The cytokinesis-block micronucleus (CBMN) assay is a well-established method to assess radiation-induced genetic damage in human cells. This assay has been adapted to imaging flow cytometry (IFC), allowing automated analysis of many cells, and eliminating the need to create microscope slides. Furthermore, to improve the efficiency of assay performance, a small-volume method previously developed was employed. Irradiated human blood samples were cultured, stained, and analysed by IFC to produce images of the cells. Samples were run using both manual and 96-well plate automated acquisition. Multiple parameter-based image features were collected for each sample and the results were compared to confirm that these acquisition methods are functionally identical. This paper details the multi-parametric analysis developed, and the resulting calibration curves up to 10 Gy. The calibration curves were created using a quadratic random coefficient model with Poisson errors, as well as a logistic discriminant function. The curves were then validated with blinded, irradiated samples, using relative bias and relative mean square error. Overall, the accuracy of the dose estimates was adequate for triage dosimetry (within 1 Gy of the true dose) over 90% of the time for lower doses and about half the time for higher doses, with the lowest success rate between 5 and 6 Gy where the calibration curve reached its peak and there was the smallest change in MN/BNC with dose. This work describes the application of novel multi-parametric analysis that fits the calibration curves and allows dose estimates up to 10 Gy, which were previously limited to 4 Gy. Furthermore, it demonstrates that the results from samples acquired manually and with the autosampler are functionally similar.

Stress response signals can propagate between cells damaged by targeted effects (TE) of ionizing radiation (e.g. energy depositions and ionizations in the nucleus) and undamaged "bystander" cells, sometimes over long distances. Their consequences, called non-targeted effects (NTE), can substantially contribute to radiation-induced damage (e.g. cell death, genomic instability, carcinogenesis), particularly at low doses/dose rates (e.g. space exploration, some occupational and accidental exposures). In addition to controlled laboratory experiments, analysis of observational data on wild animal and plant populations from areas contaminated by radionuclides can enhance our understanding of radiation responses because such data span wide ranges of dose rates applied over many generations. Here we used a mechanistically-motivated mathematical model of TE and NTE to analyze published embryonic mortality data for plants (Arabidopsis thaliana) and rodents (Clethrionomys glareolus) from the Chernobyl nuclear power plant accident region. Although these species differed strongly in intrinsic radiosensitivities and post-accident radiation exposure magnitudes, model-based analysis suggested that NTE rather than TE dominated the responses of both organisms to protracted low-dose-rate irradiation. TE were predicted to become dominant only above the highest dose rates in the data. These results support the concept of NTE involvement in radiation-induced health risks from chronic radiation exposures.

There is growing interest in far‐UVC lighting, defined as wavelengths from 200 to 230 nm, because research has demonstrated these wavelengths to be an effective antimicrobial technology while posing a minimal hazard to human health. Far‐UVC lighting is now being installed to directly irradiate spaces where humans are present, and it will be important to perform measurements to verify far‐UVC lighting installations are operating within widely accepted exposure guidelines. In this work, we explore the use of a commercially available film, known as OrthoChromic OC‐1, to measure ultraviolet radiation exposure. The film was tested with a variety of ultraviolet wavelengths and irradiance conditions, and the color change of the film was analyzed for increasing levels of radiant exposure. The film response extended over a dynamic range that was greater than the recommended exposure limits for far‐UVC radiation so it can potentially be useful for health hazard monitoring. The spectrum of the incident ultraviolet radiation strongly affected the response of the film; therefore, for accurate measurements we recommend the measured spectrum match the spectrum used for calibration. Overall, dosimetry with this film provides a simple, accurate, and inexpensive method of quantifying ultraviolet radiation exposure that is suitable for far‐UVC measurements.

Quantifying radiation-induced cancer risks associated with radiological examinations is not easy, which has resulted in much controversy. We can clarify the situation by distinguishing between higher dose examinations, such as CT, positron emission tomography-CT or fluoroscopically guided interventions, and lower dose "conventional" X-ray examinations. For higher dose examinations, the epidemiological data, from atomic bomb survivors exposed to low doses and from direct epidemiological studies of paediatric CT, are reasonably consistent, suggesting that we do have a reasonable quantitative understanding of the individual risks: in summary, very small but unlikely to be zero. For lower dose examinations, we have very little data, and the situation is much less certain, however, the collective dose from these lower dose examinations is comparatively unimportant from a public health perspective.

