Shape-specific characterization of colorectal adenoma growth and transition to cancer with stochastic cell-based models.

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.

Pyisotopomer: A Python package for obtaining intramolecular isotope ratio differences from mass spectrometric analysis of nitrous oxide isotopocules.

RATIONALE: Obtaining nitrous oxide isotopocule measurements with isotope ratio mass spectrometry (IRMS) involves analyzing the ion current ratios of the nitrous oxide parent ion (N2 O+ ) as well as those of the NO+ fragment ion. The data analysis requires correcting for "scrambling" in the ion source, whereby the NO+ fragment ion obtains the outer N atom from the N2 O molecule. While descriptions exist for this correction, and interlaboratory intercalibration efforts have been made, there has yet to be published a package of code for implementing isotopomer calibrations. METHODS: We developed a user-friendly Python package (pyisotopomer) to determine two coefficients (γ and κ) that describe scrambling in the IRMS ion source, and then used this calibration to obtain intramolecular isotope deltas in N2 O samples. RESULTS: With two appropriate reference materials, γ and κ can be determined robustly and accurately for a given IRMS system. An additional third reference material is needed to define the zero-point of the delta scale. We show that IRMS scrambling behavior can vary with time, necessitating regular calibrations. Finally, we present an intercalibration between two IRMS laboratories, using pyisotopomer to calculate γ and κ, and to obtain intramolecular N2 O isotope deltas in lake water unknowns. CONCLUSIONS: Given these considerations, we discuss how to use pyisotopomer to obtain high-quality N2 O isotopocule data from IRMS systems, including the use of appropriate reference materials and frequency of calibration.

Concepts of association between cancer and ionising radiation: accounting for specific biological mechanisms.

The probability that an observed cancer was caused by radiation exposure is usually estimated using cancer rates and risk models from radioepidemiological cohorts and is called assigned share (AS). This definition implicitly assumes that an ongoing carcinogenic process is unaffected by the studied radiation exposure. However, there is strong evidence that radiation can also accelerate an existing clonal development towards cancer. In this work, we define different association measures that an observed cancer was newly induced, accelerated, or retarded. The measures were quantified exemplarily by Monte Carlo simulations that track the development of individual cells. Three biologically based two-stage clonal expansion (TSCE) models were applied. In the first model, radiation initiates cancer development, while in the other two, radiation has a promoting effect, i.e. radiation accelerates the clonal expansion of pre-cancerous cells. The parameters of the TSCE models were derived from breast cancer data from the atomic bomb survivors of Hiroshima and Nagasaki. For exposure at age 30, all three models resulted in similar estimates of AS at age 60. For the initiation model, estimates of association were nearly identical to AS. However, for the promotion models, the cancerous clonal development was frequently accelerated towards younger ages, resulting in associations substantially higher than AS. This work shows that the association between a given cancer and exposure in an affected person depends on the underlying biological mechanism and can be substantially larger than the AS derived from classic radioepidemiology.

From Atherosclerosis to Myocardial Infarction: A Process-Oriented Model Investigating the Role of Risk Factors.

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.

Prognostic phenotypes of early-stage lung adenocarcinoma.

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.

Isotopically characterised N2 O reference materials for use as community standards.

RATIONALE: Information on the isotopic composition of nitrous oxide (N2 O) at natural abundance supports the identification of its source and sink processes. In recent years, a number of mass spectrometric and laser spectroscopic techniques have been developed and are increasingly used by the research community. Advances in this active research area, however, critically depend on the availability of suitable N2 O isotope Reference Materials (RMs). METHODS: Within the project Metrology for Stable Isotope Reference Standards (SIRS), seven pure N2 O isotope RMs have been developed and their 15 N/14 N, 18 O/16 O, 17 O/16 O ratios and 15 N site preference (SP) have been analysed by specialised laboratories against isotope reference materials. A particular focus was on the 15 N site-specific isotopic composition, as this measurand is both highly diagnostic for source appointment and challenging to analyse and link to existing scales. RESULTS: The established N2 O isotope RMs offer a wide spread in delta (δ) values: δ15 N: 0 to +104‰, δ18 O: +39 to +155‰, and δ15 NSP : -4 to +20‰. Conversion and uncertainty propagation of δ15 N and δ18 O to the Air-N2 and VSMOW scales, respectively, provides robust estimates for δ15 N(N2 O) and δ18 O(N2 O), with overall uncertainties of about 0.05‰ and 0.15‰, respectively. For δ15 NSP , an offset of >1.5‰ compared with earlier calibration approaches was detected, which should be revisited in the future. CONCLUSIONS: A set of seven N2 O isotope RMs anchored to the international isotope-ratio scales was developed that will promote the implementation of the recommended two-point calibration approach. Particularly, the availability of δ17 O data for N2 O RMs is expected to improve data quality/correction algorithms with respect to δ15 NSP and δ15 N analysis by mass spectrometry. We anticipate that the N2 O isotope RMs will enhance compatibility between laboratories and accelerate research progress in this emerging field.

