Common sense about the linear no-threshold controversy-give the general public a break

The Radiation-Specific Components Generated in the Second Step of Sequential Reactions Have a Mountain-Shaped Function

A mathematical model for radiation hormesis below 100 mSv has previously been reported, but the origins of the formula used in the previous report were not provided. In the present paper, we first considered a sequential reaction model with identical rate constants. We showed that the function of components produced in the second step of this model agreed well with the previously reported function. Furthermore, in a general sequential reaction model with different rate constants, it was mathematically proved that the function representing the component produced in the second step is always mountain-shaped: the graph has a peak with one inflection point on either side, and such a component may induce radiation hormesis.

Whole body imaging in the diagnosis of blunt trauma, ionizing radiation hazards and residual risk

Ever since the introduction of radiographic imaging, its utility in identifying injuries has been well documented and was incorporated in the workup of injured patients during advanced trauma life support algorithms [American College of Surgeons, 8th ed. Chicago, 2008]. More recently, computerized tomography (CT) has been shown to be more sensitive than radiography in the diagnosis of injury. Due to the increased use of CT scanning, concerns were raised regarding the associated exposure to ionizing radiation [N Engl J Med 357:2277-2284, 2007]. During the last several years, a significant amount of research has been published on this topic, most of it being incorporated in the BEIR VII Phase 2 report, published by the National Research Council of the National Academies [National Academy of Sciences, Washington DC, 2006]. The current review will analyze the scientific basis for the concerns over the ionizing radiation associated with the use of CT scanning and will examine the accuracy of the typical advanced trauma life support work-up for diagnosis of injuries.

Cancer-prone mice expressing the Ki-rasG12C gene show increased lung carcinogenesis after CT screening exposures

A >20-fold increase in X-ray computed tomography (CT) use during the last 30 years has caused considerable concern because of the potential carcinogenic risk from these CT exposures. Estimating the carcinogenic risk from high-energy, single high-dose exposures obtained from atomic bomb survivors and extrapolating these data to multiple low-energy, low-dose CT exposures using the Linear No-Threshold (LNT) model may not give an accurate assessment of actual cancer risk. Recently, the National Lung Cancer Screening Trial (NLST) reported that annual CT scans of current and former heavy smokers reduced lung cancer mortality by 20%, highlighting the need to better define the carcinogenic risk associated with these annual CT screening exposures. In this study, we used the bitransgenic CCSP-rtTA/Ki-ras mouse model that conditionally expresses the human mutant Ki-ras(G12C) gene in a doxycycline-inducible and lung-specific manner to measure the carcinogenic risk of exposure to multiple whole-body CT doses that approximate the annual NLST screening protocol. Irradiated mice expressing the Ki-ras(G12C) gene in their lungs had a significant (P = 0.01) 43% increase in the number of tumors/mouse (24.1 ± 1.9) compared to unirradiated mice (16.8 ± 1.3). Irradiated females had significantly (P < 0.005) more excess tumors than irradiated males. No tumor size difference or dose response was observed over the total dose range of 80-160 mGy for either sex. Irradiated bitransgenic mice that did not express the Ki-ras(G12C) gene had a low tumor incidence (≤ 0.1/mouse) that was not affected by exposure to CT radiation. These results suggest that (i) estimating the carcinogenic risk of multiple CT exposures from high-dose carcinogenesis data using the LNT model may be inappropriate for current and former smokers and (ii) any increased carcinogenic risk after exposure to fractionated low-dose CT-radiation may be restricted to only those individuals expressing cancer susceptibility genes in their tissues at the time of exposure.

Yeast DEL assay detects protection against radiation-induced cytotoxicity and genotoxicity: adaptation of a microtiter plate version

The DEL assay in yeast detects DNA deletions that are inducible by many carcinogens. Here we use the colorimetric agent MTS to adapt the yeast DEL assay for microwell plate measurement of ionizing radiation-induced cell killing and DNA deletions. Using the microwell-based DEL assay, cell killing and genotoxic DNA deletions both increased with radiation dose between 0 and 2000 Gy. We used the microwell-based DEL assay to assess the effectiveness of varying concentrations of five different radioprotectors, N-acetyl-l-cysteine, l-ascorbic acid, DMSO, Tempol and Amifostine, and one radiosensitizer, 5-bromo-2-deoxyuridine. The microwell format of the DEL assay was able to successfully detect protection against and sensitization to both radiation-induced cytotoxicity and genotoxicity. Such radioprotection and sensitization detected by the microwell-based DEL assay was validated and compared with similar measurements made using the traditional agar-based assay format. The yeast DEL assay in microwell format is an effective tool for rapidly detecting chemical protectors and sensitizers to ionizing radiation and is automatable for chemical high-throughput screening purposes.