Background 0.5% to 10% of clean surgeries result in surgical-site infections, and attempts to reduce this rate have had limited success. Germicidal UV lamps, with a broad wavelength spectrum from 200 to 400 nm are an effective bactericidal option against drug-resistant and drug-sensitive bacteria, but represent a health hazard to patient and staff. By contrast, because of its limited penetration, ∼200 nm far-UVC light is predicted to be effective in killing bacteria, but without the human health hazards to skin and eyes associated with conventional germicidal UV exposure. Aims The aim of this work was to test the biophysically-based hypothesis that ∼200 nm UV light is significantly cytotoxic to bacteria, but minimally cytotoxic or mutagenic to human cells either isolated or within tissues. Methods A Kr-Br excimer lamp was used, which produces 207-nm UV light, with a filter to remove higher-wavelength components. Comparisons were made with results from a conventional broad spectrum 254-nm UV germicidal lamp. First, cell inactivation vs. UV fluence data were generated for methicillin-resistant S. aureus (MRSA) bacteria and also for normal human fibroblasts. Second, yields of the main UV-associated pre-mutagenic DNA lesions (cyclobutane pyrimidine dimers and 6-4 photoproducts) were measured, for both UV radiations incident on 3-D human skin tissue. Results We found that 207-nm UV light kills MRSA efficiently but, unlike conventional germicidal UV lamps, produces little cell killing in human cells. In a 3-D human skin model, 207-nm UV light produced almost no pre-mutagenic UV-associated DNA lesions, in contrast to significant yields induced by a conventional germicidal UV lamp. Conclusions As predicted based on biophysical considerations, 207-nm light kills bacteria efficiently but does not appear to be significantly cytotoxic or mutagenic to human cells. Used appropriately, 207-nm light may have the potential for safely and inexpensively reducing surgical-site infection rates, including those of drug-resistant origin.

The radiation sciences are increasingly interdisciplinary, both from the research and the clinical perspectives. Beyond clinical and research issues, there are very real issues of communication between scientists from different disciplines. It follows that there is an increasing need for interdisciplinary training courses in the radiological sciences. Training courses are common in biomedical academic and clinical environments, but are typically targeted to scientists in specific technical fields. In the era of multidisciplinary biomedical science, there is a need for highly integrated multidisciplinary training courses that are designed for, and are useful to, scientists who are from a mix of very different academic fields and backgrounds. We briefly describe our experiences running such an integrated training course for researchers in the field of biomedical radiation microbeams, and draw some conclusions about how such interdisciplinary training courses can best function. These conclusions should be applicable to many other areas of the radiological sciences. In summary, we found that it is highly beneficial to keep the scientists from the different disciplines together. In practice, this means not segregating the training course into sections specifically for biologists and sections specifically for physicists and engineers, but rather keeping the students together to attend the same lectures and hands-on studies throughout the course. This structure added value to the learning experience not only in terms of the cross fertilization of information and ideas between scientists from the different disciplines, but also in terms of reinforcing some basic concepts for scientists in their own discipline.

Failla, Marie Curie, and Columbia University It was a particular pleasure to receive the Radiation Research Society Failla Award in Warsaw, Poland, the birthplace of Marie Sklodowska Curie. Gioacchino Failla was the first director of my own Institute, now called the Columbia University Center for Radiological Research (CRR). Starting in 1918, Failla was in charge of the Columbia University Center for an astonishing 43 years, before Harold Rossi and then Eric Hall took over the reins. Between them, Rossi and Hall led the CRR for a further 49 years. Perhaps radiation is linked to scientific longevity, if not to increased lifespan (1). Failla was in fact one of Marie Curie’s graduate students, and he received his doctorate from the Sorbonne in 1923. Two years earlier, Marie Curie had visited Failla in New York City during her trip to the U.S. The New York Times recorded her arrival (Fig. 1) with the headline “Mme. Curie Plans to End All Cancers,” together with the memorable subheading “Motherly looking scientist in plain black frock gives thanks to Americans.” FIG. 1 New York Times, May 12 1921, describing Marie Curie’s arrival in New York City. Curie met with her student, Gioacchino Failla, during her visit. The Two Two-Edged Swords Radiation’s two two-edged swords that have dominated my own scientific thinking are: Radiation can cure cancer versus radiation can induce cancer. Radiotherapy needs physics research versus radiotherapy needs biological research. The goal of this brief summary is to give some examples of these contrasts, and try to draw some conclusions about research directions, interleaved with some observations about the scientists who have tried to push me in the right directions over the years.

