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Recent analyses of the Canadian fluoroscopy cohort study reported significantly increased radiation risks of mortality from ischemic heart diseases (IHD) with a linear dose-response adjusted for dose fractionation. This cohort includes 63,707 tuberculosis patients from Canada who were exposed to low-to-moderate dose fractionated X-rays in 1930s-1950s and were followed-up for death from non-cancer causes during 1950-1987. In the current analysis, we scrutinized the assumption of linearity by analyzing a series of radio-biologically motivated nonlinear dose-response models to get a better understanding of the impact of radiation damage on IHD. The models were weighted according to their quality of fit and were then mathematically superposed applying the multi-model inference (MMI) technique. Our results indicated an essentially linear dose-response relationship for IHD mortality at low and medium doses and a supra-linear relationship at higher doses (> 1.5 Gy). At 5 Gy, the estimated radiation risks were fivefold higher compared to the linear no-threshold (LNT) model. This is the largest study of patients exposed to fractionated low-to-moderate doses of radiation. Our analyses confirm previously reported significantly increased radiation risks of IHD from doses similar to those from diagnostic radiation procedures.

The Organisation for Economic Co-operation and Development (OECD) Adverse Outcome Pathway (AOP) Development Programme is being explored in the radiation field, as an overarching framework to identify and prioritize research needs that best support strengthening of radiation risk assessment and risk management strategies. To advance the use of AOPs, an international horizon-style exercise (HSE) was initiated through the Radiation/Chemical AOP Joint Topical Group (JTG) formed by the OECD Nuclear Energy Agency (NEA) High-Level Group on Low Dose Research (HLG-LDR) under the auspices of the Committee on Radiological Protection and Public Health (CRPPH). The intent of the HSE was to identify key research questions for consideration in AOP development that would help to reduce uncertainties in estimating the health risks following exposures to low dose and low dose-rate ionizing radiation. The HSE was conducted in several phases involving the solicitation of relevant questions, a collaborative review of open-ended candidate questions and an elimination exercise that led to the selection of 25 highest priority questions for the stated purpose. These questions were further ranked by over 100 respondents through an international survey. This final set of questions was judged to provide insights into how the OECD's AOP approach can be put into practice to meet the needs of hazard and risk assessors, regulators, and researchers. This paper examines the 25 priority questions in the context of hazard/risk assessment framework for ionizing radiation. By addressing the 25 priority questions, it is anticipated that constructed AOPs will have a high level of specificity, making them valuable tools for simplifying and prioritizing complex biological processes for use in developing revised radiation hazard and risk assessment strategies. [ABSTRACT FROM AUTHOR]

Colorectal adenoma are precursor lesions on the pathway to cancer. Their removal in screening colonoscopies has markedly reduced rates of cancer incidence and death. Generic models of adenoma growth and transition to cancer can guide the implementation of screening strategies. But adenoma shape has rarely featured as a relevant risk factor. Against this backdrop we aim to demonstrate that shape influences growth dynamics and cancer risk. Stochastic cell-based models are applied to a data set of 197,347 Bavarian outpatients who had colonoscopies from 2006-2009, 50,649 patients were reported with adenoma and 296 patients had cancer. For multi-stage clonal expansion (MSCE) models with up to three initiating stages parameters were estimated by fits to data sets of all shapes combined, and of sessile (70% of all adenoma), peduncular (17%) and flat (13%) adenoma separately for both sexes. Pertinent features of adenoma growth present themselves in contrast to previous assumptions. Stem cells with initial molecular changes residing in early adenoma predominantly multiply within two-dimensional structures such as crypts. For these cells mutation and division rates decrease with age. The absolute number of initiated cells in an adenoma of size 1 cm is small around 103, related to all bulk cells they constitute a share of about 10−5. The notion of very few proliferating stem cells with age-decreasing division rates is supported by cell marker experiments. The probability for adenoma transiting to cancer increases with squared linear size and shows a shape dependence. Compared to peduncular and flat adenoma, it is twice as high for sessile adenoma of the same size. We present a simple mathematical expression for the hazard ratio of interval cancers which provides a mechanistic understanding of this important quality indicator. We conclude that adenoma shape deserves closer consideration in screening strategies and as risk factor for transition to cancer. Author summary: The incidence of colorectal cancer has been markedly reduced by removal of adenoma in screening colonoscopies. Adenoma contain precancerous cells which have already accumulated initial molecular changes on the pathway to cancer. Whereas adenoma size has long been recognized as a major cancer risk factor, the role of adenoma shape has not been studied intensively. Cell-based models ascribe the detected adenoma number and size in large screening cohorts to biological processes of early mutation, cell division, inactivation and transformation to cancer. They link different levels of biological organization which cannot be provided by mere statistical association. With biologically-based modeling we investigate shape-specific features of adenoma development. Model results reveal that adenoma of sessile, peduncular and flat shape exhibit differential growth dynamics, tendency of regression and carcinogenic potential. [ABSTRACT FROM AUTHOR]

