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Atherosclerosis is the development of lipid-laden plaques in arteries and is nowadays considered as an inflammatory disease. It has been shown that high doses of ionizing radiation, as used in radiotherapy, can increase the risk of development or progression of atherosclerosis. To elucidate the effects of radiation on atherosclerosis, we propose a mathematical model to describe radiation-promoted plaque development. This model distinguishes itself from other models by combining plaque initiation and plaque growth, and by incorporating information from biological experiments. It is based on two consecutive processes: a probabilistic dose-dependent plaque initiation process, followed by deterministic plaque growth. As a proof of principle, experimental plaque size data from carotid arteries from irradiated ApoE mice was used to illustrate how this model can provide insight into the underlying biological processes. This analysis supports the promoting role for radiation in plaque initiation, but the model can easily be extended to include dose-related effects on plaque growth if available experimental data would point in that direction. Moreover, the model could assist in designing future biological experiments on this research topic. Additional biological data such as plaque size data from chronically-irradiated mice or experimental data sets with a larger variety in biological parameters can help to further unravel the influence of radiation on plaque development. To the authors’ knowledge, this is the first biophysical model that combines probabilistic and mechanistic modeling which uses experimental data to investigate the influence of radiation on plaque development.Electronic supplementary materialThe online version of this article (doi:10.1007/s00411-017-0709-2) contains supplementary material, which is available to authorized users.

Group-housed young growing pigs, given food ad libitum, were exposed to two temperatures, one within thermal neutrality (25°C) and one around the lower critical temperature (15°C). Pigs at 15°C had daily gains reduced by 57 g for 6 days after initial exposure. Food intake was increased significantly after 6 days at 15°C but not at 25°C. Maintenance requirement was increased by 58 kJ/kg M" 75 and energy retained as protein was decreased by 49 kJ/kg M°7 5 for the first 6 days after exposure to the treatment of 15°C and thereafter both became equivalent to those of pigs at 25°C afterwards. It is concluded that animals were acclimatized after 6 days exposure.

SUMMARY Background Surveillance of SARS-CoV-2 in wastewater offers an unbiased and near real-time tool to track circulation of SARS-CoV-2 at a local scale, next to other epidemic indicators such as hospital admissions and test data. However, individual measurements of SARS-CoV-2 in sewage are noisy, inherently variable, and can be left-censored. Aim We aimed to infer latent virus loads in a comprehensive sewage surveillance program that includes all sewage treatment plants (STPs) in the Netherlands and covers 99.6% of the Dutch population. Methods A multilevel Bayesian penalized spline model was developed and applied to estimate time- and STP-specific virus loads based on water flow adjusted SARS-CoV-2 qRT-PCR data from 1-4 sewage samples per week for each of the >300 STPs. Results The model provided an adequate fit to the data and captured the epidemic upsurges and downturns in the Netherlands, despite substantial day-to-day measurement variation. Estimated STP virus loads varied by more than two orders of magnitude, from approximately 1012 (virus particles per 100,000 persons per day) in the epidemic trough in August 2020 to almost 1015 in many STPs in January 2022. Epidemics at the local levels were slightly shifted between STPs and municipalities, which resulted in less pronounced peaks and troughs at the national level. Conclusion Although substantial day-to-day variation is observed in virus load measurements, wastewater-based surveillance of SARS-CoV-2 can track long-term epidemic progression at a local scale in near real-time, especially at high sampling frequency.

Background Surveillance of SARS-CoV-2 in wastewater offers a near real-time tool to track circulation of SARS-CoV-2 at a local scale. However, individual measurements of SARS-CoV-2 in sewage are noisy, inherently variable and can be left-censored. Aim We aimed to infer latent virus loads in a comprehensive sewage surveillance programme that includes all sewage treatment plants (STPs) in the Netherlands and covers 99.6% of the Dutch population. Methods We applied a multilevel Bayesian penalised spline model to estimate time- and STP-specific virus loads based on water flow-adjusted SARS-CoV-2 qRT-PCR data for one to four sewage samples per week for each of the more than 300 STPs. Results The model captured the epidemic upsurges and downturns in the Netherlands, despite substantial day-to-day variation in the measurements. Estimated STP virus loads varied by more than two orders of magnitude, from ca 1012 virus particles per 100,000 persons per day in the epidemic trough in August 2020 to almost 1015 per 100,000 in many STPs in January 2022. The timing of epidemics at the local level was slightly shifted between STPs and municipalities, which resulted in less pronounced peaks and troughs at the national level. Conclusion Although substantial day-to-day variation is observed in virus load measurements, wastewater-based surveillance of SARS-CoV-2 that is performed at high sampling frequency can track long-term progression of an epidemic at a local scale in near real time.

In this paper, we describe a practical and convenient method to include the contribution of the ingrowth of radioactive progeny in dose assessments of the corresponding parent nuclides. This method modifies the dose coefficients (DCs) of parent nuclides by adding weighted DCs of the corresponding daughter nuclides to them. Based on the decay kinetics of serial nuclear transformations, the progeny weighting factors, with values between 0 and 1, are derived by analysis of the time-integrated activity of each nuclide in the (branched) decay chain headed by a parent nuclide. Using the electronic, nuclear-decay database of Publication 107 of the International Commission on Radiological Protection (ICRP 2008), DC weighting factors for annual dose assessments are calculated for all daughter radionuclides in the decay chains and are tabulated in this paper. Weighting factors based on integration periods other than one year, ranging from 1 h–70 years, are also provided (see the supplementary material). With a priori established weighting factors, dose assessments become significantly simplified by considering the decay kinetics of only the parent nuclides and by applying the modified DCs. This ensures that the ingrowth of progeny is taken into account realistically. In some cases, one requires a conservative estimate of the dose, for instance when dealing with issues of the clearance of materials under regulatory control. Therefore, we adapted the weighting-factor method to derive conservative DC weighting factors for dose evaluations. These values are calculated for various integration periods and compared with those from an existing method adopted by the Euratom Article 31 Group of Experts and by the International Atomic Energy Agency. Identical progeny weighting factors are obtained for long-lived parent radionuclides, whereas for short-lived parent radionuclides, the new method can yield significantly larger values. For example, the weighting factor of I-131 (daughter of parent Te-131) increases from 0.002 to 1.0 based on an integration period of 1 year. The progeny DC weighting factors, derived based on nuclear transformations in exit-only decay chains, may not always be suitable for use in radiological dose evaluations. For instance, when environmental removal pathways are dominant, the application of these weighting factors may have its limitations. This paper, therefore, provides guidance on the proper selection and application of weighting factors.

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