Advantages of Synthetic Noise and Machine Learning for Analyzing Radioecological Data Sets

The ecological effects of accidental or malicious radioactive contamination are insufficiently understood because of the hazards and difficulties associated with conducting studies in radioactively-polluted areas. Data sets from severely contaminated locations can therefore be small. Moreover, many potentially important factors, such as soil concentrations of toxic chemicals, pH, and temperature, can be correlated with radiation levels and with each other. In such situations, commonly-used statistical techniques like generalized linear models (GLMs) may not be able to provide useful information about how radiation and/or these other variables affect the outcome (e.g. abundance of the studied organisms). Ensemble machine learning methods such as random forests offer powerful alternatives. We propose that analysis of small radioecological data sets by GLMs and/or machine learning can be made more informative by using the following techniques: (1) adding synthetic noise variables to provide benchmarks for distinguishing the performances of valuable predictors from irrelevant ones; (2) adding noise directly to the predictors and/or to the outcome to test the robustness of analysis results against random data fluctuations; (3) adding artificial effects to selected predictors to test the sensitivity of the analysis methods in detecting predictor effects; (4) running a selected machine learning method multiple times (with different random-number seeds) to test the robustness of the detected “signal”; (5) using several machine learning methods to test the “signal’s” sensitivity to differences in analysis techniques. Here, we applied these approaches to simulated data, and to two published examples of small radioecological data sets: (I) counts of fungal taxa in samples of soil contaminated by the Chernobyl nuclear power plan accident (Ukraine), and (II) bacterial abundance in soil samples under a ruptured nuclear waste storage tank (USA). We show that the proposed techniques were advantageous compared with the methodology used in the original publications where the data sets were presented. Specifically, our approach identified a negative effect of radioactive contamination in data set I, and suggested that in data set II stable chromium could have been a stronger limiting factor for bacterial abundance than the radionuclides 137Cs and 99Tc. This new information, which was extracted from these data sets using the proposed techniques, can potentially enhance the design of radioactive waste bioremediation

Mechanistic Modeling of Dose and Dose Rate Dependences of Radiation-Induced DNA Double Strand Break Rejoining Kinetics in Saccharomyces cerevisiae

Mechanistic modeling of DNA double strand break (DSB) rejoining is important for quantifying and medically exploiting radiation-induced cytotoxicity (e.g. in cancer radiotherapy). Most radiation-induced DSBs are quickly-rejoinable and are rejoined within the first 1–2 hours after irradiation. Others are slowly-rejoinable (persist for several hours), and yet others are essentially unrejoinable (persist for >24 hours). The dependences of DSB rejoining kinetics on radiation dose and dose rate remain incompletely understood. We hypothesize that the fraction of slowly-rejoinable and/or unrejoinable DSBs increases with increasing dose/dose rate. This radiation-dependent (RD) model was implemented using differential equations for three DSB classes: quickly-rejoinable, slowly-rejoinable and unrejoinable. Radiation converts quickly-rejoinable to slowly-rejoinable, and slowly-rejoinable to unrejoinable DSBs. We used large published data sets on DSB rejoining in yeast exposed to sparsely-ionizing (electrons and γ-rays, single or split-doses, high or low dose rates) and densely-ionizing (α-particles) radiation to compare the performances of the proposed RD formalism and the established two-lesion kinetic (TLK) model. These yeast DSB rejoining data were measured within the radiation dose range relevant for clonogenic cell survival, whereas in mammalian cells DSB rejoining is usually measured only at supra-lethal doses for technical reasons. The RD model described both sparsely-ionizing and densely-ionizing radiation data much better than the TLK model: by 217 and 14 sample-size-adjusted Akaike information criterion units, respectively. This occurred because: the RD (but not the TLK) model reproduced the observed upwardly-curving dose responses for slowly-rejoinable/unrejoinable DSBs at long times after irradiation; the RD model adequately described DSB yields at both high and low dose rates using one parameter set, whereas the TLK model overestimated low dose rate data. These results support the hypothesis that DSB rejoining is progressively impeded at increasing radiation doses/dose rates

Quantitative Modeling of Microbial Population Responses to Chronic Irradiation Combined with Other Stressors