The Adverse Outcome Pathway (AOP) framework, a systematic tool that can link available mechanistic data with phenotypic outcomes of relevance to regulatory decision-making, is being explored in areas related to radiation risk assessment. To examine the challenges including the use of AOPs to support the radiation protection community, an international horizon-style exercise was initiated through the Organisation for Economic Co-operation and Development Nuclear Energy Agency High-Level Group on Low Dose Research Radiation/Chemical AOP Joint Topical Group. The objective of the HSE was to facilitate the collection of ideas from a range of experts, to short-list a set of priority research questions that could, if answered, improve the description of the radiation dose-response relationship for low dose/dose-rate exposures, as well as reduce uncertainties in estimating the risk of developing adverse health outcomes following such exposures. The HSE was guided by an international steering committee of radiation risk experts. In the first phase, research questions were solicited on areas that can be supported by the AOP framework, or challenges on the use of AOPs in radiation risk assessment. In the second phase, questions received were refined and sorted by the SC using a best-worst scaling method. During a virtual 3-day workshop, the list of questions was further narrowed. In the third phase, an international survey of the broader radiation protection community led to an orderly ranking of the top questions. Of the 271 questions solicited, 254 were accepted and categorized into 9 themes. These were further refined to the top 25 prioritized questions. Among these, the higher ranked questions will be considered as 'important' to drive future initiatives in the low dose radiation protection community. These included questions on the ability of AOPs to delineate responses across different levels of biological organization, and how AOPs could be applied to address research questions on radiation quality, doses or dose-rates, exposure time patterns and deliveries, and uncertainties in low dose/dose-rate effects. A better understanding of these concepts is required to support the use of the AOP framework in radiation risk assessment. Through dissemination of these results and considerations on next steps, the JTG will address select priority questions to advance the development and use of AOPs in the radiation protection community. The major themes observed will be discussed in the context of their relevance to areas of research that support the system of radiation protection. [ABSTRACT FROM AUTHOR]

Epidemiological studies have indicated that exposure of the heart to doses of ionizing radiation as low as 0.5 Gy increases the risk of cardiac morbidity and mortality with a latency period of decades. The damaging effects of radiation to myocardial and endothelial structures and functions have been confirmed radiobiologically at high dose, but much less are known at low dose. Integration of radiation biology and epidemiology data is a recommended approach to improve the radiation risk assessment process. The adverse outcome pathway (AOP) framework offers a comprehensive tool to compile and translate mechanistic information into pathological endpoints which may be relevant for risk assessment at the different levels of a biological system. Omics technologies enable the generation of large volumes of biological data at various levels of complexity, from molecular pathways to functional organisms. Given the quality and quantity of available data across levels of biology, omics data can be attractive sources of information for use within the AOP framework. It is anticipated that radiation omics studies could improve our understanding of the molecular mechanisms behind the adverse effects of radiation on the cardiovascular system. In this review, we explored the available omics studies on radiation-induced cardiovascular disease (CVD) and their applicability to the proposed AOP for CVD. The results of 80 omics studies published on radiation-induced CVD over the past 20 years have been discussed in the context of the AOP of CVD proposed by Chauhan et al. Most of the available omics data on radiation-induced CVD are from proteomics, transcriptomics, and metabolomics, whereas few datasets were available from epigenomics and multi-omics. The omics data presented here show great promise in providing information for several key events (KEs) of the proposed AOP of CVD, particularly oxidative stress, alterations of energy metabolism, extracellular matrix (ECM), and vascular remodeling. The omics data presented here shows promise to inform the various levels of the proposed AOP of CVD. However, the data highlight the urgent need of designing omics studies to address the knowledge gap concerning different radiation scenarios, time after exposure, and experimental models. This review presents the evidence to build a qualitative omics-informed AOP and provides views on the potential benefits and challenges in using omics data to assess risk-related outcomes. [ABSTRACT FROM AUTHOR]

