Multiwell-based G0-PCC assay for radiation biodosimetry.

In cytogenetic biodosimetry, assessing radiation exposure typically requires over 48 hours for cells to reach mitosis, significantly delaying the administration of crucial radiation countermeasures needed within the first 24 hours post-exposure. To improve medical response times, we incorporated the G0-Premature Chromosome Condensation (G0-PCC) technique with the Rapid Automated Biodosimetry Tool-II (RABiT-II), creating a faster alternative for large-scale radiation emergencies. Our findings revealed that using a lower concentration of Calyculin A (Cal A) than recommended effectively increased the yield of highly-condensed G0-PCC cells (hPCC). However, integrating recombinant CDK1/Cyclin B kinase, vital for chromosome condensation, proved challenging due to the properties of these proteins affecting interactions with cellular membranes. Interestingly, Cal A alone was capable of inducing chromosome compaction in some G0 cells even in the absence of mitotic kinases, although these chromosomes displayed atypical morphologies. This suggests that Cal A mechanism for compacting G0 chromatin may differ from condensation driven by mitotic kinases. Additionally, we observed a correlation between radiation dose and extent of hPCC chromosome fragmentation, which allowed us to automate radiation damage quantification using a Convolutional Neural Network (CNN). Our method can address the need for a same-day cytogenetic biodosimetry test in radiation emergency situations.

Host microbiome depletion attenuates biofluid metabolite responses following radiation exposure.

Development of novel biodosimetry assays and medical countermeasures is needed to obtain a level of radiation preparedness in the event of malicious or accidental mass exposures to ionizing radiation (IR). For biodosimetry, metabolic profiling with mass spectrometry (MS) platforms has identified several small molecules in easily accessible biofluids that are promising for dose reconstruction. As our microbiome has profound effects on biofluid metabolite composition, it is of interest how variation in the host microbiome may affect metabolomics based biodosimetry. Here, we 'knocked out' the microbiome of male and female C57BL/6 mice (Abx mice) using antibiotics and then irradiated (0, 3, or 8 Gy) them to determine the role of the host microbiome on biofluid radiation signatures (1 and 3 d urine, 3 d serum). Biofluid metabolite levels were compared to a sham and irradiated group of mice with a normal microbiome (Abx-con mice). To compare post-irradiation effects in urine, we calculated the Spearman's correlation coefficients of metabolite levels with radiation dose. For selected metabolites of interest, we performed more detailed analyses using linear mixed effect models to determine the effects of radiation dose, time, and microbiome depletion. Serum metabolite levels were compared using an ANOVA. Several metabolites were affected after antibiotic administration in the tryptophan and amino acid pathways, sterol hormone, xenobiotic and bile acid pathways (urine) and lipid metabolism (serum), with a post-irradiation attenuative effect observed for Abx mice. In urine, dose×time interactions were supported for a defined radiation metabolite panel (carnitine, hexosamine-valine-isoleucine [Hex-V-I], creatine, citric acid, and Nε,Nε,Nε-trimethyllysine [TML]) and dose for N1-acetylspermidine, which also provided excellent (AUROC ≥ 0.90) to good (AUROC ≥ 0.80) sensitivity and specificity according to the area under the receiver operator characteristic curve (AUROC) analysis. In serum, a panel consisting of carnitine, citric acid, lysophosphatidylcholine (LysoPC) (14:0), LysoPC (20:3), and LysoPC (22:5) also gave excellent to good sensitivity and specificity for identifying post-irradiated individuals at 3 d. Although the microbiome affected the basal levels and/or post-irradiation levels of these metabolites, their utility in dose reconstruction irrespective of microbiome status is encouraging for the use of metabolomics as a novel biodosimetry assay.

Susceptibility of extremophiles to far-UVC light for bioburden reduction in spacecraft assembly facilities.

