Modelling radiation-induced cell cycle delays

Ionizing radiation is known to delay the cell cycle progression. In particular after particle exposure significant delays have been observed and it has been shown that the extent of delay affects the expression of damage such as chromosome aberrations. Thus, to predict how cells respond to ionizing radiation and to derive reliable estimates of radiation risks, information about radiation-induced cell cycle perturbations is required. In the present study we describe and apply a method for retrieval of information about the time-course of all cell cycle phases from experimental data on the mitotic index only. We study the progression of mammalian cells through the cell cycle after exposure. The analysis reveals a prolonged block of damaged cells in the G2 phase. Furthermore, by performing an error analysis on simulated data valuable information for the design of experimental studies has been obtained. The analysis showed that the number of cells analyzed in an experimental sample should be at least 100 to obtain a relative error less than 20%.Comment: 19 pages, 11 figures, accepted for publication in Radiation and Environmental Biophysic

Radiation-Induced Bystander Effects in Cultured Human Stem Cells

The radiation-induced "bystander effect" (RIBE) was shown to occur in a number of experimental systems both in vitro and in vivo as a result of exposure to ionizing radiation (IR). RIBE manifests itself by intercellular communication from irradiated cells to non-irradiated cells which may cause DNA damage and eventual death in these bystander cells. It is known that human stem cells (hSC) are ultimately involved in numerous crucial biological processes such as embryologic development; maintenance of normal homeostasis; aging; and aging-related pathologies such as cancerogenesis and other diseases. However, very little is known about radiation-induced bystander effect in hSC. To mechanistically interrogate RIBE responses and to gain novel insights into RIBE specifically in hSC compartment, both medium transfer and cell co-culture bystander protocols were employed.Human bone-marrow mesenchymal stem cells (hMSC) and embryonic stem cells (hESC) were irradiated with doses 0.2 Gy, 2 Gy and 10 Gy of X-rays, allowed to recover either for 1 hr or 24 hr. Then conditioned medium was collected and transferred to non-irradiated hSC for time course studies. In addition, irradiated hMSC were labeled with a vital CMRA dye and co-cultured with non-irradiated bystander hMSC. The medium transfer data showed no evidence for RIBE either in hMSC and hESC by the criteria of induction of DNA damage and for apoptotic cell death compared to non-irradiated cells (p>0.05). A lack of robust RIBE was also demonstrated in hMSC co-cultured with irradiated cells (p>0.05).These data indicate that hSC might not be susceptible to damaging effects of RIBE signaling compared to differentiated adult human somatic cells as shown previously. This finding could have profound implications in a field of radiation biology/oncology, in evaluating radiation risk of IR exposures, and for the safety and efficacy of hSC regenerative-based therapies

A comprehensive method for comparing mental models of dynamic systems

Mental models are the basis on which managers make decisions even though external decision support systems may provide help. Research has demonstrated that more comprehensive and dynamic mental models seem to be at the foundation for improved policies and decisions. Eliciting and comparing such models can systematically explicate key variables and their main underlying structures. In addition, superior dynamic mental models can be identified. This paper reviews existing studies which measure and compare mental models. It shows that the methods used to compare such models lack to account for relevant aspects of dynamic systems, such as, time delays in causal links, feedback structures, and the polarities of feedback loops. Mental models without those properties are mostly static models. To overcome these limitations of the methods to compare mental models, we enhance the widely used distance ratio approach (Markóczy and Goldberg, 1995) so as to comprehend these dynamic characteristics and detect differences among mental models at three levels: the level of elements, the level of individual feedback loops, and the level of the complete model. Our contribution lies in a new method to compare explicated mental models, not to elicit such models. An application of the method shows that this previously non-existent information is essential for understanding differences between managers' mental models of dynamic systems. Thereby, a further path is created to critically analyze and elaborate the models managers use in real world decision making. We discuss the benefits and limitations of our approach for research about mental models and decision making and conclude by identifying directions for further research for operational researchers.Problem structuring Mental models Dynamic systems Feedback