Human Lung Cancer Risks from Radon – Part I - Influence from Bystander Effects - A Microdose Analysis

Since the publication of the BEIR VI report in 1999 on health risks from radon, a significant amount of new data has been published showing various mechanisms that may affect the ultimate assessment of radon as a carcinogen, at low domestic and workplace radon levels, in particular the Bystander Effect (BE) and the Adaptive Response radio-protection (AR). We analyzed the microbeam and broadbeam alpha particle data of Miller et al. (1995, 1999), Zhou et al. (2001, 2003, 2004), Nagasawa and Little (1999, 2002), Hei et al. (1999), Sawant et al. (2001a) and found that the shape of the cellular response to alphas is relatively independent of cell species and LET of the alphas. The same alpha particle traversal dose response behavior should be true for human lung tissue exposure to radon progeny alpha particles. In the Bystander Damage Region of the alpha particle response, there is a variation of RBE from about 10 to 35. There is a transition region between the Bystander Damage Region and Direct Damage Region of between one and two microdose alpha particle traversals indicating that perhaps two alpha particle “hits” are necessary to produce the direct damage. Extrapolation of underground miners lung cancer risks to human risks at domestic and workplace levels may not be valid

Animal models of obesity and diabetes mellitus.

More than one-third of the worldwide population is overweight or obese and therefore at risk of developing type 2 diabetes mellitus. In order to mitigate this pandemic, safer and more potent therapeutics are urgently required. This necessitates the continued use of animal models to discover, validate and optimize novel therapeutics for their safe use in humans. In order to improve the transition from bench to bedside, researchers must not only carefully select the appropriate model but also draw the right conclusions. In this Review, we consolidate the key information on the currently available animal models of obesity and diabetes and highlight the advantages, limitations and important caveats of each of these models