The Relative Biological Effectiveness of 200-Kvp X-Rays, Cobalt-60 Gamma-Rays, and 22-Mevp X-Rays, Determined from the Dose-Survival Curve of Saccharomyces cerevisiae

Sinclair, Warren K.; Gunter, Shirley E.; Cole, Aidan

doi:10.2307/3570834

Cited by 29 publications

(3 citation statements)

References 7 publications

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“…particles with high charge and energy). Risk uncertainties for space radiation tumorigenesis are typically inferred from low-LET risk using a quality factor or RBE (relative biological effectiveness) [2]. RBE as high as 40 have been reported for Harderian gland tumors detected in mice exposed to 600 MeV/n Fe [3].…”

Section: Introductionmentioning

confidence: 99%

Combinatorial DNA Damage Pairing Model Based on X-Ray-Induced Foci Predicts the Dose and LET Dependence of Cell Death in Human Breast Cells

et al. 2014

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In contrast to the classic view of static DNA double strand breaks (DSBs) being repaired at the site of damage, we hypothesize that DSBs move and merge with each other over large distances (µm). As X-ray dose increases, the probability of having DSB clusters increases and so does the probability of misrepair and cell death. Experimental work characterizing the dose dependence of radiation-induced foci (RIF) from X-ray in nonmalignant human mammary epithelial cells (MCF10A) is used here to validate a DSB clustering model. We then use the principles of the local effect model (LEM) to predict the yield of DSB at the sub-micron level. Two mechanisms for DSB clustering are first compared: random coalescence of DSBs versus active movement of DSBs into repair domains. Simulations that best predict both RIF dose dependence and cell survival following X-ray favor the repair domain hypothesis, suggesting the nucleus is divided into an array of regularly spaced repair domains of ~1.55 µm sides. Applying the same approach to high-LET ion tracks, we can predict experimental RIF/µm along tracks with an overall relative error of 12%, for LET ranging between 30 and 350 keV/µm and for three different ions. Finally, cell death is predicted by assuming an exponential dependence on the total number of DSBs and of all possible combinations of paired DSBs within each simulated RIF. RBE predictions for cell survival of MCF10A exposed to high-LET show an LET dependence that matches previous experimental results for similar cell types. Overall, this work suggests that microdosimetric properties of ion tracks at the sub-micron level are sufficient to explain both RIF data and survival curves for any LET, similarly to the LEM assumption. On the other hand, high-LET death mechanism does not have to infer linear-quadratic dose formalism as done in the LEM. In addition, the size of repair domains derived in our model are based on experimental RIF and are three times larger than the hypothetical LEM voxel used to fit survival curves. Our model is therefore an alternative to previous approaches by providing a testable biological mechanism (i.e. RIF). More generally, DSB pairing will help develop more accurate alternatives to the simplistic linear cancer risk model (LNT) currently used for regulating exposure to very low levels of ionizing radiation.Vadhavkar et al.

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Section: Introductionmentioning

confidence: 99%

Combinatorial DNA Damage Pairing Model Based on X-Ray-Induced Foci Predicts the Dose and LET Dependence of Cell Death in Human Breast Cells

et al. 2014

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“…This results in RBE differences of 20-30% for mammalian cell survival between 250kV, and megavoltage x-rays. These differences are important considerations for clinical radiation therapy and for radiobiological experiments (Sinklair et al 1959). For lower x-ray energies, even more substantial biological differences may occur, since R B E is proportional to the dose mean restricted LET (LA,,,) for x-rays and electrons (Harder and Blohm 1984, Blohm 1983, Blohm and Harder 1985.…”

Section: Introductionmentioning

confidence: 99%

Measurement of the restricted LET of orthovoltage and low-energy X-rays in tissue-equivalent plastic

Makrigiorgos¹,

Chin

1991

Phys. Med. Biol.

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“…The finding of a value of approximately 0.6 for the RBE of gamma rays vs. X rays at low doses may appear to contradict the usual assumption (see for example Sinclair et al, [12] ) of a value of about 0.85 for the RBE of gamma rays vs. X rays. However, there are two reasons which may account for this difference.…”

Section: Resultsmentioning

confidence: 75%

Comparison of X-ray and gamma-ray dose-response curves for pink somatic mutations in Tradescantia clone 02

Underbrink

Kellerer

Mills

et al. 1976

Radiat Environ Biophys

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Summary.Microdosimetric data indicate that the mean specific energy, ~, produced by individual charged particles from X rays and gamma rays is different for the two radiation qualities by nearly a factor of two. In order to test whether this influences the initial, linear component in the dose-effect relations, a comparison was made between dose-response curves for pink somatic mutations in Tradescantia clone 02 stamen hairs following X and gamma irradiations. Absorbed doses ranged from 2.66 to 300 rad. The results are in agreement with predictions made on the basis of microdosimetric data. At low doses gamma rays are substantially less effective than X rays. The RBE of gamma rays vs. X rays at low doses was approximately 0.6, a value lower than those usually reported in other experimental systems.

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The Relative Biological Effectiveness of 200-Kvp X-Rays, Cobalt-60 Gamma-Rays, and 22-Mevp X-Rays, Determined from the Dose-Survival Curve of Saccharomyces cerevisiae

Cited by 29 publications

References 7 publications

Combinatorial DNA Damage Pairing Model Based on X-Ray-Induced Foci Predicts the Dose and LET Dependence of Cell Death in Human Breast Cells

Combinatorial DNA Damage Pairing Model Based on X-Ray-Induced Foci Predicts the Dose and LET Dependence of Cell Death in Human Breast Cells

Measurement of the restricted LET of orthovoltage and low-energy X-rays in tissue-equivalent plastic

Comparison of X-ray and gamma-ray dose-response curves for pink somatic mutations in Tradescantia clone 02

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