The prevention and reduction of microbial species entering and leaving Earth's biosphere is a critical aspect of planetary protection research. While various decontamination methods exist and are currently utilized for planetary protection purposes, the use of far-UVC light (200-230 nm) as a means for microbial reduction remains underexplored. Unlike conventional germicidal ultraviolet at 254 nm, which can pose a health risk to humans even with small exposure doses, far-UVC light poses minimal health hazard making it a suitable candidate for implementation in occupied areas of spacecraft assembly facilities. This study investigates the efficacy of far-UVC 222-nm light to inactivate bacteria using microbial species which are relevant to planetary protection either in vegetative cell or spore form. All the tested vegetative cells demonstrated susceptibility to 222-nm exposure, although susceptibility varied among the tested species. Notably, Deinococcus radiodurans, a species highly tolerant to extreme environmental conditions, exhibited the most resistance to far-UVC exposure with a dose of 112 mJ/cm2 required for a 1-log reduction in survival. While spore susceptibility was similar across the species tested, Bacillus pumilus spores were the most resistant of the tested spores when analyzed with a bi-exponential cell killing model (D90 of 6.8 mJ/cm2). Overall, these results demonstrate the efficacy of far-UVC light for reducing microbial bioburden to help ensure the success and safety of future space exploration missions.

222 nm far-UVC light markedly reduces the level of infectious airborne virus in an occupied room.

An emerging intervention for control of airborne-mediated pandemics and epidemics is whole-room far-UVC (200-235 nm). Laboratory studies have shown that 222-nm light inactivates airborne pathogens, potentially without harm to exposed occupants. While encouraging results have been reported in benchtop studies and in room-sized bioaerosol chambers, there is a need for quantitative studies of airborne pathogen reduction in occupied rooms. We quantified far-UVC mediated reduction of aerosolized murine norovirus (MNV) in an occupied mouse-cage cleaning room within an animal-care facility. Benchtop studies suggest that MNV is a conservative surrogate for airborne viruses such as influenza and coronavirus. Using four 222-nm fixtures installed in the ceiling, and staying well within current recommended regulatory limits, far-UVC reduced airborne infectious MNV by 99.8% (95% CI: 98.2-99.9%). Similar to previous room-sized bioaerosol chamber studies on far-UVC efficacy, these results suggest that aerosolized virus susceptibility is significantly higher in room-scale tests than in bench-scale laboratory studies. That said, as opposed to controlled laboratory studies, uncertainties in this study related to airflow patterns, virus residence time, and dose to the collected virus introduce uncertainty into the inactivation estimates. This study is the first to directly demonstrate far-UVC anti-microbial efficacy against airborne pathogens in an occupied indoor location.

Quantifying the effects of neutron dose, dose protraction, age and sex on mouse survival using parametric regression and machine learning on a 21,000-mouse data set.

The biological effects of densely-ionizing radiations such as neutrons and heavy ions encountered in space travel, nuclear incidents, and cancer radiotherapy, significantly differ from those of sparsely-ionizing photons and necessitate a comprehensive understanding for improved protection measures. Data on lifespan studies of laboratory rodents exposed to fission neutrons, accumulated in the Janus archive, afford unique insights into the impact of densely ionizing radiation on mortality from cancers and various organ dysfunction. We extracted and analyzed data for 21,308 individual B6CF1 mice to investigate the effects of neutron dose, fractionation, protraction, age, and sex on mortality. As Cox regression encountered limitations owing to assumption violations, we turned to Random Survival Forests (RSF), a machine learning algorithm adept at modeling nonlinear relationships. RSF interpretation using Shapley Additive Explanations revealed a dose response for mortality risk that curved upwards at low doses < 20 cGy, became nearly-linear over 20-150 cGy, and saturated at high doses. The response was enhanced by fractionation/protraction of irradiation (exhibiting an inverse dose rate effect), and diminished by older age at exposure. Somewhat reduced mortality was predicted for males vs females. This research expands our knowledge on the long-term effects of densely ionizing radiations on mammal mortality.

Sex and dose rate effects in automated cytogenetics.