Mathematical models are able to reflect biological processes and to capture epidemiologic data. Thus, they may help elucidate roles of risk factors in disease progression. We propose to account for smoking, hypertension, and dyslipidemia in a previously published process-oriented model that describes the development of atherosclerotic lesions resulting in myocardial infarction (MI). The model is sex-specific and incorporates individual heterogeneity. It was applied to population-based individual risk factors and MI rates (Cooperative Health Research in the Region of Augsburg (KORA) study) together with subclinical atherosclerotic lesion data (Pathobiological Determinants of Atherosclerosis in Youth (PDAY) study). Different model variants were evaluated, testing the association of risk factors with different disease processes. Best fits were obtained for smoking affecting a late-stage disease process, suggesting a thrombogenic role. Hypertension was mainly related to complicated, vulnerable lesions. Dyslipidemia was consistent with increasing the number of initial lesions. By accounting for heterogeneity, individual hazard ratios differ from the population average. The mean individual hazard ratio for smoking was twice the population-based hazard ratio for men and even more for women. Atherosclerotic lesion progression and MI incidence data can be related in a mathematical model to illuminate how risk factors affect different phases of this pathological process. [ABSTRACT FROM AUTHOR]

The circulatory system distributes nutrients, signaling molecules, and immune cells to vital organs and soft tissues. Epidemiological, animal, and in vitro cellular mechanistic studies have highlighted that exposure to ionizing radiation (IR) can induce molecular changes in cellular and subcellular milieus leading to long-term health impacts, particularly on the circulatory system. Although the mechanisms for the pathologies are not fully elucidated, endothelial dysfunction is proven to be a critical event via radiation-induced oxidative stress mediators. To delineate connectivities of events specifically to cardiovascular disease (CVD) initiation and progression, the adverse outcome pathway (AOP) approach was used with consultation from field experts. AOPs are a means to organize information around a disease of interest to a regulatory question. An AOP begins with a molecular initiating event and ends in an adverse outcome via sequential linkages of key event relationships that are supported by evidence in the form of the modified Bradford-Hill criteria. Detailed guidelines on building AOPs are provided by the Organisation for Economic Cooperation and Development (OECD) AOP program. Here, we report on the questions and discussions needed to develop an AOP for CVD resulting from IR exposure. A recent workshop jointly organized by the MELODI (Multidisciplinary European Low Dose Initiative) and the ALLIANCE (European Radioecology Alliance) associations brought together experts from the OECD to present the AOP approach and tools with examples from the toxicology field. As part of this workshop, four working groups were formed to discuss the identification of adverse outcomes relevant to radiation exposures and development of potential AOPs, one of which was focused on IR-induced cardiovascular effects. Each working group comprised subject matter experts and radiation researchers interested in the specific disease area and included an AOP coach. The CVD working group identified the critical questions of interest for AOP development, including the exposure scenario that would inform the evidence, the mechanisms of toxicity, the initiating event, intermediate key events/relationships, and the type of data currently available. This commentary describes the four-day discussion of the CVD working group, its outcomes, and demonstrates how collaboration and expert consultation is vital to informing AOP construction. [ABSTRACT FROM AUTHOR]

Analyzing epidemiological data with simplified mathematical models of disease development provides a link between the time-course of incidence and the underlying biological processes. Here we point out that considerable modeling flexibility is gained if the model is solved by simulation only. To this aim, a model of atherosclerosis is proposed: a Markov Chain with continuous state space which represents the coronary artery intimal surface area involved with atherosclerotic lesions of increasing severity. Myocardial infarction rates are assumed to be proportional to the area of most severe lesions. The model can be fitted simultaneously to infarction incidence rates observed in the KORA registry, and to the age-dependent prevalence and extent of atherosclerotic lesions in the PDAY study. Moreover, the simulation approach allows for non-linear transition rates, and to consider at the same time randomness and inter-individual heterogeneity. Interestingly, the fit revealed significant age dependence of parameters in females around the age of menopause, qualitatively reproducing the known vascular effects of female sex hormones. For males, the incidence curve flattens for higher ages. According to the model, frailty explains this flattening only partially, and saturation of the disease process plays also an important role. This study shows the feasibility of simulating subclinical and epidemiological data with the same mathematical model. The approach is very general and may be extended to investigate the effects of risk factors or interventions. Moreover, it offers an interface to integrate quantitative individual health data as assessed, for example, by imaging. [ABSTRACT FROM AUTHOR]