Assessing the Spectral Characteristics of Dye- and Pigment-Based Inkjet Prints by VNIR Hyperspectral Imaging.

Fine art photography, paper documents, and other parts of printing that aim to keep value are searching for credible techniques and mediums suitable for long-term archiving purposes. In general, long-lasting pigment-based inks are used for archival print creation. However, they are very often replaced or forged by dye-based inks, with lower fade resistance and, therefore, lower archiving potential. Frequently, the difference between the dye- and pigment-based prints is hard to uncover. Finding a simple tool for countrified identification is, therefore, necessary. This paper assesses the spectral characteristics of dye- and pigment-based ink prints using visible near-infrared (VNIR) hyperspectral imaging. The main aim is to show the spectral differences between these ink prints using a hyperspectral camera and subsequent hyperspectral image processing. Two diverse printers were exploited for comparison, a hobby dye-based EPSON L1800 and a professional pigment-based EPSON SC-P9500. The identical prints created via these printers on three different types of photo paper were recaptured by the hyperspectral camera. The acquired pixel values were studied in terms of spectral characteristics and principal component analysis (PCA). In addition, the obtained spectral differences were quantified by the selected spectral metrics. The possible usage for print forgery detection via VNIR hyperspectral imaging is discussed in the results.

Demonstration of Nanosecond Operation in Stochastic Magnetic Tunnel Junctions.

Magnetic tunnel junctions operating in the superparamagnetic regime are promising devices in the field of probabilistic computing, which is suitable for applications like high-dimensional optimization or sampling problems. Further, random number generation is of interest in the field of cryptography. For such applications, a device's uncorrelated fluctuation time-scale can determine the effective system speed. It has been theoretically proposed that a magnetic tunnel junction designed to have only easy-plane anisotropy provides fluctuation rates determined by its easy-plane anisotropy field and can perform on a nanosecond or faster time-scale as measured by its magnetoresistance's autocorrelation in time. Here, we provide experimental evidence of nanosecond scale fluctuations in a circular-shaped easy-plane magnetic tunnel junction, consistent with finite-temperature coupled macrospin simulation results and prior theoretical expectations. We further assess the degree of stochasticity of such a signal.

Simulating the dynamics of atherosclerosis to the incidence of myocardial infarction, applied to the KORA population.

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.

Investigating the Uptake and Fate of Poly- and Perfluoroalkylated Substances (PFAS) in Sea Ice Using an Experimental Sea Ice Chamber.

Poly- and perfluoroalkyl substances (PFAS) are contaminants of emerging Arctic concern and are present in the marine environments of the polar regions. Their input to and fate within the marine cryosphere are poorly understood. We conducted a series of laboratory experiments to investigate the uptake, distribution, and release of 10 PFAS of varying carbon chain length (C4-C12) in young sea ice grown from artificial seawater (NaClsolution). We show that PFAS are incorporated into bulk sea ice during ice formation and regression analyses for individual PFAS concentrations in bulk sea ice were linearly related to salinity (r2 = 0.30 to 0.88, n = 18, p < 0.05). This shows that their distribution is strongly governed by the presence and dynamics of brine (high salinity water) within the sea ice. Furthermore, long-chain PFAS (C8-C12), were enriched in bulk ice up to 3-fold more than short-chain PFAS (C4-C7) and NaCl. This suggests that chemical partitioning of PFAS between the different phases of sea ice also plays a role in their uptake during its formation. During sea ice melt, initial meltwater fractions were highly saline and predominantly contained short-chain PFAS, whereas the later, fresher meltwater fractions predominantly contained long-chain PFAS. Our results demonstrate that in highly saline parts of sea ice (near the upper and lower interfaces and in brine channels) significant chemical enrichment (ε) of PFAS can occur with concentrations in brine channels greatly exceeding those in seawater from which it forms (e.g., for PFOA, εbrine = 10 ± 4). This observation has implications for biological exposure to PFAS present in brine channels, a common feature of first-year sea ice which is the dominant ice type in a warming Arctic.

Monte Carlo simulation and thermodynamic integration applied to protein charge transfer.

We introduce a combination of Monte Carlo simulation and thermodynamic integration methods to address a model problem in free energy computations, electron transfer in proteins. The feasibility of this approach is tested using the ferredoxin protein from Clostridium acidurici. The results are compared to numerical solutions of the Poisson-Boltzmann equation and data from recent molecular dynamics simulations on charge transfer in a protein complex, the NrfHA nitrite reductase of Desulfovibrio vulgaris. Despite the conceptual and computational simplicity of the Monte Carlo approach, the data agree well with those obtained by other methods. A link to experiments is established via the cytochrome subunit of the bacterial photosynthetic reaction center of Rhodopseudomonas viridis.

