Dynamics of cellular responses to radiation

An Overview of Appropriate Medical Practice and Preparedness in Radiation Emergency Response

Radiation emergencies involving high doses of nuclear radiation pose significant risks from exposure to ionizing radiation in various scenarios. These situations include transportation accidents involving radioactive materials, occupational exposure, nuclear detonations, dirty bombs, and nuclear power plant accidents. In addition to the immediate risks of acute radiation syndrome (ARS) and related diseases, long-term exposure can increase the risk of other health issues such as cardiovascular disease and cancer. Vulnerable populations, including pregnant women and children, face particular concern due to potential impacts on their health and the health of unborn babies. The severity of ARS depends on several factors such as radiation dose, quality, dose rate, exposure uniformity, and individual biological responses. Bioindicators are biological responses or markers that help assess the severity and effects of radiation exposure on an individual. Bioindicators can include physical symptoms such as nausea, vomiting, and diarrhea, or laboratory tests such as changes in blood cell counts and gene expression that can help in assessing and treating exposed individuals. Additionally, early prodromal symptoms such as vomiting, diarrhea, and erythema can provide important clues for diagnosis and treatment. Developing a comprehensive plan for radiation emergencies is vital for safeguarding public health, infrastructure, and the environment. First responders play a critical role in establishing safety perimeters, triage, and coordination with various stakeholders. Education and training are essential for medical personnel and the public. This article provides general recommendations and identifies challenges to effective radiation emergency preparedness and response.

The Radiation-Specific Components Generated in the Second Step of Sequential Reactions Have a Mountain-Shaped Function

A mathematical model for radiation hormesis below 100 mSv has previously been reported, but the origins of the formula used in the previous report were not provided. In the present paper, we first considered a sequential reaction model with identical rate constants. We showed that the function of components produced in the second step of this model agreed well with the previously reported function. Furthermore, in a general sequential reaction model with different rate constants, it was mathematically proved that the function representing the component produced in the second step is always mountain-shaped: the graph has a peak with one inflection point on either side, and such a component may induce radiation hormesis.

The radiation adaptive response and priming dose influence: the quantification of the Raper-Yonezawa effect and its three-parameter model for postradiation DNA lesions and mutations

The priming dose effect, called also the Raper-Yonezawa effect or simply the Yonezawa effect, is a special case of the radiation adaptive response phenomenon (radioadaptation), which refers to: (a) faster repair of direct DNA lesions (damage), and (b) DNA mutation frequency reduction after irradiation, by applying a small priming (conditioning) dose prior to the high detrimental (challenging) one. This effect is observed in many (but not all) radiobiological experiments which present the reduction of lesion, mutation or even mortality frequency of the irradiated cells or species. Additionally, the multi-parameter model created by Dr. Yonezawa and collaborators tried to explain it theoretically based on experimental data on the mortality of mice with chronic internal irradiation. The presented paper proposes a new theoretical approach to understanding and explaining the priming dose effect: it starts from the radiation adaptive response theory and moves to the three-parameter model, separately for two previously mentioned situations: creation of fast (lesions) and delayed damage (mutations). The proposed biophysical model was applied to experimental data-lesions in human lymphocytes and chromosomal inversions in mice-and was shown to be able to predict the Yonezawa effect for future investigations. It was also found that the strongest radioadaptation is correlated with the weakest cellular radiosensitivity. Additional discussions were focussed on more general situations where many small priming doses are used.

Towards an ecological modelling approach for assessing ionizing radiation impact on wildlife populations

The emphasis of the international system of radiological protection of the environment is to protect populations of flora and fauna. Throughout the MODARIA programmes, the United Nations' International Atomic Energy Agency (IAEA) has facilitated knowledge sharing, data gathering and model development on the effect of radiation on wildlife. We present a summary of the achievements of MODARIA I and II on wildlife dose effect modelling, extending to a new sensitivity analysis and model development to incorporate other stressors. We reviewed evidence on historical doses and transgenerational effects on wildlife from radioactively contaminated areas. We also evaluated chemical population modelling approaches, discussing similarities and differences between chemical and radiological impact assessment in wildlife. We developed population modelling methodologies by sourcing life history and radiosensitivity data and evaluating the available models, leading to the formulation of an ecosystem-based mathematical approach. This resulted in an ecologically relevant conceptual population model, which we used to produce advice on the evaluation of risk criteria used in the radiological protection of the environment and a proposed modelling extension for chemicals. This work seeks to inform stakeholder dialogue on factors influencing wildlife population responses to radiation, including discussions on the ecological relevance of current environmental protection criteria. The area of assessment of radiation effects in wildlife is still developing with underlying data and models continuing to be improved. IAEA's ongoing support to facilitate the sharing of new knowledge, models and approaches to Member States is highlighted, and we give suggestions for future developments in this regard.