HomeRadiologyVol. 265, No. 2 PreviousNext Reviews and CommentaryEditorialsCancer Risks from CT Scans: Now We Have Data, What Next?David J. Brenner , Eric J. HallDavid J. Brenner , Eric J. HallAuthor AffiliationsFrom the Center for Radiological Research, Columbia University Medical Center, 630 W 168th St, New York, NY 10032.Address correspondence to D.J.B. (e-mail: [email protected]).David J. Brenner Eric J. HallPublished Online:Nov 1 2012https://doi.org/10.1148/radiol.12121248MoreSectionsFull textPDF ToolsAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookXLinked In AbstractTen years after the suggestion that CT scans might produce a small cancer risk, Pearce et al have shown that this is almost certainly the case, and they have confirmed the numerical magnitude of the risks; more complete epidemiologic studies are needed and several are indeed in progress, but in the interim, estimation of medical radiation risks based on atomic bomb survivor data appears to yield reasonable results.References1 Brenner DJ, Elliston CD, Hall EJ, Berdon WE. Estimated risks of radiation-induced fatal cancer from pediatric CT. AJR Am J Roentgenol 2001;176(2):289–296. Crossref, Medline, Google Scholar2 Paterson A, Frush DP, Donnelly LF. Helical CT of the body: are settings adjusted for pediatric patients? AJR Am J Roentgenol 2001;176(2):297–301. 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Dr. Glatstein's recent Editorial, "The Omega on Alpha and Beta" provided a thoughtful, provocative, and skeptical view regarding the utility of the linear-quadratic (LQ) model in radiotherapy (1Glatstein E. The omega on alpha and beta.Int J Radiat Oncol Biol Phys. 2011; 81: 319-320Abstract Full Text Full Text PDF PubMed Scopus (18) Google Scholar). By contrast, we suggest that, over the past quarter century, the use of α/β ratios in the context of the LQ model has markedly improved our understanding of one of the most basic tools that radiation oncologists have at their disposal: the potential to optimize fractionation. We do not doubt Dr. Glatstein's suggestion that one can indeed be an excellent clinical radiation oncologist without "knowing squat about α/β" ratios. We do, however, suggest that the LQ model continues to provide our field with two important tools. First, with appropriate caveats, LQ is an important tool for the research-oriented radiation oncologist wishing to design improved radiotherapeutic protocols. However, beyond this, we also suggest that the LQ model provides our field with ongoing easily digestible lessons about the clinical significance of fractionation and overall time—lessons that can often get lost in the enthusiasm for new irradiation technologies. It has been well established since the 1930s that fractionation is a key determinant of radiotherapeutic response (2Thames H.D. Hendry J.H. Fractionation in radiotherapy. Taylor & Francis, London1987Google Scholar); however, until the 1980s, we did not have a reliable quantitative framework to use this insight to generate improved protocols. What we had were empirical formulae such as the NSD, CRE and TDF (Nominal Standard Dose, Cumulative Radiation Effect and Time-Dose Factor [2Thames H.D. Hendry J.H. Fractionation in radiotherapy. Taylor & Francis, London1987Google Scholar]), which summarized past clinical experience. However, when these were used to design protocols with very different fractionation schemes from those on which they were based, the results were sometimes disastrous (3Bates T.D. Peters L.J. Dangers of the clinical use of the NSD formula for small fraction numbers.Br J Radiol. 1975; 48: 773Crossref PubMed Scopus (40) Google Scholar, 4Dische S. Martin W.M. Anderson P. Radiation myelopathy in patients treated for carcinoma of bronchus using a six fraction regime of radiotherapy.Br J Radiol. 1981; 54: 29-35Crossref PubMed Scopus (49) Google Scholar, 5Cox J.D. Large-dose fractionation (hypofractionation).Cancer. 1985; 55: 2105-2111Crossref PubMed Scopus (71) Google Scholar). By the early 1980s came the application of the LQ α/β formalism to clinical radiotherapy, initially by the Houston (6Thames Jr., H.D. Withers H.R. Peters L.J. et al.Changes in early and late radiation responses with altered dose fractionation: Implications for dose–survival relationships.Int J Radiat Oncol Biol Phys. 1982; 8: 219-226Abstract Full Text PDF PubMed Scopus (712) Google Scholar) and Amsterdam (7Barendsen G.W. Dose fractionation, dose rate and iso-effect relationships for normal tissue responses.Int J Radiat Oncol Biol Phys. 1982; 8: 1981-1997Abstract Full Text PDF PubMed Scopus (922) Google Scholar) groups. Essentially this provided a formalism that quantified the changes in the response of early-responding tissues, including tumors, and late-responding sequelae, when the fractionation pattern (and, subsequently, the overall time [8]) was changed. The LQ formalism is a consequence of the repair/misrepair kinetics of radiation-induced damage (9Brenner D.J. Hlatky L.R. Hahnfeldt P.J. et al.The linear-quadratic model and most other common radiobiological models result in similar predictions of time–dose relationships.Radiat Res. 1998; 150: 83-91Crossref PubMed Scopus (174) Google Scholar); by the 1980s, it was already a well-studied mechanistically based model of dose and dose–rate response in laboratory settings, but the insight of the Houston and Amsterdam groups was to see that by using clinically derived parameters, the model could be applied in the clinic. Both groups showed that the LQ model parameter α/β provided a quantification of the fractionation response; thus, the already established qualitative differences in fractionation response between early- and late-responding tissues (10Withers H.R. Thames H.D. Peters L.J. et al.Normal tissue radioresistance in clinical radiotherapy.in: Fletcher G.H. Nervi C. Withers H.R. Biological bases and clinical implications of tumor radioresistance (Rome 1980). Masson, New York1983Google Scholar) could be quantified through differences in this α/β ratio. So in its clinical context, the LQ model became, and still is, a mechanistically based formalism but with parameters directly derived from clinical data (2Thames H.D. Hendry J.H. Fractionation in radiotherapy. Taylor & Francis, London1987Google Scholar). The key here is that the LQ formalism has worked. Over the past two decades, dozens of new radiotherapeutic protocols have been designed using the LQ formalism with α/β parameter values derived from clinical data, and we have not had any of the clinical disasters that were associated with the application of empirical formulae such as NSD. Alternative fractionation schemes designed using the LQ approach have not only shown clear survival benefit (11Baujat B. Bourhis J. Blanchard P. et al.Hyperfractionated or accelerated radiotherapy for head and neck cancer.Cochrane Database Syst Rev. 2010; (CD002026)PubMed Google Scholar), but have also come out very much as predicted by the LQ modeling using clinical α/β parameters, even for highly nonstandard protocols such as hyperfractionation (12Horiot J.C. Maingon P. Barillot I. Radiotherapy for head and neck cancers including chemoradiotherapy.Curr Opin Oncol. 