Policy decision-making under scientific uncertainty: radiological risk assessment and the role of expert advisory groups

Standard-setting agencies such as the U.S. Nuclear Regulatory Commission and the U.S. Environmental Protection Agency depend on advice from external expert advisory groups on matters of public policy and standard-setting. Authoritative bodies including the National Research Council and the National Council on Radiation Protection and Measurements provide analyses and recommendations that enable the technical and scientific soundness in decision-making. In radiological protection the nature of the scientific evidence is such that risk assessment at radiation doses typically encountered in environmental and occupational settings is highly uncertain, and several policy alternatives are scientifically defensible. The link between science and policy is problematic. The fundamental issue is the failure to properly consider risk assessment, risk communication, and risk management and then consolidate them in a process that leads to sound policy. Authoritative bodies should serve as unbiased brokers of policy choices by providing balanced and objective scientific analyses. As long as the policy-decision environment is characterized by high scientific uncertainty and a lack of values consensus, advisory groups should present unbiased evaluations of all scientifically plausible alternatives and recommend selection criteria that decision makers can use in the policy-setting process. To do otherwise (e.g., by serving as single position advocates) weakens decision-making by eliminating options and narrowing discussions of scientific perspectives. Understanding uncertainties and the limitations on available scientific information and conveying such information to policy makers remain key challenges for the technical and policy communities.

Regulatory implications of a linear non-threshold (LNT) dose-based risks

Current radiation protection regulatory limits are based on the linear non-threshold (LNT) theory using health data from atomic bombing survivors. Studies in recent years sparked debate on the validity of the theory, especially at low doses. The present LNT overestimates radiation risks since the dosimetry included only acute gammas and neutrons; the role of other bomb-caused factors, e.g. fallout, induced radioactivity, thermal radiation (UVR), electromagnetic pulse (EMP), and blast, were excluded. Studies are proposed to improve the dose-response relationship.

A composite microdose Adaptive Response (AR) and Bystander Effect (BE) model-application to low LET and high LET AR and BE data

PURPOSE

It has been suggested that Adaptive Response (AR) may reduce risk of adverse health effects due to ionizing radiation. But very low dose Bystander Effects (BE) may impose dominant deleterious human risks. These conflicting behaviors have stimulated controversy regarding the Linear No-Threshold human risk model. A dose and dose rate-dependent microdose model, to examine AR behavior, was developed in prior work. In the prior work a number of in vitro and in vivo dose response data were examined with the model. Recent new data show AR behavior with some evidence of very low dose BE. The purpose of this work is to supplement the microdose model to encompass the Brenner and colleagues BaD (Bystander and Direct Damage) model and apply this composite model to obtain new knowledge regarding AR and BE and illustrate the use of the model to plan radio-biology experiments.

MATERIALS AND METHODS

The biophysical composite AR and BE Microdose Model quantifies the accumulation of hits (Poisson distributed, microdose specific energy depositions) to cell nucleus volumes. This new composite AR and BE model provides predictions of dose response at very low dose BE levels, higher dose AR levels and even higher dose Direct (linear-quadratic) Damage radiation levels.

RESULTS

We find good fits of the model to both BE data from the Columbia University microbeam facility and combined AR and BE data for low Linear Energy Transfer (LET) and high LET data. A Bystander Factor of about 27,000 and an AR protection factor of 0.61 are obtained for the low LET in vivo mouse spleen exposures. A Bystander Factor of 317 and an AR protection factor of 0.53 are obtained for high LET radon alpha particles in human lymphocytes. In both cases the AR is activated at most by one or two radiation induced charged particle traversals through the cell nucleus.

CONCLUSIONS

The results of the model analysis is consistent with a premise that both Bystander damage and Adaptive Response radioprotection can occur in the same cell type, derived from the same cell species. The model provides an analytical tool to biophysically study the combined effects of BE and AR.