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Human Radiation Injury, edited by Dennis C. Shrieve and. Jay S. Loeffler, is a comprehensive textbook of relevant in- formation by a collection of experts.
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With an estimated 3. In addition, rapid growth in the number of nuclear power plants around the world increases the risk of a nuclear accident similar to that of Fukushima, Japan. Add to this, exposure to non-ionizing radiation from prolonged cell phone use, proton radiation from solar flares, and potential nuclear conflict or a dirty bomb attack, and the need to expand our repertoire of radiation prevention and mitigation strategies becomes increasingly urgent. Radiation Injury Prevention and Mitigation in Humans identifies and examines physical protection strategies as well as non-toxic, cost-effective biological protection strategies.

The book discusses implementing physical and biological protection strategies particularly for first responders, radiation workers, astronauts, and civilians who might be exposed to higher doses of radiation in the course of their activities. The book describes:. Physics of ionizing radiation and radiological weapons, principles of nuclear reactors, the types of radiological weapons, and consequences of their explosions Acute and late health effects of high and low doses of radiation The efficacy of FDA-approved and unapproved radioprotective and radiation mitigating agents The efficacy of radioprotective and radiation mitigating agents not requiring FDA approval antioxidants and herbs Scientific data and rationale in support of using micronutrient preparations containing dietary and endogenous antioxidants for preventing acute radiation sickness and for mitigating the late adverse health effects among survivors of high and low doses of radiation.

Examining cutting-edge advances in the research of the effects of non-ionizing radiation on cellular and genetic levels, the book proposes an implementation plan of both physical and biological protection strategies. It covers the full range of potential sources of radiation and includes an up-to-date list of helpful resources and references for the latest research and readings on the topic.

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Currently, health care providers lack an accurate, high-throughput biodosimetric assay which is suitable for the triage of large numbers of radiation injury victims. Here, we describe the development of a biodosimetric assay based on the analysis of irradiated mice, ex vivo-irradiated human peripheral blood PB and humans treated with total body irradiation TBI.

Interestingly, a gene expression profile developed via analysis of murine PB radiation response alone was inaccurate in predicting human radiation injury. In contrast, generation of a gene expression profile which incorporated data from ex vivo irradiated human PB and human TBI patients yielded an gene radiation classifier which was highly accurate at predicting human radiation status and discriminating medically relevant radiation dose levels in human samples.

Although the patient population was relatively small, the accuracy of this classifier in discriminating radiation dose levels in human TBI patients was not substantially confounded by gender, diagnosis or prior exposure to chemotherapy. We have further incorporated genes from this human radiation signature into a rapid and high-throughput chemical ligation-dependent probe amplification assay CLPA which was able to discriminate radiation dose levels in a pilot study of ex vivo irradiated human blood and samples from human TBI patients. Our results illustrate the potential for translation of a human genetic signature for the diagnosis of human radiation exposure and suggest the basis for further testing of CLPA as a candidate biodosimetric assay.

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    Reducing exposure to radiation

    Images from this publication. See all images 4 Free text. Figure 1 A gene classifier can predict radiation dose levels in mice. The Y axis shows the radiation dose levels predicted by application of the classifier against the irradiated samples. As shown, at each dose level tested and at every time point through 7 days hrs , the classifier discriminated radiation dose with high accuracy.


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    • Figure 2 Murine gene expression profiles do not predict human radiation status. The scatterplot shows —log P-value for a Pearson test of correlation between radiation exposure dose and gene expression for each gene with a mouse-human analog. If mouse y-axis and human x-axis were identifying the same genes, then we would expect that the points would fall on a diagonal line.