Testing and validation of biodosimetry assays is routinely performed using conventional dose rate irradiation platforms, at a dose rate of approximately 1 Gy/min. In contrast, the exposures from an improvised nuclear device will be delivered over a large range of dose rates with a prompt irradiation component, delivered in less than 1 µs, and a protracted component delivered over hours and days. We present preliminary data from a large demographic study we have undertaken for investigation of age, sex and dose rate effects on dicentric and micronucleus yields. Our data demonstrate reduced dicentric and micronucleus yields at very high dose rates. Additionally, we have seen small differences between males and females, with males having slightly fewer micronuclei and slightly more dicentrics than females, at high doses.

Impact of GADD45A on Radiation Biodosimetry Using Mouse Peripheral Blood.

High-dose-radiation exposure in a short period of time leads to radiation syndromes characterized by severe acute and delayed organ-specific injury accompanied by elevated organismal morbidity and mortality. Radiation biodosimetry based on gene expression analysis of peripheral blood is a valuable tool to detect exposure to radiation after a radiological/nuclear incident and obtain useful biological information that could predict tissue and organismal injury. However, confounding factors, including chronic inflammation, can potentially obscure the predictive power of the method. GADD45A (Growth arrest and DNA damage-inducible gene a) plays important roles in cell growth control, differentiation, DNA repair, and apoptosis. GADD45A-deficient mice develop an autoimmune disease, similar to human systemic lupus erythematosus, characterized by severe hematological disorders, kidney disease, and premature death. The goal of this study was to elucidate how pre-existing inflammation in mice, induced by GADD45A ablation, can affect radiation biodosimetry. We exposed wild-type and GADD45A knockout male C57BL/6J mice to 7 Gy of X rays and 24 h later RNA was isolated from whole blood and subjected to whole genome microarray and gene ontology analyses. Dose reconstruction analysis using a gene signature trained on gene expression data from irradiated wild-type male mice showed accurate reconstruction of either a 0 Gy or 7 Gy dose with root mean square error of ± 1.05 Gy (R^2 = 1.00) in GADD45A knockout mice. Gene ontology analysis revealed that irradiation of both wild-type and GADD45A-null mice led to a significant overrepresentation of pathways associated with morbidity and mortality, as well as organismal cell death. However, based on their z-score, these pathways were predicted to be more significantly overrepresented in GADD45A-null mice, implying that GADD45A deletion may exacerbate the deleterious effects of radiation on blood cells. Numerous immune cell functions and quantities were predicted to be underrepresented in both genotypes; however, differentially expressed genes from irradiated GADD45A knockout mice predicted an increased deterioration in the numbers of T lymphocytes, as well as myeloid cells, compared with wild-type mice. Furthermore, an overrepresentation of genes associated with radiation-induced hematological malignancies was associated with GADD45A knockout mice, whereas hematopoietic and progenitor cell functions were predicted to be downregulated in irradiated GADD45A knockout mice. In conclusion, despite the significant differences in gene expression between wild-type and GADD45A knockout mice, it is still feasible to identify a panel of genes that could accurately distinguish between irradiated and control mice, irrespective of pre-existing inflammation status.

Improved prediction of breast cancer risk based on phenotypic DNA damage repair capacity in peripheral blood B cells.