Radio-biologically motivated modeling of radiation risks of mortality from ischemic heart diseases in the Canadian fluoroscopy cohort study.

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.

ProZES: the methodology and software tool for assessment of assigned share of radiation in probability of cancer occurrence.

ProZES is a software tool for estimating the probability that a given cancer was caused by preceding exposure to ionising radiation. ProZES calculates this probability, the assigned share, for solid cancers and hematopoietic malignant diseases, in cases of exposures to low-LET radiation, and for lung cancer in cases of exposure to radon. User-specified inputs include birth year, sex, type of diagnosed cancer, age at diagnosis, radiation exposure history and characteristics, and smoking behaviour for lung cancer. Cancer risk models are an essential part of ProZES. Linking disease and exposure to radiation involves several methodological aspects, and assessment of uncertainties received particular attention. ProZES systematically uses the principle of multi-model inference. Models of radiation risk were either newly developed or critically re-evaluated for ProZES, including dedicated models for frequent types of cancer and, for less common diseases, models for groups of functionally similar cancer sites. The low-LET models originate mostly from the study of atomic bomb survivors in Hiroshima and Nagasaki. Risks predicted by these models are adjusted to be applicable to the population of Germany and to different time periods. Adjustment factors for low dose rates and for a reduced risk during the minimum latency time between exposure and cancer are also applied. The development of the methodology and software was initiated and supported by the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) taking up advice by the German Commission on Radiological Protection (SSK, Strahlenschutzkommission). These provide the scientific basis to support decision making on compensation claims regarding malignancies following occupational exposure to radiation in Germany.

Risk of lung adenocarcinoma from smoking and radiation arises in distinct molecular pathways.

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.

Mechanistic Insight into the Uptake and Fate of Persistent Organic Pollutants in Sea Ice.

The fate of persistent organic pollutants in sea ice is a poorly researched area and yet ice serves as an important habitat for organisms at the base of the marine foodweb. This study presents laboratory-controlled experiments to investigate the mechanisms governing the fate of organic contaminants in sea ice grown from artificial seawater. Sea ice formation was shown to result in the entrainment of chemicals from seawater, and concentration profiles in bulk ice generally showed the highest levels in both the upper (ice-atmosphere interface) and lower (ice-ocean interface) ice layers, suggesting their incorporation and distribution is influenced by brine advection. Results from a 1-D sea ice brine dynamics model supported this, but also indicated that other processes may be needed to accurately model low-polarity compounds in sea ice. This was reinforced by results from a melt experiment, which not only showed chemicals were more enriched in saltier brine, but also revealed that chemicals are released from sea ice at variable rates. We use our results to demonstrate the importance of processes related to the occurrence and movement of brine for controlling chemical fate in sea ice which provides a pathway for exposure to ice-associated biota at the base of the pelagic food web.

On prognostic estimates of radiation risk in medicine and radiation protection.

The problem of expressing cumulative detrimental effect of radiation exposure is revisited. All conventionally used and computationally complex lifetime or time-integrated risks are based on current population and health statistical data, with unknown future secular trends, that are projected far into the future. It is shown that application of conventionally used lifetime or time-integrated attributable risks (LAR, AR) should be limited to exposures under 1 Gy. More general quantities, such as excess lifetime risk (ELR) and, to a lesser extent, risk of exposure-induced death (REID), are free of dose constraints, but are even more computationally complex than LAR and AR and rely on the unknown total radiation effect on demographic and health statistical data. Appropriate assessment of time-integrated risk of a specific outcome following high-dose (more than 1 Gy) exposure requires consideration of competing risks for other radiation-attributed outcomes and the resulting ELR estimate has an essentially non-linear dose response. Limitations caused by basing conventionally applied time-integrated risks on current population and health statistical data are that they are: (a) not well suited for risk estimates for atypical groups of exposed persons not readily represented by the general population; and (b) not optimal for risk projections decades into the future due to large uncertainties in developments of the future secular trends in the population-specific disease rates. Alternative disease-specific quantities, baseline and attributable survival fractions, based on reduction of survival chances are considered here and are shown to be very useful in circumventing most aspects of these limitations. Another main quantity, named as radiation-attributed decrease of survival (RADS), is recommended here to represent cumulative radiation risk conditional on survival until a certain age. RADS, historically known in statistical literature as "cumulative risk", is only based on the radiation-attributed hazard and is insensitive to competing risks. Therefore, RADS is eminently suitable for risk projections in emergency situations and for estimating radiation risks for persons exposed after therapeutic or interventional medical applications of radiation or in other highly atypical groups of exposed persons, such as astronauts.

Exposure-lag-response associations between lung cancer mortality and radon exposure in German uranium miners.

