Optimal weighing schemes

We study the problem of determining the masses of a set of weights, given one standard weight, based on comparing two disjoint subsets of those weights with approximately equal mass. The question is how to choose a weighing scheme, i.e., different pairs of subsets, such that the masses can be determined as accurately as possible within a given number of measurements. In this paper we discuss a new way of using the so-called STS method of comparing two approximately equal masses, and we will give optimal weighing schemes which turn out to outperform schemes that are currently used by national metrology institutes

Modeling Lung Carcinogenesis in Radon-Exposed Miner

Epidemiological miner cohort data used to estimate lung cancer risks related to occupational radon exposure often lack cohort-wide information on exposure to tobacco smoke, a potential confounder and important effect modifier. We have developed a method to project data on smoking habits from a case-control study onto an entire cohort by means of a Monte Carlo resampling technique. As a proof of principle, this method is tested on a subcohort of 35,084 former uranium miners employed at the WISMUT company (Germany), with 461 lung cancer deaths in the follow-up period 1955–1998. After applying the proposed imputation technique, a biologically-based carcinogenesis model is employed to analyze the cohort's lung cancer mortality data. A sensitivity analysis based on a set of 200 independent projections with subsequent model analyses yields narrow distributions of the free model parameters, indicating that parameter values are relatively stable and independent of individual projections. This technique thus offers a possibility to account for unknown smoking habits, enabling us to unravel risks related to radon, to smoking, and to the combination of both

Hyper-radiosensitivity affects low-dose acute myeloid leukemia incidence in a mathematical model.

In vitro experiments show that the cells possibly responsible for radiation-induced acute myeloid leukemia (rAML) exhibit low-dose hyper-radiosensitivity (HRS). In these cells, HRS is responsible for excess cell killing at low doses. Besides the endpoint of cell killing, HRS has also been shown to stimulate the low-dose formation of chromosomal aberrations such as deletions. Although HRS has been investigated extensively, little is known about the possible effect of HRS on low-dose cancer risk. In CBA mice, rAML can largely be explained in terms of a radiation-induced Sfpi1 deletion and a point mutation in the remaining Sfpi1 gene copy. The aim of this paper is to present and quantify possible mechanisms through which HRS may influence low-dose rAML incidence in CBA mice. To accomplish this, a mechanistic rAML CBA mouse model was developed to study HRS-dependent AML onset after low-dose photon irradiation. The rAML incidence was computed under the assumptions that target cells: (1) do not exhibit HRS; (2) HRS only stimulates cell killing; or (3) HRS stimulates cell killing and the formation of the Sfpi1 deletion. In absence of HRS (control), the rAML dose-response curve can be approximated with a linear-quadratic function of the absorbed dose. Compared to the control, the assumption that HRS stimulates cell killing lowered the rAML incidence, whereas increased incidence was observed at low doses if HRS additionally stimulates the induction of the Sfpi1 deletion. In conclusion, cellular HRS affects the number of surviving pre-leukemic cells with an Sfpi1 deletion which, depending on the HRS assumption, directly translates to a lower/higher probability of developing rAML. Low-dose HRS may affect cancer risk in general by altering the probability that certain mutations occur/persist

How radiation influences atherosclerotic plaque development: a biophysical approach in ApoE[Formula: see text] mice.

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[Formula: see text] 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

International expert group collaboration for developing an adverse outcome pathway for radiation induced leukaemia.

International audiencePurpose: The concept of the adverse outcome pathway (AOP) has recently gained significant attention as to its potential for incorporation of mechanistic biological information into the assessment of adverse health outcomes following ionizing radiation (IR) exposure. This work is an account of the activities of an international expert group formed specifically to develop an AOP for IR-induced leukemia. Group discussions were held during dedicated sessions at the international AOP workshop jointly organized by the MELODI (Multidisciplinary European Low Dose Initiative) and the ALLIANCE (European Radioecology Alliance) associations to consolidate knowledge into a number of biological key events causally linked by key event relationships and connecting a molecular initiating event with the adverse outcome. Further knowledge review to generate a weight of evidence support for the Key Event Relationships (KERs) was undertaken using a systematic review approach. Conclusions: An AOP for IR-induced acute myeloid leukemia was proposed and submitted for review to the OECD-curated AOP-wiki (aopwiki.org). The systematic review identified over 500 studies that link IR, as a stressor, to leukemia, as an adverse outcome. Knowledge gap identification, although requiring a substantial effort via systematic review of literature, appears to be one of the major added values of the AOP concept. Further work, both within this leukemia AOP working group and other similar working groups, is warranted and is anticipated to produce highly demanded products for the radiation protection research community