Microbial population responses to combined effects of chronic irradiation and other stressors (chemical contaminants, other sub-optimal conditions) are important for ecosystem functioning and bioremediation in radionuclide-contaminated areas. Quantitative mathematical modeling can improve our understanding of these phenomena. To identify general patterns of microbial responses to multiple stressors in radioactive environments, we analyzed three data sets on: (1) bacteria isolated from soil contaminated by nuclear waste at the Hanford site (USA); (2) fungi isolated from the Chernobyl nuclear-power plant (Ukraine) buildings after the accident; (3) yeast subjected to continuous γ-irradiation in the laboratory, where radiation dose rate and cell removal rate were independently varied. We applied generalized linear mixed-effects models to describe the first two data sets, whereas the third data set was amenable to mechanistic modeling using differential equations. Machine learning and information-theoretic approaches were used to select the best-supported formalism(s) among biologically-plausible alternatives. Our analysis suggests the following: (1) Both radionuclides and co-occurring chemical contaminants (e.g. NO2) are important for explaining microbial responses to radioactive contamination. (2) Radionuclides may produce non-monotonic dose responses: stimulation of microbial growth at low concentrations vs. inhibition at higher ones. (3) The extinction-defining critical radiation dose rate is dramatically lowered by additional stressors. (4) Reproduction suppression by radiation can be more important for determining the critical dose rate, than radiation-induced cell mortality. In conclusion, the modeling approaches used here on three diverse data sets provide insight into explaining and predicting multi-stressor effects on microbial communities: (1) the most severe effects (e.g. extinction) on microbial populations may occur when unfavorable environmental conditions (e.g. fluctuations of temperature and/or nutrient levels) coincide with radioactive contamination; (2) an organism’s radioresistance and bioremediation efficiency in rich laboratory media may be insufficient to carry out radionuclide bioremediation in the field—robustness against multiple stressors is needed

Mathematical Modeling Predicts Enhanced Growth of X-Ray Irradiated Pigmented Fungi

Ionizing radiation is known for its cytotoxic and mutagenic properties. However, recent evidence suggests that chronic sub-lethal irradiation stimulates the growth of melanin-pigmented (melanized) fungi, supporting the hypothesis that interactions between melanin and ionizing photons generate energy useful for fungal growth, and/or regulate growth-promoting genes. There are no quantitative models of how fungal proliferation is affected by ionizing photon energy, dose rate, and presence versus absence of melanin on the same genetic background. Here we present such a model, which we test using experimental data on melanin-modulated radiation-induced proliferation enhancement in the fungus Cryptococcus neoformans, exposed to two different peak energies (150 and 320 kVp) over a wide range of X-ray dose rates. Our analysis demonstrates that radiation-induced proliferation enhancement in C. neoformans behaves as a binary “on/off” phenomenon, which is triggered by dose rates 5000 mGy/h. Proliferation enhancement of irradiated cells compared with unirradiated controls occurs at both X-ray peak energies, but its magnitude is modulated by X-ray peak energy and cell melanization. At dose rates <5000 mGy/h, both melanized and non-melanized cells exposed to 150 kVp X-rays, and non-melanized cells exposed to 320 kVp X-rays, all exhibit the same proliferation enhancement: on average, chronic irradiation stimulates each founder cell to produce 100 (95% CI: 83, 116) extra descendants over 48 hours. Interactions between melanin and 320 kVp X-rays result in a significant (2-tailed p-value = 4.8×10−5) additional increase in the number of radiation-induced descendants per founder cell: by 55 (95% CI: 29, 81). These results show that both melanin-dependent and melanin-independent mechanisms are involved in radiation-induced fungal growth enhancement, and implicate direct and/or indirect interactions of melanin with high energy ionizing photons as an important pro-proliferative factor

A new view of radiation-induced cancer: integrating short- and long-term processes. Part I: Approach

Mathematical models of radiation carcinogenesis are important for understanding mechanisms and for interpreting or extrapolating risk. There are two classes of such models: (1) long-term formalisms that track pre-malignant cell numbers throughout an entire lifetime but treat initial radiation dose–response simplistically and (2) short-term formalisms that provide a detailed initial dose–response even for complicated radiation protocols, but address its modulation during the subsequent cancer latency period only indirectly. We argue that integrating short- and long-term models is needed. As an example of this novel approach, we integrate a stochastic short-term initiation/inactivation/repopulation model with a deterministic two-stage long-term model. Within this new formalism, the following assumptions are implemented: radiation initiates, promotes, or kills pre-malignant cells; a pre-malignant cell generates a clone, which, if it survives, quickly reaches a size limitation; the clone subsequently grows more slowly and can eventually generate a malignant cell; the carcinogenic potential of pre-malignant cells decreases with age

A new view of radiation-induced cancer: integrating short- and long-term processes. Part II: second cancer risk estimation

As the number of cancer survivors grows, prediction of radiotherapy-induced second cancer risks becomes increasingly important. Because the latency period for solid tumors is long, the risks of recently introduced radiotherapy protocols are not yet directly measurable. In the accompanying article, we presented a new biologically based mathematical model, which, in principle, can estimate second cancer risks for any protocol. The novelty of the model is that it integrates, into a single formalism, mechanistic analyses of pre-malignant cell dynamics on two different time scales: short-term during radiotherapy and recovery; long-term during the entire life span. Here, we apply the model to nine solid cancer types (stomach, lung, colon, rectal, pancreatic, bladder, breast, central nervous system, and thyroid) using data on radiotherapy-induced second malignancies, on Japanese atomic bomb survivors, and on background US cancer incidence. Potentially, the model can be incorporated into radiotherapy treatment planning algorithms, adding second cancer risk as an optimization criterion