Exposure-lag-response associations shed light on the duration of pathogenesis for radiation-induced diseases. To investigate such relations for lung cancer mortality in the German uranium miners of the Wismut company, we apply distributed lag non-linear models (DLNMs) which offer a flexible description of the lagged risk response to protracted radon exposure. Exposure-lag functions are implemented with B-Splines in Cox models of proportional hazards. The DLNM approach yielded good agreement of exposure-lag-response surfaces for the German cohort and for the previously studied cohort of American Colorado miners. For both cohorts, a minimum lag of about 2 year for the onset of risk after first exposure explained the data well, but possibly with large uncertainty. Risk estimates from DLNMs were directly compared with estimates from both standard radio-epidemiological models and biologically based mechanistic models. For age > 45 year, all models predict decreasing estimates of the Excess Relative Risk (ERR). However, at younger age, marked differences appear as DLNMs exhibit ERR peaks, which are not detected by the other models. After comparing exposure-responses for biological processes in mechanistic risk models with exposure-responses for hazard ratios in DLNMs, we propose a typical period of 15 year for radon-related lung carcinogenesis. The period covers the onset of radiation-induced inflammation of lung tissue until cancer death. The DLNM framework provides a view on age-risk patterns supplemental to the standard radio-epidemiological approach and to biologically based modeling.

Risk bases can complement dose bases for implementing and optimising a radiological protection strategy in urgent and transition emergency phases.

Current radiological emergency response recommendations have been provided by the International Commission on Radiological Protection and adopted by the International Atomic Energy Agency in comprehensive Safety Standards. These standards provide dose-based guidance for decision making (e.g., on sheltering or relocation) via generic criteria in terms of effective dose in the range from 20 mSv per year, during transition from emergency to existing exposure situation, to 100 mSv, acute or annual, in the urgent phase of a nuclear accident. The purpose of this paper was to examine how such dose reference levels directly translate into radiation-related risks of the main stochastic detrimental health effects (cancer). Methodologies, provided by the World Health Organization after the Fukushima accident, for calculating the lifetime and 20 year cancer risks and for attributing relevant organ doses from effective doses, have been applied here for this purpose with new software, designed to be available for use immediately after a nuclear accident. A new feature in this software is a comprehensive accounting for uncertainty via simulation technique, so that the risks may now be presented with realistic confidence intervals. The types of cancer risks considered here are time-integrated over lifetime and the first 20 years after exposure for all solid cancers and either the most radiation-sensitive types of cancer, i.e., leukaemia and female breast cancer, or the most radiation-relevant type of cancer occurring early in life, i.e., thyroid. It is demonstrated here how reference dose levels translate differently into specific cancer risk levels (with varying confidence interval sizes), depending on age at exposure, gender, time-frame at-risk and type of cancer considered. This demonstration applies German population data and considers external exposures. Further work is required to comprehensively extend this methodology to internal exposures that are likely to be important in the early stages of a nuclear accident. A discussion is provided here on the potential for such risk-based information to be used by decision makers, in the urgent and transition phases of nuclear emergencies, to identify protective measures (e.g., sheltering, evacuation) in a differential way (i.e., for particularly susceptible sub-groups of a population).

Correction to: Dose-responses for mortality from cerebrovascular and heart diseases in atomic bomb survivors: 1950-2003.

The article Dose-responses for mortality from cerebrovascular and heart diseases in atomic bomb survivors: 1950-2003, written by Helmut Schöllnberger.

Dose-responses for mortality from cerebrovascular and heart diseases in atomic bomb survivors: 1950-2003.

The scientific community faces important discussions on the validity of the linear no-threshold (LNT) model for radiation-associated cardiovascular diseases at low and moderate doses. In the present study, mortalities from cerebrovascular diseases (CeVD) and heart diseases from the latest data on atomic bomb survivors were analyzed. The analysis was performed with several radio-biologically motivated linear and nonlinear dose-response models. For each detrimental health outcome one set of models was identified that all fitted the data about equally well. This set was used for multi-model inference (MMI), a statistical method of superposing different models to allow risk estimates to be based on several plausible dose-response models rather than just relying on a single model of choice. MMI provides a more accurate determination of the dose response and a more comprehensive characterization of uncertainties. It was found that for CeVD, the dose-response curve from MMI is located below the linear no-threshold model at low and medium doses (0-1.4 Gy). At higher doses MMI predicts a higher risk compared to the LNT model. A sublinear dose-response was also found for heart diseases (0-3 Gy). The analyses provide no conclusive answer to the question whether there is a radiation risk below 0.75 Gy for CeVD and 2.6 Gy for heart diseases. MMI suggests that the dose-response curves for CeVD and heart diseases in the Lifespan Study are sublinear at low and moderate doses. This has relevance for radiotherapy treatment planning and for international radiation protection practices in general.