Background: Standard Breast Cancer (BC) risk prediction models based only on epidemiologic factors generally have quite poor performance, and there have been a number of risk scores proposed to improve them, such as AI-based mammographic information, polygenic risk scores and pathogenic variants. Even with these additions BC risk prediction performance is still at best moderate. In that decreased DNA repair capacity (DRC) is a major risk factor for development of cancer, we investigated the potential to improve BC risk prediction models by including a measured phenotypic DRC assay. Methods: Using blood samples from the Breast Cancer Family Registry we assessed the performance of phenotypic markers of DRC in 46 matched pairs of individuals, one from each pair with BC (with blood drawn before BC diagnosis) and the other from controls matched by age and time since blood draw. We assessed DRC in thawed cryopreserved peripheral blood mononuclear cells (PBMCs) by measuring γ-H2AX yields (a marker for DNA double-strand breaks) at multiple times from 1 to 20 hrs after a radiation challenge. The studies were performed using surface markers to discriminate between different PBMC subtypes. Results: The parameter Fres, the residual damage signal in PBMC B cells at 20 hrs post challenge, was the strongest predictor of breast cancer with an AUC (Area Under receiver-operator Curve) of 0.89 [95% Confidence Interval: 0.84-0.93] and a BC status prediction accuracy of 0.80. To illustrate the combined use of a phenotypic predictor with standard BC predictors, we combined Fres in B cells with age at blood draw, and found that the combination resulted in significantly greater BC predictive power (AUC of 0.97 [95% CI: 0.94-0.99]), an increase of 13 percentage points over age alone. Conclusions: If replicated in larger studies, these results suggest that inclusion of a fingerstick-based phenotypic DRC blood test has the potential to markedly improve BC risk prediction.

Biomarker integration for improved biodosimetry of mixed neutron + photon exposures.

There is a persistent risk of a large-scale malicious or accidental exposure to ionizing radiation that may affect a large number of people. Exposure will consist of both a photon and neutron component, which will vary in magnitude between individuals and is likely to have profound impacts on radiation-induced diseases. To mitigate these potential disasters, there exists a need for novel biodosimetry approaches that can estimate the radiation dose absorbed by each person based on biofluid samples, and predict delayed effects. Integration of several radiation-responsive biomarker types (transcripts, metabolites, blood cell counts) by machine learning (ML) can improve biodosimetry. Here we integrated data from mice exposed to various neutron + photon mixtures, total 3 Gy dose, using multiple ML algorithms to select the strongest biomarker combinations and reconstruct radiation exposure magnitude and composition. We obtained promising results, such as receiver operating characteristic curve area of 0.904 (95% CI: 0.821, 0.969) for classifying samples exposed to ≥ 10% neutrons vs. < 10% neutrons, and R2 of 0.964 for reconstructing photon-equivalent dose (weighted by neutron relative biological effectiveness) for neutron + photon mixtures. These findings demonstrate the potential of combining various -omic biomarkers for novel biodosimetry.

Analysis of causal effects of 137Cs deposition on 137Cs concentrations in trees after the Fukushima accident using machine learning.

Radioactive contamination of forests by long-lived radionuclides from nuclear accidents such as Chernobyl and Fukushima continues to be studied and quantitatively modeled. Whereas traditional statistical and machine learning (ML) techniques generate predictions by focusing on correlations between variables, quantification of causal effects of radioactivity deposition levels on contamination of plant tissues represents a more fundamental and relevant research goal. Modeling of cause-and-effect relationships is advantageous over standard predictive modeling, particularly by improving the generalizability of results to other situations, where the distributions of variables, including potential confounders, differ from those in the training data. Here we used the state-of-the-art causal forest (CF) algorithm to quantify the causal effect of 137Cs land contamination after the Fukushima accident on 137Cs activity concentrations in the wood of four common Japanese forest tree species: Hinoki cypress (Chamaecyparis obtusa), konara oak (Quercus serrata), red pine (Pinus densiflora), and Sugi cedar (Cryptomeria japonica). We estimated the average causal effect for the population, quantified how it was influenced by other environmental variables, and produced effect estimates at the individual level. The estimated causal effect was quite robust to various refutation methods, and was negatively influenced by high mean annual precipitation, elevation, and time after the accident. Wood subtype (e.g. sapwood, heartwood) and tree species made smaller contributions to the causal effect. We believe that causal ML techniques have promising potential in radiation ecology and can usefully expand the toolkit of modeling approaches available to researchers in this field.

The abundance of the potential pathogen Staphylococcus hominis in the air microbiome in a dental clinic and its susceptibility to far-UVC light.

