteworthy that also the findings of different epidemiological studies, conducted in different categories of occupationally exposed workers (e.g., healthcare, nuclear industrial and aircrew workers), observed lower rates of mortality and/or morbidity from cancer and/or other diseases in exposed workers than in unexposed ones or in the general population, then suggesting the possible occurrence of hormesis. Nevertheless, these results should be considered with caution since the identification of hormetic response in epidemiological studies is rather challenging because of a number of major limitations. In this regard, some of the most remarkable shortcomings found in epidemiological studies performed in workers exposed to ionizing radiation are represented by lack or inadequate definition of exposure doses, use of surrogates of exposure, narrow dose ranges, lack of proper control groups and poor evaluation of confounding factors. Therefore, considering the valuable role and contribution that epidemiological studies might provide to the complex risk assessment and management process, there is a clear and urgent need to overcome the aforementioned limits in order to achieve an adequate, useful and more real-life risk assessment that should also include the key concept of hormesis. Thus, in the present conceptual article we also discuss and provide possible approaches to improve the capacity of epidemiological studies to identify/define the hormetic response and consequently improve the complex process of risk assessment of ionizing radiation at low exposure doses.

Why Low-level Radiation Exposure Should Not Be Feared.

The purpose of this paper is to address the public fear that is usually associated with low-level radiation exposure situations. Its ultimate objective is to provide persuasive assurances to informed but skeptical members of the public that exposure situations involving low-level radiation are not to be feared. Unfortunately, just acquiescing to an unsupportive public fear of low-level radiation is not without consequences. It is causing severe disruptions to the benefits that harnessed radiation can produce for the well-being of all humanity. In this pursuit, the paper provides the scientific and epistemological basis needed for regulatory reform by reviewing the history in quantifying, understanding, modeling, and controlling radiation exposure, including some of the evolving contributions of the United Nations Scientific Committee on the Effects of Atomic Radiation, the International Commission on Radiological Protection, and the myriad of international and intergovernmental organizations establishing radiation safety standards. It also explores the various interpretations of the linear no-threshold model and the insights gained from radiation pathologists, radiation epidemiologists, radiation biologists, and radiation protectionists. Given that the linear no-threshold model is so deeply imbedded in current radiation exposure guidance, despite the lack of a solid scientific base on the actually proven radiation effects at low-doses, the paper suggests near-term ways to improve regulatory implementation and better serve the public by excluding and/or exempting trivial low-dose situations from the regulatory scope. Several examples are given where the unsubstantiated public fear of low-level radiation has resulted in crippling the beneficial effects that controlled radiation offers to a modern society.

The scientific basis for the use of the linear no-threshold (LNT) model at low doses and dose rates in radiological protection

The linear no-threshold (LNT) model was introduced into the radiological protection system about 60 years ago, but this model and its use in radiation protection are still debated today. This article presents an overview of results on effects of exposure to low linear-energy-transfer radiation in radiobiology and epidemiology accumulated over the last decade and discusses their impact on the use of the LNT model in the assessment of radiation-related cancer risks at low doses. The knowledge acquired over the past 10 years, both in radiobiology and epidemiology, has reinforced scientific knowledge about cancer risks at low doses. In radiobiology, although certain mechanisms do not support linearity, the early stages of carcinogenesis comprised of mutational events, which are assumed to play a key role in carcinogenesis, show linear responses to doses from as low as 10 mGy. The impact of non-mutational mechanisms on the risk of radiation-related cancer at low doses is currently difficult to assess. In epidemiology, the results show excess cancer risks at dose levels of 100 mGy or less. While some recent results indicate non-linear dose relationships for some cancers, overall, the LNT model does not substantially overestimate the risks at low doses. Recent results, in radiobiology or in epidemiology, suggest that a dose threshold, if any, could not be greater than a few tens of mGy. The scientific knowledge currently available does not contradict the use of the LNT model for the assessment of radiation-related cancer risks within the radiological protection system, and no other dose-risk relationship seems more appropriate for radiological protection purposes.

The Relationship between Cancer and Radiation: A New Paradigm.