1994; 6: 272-276Crossref PubMed Scopus (8) Google Scholar), high-dose-rate vs. low-dose-rate brachytherapy (13Akagi Y. Hirokawa Y. Kagemoto M. et al.Optimum fractionation for high-dose-rate endoesophageal brachytherapy following external irradiation of early stage esophageal cancer.Int J Radiat Oncol Biol Phys. 1999; 43: 525-530Abstract Full Text Full Text PDF PubMed Scopus (61) Google Scholar), or prostate hypofractionation (14Yeoh E.E. Botten R.J. Butters J. et al.Hypofractionated versus conventionally fractionated radiotherapy for prostate carcinoma: Final results of phase III randomized trial.Int J Radiat Oncol Biol Phys. 2011; 81: 1271-1278Abstract Full Text Full Text PDF PubMed Scopus (190) Google Scholar). We suspect that the perceived "trouble with α/β ratios" (1Glatstein E. The omega on alpha and beta.Int J Radiat Oncol Biol Phys. 2011; 81: 319-320Abstract Full Text Full Text PDF PubMed Scopus (18) Google Scholar) stems from three main concerns:1.That it is inappropriate to derive α/β values from in vitro laboratory-based systems, in that no single in vitro assay could reflect the multitude of mechanisms that lead, particularly, to late sequelae. We would agree with this concern if that was indeed how α/β values for late-responding tissues were routinely estimated. However, they are almost always estimated by an analysis of clinical data (2Thames H.D. Hendry J.H. Fractionation in radiotherapy. Taylor & Francis, London1987Google Scholar, 15Tucker S.L. Thames H.D. Michalski J.M. et al.Estimation of alpha/beta for late rectal toxicity based on RTOG 94-06.Int J Radiat Oncol Biol Phys. 2011; 81: 600-605Abstract Full Text Full Text PDF PubMed Scopus (75) Google Scholar), and thus the dominant processes are effectively "built in" to the α/β estimates.2.That, because radiation-induced late effects are not wholly attributable to cell killing (and indeed radiation-induced nonlethal cellular dysfunction is clearly an important mechanism here (16Dörr W. Pathogenesis of normal tissue side effects.in: Joiner M.C. Van der Kogel A.J. Basic clinical radiobiology. 4th ed. Hodder Arnold, London2009: 169-190Crossref Google Scholar)), this might invalidate the use of the LQ model. However, it has long been established that radiation-induced nonlethal mutation yields also typically follow the standard LQ formalism at radiotherapeutic doses (17Schwartz J.L. Jordan R. Sun J. et al.Dose-dependent changes in the spectrum of mutations induced by ionizing radiation.Radiat Res. 2000; 153: 312-317Crossref PubMed Scopus (38) Google Scholar).3.That estimated α/β values represent averages over many patients. This is certainly true, but then the same applies to all radiotherapy treatment protocols—and the possibility of assessing individualized α/β values represents just one of the directions that might be possible in the future for individualized predictive assays. Quite conspicuous by their absence in Dr. Glatstein's critique (1Glatstein E. The omega on alpha and beta.Int J Radiat Oncol Biol Phys. 2011; 81: 319-320Abstract Full Text Full Text PDF PubMed Scopus (18) Google Scholar), or indeed elsewhere, are specific suggestions for alternatives. Unless we think our field has progressed just about as far as it can go, we need to take advantage of the rapidly developing technologies for targeting and timing; thus, some practical and reliable tool is needed to design and assess potential new fractionation protocols. The LQ model with clinically derived α/β values represents the simplest reliable mechanistically based quantitative description of how different tumors, different early-responding tissues, and different late-responding normal tissues respond to changes in fractionation and overall time (6Thames Jr., H.D. Withers H.R. Peters L.J. et al.Changes in early and late radiation responses with altered dose fractionation: Implications for dose–survival relationships.Int J Radiat Oncol Biol Phys. 1982; 8: 219-226Abstract Full Text PDF PubMed Scopus (712) Google Scholar, 7Barendsen G.W. Dose fractionation, dose rate and iso-effect relationships for normal tissue responses.Int J Radiat Oncol Biol Phys. 1982; 8: 1981-1997Abstract Full Text PDF PubMed Scopus (922) Google Scholar, 8Travis E.L. Tucker S.L. Isoeffect models and fractionated radiation therapy.Int J Radiat Oncol Biol Phys. 1987; 13: 283-287Abstract Full Text PDF PubMed Scopus (129) Google Scholar). It represents a tractable mechanistic model that is nevertheless anchored in clinical experience through clinically derived α/β ratios. It should be emphasized that the clinical application of LQ is not for generating absolute ab initio predictions of radiotherapeutic response, but rather to compare one fractionation/protraction protocol with another. When two fractionation schemes being compared each contain more than just a few fractions, their differences are expected to be dominated by repair and repopulation, and here the standard LQ model (6Thames Jr., H.D. Withers H.R. Peters L.J. et al.Changes in early and late radiation responses with altered dose fractionation: Implications for dose–survival relationships.Int J Radiat Oncol Biol Phys. 1982; 8: 219-226Abstract Full Text PDF PubMed Scopus (712) Google Scholar, 7Barendsen G.W. Dose fractionation, dose rate and iso-effect relationships for normal tissue responses.Int J Radiat Oncol Biol Phys. 1982; 8: 1981-1997Abstract Full Text PDF PubMed Scopus (922) Google Scholar, 8Travis E.L. Tucker S.L. Isoeffect models and fractionated radiation therapy.Int J Radiat Oncol Biol Phys. 1987; 13: 283-287Abstract Full Text PDF PubMed Scopus (129) Google Scholar) would be expected to perform well. For comparative studies involving more "extreme" protocols, such as a single very high-dose fraction, the standard LQ model undoubtedly becomes less reliable (18Kirkpatrick J.P. Brenner D.J. Orton C.G. Point/counterpoint: The linear-quadratic model is inappropriate to model high dose per fraction effects in radiosurgery.Med Phys. 2009; 36: 3381-3384Crossref PubMed Scopus (70) Google Scholar). Modifications of the LQ model for such situations do exist (19Guerrero M. Carlone M. Mechanistic formulation of a lineal-quadratic-linear (LQL) model: Split-dose experiments and exponentially decaying sources.Med Phys. 2010; 37: 4173-4181Crossref PubMed Scopus (41) Google Scholar, 20Brenner D.J. Hlatky L.R. Hahnfeldt P.J. et al.A convenient extension of the linear-quadratic model to include redistribution and reoxygenation.Int J Radiat Oncol Biol Phys. 1995; 32: 379-390Abstract Full Text PDF PubMed Scopus (94) Google Scholar), although at the price of increased model complexity and consequent decreased practical usability. When used with appropriate caution, the LQ model has proved a very useful tool for designing and comparing the effects of new fractionation protocols. More than that, built into the LQ model with its clinically derived parameters, are key lessons about fractionation and overall time, learnt over many decades and at considerable cost to many patients, and that are likely to be forgotten if designers of new radiotherapy protocols do not appreciate the significance of clinical α/β parameters. A pertinent example is the growing trend toward the use of hypofractionation. There are specific biologic situations when hypofractionation makes sense relative to more standard protocols (21Kavanagh B.D. Miften M. Rabinovitch R.A. Advances in treatment techniques: Stereotactic body radiation therapy and the spread of hypofractionation.Cancer J. 2011; 17: 177-181Crossref PubMed Scopus (24) Google Scholar, 22Brenner D.J. Hall E.J. Fractionation and protraction for radiotherapy of prostate carcinoma.Int J Radiat Oncol Biol Phys. 1999; 43: 1095-1101Abstract Full Text Full Text PDF PubMed Scopus (824) Google Scholar); in general, however, the LQ model provides explicit quantitative predictions of increased sequelae when the number of fractions is markedly reduced, particularly when critical normal tissues are too close (23Dunlap N.E. Cai J. Biedermann G.B. et al.Chest wall volume receiving >30 Gy predicts risk of severe pain and/or rib fracture after lung stereotactic body radiotherapy.Int J Radiat Oncol Biol Phys. 2010; 76: 796-801Abstract Full Text Full Text PDF PubMed Scopus (213) Google Scholar, 24Forquer J.A. Fakiris A.J. Timmerman R.D. et al.Brachial plexopathy from stereotactic body radiotherapy in early-stage NSCLC: Dose-limiting toxicity in apical tumor sites.Radiother Oncol. 2009; 93: 408-413Abstract Full Text Full Text PDF PubMed Scopus (150) Google Scholar, 25Timmerman R. McGarry R. Yiannoutsos C. et al.Excessive toxicity when treating central tumors in a phase II study of stereotactic body radiation therapy for medically inoperable early-stage lung cancer.J Clin Oncol. 2006; 24: 4833-4839Crossref PubMed Scopus (1267) Google Scholar) to the target volume. We forget at our peril the lessons built into the α/β model.