A comparison of CFPD, compartment, and uniform distribution models for radiation dosimetry of radionuclides in the lung

Radioactive aerosols that arise from natural sources and nuclear accidents can be a long-term hazard to human health. Despite the heterogeneous particle deposition in the respiratory tract, uniform aerosol doses have long been assumed in respiratory radiation dosimetry predictions, such as in the compartment and uniform distribution models. It is unclear how these deposition patterns affect internal radiation doses, which are critical in the health assessment of radioactive hazards. This work seeks to quantify the radio-dosimetry sensitivity to initial deposition patterns by comparing computational and compartment/uniform models. A new approach was developed to implement the compartment model into voxel phantoms (e.g. VIP-man) for radiation dosimetry. The calculated radiation fluence, energy deposition density and organ doses were compared to those obtained from coupling computational fluid-particle dynamics (CFPD) with Monte Carlo radiation transport and to those obtained from uniform source distribution approximation. The results show that the source particle distribution within the respiratory system substantially influences the radiation dosimetry distribution. The compartment and uniform models underestimated aerosol deposition in the crania ridge, leading to lower doses in the trachea and surrounding organs. For 0.5 MeV gammas, the CFPD-Monte Carlo N-particle (MCNP) model predicted a tracheal dose twice that of the compartment model and four times the uniform model. For 1 MeV betas, the CFPD-MCNP-predicted tracheal dose is 2.6 times that of the compartment model and 14 times the uniform model. Compared to the compartment/uniform models, the CFPD approach predicted a 50% lower beta dose in the lung but higher beta doses in the heart (six times), liver (four times) and stomach (2.5 times). It is suggested that including compartments for the lung periphery and tracheal carina ridge may improve the dosimetry accuracy of compartment models.

A hypothesis for the pathogenesis of radiation-induced oral mucositis: when biological challenges exceed physiologic protective mechanisms. Implications for pharmacological prevention and treatment

Oral mucositis (OM) remains a significant unmet need for patients being treated with standard concomitant chemoradiation (CRT) regimens for head and neck cancers (HNC). OM's pathogenesis is complex and includes both direct and indirect damage pathways. In this paper, the field is reviewed with emphasis on the initiating and sustaining role of oxidative stress on OM's pathobiology. A hypothesis is presented which suggests that based on OM's clinical and biological trajectory, mucosal damage is largely the consequence of cumulative CRT-induced biological changes overwhelming physiologic self-protective mechanisms. Furthermore, an individual's ability to mount and maintain a protective response is dependent on interacting pathways which are primarily determined by a multiplex consisting of genomics, epigenomics, and microbiomics. Effective biologic or pharmacologic OM interventions are likely to supplement or stimulate existing physiologic damage-control mechanisms.

Time to rejuvenate ultra-low dose whole-body radiotherapy of cancer

The results of clinical trials performed from the 1930s until the end of the 20th century in which total-body ultra-low level ionizing radiation (TB-LLR) was used demonstrate that this form of treatment can be equal or superior to other systemic anti-neoplastic modalities in terms of the rates of remissions, toxicity, and side effects. In this review, we provide the rationale for TB-LLR and analyze the results of reliable clinical trials in patients with predominantly lymphoproliferative disorders but also advanced solid cancers. The doses used in these trials did not exceed 0.1-0.2 Gy per fraction and cumulative totals ranged from 1 to 4 Gy. Based on the reviewed results we conclude that it is appropriate to revive interest in and resume clinical investigations of TB-LLR in order to refine and improve the effectiveness of such treatment, whether employed alone or in combination with other anticancer strategies.

Lessons and perspectives for applications of stochastic models in biological and cancer research

The effects of randomness, an unavoidable feature of intracellular environments, are observed at higher hierarchical levels of living matter organization, such as cells, tissues, and organisms. Additionally, the many compounds interacting as a well-orchestrated network of reactions increase the difficulties of assessing these systems using only experiments. This limitation indicates that elucidation of the dynamics of biological systems is a complex task that will benefit from the establishment of principles to help describe, categorize, and predict the behavior of these systems. The theoretical machinery already available, or ones to be discovered to help solve biological problems, might play an important role in these processes. Here, we demonstrate the application of theoretical tools by discussing some biological problems that we have approached mathematically: fluctuations in gene expression and cell proliferation in the context of loss of contact inhibition. We discuss the methods that have been employed to provide the reader with a biologically motivated phenomenological perspective of the use of theoretical methods. Finally, we end this review with a discussion of new research perspectives motivated by our results.