A key concern with the use of radiation sources (including nuclear power) is the health effects of low levels of radiation, especially the regulatory assumption that every additional increment of radiation increases the risk of cancer (linear no-threshold model, or LNT). The LNT model is nearly a century old. There are dozens if not hundreds of studies showing that this model is incompatible with animal, cellular, molecular, and epidemiological data for low-dose rates in the range of both background radiation levels and much of occupational exposure. The assumption that every increment of radiation equally increases the risk of cancer results in increased physical risks to workers involved with actions to reduce radiation exposure (such as risks from welding additional shielding in place or from additional construction activities to reduce post-closure waste site radiation levels) and avoidance of medical exposure even when radiation treatment has a lower risk than other options such as surgery. One fundamental shortcoming of the LNT model is that it does not account for natural processes that repair DNA damage. However, there is no contiguous mathematical model that estimates cancer risk for both high- and low-dose rates that incorporates what we have learned about DNA repair mechanisms and is sufficiently simple and conservative to address regulatory concerns. The author proposes a mathematical model that dramatically reduces the estimated cancer risks for low-dose rates while recognizing the linear relationship between cancer and dose at high-dose rates.

Exaggerated risk perception of asbestos-related diseases: commentary

Health risks from asbestos have been evaluated on the basis of professional histories from remote past, when exposures at workplaces were greater than today. The linear no-threshold model has been applied, although its relevance has not been demonstrated. Fibers are often found in the lungs and pleura at post mortem examinations. The fnding of fbers does not prove that a disease was caused by asbestos. It can be reasonably assumed that targeted search for mesothelioma and other asbestos-related diseases in exposed people resulted in increased detection rate. Histological and immunochemical characteristics of malignant mesothelioma partly overlap with other cancers, which may contribute to overdiagnosis in exposed populations. Amphibole asbestos is more toxic than chrysotile but there are discrepancies between experimental and epidemiological data. The promising way to obtain reliable information is lifelong animal experiments. Asbestos bans applied in some countries are excessive and should be reconsidered on the basis of independent research. It can be reasonably assumed that non-use of asbestos-containing brakes, freproofng, and insulation increases the harm from fres, armed conflicts and trafc accidents.

Ultrasensitive dose-response for asbestos cancer risk implied by new inflammation-mutation model

Alterations in complex cellular phenotype each typically involve multistep activation of an ultrasensitive molecular switch (e.g., to adaptively initiate an apoptosis, inflammasome, Nrf2-ARE anti-oxidant, or heat-shock activation pathway) that triggers expression of a suite of target genes while efficiently limiting false-positive switching from a baseline state. Such switches exhibit nonlinear signal-activation relationships. In contrast, a linear no-threshold (LNT) dose-response relationship is expected for damage that accumulates in proportion to dose, as hypothesized for increased risk of cancer in relation to genotoxic dose according to the multistage somatic mutation/clonal-expansion theory of cancer, e.g., as represented in the Moolgavkar-Venzon-Knudsen (MVK) cancer model by a doubly stochastic nonhomogeneous Poisson process. Mesothelioma and lung cancer induced by exposure to carcinogenic (e.g., certain asbestos) fibers in humans and experimental animals are thought to involve modes of action driven by mutations, cytotoxicity-associated inflammation, or both, rendering ambiguous expectations concerning the nature of model-implied shape of the low-dose response for above-background increase in risk of incurring these endpoints. A recent Inflammation Somatic Mutation (ISM) theory of cancer posits instead that tissue-damage-associated inflammation that epigenetically recruits, activates and orchestrates stem cells to engage in tissue repair does not merely promote cancer, but rather is a requisite co-initiator (acting together with as few as two somatic mutations) of the most efficient pathway to any type of cancer in any reparable tissue (Dose-Response 2019; 17(2):1–12). This theory is reviewed, implications of this theory are discussed in relation to mesothelioma and lung cancer associated with chronic asbestos inhalation, one of the two types of ISM-required mutations is here hypothesized to block or impede inflammation resolution (e.g., by doing so for GPCR-mediated signal transduction by one or more endogenous autacoid specialized pro-resolving mediators or SPMs), and supporting evidence for this hypothesis is discussed.

Asbestos-related Cancer: Exaggerated Risk Perception

Health risks from exposure to asbestos fibers have been evaluated based on professional histories, when fiber concentrations at workplaces were greater than today. A linear no-threshold model was used for risk estimation, although its relevance has not been proven. Asbestos fibers are often detected in lungs and pleura during autopsy, but finding evidence of fibers does not prove that a disease has been caused by asbestos. Thus, targeted detection of mesothelioma and other conditions associated with asbestos exposures has resulted in an increase in the reported incidence of mesothelioma among high-risk groups. Histological and immunochemical characteristics of malignant mesothelioma partially overlap with other cancers, which may also contribute to the overdiagnosis in exposed populations. Differences in carcinogenicity of various asbestos types are discussed here. Prohibitions of asbestos in some developed countries must be reconsidered on the basis of independent research. Life-long bioassays are the most promising way to obtain reliable information regarding asbestos-related malignancy. It should be stressed that non-use of asbestos contributes to an increase of harm from fires, armed conflicts, and traffic accidents.