Keywords: Biologically based models of cancer risk; radiation epidemiology; molecular biology; integrative modeling; adverse outcome pathways EN Biologically based models of cancer risk radiation epidemiology molecular biology integrative modeling adverse outcome pathways 2 11 10 01/18/21 20210101 NES 210101 Introduction Increasing grasp of disease processes leading to cancer and concomitantly the establishment of observational data sets for the general population prompted the development of biologically based models of cancer risk (BBCR models) (Armitage and Doll [4]; Moolgavkar et al. [64]; Moolgavkar and Knudson [65]). In radiation epidemiology the first deployment of BBCR models occurred with the Life Span Study (LSS) of Japanese a-bomb survivors decades after their application to observational cancer data (Little et al. [55]; Little [54]; Heidenreich et al. [37]; Kai et al. [42]). Early pioneering studies of radiation risk in the LSS were based on descriptive models which linked excess rates of cancer incidence and mortality to radiation exposure by statistical association (Wakabayashi et al. [85]; Thompson et al. [82]). Persistent radiation effects and radiation-associated inflammation Radiation can modulate cancer initiation, progression, and transformation in multiple ways thereby leading to multiple cancer types. [Extracted from the article]

Thyroid cancer of papillary histology (PTC) is the dominant type in radio-epidemiological cohorts established after nuclear accidents or warfare. Studies on post-Chernobyl PTC and on thyroid cancer in the life span study (LSS) of Japanese a-bomb survivors consistently revealed high radiation risk after exposure during childhood and adolescence. For post-Chernobyl risk assessment overexpression of the CLIP2 gene was proposed as molecular biomarker to separate radiogenic from sporadic PTC. Based on such binary marker a biologically-based risk model of PTC carcinogenesis has been developed for observational Chernobyl data. The model featured two independent molecular pathways of disease development, of which one was associated with radiation exposure. To gain credibility the concept for a mechanistic risk model must be based on general biological features which transcend findings in a single cohort. The purpose of the present study is therefore to demonstrate portability of the model concept by application to PTC incidence data in the LSS. By exploiting the molecular two-path concept we improve the determination of the probability of radiation causing cancer (POC). The current analysis uses thyroid cancer incidence data of the LSS with thyroid cancer diagnoses and papillary histology (n = 292) from the follow-up period between 1958 and 2005. Risk analysis was performed with both descriptive and biologically-based models. Judged by goodness-of-fit all applied models described the data almost equally well. They yielded similar risk estimates in cohorts post-Chernobyl and LSS. The preferred mechanistic model was selected by biological plausibility. It reflected important features of an imperfect radiation marker which are not easily addressed by descriptive models. Precise model predictions of marker prevalence in strata of epidemiological covariables can be tested by molecular measurements. Application of the radiation-related molecular pathway from our preferred model in retrospective risk assessment decreases the threshold dose for 50% POC from 0.33 (95% confidence interval (CI) 0.18; 0.64) Gy to 0.04 (95% CI 0.01; 0.19) Gy for females and from 0.43 (95% CI 0.17; 1.84) Gy to 0.19 (95% CI 0.05; 1.00) Gy for males. These improvements are still not sufficient to separate radiation-induced from sporadic PTC cases at very low doses <0.015 Gy typical for the Fukushima accident. Successful application of our preferred mechanistic model to LSS incidence data confirms and improves the biological two-path concept of radiation-induced PTC. Model predictions suggest further molecular validation studies to consolidate the basis of biologically-based risk estimation. [ABSTRACT FROM AUTHOR]