Protein oxidation can contribute to radiation-induced cell death by two mechanisms: (1) by reducing the fidelity of DNA repair, and (2) by decreasing cell viability directly. Previously, we explored the first mechanism by developing a mathematical model and applying it to data on Deinococcus radiodurans. Here we extend the model to both mechanisms, and analyze a recently published data set of protein carbonylation and cell survival in D. radiodurans and Escherichia coli exposed to gamma and ultraviolet radiation. Our results suggest that similar cell survival curves can be produced by very different mechanisms. For example, wild-type E. coli and DNA double-strand break (DSB) repair-deficient recA- D. radiodurans succumb to radiation doses of similar magnitude, but for different reasons: wild-type E. coli proteins are easily oxidized, causing cell death even at low levels of DNA damage, whereas proteins in recA- D. radiodurans are well protected from oxidation, but DSBs are not repaired correctly even when most proteins are intact. Radioresistant E. coli mutants survive higher radiation doses than the wild-type because of superior protection of cellular proteins from radiogenic oxidation. In contrast, wild-type D. radiodurans is much more radioresistant than the recA- mutant because of superior DSB repair, whereas protein protection in both strains is similar. With further development, the modeling approach presented here can also quantify the causes of radiation-induced cell death in other organisms. Enhanced understanding of these causes can stimulate research on novel radioprotection strategies.