Instanton Contribution to the Quark Form Factor

The nonperturbative effects in the quark form factor are considered in the Wilson loop formalism. The properties of the Wilson loops with cusp singularities are studied taking into account the perturbative and nonperturbative contributions, where the latter are considered within the framework of the instanton liquid model. For the integration path corresponding to this form factor -- the angle with infinite sides -- the explicit expression for the vacuum expectation value of the Wilson operator is found to leading order. The calculations are performed in the weak-field limit for the instanton vacuum contribution and compared with the one- and two-loop order results for the perturbative part. It is shown that the instantons produce the powerlike corrections to the perturbative result, which are comparable in magnitude with the perturbative part at the scale of order of the inverse average instanton size. It is demonstrated that the instanton contributions to the quark form factor are exponentiated to high orders in the small instanton density parameter.Comment: Version coincident with the journal publication. LaTeX, 15 pages, 1 figur

Microbial cells can cooperate to resist high-level chronic ionizing radiation

Understanding chronic ionizing radiation (CIR) effects is of utmost importance to protecting human health and the environment. Diverse bacteria and fungi inhabiting extremely radioactive waste and disaster sites (e.g. Hanford, Chernobyl, Fukushima) represent new targets of CIR research. We show that many microorganisms can grow under intense gamma-CIR dose rates of 13–126 Gy/h, with fungi identified as a particularly CIR-resistant group of eukaryotes: among 145 phylogenetically diverse strains tested, 78 grew under 36 Gy/h. Importantly, we demonstrate that CIR resistance can depend on cell concentration and that certain resistant microbial cells protect their neighbors (not only conspecifics, but even radiosensitive species from a different phylum), from high-level CIR. We apply a mechanistically-motivated mathematical model of CIR effects, based on accumulation/removal kinetics of reactive oxygen species (ROS) and antioxidants, in bacteria (3 Escherichia coli strains and Deinococcus radiodurans) and in fungi (Candida parapsilosis, Kazachstania exigua, Pichia kudriavzevii, Rhodotorula lysinophila, Saccharomyces cerevisiae, and Trichosporon mucoides). We also show that correlations between responses to CIR and acute ionizing radiation (AIR) among studied microorganisms are weak. For example, in D. radiodurans, the best molecular correlate for CIR resistance is the antioxidant enzyme catalase, which is dispensable for AIR resistance; and numerous CIR-resistant fungi are not AIR-resistant. Our experimental findings and quantitative modeling thus demonstrate the importance of investigating CIR responses directly, rather than extrapolating from AIR. Protection of radiosensitive cell-types by radioresistant ones under high-level CIR is a potentially important new tool for bioremediation of radioactive sites and development of CIR-resistant microbiota as radioprotectors

γ-H2AX Kinetic Profile in Mouse Lymphocytes Exposed to the Internal Emitters Cesium-137 and Strontium-90

In the event of a dirty bomb scenario or an industrial nuclear accident, a significant dose of volatile radionuclides such as 137Cs and 90Sr may be dispersed into the atmosphere as a component of fallout and inhaled or ingested by hundreds and thousands of people. To study the effects of prolonged exposure to ingested radionuclides, we have performed long-term (30 day) internal-emitter mouse irradiations using soluble-injected 137CsCl and 90SrCl2 radioisotopes. The effect of ionizing radiation on the induction and repair of DNA double strand breaks (DSBs) in peripheral mouse lymphocytes in vivo was determined using the γ-H2AX biodosimetry marker. Using a serial sacrifice experimental design, whole-body radiation absorbed doses for 137Cs (0 to 10 Gy) and 90Sr (0 to 49 Gy) were delivered over 30 days following exposure to each radionuclide. The committed absorbed doses of the two internal emitters as a function of time post exposure were calculated based on their retention parameters and their derived dose coefficients for each specific sacrifice time. In order to measure the kinetic profile for γ-H2AX, peripheral blood samples were drawn at 5 specific timed dose points over the 30-day study period and the total γ-H2AX nuclear fluorescence per lymphocyte was determined using image analysis software. A key finding was that a significant γ-H2AX signal was observed in vivo several weeks after a single radionuclide exposure. A mechanistically-motivated model was used to analyze the temporal kinetics of γ-H2AX fluorescence. Exposure to either radionuclide showed two peaks of γ-H2AX: one within the first week, which may represent the death of mature, differentiated lymphocytes, and the second at approximately three weeks, which may represent the production of new lymphocytes from damaged progenitor cells. The complexity of the observed responses to internal irradiation is likely caused by the interplay between continual production and repair of DNA damage, cell cycle effects and apoptosis

Instanton Corrections to Quark Form Factor at Large Momentum Transfer

Within the Wilson integral formalism, we discuss the structure of nonperturbative corrections to the quark form factor at large momentum transfer analyzing the infrared renormalon and instanton effects. We show that the nonperturbative effects determine the initial value for the perturbative evolution of the quark form factor and attribute their general structure to the renormalon ambiguities of the perturbative series. It is demonstrated that the instanton contributions result in the finite renormalization of the next-to-leading perturbative result and numerically are characterized by a small factor reflecting the diluteness of the QCD vacuum within the instanton liquid model.Comment: Version coincident with the journal publication, 9 pages; REVTe