KRAS mutations of lung adenocarcinoma (LADC) are associated with smoking but little is known on other exposure-oncogene associations. Hypothesizing that different inciting agents may cause different driver mutations, we aimed to identify distinct molecular pathways to LADC, applying two entirely different approaches. First, we examined clinicopathologic features and genomic signatures of environmental exposures in the large LADC Campbell data set. Second, we designed a molecular mechanistic risk model of LADC (M3LADC) that links environmental exposure to incidence risk by mathematically emulating the disease process. This model was applied to incidence data of Japanese atom-bomb survivors which contains information on radiation and smoking exposure. Grouping the clinical data by driver mutations revealed two main distinct molecular pathways to LADC: one unique to transmembrane receptor-mutant patients that displayed robust signatures of radiation exposure and one shared between submembrane transducer-mutant patients and patients with no evident driver mutation that carried the signature of smoking. Consistently, best fit of the incidence data was achieved with a M3LADC with two pathways: in one LADC risk increased with radiation exposure and in the other with cigarette consumption. We conclude there are two main molecular pathways to LADC associated with different environmental exposures. Future molecular measurements in lung cancer tissue of atom-bomb survivors may allow to further test quantitatively the M3LADC-predicted link of radiation to transmembrane receptor mutations. Moreover, the developed molecular mechanistic model showed that for low doses, as relevant e.g. for medical imaging, smokers have the same radiation risk compared with never smokers. [ABSTRACT FROM AUTHOR]

A comprehensive characterization of lung adenocarcinoma (LADC) clinical features is currently missing. We prospectively evaluated Caucasian patients with early‐stage LADC. Patients with LADC diagnosed between 2011 and 2015 were prospectively assessed for lung resection with curative intent. Fifty clinical, pathologic, radiologic, and molecular variables were recorded. Patients were followed till death/study conclusion. The main findings were compared to a separate cohort from France. Of 1943 patients evaluated, 366 were enrolled (18.8%; 181 female; 75 never‐smokers; 28% of registered Bavarian cases over the study period). Smoking and obstruction were significantly more prevalent in GLAD compared with adult Bavarians (P < 0.0001). Ever‐smoker tumors were preferentially localized to the upper lobes. We observed 120 relapses and 74 deaths over 704 cumulative follow‐up years. Median overall and disease‐free survival were >7.5 and 3.6 years, respectively. Patients aged <45 or >65 years, resected >60 days postdiagnosis, with abnormal FVC/DLCOVA, N2/N3 stage, or solid histology had significantly decreased survival estimates. These were fit into a weighted locoregional LADC death risk score that outperformed pTNM7 in predicting survival in the GLAD and in our second cohort. We define the clinical gestalt of locoregional LADC and provide a new clinical tool to predict survival, findings that may aid future management and research design. [ABSTRACT FROM AUTHOR]

The article responds to comments made on the authors' article about the mechanistic models in epidemiology. Topics mentioned include the benefits of mechanistic models, the use of two-stage clonal expansion model and user-friendly software to address the complexity of mechanistic models, and the role of data availability and technical manageability in promoting the applications of mechanistic models.

Purpose: Biologically-based mechanistic models that are used in combining current understanding of human carcinogenesis with epidemiological studies were reviewed. Assessment was made of how well they fit the data, whether they account for non-linear radiobiological low-dose effects, and whether they suggest any implications for the dose response at low doses and dose rates. However, the present paper does not make an attempt to provide a complete review of the existing literature on biologically-based models and their application to epidemiological data. Conclusion: In most studies the two-stage clonal expansion (TSCE) model of carcinogenesis was used. The model provided robust estimates of identifiable parameters and radiation risk. While relatively simple, it is flexible, so that more stages can easily be added, and tests made of various types of radiation action. In general, the model performed similarly or better than descriptive excess absolute and excess relative risk models, in terms of quality of fit and number of parameters. Only very rarely the shape of dose-response predicted by the models was investigated. For some tumors, when more detailed biological information was known, additional pathways were included in the model. The future development of these models will benefit from growing knowledge on carcinogenesis processes, and in particular from use of biobank tissue samples and advances in omics technologies. Their use appears a promising approach to investigate the radiation risk at low doses and low dose rates. However, the uncertainties involved are still considerable, and the models provide only a simplified description of the underlying complexity of carcinogenesis. Current assumptions in radiation protection including the linearnon-threshold (LNT) model are not in contradiction to what is presently known on the process of cancer development. [ABSTRACT FROM AUTHOR]