Purpose: Biomarkers of ionising radiation exposure are useful in a variety of scenarios, such as medical diagnostic imaging, occupational exposures, and spaceflight. This study investigates to what extent microRNA (miRNA) expression signatures in mouse peripheral blood can be used as biomarkers for exposures to radiation with low and high linear energy transfers. Materials and methods: Mice were irradiated with doses of 0.5, 1.5, or 5.0 Gy γ-rays (dose rate of 0.0136 Gy/s) or with doses of 0.1 or 0.5 Gy 56Fe ions (dose rate of 0.00208 Gy/s). Total RNA was isolated from whole blood at 6 h or 24 h after irradiation. Three animals per irradiation condition were used. Differentially expressed miRNA were determined by means of quantitative real-time polymerase chain reaction. Results: miRNA expression signatures were radiation type-specific and dose- and time-dependent. The differentially expressed miRNA were expressed in either one condition (71%) or multiple conditions (29%). Classifiers based on the differentially expressed miRNA predicted radiation type or dose with accuracies between 75% and 100%. Gene-ontology analyses show that miRNA induced by irradiation are involved in the control of several biological processes, such as mRNA transcription regulation, nucleic-acid metabolism, and development. Conclusion: miRNA signatures induced by ionising radiation in mouse blood are radiation type- and radiation dose-specific. These findings underline the complexity of the radiation response and the importance of miRNA in it.