Analysis of DNA methylation alterations in rice seeds induced by different doses of carbon-ion radiation

To investigate the mechanism underlying differences in biological effects induced by low- versus high-dose heavy-ion radiation (HIR) in rice plants, two-dimensional gel electrophoresis (2-DE) coupled with methylation-sensitive amplification polymorphism (MSAP) analysis were used to check the expression changes in rice leaf proteome profiles and the changes in DNA methylation after exposure of seeds to ground-based carbon-ion radiation at various cumulative doses (0, 0.01, 0.02, 0.1, 0.2, 1, 2, 5 or 20 Gy; 12C6+; energy, 165 MeV/u; mean linear energy transfer, 30 KeV/μm). In this study, principal component analysis (PCA) and gene ontology (GO) functional analysis of differentially expressed proteins of rice at tillering stage showed that proteins expressed in rice samples exposed to 0.01, 0.02, 0.1, 0.2 or 1 Gy differed from those exposed to 2, 5 or 20 Gy. Correspondingly, the proportion of hypermethylation was higher than that of hypomethylation at CG sites following low-dose HIR (LDR; 0.01, 0.2 or 1 Gy), whereas this was reversed at high-dose HIR (HDR; 2, 5 or 20 Gy). The hypomethylation changes tended to occur at CHG sites with both low- and high-dose HIR. Furthermore, sequencing of MSAP variant bands indicated that the plants might activate more metabolic processes and biosynthetic pathways on exposure to LDR, but activate stress resistance on exposure to HDR. This study showed that radiation induced different biological effects with low- and high-dose HIR, and that this may have been caused by different patterns of hyper- and hypomethylation at the CG sites.

Cancer immunotherapy: how low-level ionizing radiation can play a key role

The cancer immunoediting hypothesis assumes that the immune system guards the host against the incipient cancer, but also "edits" the immunogenicity of surviving neoplastic cells and supports remodeling of tumor microenvironment towards an immunosuppressive and pro-neoplastic state. Local irradiation of tumors during standard radiotherapy, by killing neoplastic cells and generating inflammation, stimulates anti-cancer immunity and/or partially reverses cancer-promoting immunosuppression. These effects are induced by moderate (0.1-2.0 Gy) or high (>2 Gy) doses of ionizing radiation which can also harm normal tissues, impede immune functions, and increase the risk of secondary neoplasms. In contrast, such complications do not occur with exposures to low doses (≤0.1 Gy for acute irradiation or ≤0.1 mGy/min dose rate for chronic exposures) of low-LET ionizing radiation. Furthermore, considerable evidence indicates that such low-level radiation (LLR) exposures retard the development of neoplasms in humans and experimental animals. Here, we review immunosuppressive mechanisms induced by growing tumors as well as immunomodulatory effects of LLR evidently or likely associated with cancer-inhibiting outcomes of such exposures. We also offer suggestions how LLR may restore and/or stimulate effective anti-tumor immunity during the more advanced stages of carcinogenesis. We postulate that, based on epidemiological and experimental data amassed over the last few decades, whole- or half-body irradiations with LLR should be systematically examined for its potential to be a viable immunotherapeutic treatment option for patients with systemic cancer.

Mechanistic Modelling of DNA Repair and Cellular Survival Following Radiation-Induced DNA Damage

Characterising and predicting the effects of ionising radiation on cells remains challenging, with the lack of robust models of the underlying mechanism of radiation responses providing a significant limitation to the development of personalised radiotherapy. In this paper we present a mechanistic model of cellular response to radiation that incorporates the kinetics of different DNA repair processes, the spatial distribution of double strand breaks and the resulting probability and severity of misrepair. This model enables predictions to be made of a range of key biological endpoints (DNA repair kinetics, chromosome aberration and mutation formation, survival) across a range of cell types based on a set of 11 mechanistic fitting parameters that are common across all cells. Applying this model to cellular survival showed its capacity to stratify the radiosensitivity of cells based on aspects of their phenotype and experimental conditions such as cell cycle phase and plating delay (correlation between modelled and observed Mean Inactivation Doses R(2) > 0.9). By explicitly incorporating underlying mechanistic factors, this model can integrate knowledge from a wide range of biological studies to provide robust predictions and may act as a foundation for future calculations of individualised radiosensitivity.

Development of a robust DNA damage model including persistent telomere-associated damage with application to secondary cancer risk assessment

Mathematical modelling has been instrumental to understand kinetics of radiation-induced DNA damage repair and associated secondary cancer risk. The widely accepted two-lesion kinetic (TLK) model assumes two kinds of double strand breaks, simple and complex ones, with different repair rates. Recently, persistent DNA damage associated with telomeres was reported as a new kind of DNA damage. We therefore extended existing versions of the TLK model by new categories of DNA damage and re-evaluated those models using extensive data. We subjected different versions of the TLK model to a rigorous model discrimination approach. This enabled us to robustly select a best approximating parsimonious model that can both recapitulate and predict transient and persistent DNA damage after ionizing radiation. Models and data argue for i) nonlinear dose-damage relationships, and ii) negligible saturation of repair kinetics even for high doses. Additionally, we show that simulated radiation-induced persistent telomere-associated DNA damage foci (TAF) can be used to predict excess relative risk (ERR) of developing secondary leukemia after fractionated radiotherapy. We suggest that TAF may serve as an additional measure to predict cancer risk after radiotherapy using high dose rates. This may improve predicting risk-dose dependency of ionizing radiation especially for long-term therapies.