We propose a stochastic model for use in epidemiological analysis, describing the age-dependent development of atherosclerosis with adequate simplification. The model features the uptake of monocytes into the arterial wall, their proliferation and transition into foam cells. The number of foam cells is assumed to determine the health risk for clinically relevant events such as stroke. In a simulation study, the model was checked against the age-dependent prevalence of atherosclerotic lesions. Next, the model was applied to incidence of atherosclerotic stroke in the cohort of male workers from the Mayak nuclear facility in the Southern Urals. It describes the data as well as standard epidemiological models. Based on goodness-of-fit criteria the risk factors smoking, hypertension and radiation exposure were tested for their effect on disease development. Hypertension was identified to affect disease progression mainly in the late stage of atherosclerosis. Fitting mechanistic models to incidence data allows to integrate biological evidence on disease progression into epidemiological studies. The mechanistic approach adds to an understanding of pathogenic processes, whereas standard epidemiological methods mainly explore the statistical association between risk factors and disease outcome. Due to a more comprehensive scientific foundation, risk estimates from mechanistic models can be deemed more reliable. To the best of our knowledge, such models are applied to epidemiological data on cardiovascular diseases for the first time. [ABSTRACT FROM AUTHOR]

Strong evidence for the statistical association between radiation exposure and disease has been produced for thyroid cancer by epidemiological studies after the Chernobyl accident. However, limitations of the epidemiological approach in order to explore health risks especially at low doses of radiation appear obvious. Statistical fluctuations due to small case numbers dominate the uncertainty of risk estimates. Molecular radiation markers have been searched extensively to separate radiation-induced cancer cases from sporadic cases. The overexpression of the CLIP2 gene is the most promising of these markers. It was found in the majority of papillary thyroid cancers (PTCs) from young patients included in the Chernobyl tissue bank. Motivated by the CLIP2 findings we propose a mechanistic model which describes PTC development as a sequence of rate-limiting events in two distinct paths of CLIP2-associated and multistage carcinogenesis. It integrates molecular measurements of the dichotomous CLIP2 marker from 141 patients into the epidemiological risk analysis for about 13 000 subjects from the Ukrainian-American cohort which were exposed below age 19 years and were put under enhanced medical surveillance since 1998. For the first time, a radiation risk has been estimated solely from marker measurements. Cross checking with epidemiological estimates and model validation suggests that CLIP2 is a marker of high precision. CLIP2 leaves an imprint in the epidemiological incidence data which is typical for a driver gene. With the mechanistic model, we explore the impact of radiation on the molecular landscape of PTC. The model constitutes a unique interface between molecular biology and radiation epidemiology. [ABSTRACT FROM AUTHOR]

Colon cancer is caused by multiple genomic alterations which lead to genomic instability (GI). GI appears in molecular pathways of microsatellite instability (MSI) and chromosomal instability (CIN) with clinically observed case shares of about 15–20% and 80–85%. Radiation enhances the colon cancer risk by inducing GI, but little is known about different outcomes for MSI and CIN. Computer-based modelling can facilitate the understanding of the phenomena named above. Comprehensive biological models, which combine the two main molecular pathways to colon cancer, are fitted to incidence data of Japanese a-bomb survivors. The preferred model is selected according to statistical criteria and biological plausibility. Imprints of cell-based processes in the succession from adenoma to carcinoma are identified by the model from age dependences and secular trends of the incidence data. Model parameters show remarkable compliance with mutation rates and growth rates for adenoma, which has been reported over the last fifteen years. Model results suggest that CIN begins during fission of intestinal crypts. Chromosomal aberrations are generated at a markedly elevated rate which favors the accelerated growth of premalignant adenoma. Possibly driven by a trend of Westernization in the Japanese diet, incidence rates for the CIN pathway increased notably in subsequent birth cohorts, whereas rates pertaining to MSI remained constant. An imbalance between number of CIN and MSI cases began to emerge in the 1980s, whereas in previous decades the number of cases was almost equal. The CIN pathway exhibits a strong radio-sensitivity, probably more intensive in men. Among young birth cohorts of both sexes the excess absolute radiation risk related to CIN is larger by an order of magnitude compared to the MSI-related risk. Observance of pathway-specific risks improves the determination of the probability of causation for radiation-induced colon cancer in individual patients, if their exposure histories are known. [ABSTRACT FROM AUTHOR]