To provide the best opportunities for life-saving interventions in the event of a radiological or nuclear threat, there is an urgent need to improve the speed and efficiency of biodosimetric assays for triage and therapy. A rapid automated biodosimetric system used to assess thousands of individual radiation exposure doses is helpful to curb mass panic, and to conserve limited medical resources. This paper presents the development of a new robotically-based automated biodosimetry tool (RABiT). The RABiT is capable of automating two mature biodosimetry assays: the micronucleus and γ-H2AX assay. The design considerations guiding the hardware and software architecture are presented with focus on ease of implementation, methods of communication and need for real-time control versus soft time control cycles. Advanced technological developments for the RABiT including multipurpose gripper, non-contact laser cutting, automated biology protocols and transferring of the samples to a transparent substrate and high-speed multiple camera imaging are described in detail. The evaluation results show that the RABiT prototype has a throughput of 5,859 samples in an 18-hour duty cycle.

The annual number of CT scans in the U.S. is now over 70 million. The concern is that organ doses from CT are typically far larger than those from conventional X-ray examinations, and there is epidemiological evidence of a small but significant increased cancer risk at typical CT doses. Because CT is a superb diagnostic tool and because individual CT risks are small, when a CT scan is clinically indicated, the CT benefit/risk balance is by far in the patient's favor. Nevertheless, CT should operate under the ALARA (As Low As Reasonably Achievable) principle, and opportunities exist to reduce the significant population dose associated with CT without compromising patient care. The first opportunity is to reduce the dose per scan, and improved technology has much potential here. The second opportunity is selective replacement of CT with other modalities, such as for many head and spinal examinations (with MRI), and for diagnosing appendicitis (selective use of ultrasound + CT). Finally, a fraction of CT scans could be avoided entirely, as indicated by CT decision rules: Clinical decision rules for CT use represent a powerful approach for slowing down the increase in CT use, because they have the potential to overcome some of the major factors that result in some CT scans being undertaken when they are potentially not clinically helpful. In the U.S. and potentially elsewhere, legislative approaches are a possible option, to improve quality control and reduce clinically unneeded CT use, and it is also possible that upcoming changes in heath care economics will tend to slow the increase in such CT use.

Background Epidemiological data show that radiation exposure during childhood is associated with larger cancer risks compared with exposure at older ages. For exposures in adulthood, however, the relative risks of radiation-induced cancer in Japanese atomic bomb survivors generally do not decrease monotonically with increasing age of adult exposure. These observations are inconsistent with most standard models of radiation-induced cancer, which predict that relative risks decrease monotonically with increasing age at exposure, at all ages.Methods We analyzed observed cancer risk patterns as a function of age at exposure in Japanese atomic bomb survivors by using a biologically based quantitative model of radiation carcinogenesis that incorporates both radiation induction of premalignant cells (initiation) and radiation-induced promotion of premalignant damage. This approach emphasizes the kinetics of radiation-induced initiation and promotion, and tracks the yields of premalignant cells before, during, shortly after, and long after radiation exposure.Results Radiation risks after exposure in younger individuals are dominated by initiation processes, whereas radiation risks after exposure at later ages are more influenced by promotion of preexisting premalignant cells. Thus, the cancer site-dependent balance between initiation and promotion determines the dependence of cancer risk on age at radiation exposure. For example, in terms of radiation induction of premalignant cells, a quantitative measure of the relative contribution of initiation vs promotion is 10-fold larger for breast cancer than for lung cancer. Reflecting this difference, radiation-induced breast cancer risks decrease with age at exposure at all ages, whereas radiation-induced lung cancer risks do not.Conclusion For radiation exposure in middle age, most radiation-induced cancer risks do not, as often assumed, decrease with increasing age at exposure. This observation suggests that promotional processes in radiation carcinogenesis become increasingly important as the age at exposure increases. Radiation-induced cancer risks after exposure in middle age may be up to twice as high as previously estimated, which could have implications for occupational exposure and radiological imaging.

Long-term survival after a breast cancer diagnosis has increased markedly in the last decade: 15-year relative survival in the United States is now 75% (1), up from 58% in 2001. This increase is due in part to earlier detection but also to improved treatment options (2,3). So it is highly appropriate that increasing attention is being paid to the issue of breast cancer survivorship and, in particular, the issue of second breast cancers. Several long-term studies suggest that contralateral second breast cancer rates range from 10% to 15% at 15 years after treatment and are even higher for still longerterm survivors (4,5). The risk of a breast cancer survivor developing a second breast cancer is much higher than the risk of a comparable healthy woman developing a first breast cancer. For example, a healthy 55-year-old woman has about a 2.5% chance of developing invasive cancer in a given breast over the next 15 years, whereas a 55-year-old breast cancer survivor has a 10%–15% chance of developing invasive cancer in the contralateral breast over the next 15 years. Only a small component of this disturbingly large risk of a second breast cancer is treatment related: If anything, some chemotherapy regimens may reduce the rate of second breast cancers (6), and the comparatively low and inhomogeneous dose of scattered or leakage radiation to the contralateral breast during radiotherapy (7) results in only a small increase in the risk of contralateral breast cancer (5,8–10). These considerations imply that women with breast cancer are prone to develop a second breast cancer. Lifestyle and reproductive factors (11), as well as genetic factors (12), are each presumably major players in the etiology of second breast cancers, as they are in the etiology of primary breast cancers. Thus, there has been much interest in trying to identify genes that are associated with second breast cancers. Not surprisingly, the same genes that have been linked to increased susceptibility to primary breast cancer have been the most studied with regard to susceptibility to second cancers. For example, Graeser et al. (13) investigated the risk of contralateral second breast cancer in BRCA1 and BRCA2 mutation carriers and found that women with these mutations were more likely to develop a contralateral second breast cancer compared with breast cancer survivors without these mutations. Likewise, the clinical signifi cance of mutations in the ATM gene with respect to the risk of a

Biologically motivated mathematical models are important for understanding the mechanisms of radiation-induced carcinogenesis. Existing models fall into two categories: (1) short-term formalisms, which focus on the processes taking place during and shortly after irradiation (effects of dose, radiation quality, dose rate and fractionation), and (2) long-term formalisms, which track background cancer risks throughout the entire lifetime (effects of age at exposure and time since exposure) but make relatively simplistic assumptions about radiation effects. Grafting long-term mechanisms on to short-term models is badly needed for modelling radiogenic cancer. A combined formalism was developed and applied to cancer risk data in atomic bomb survivors and radiotherapy patients and to background cancer incidence. The data for nine cancer types were described adequately with a set of biologically meaningful parameters for each cancer. These results suggest that the combined short-long-term approach is a potentially promising method for predicting radiogenic cancer risks and interpreting the underlying biological mechanisms.

Ionizing radiation damages DNA and also induces oxidative stress, which can affect the function of proteins involved in DNA repair, thereby causing repair of DNA damage to become less efficient. We previously developed a mathematical model of this potentially synergistic relationship and applied it to γ-ray exposure data on the radiation-resistant prokaryote Deinococcus radiodurans. Here, we investigate the effects of radiation quality on these processes by applying the model to data on exposures of D. radiodurans to heavy ions with linear energy transfer (LET) of 18.5–11,300 keV/μm. The model adequately describes these data using three parameters combinations: radiogenic DNA damage induction, repair protein inactivation and cellular repair capacity. Although statistical uncertainties around best-fit parameter estimates are substantial, the behaviors of model parameters are consistent with current knowledge of LET effects: inactivation cross-sections for both DNA and proteins increase with increasing LET; DNA damage yield per unit of radiation dose also increases with LET; protein damage per unit dose tends to decrease with LET; DNA and especially protein damage yields are reduced when cells are irradiated in the dry state. These results suggest that synergism between oxidative stress and DNA damage may play an important role not only during γ-ray exposure, but during high-LET radiation exposure as well.