Many countries are reexamining the risks connected with nuclear power generation after the Fukushima accidents. To provide updated information for the corresponding discussion a simple empirical approach is applied for risk quantification of severe reactor accidents with International Nuclear and Radiological Event Scale (INES) level ≧ 5. The analysis is based on worldwide data of commercial nuclear facilities. An empirical hazard of 21 (95% confidence intervals (CI) 4; 62) severe accidents among the world's reactors in 100,000 years of operation has been estimated. This result is compatible with the frequency estimate of a probabilistic safety assessment for a typical pressurised power reactor in Germany. It is used in scenario calculations concerning the development in numbers of reactors in the next twenty years. For the base scenario with constant reactor numbers the time to the next accident among the world's 441 reactors, which were connected to the grid in 2010, is estimated to 11 (95% CI 3.7; 52) years. In two other scenarios a moderate increase or decrease in reactor numbers have negligible influence on the results. The time to the next accident can be extended well above the lifetime of reactors by retiring a sizeable number of less secure ones and by safety improvements for the rest. [ABSTRACT FROM AUTHOR]

Abstract: Recent publications on the integration of radiobiological effects in the two-step clonal expansion (TSCE) model of carcinogenesis and applications to radioepidemiological data are reviewed and updated. First, a model version with radiation-induced genomic instability was shown to be a possible explanation for the age dependence of the radiation-induced cancer mortality in the Techa River Cohort. Second, it is demonstrated that inclusion of a bystander effect with a dose threshold allows an improved description of the lung cancer mortality risk for the Mayak workers cohort due to incorporation of plutonium. The threshold for the annual lung dose is estimated to 12 (90%CI: 4; 14)mGy/year. This threshold applies to the initiation of preneoplastic cells and to hyperplastic growth. There is, however, no evidence for a threshold for the effects of gamma radiation. Third, models with radiation-induced cell inactivation tend to predict lower cancer risks among the atomic bomb survivors with exposure at young age than conventionally used empirical models. Also, risks after exposures with doses in the order of 100mGy are predicted to be higher in models with low-dose hypersensitivity than in models with conventional cell survival curves. In the reviewed literature, models of carcinogenesis tend to describe radioepidemiological data better than conventionally used empirical models. [Copyright &y& Elsevier]

• Ionizing radiation causes adverse circulatory and metabolic effects at high doses. • Low-dose radiation is causally associated with circulatory disease. • Impact of low-dose radiation is modulated by inflammatory, stress, and immune responses. Risks to health are the prime consideration in all human situations of ionizing radiation exposure and therefore of relevance to radiation protection in all occupational, medical, and public exposure situations. Over the past few decades, advances in therapeutic strategies have led to significant improvements in cancer survival rates. However, a wide range of long-term complications have been reported in cancer survivors, in particular circulatory diseases and their major risk factors, metabolic diseases. However, at lower levels of exposure, the evidence is less clear. Under real-life exposure scenarios, including radiotherapy, radiation effects in the whole organism will be determined mainly by the response of normal tissues receiving relatively low doses, and will be mediated and moderated by systemic effects. Therefore, there is an urgent need for further research on the impact of low-dose radiation. In this article, we review radiation-associated risks of circulatory and metabolic diseases in clinical, occupational or environmental exposure situations, addressing epidemiological, biological, risk modelling, and systems biology aspects, highlight the gaps in knowledge and discuss future directions to address these gaps. [ABSTRACT FROM AUTHOR]

Background: Survival after curative resection of early-stage lung adenocarcinoma (LUAD) varies and prognostic biomarkers are urgently needed., Methods: Large-format tissue samples from a prospective cohort of 200 patients with resected LUAD were immunophenotyped for cancer hallmarks TP53, NF1, CD45, PD-1, PCNA, TUNEL and FVIII, and were followed for a median of 2.34 (95% CI 1.71-3.49) years., Results: Unsupervised hierarchical clustering revealed two patient subgroups with similar clinicopathological features and genotype, but with markedly different survival: "proliferative" patients (60%) with elevated TP53, NF1, CD45 and PCNA expression had 50% 5-year overall survival, while "apoptotic" patients (40%) with high TUNEL had 70% 5-year survival (hazard ratio 2.23, 95% CI 1.33-3.80; p=0.0069). Cox regression and machine learning algorithms including random forests built clinically useful models: a score to predict overall survival and a formula and nomogram to predict tumour phenotype. The distinct LUAD phenotypes were validated in The Cancer Genome Atlas and KMplotter data, and showed prognostic power supplementary to International Association for the Study of Lung Cancer tumour-node-metastasis stage and World Health Organization histologic classification., Conclusions: Two molecular subtypes of LUAD exist and their identification provides important prognostic information., Competing Interests: Conflict of interest: The authors declare no potential conflicts of interest., (Copyright ©The authors 2022. For reproduction rights and permissions contact permissions@ersnet.org.)