The dental clinic air microbiome incorporates microbes from the oral cavity and upper respiratory tract (URT). This study aimed to establish a reliable methodology for air sampling in a dental clinic setting and quantify the abundance of culturable mesophilic aerobic bacteria present in these samples using regression modeling. Staphylococcus hominis, a potentially pathogenic bacterium typically found in the human oropharynx and URT, was consistently isolated. S. hominis was the most abundant species of aerobic bacteria (22%-24%) and comprised 60%-80% of all Staphylococcus spp. The study also assessed the susceptibility of S. hominis to 222 nm-far-UVC light in laboratory experiments, which showed an exponential surface inactivation constant of k = 0.475 cm2 /mJ. This constant is a critical parameter for future on-site use of far-UVC light as a technique for reducing pathogenic bacterial load in dental clinics.

Variable Dose Rates in Realistic Radiation Exposures: Effects on Small Molecule Markers of Ionizing Radiation in the Murine Model.

Novel biodosimetry assays for use in preparedness and response to potential malicious attacks or nuclear accidents would ideally provide accurate dose reconstruction independent of the idiosyncrasies of a complex exposure to ionizing radiation. Complex exposures will consist of dose rates spanning the low dose rates (LDR) to very high-dose rates (VHDR) that need to be tested for assay validation. Here, we investigate how a range of relevant dose rates affect metabolomic dose reconstruction at potentially lethal radiation exposures (8 Gy in mice) from an initial blast or subsequent fallout exposures compared to zero or sublethal exposures (0 or 3 Gy in mice) in the first 2 days, which corresponds to an integral time individuals will reach medical facilities after a radiological emergency. Biofluids (urine and serum) were collected from both male and female 9-10-week-old C57BL/6 mice at 1 and 2 days postirradiation (total doses of 0, 3 or 8 Gy) after a VHDR of 7 Gy/s. Additionally, samples were collected after a 2-day exposure consisting of a declining dose rate (1 to 0.004 Gy/min) recapitulating the 7:10 rule-of-thumb time dependency of nuclear fallout. Overall similar perturbations were observed in both urine and serum metabolite concentrations irrespective of sex or dose rate, with the exception of xanthurenic acid in urine (female specific) and taurine in serum (VHDR specific). In urine, we developed identical multiplex metabolite panels (N6, N6,N6-trimethyllysine, carnitine, propionylcarnitine, hexosamine-valine-isoleucine, and taurine) that could identify individuals receiving potentially lethal levels of radiation from the zero or sublethal cohorts with excellent sensitivity and specificity, with creatine increasing model performance at day 1. In serum, individuals receiving a 3 or 8 Gy exposure could be identified from their pre-irradiation samples with excellent sensitivity and specificity, however, due to a lower dose response the 3 vs. 8 Gy groups could not be distinguished from each other. Together with previous results, these data indicate that dose-rate-independent small molecule fingerprints have potential in novel biodosimetry assays.

Longitudinal multi-omic changes in the transcriptome and proteome of peripheral blood cells after a 4 Gy total body radiation dose to Rhesus macaques.

BACKGROUND: Non-human primates, such as Rhesus macaques, are a powerful model for studies of the cellular and physiological effects of radiation, development of radiation biodosimetry, and for understanding the impact of radiation on human health. Here, we study the effects of 4 Gy total body irradiation (TBI) at the molecular level out to 28 days and at the cytogenetic level out to 56 days after exposure. We combine the global transcriptomic and proteomic responses in peripheral whole blood to assess the impact of acute TBI exposure at extended times post irradiation. RESULTS: The overall mRNA response in the first week reflects a strong inflammatory reaction, infection response with neutrophil and platelet activation. At 1 week, cell cycle arrest and re-entry processes were enriched among mRNA changes, oncogene-induced senescence and MAPK signaling among the proteome changes. Influenza life cycle and infection pathways initiated earlier in mRNA and are reflected among the proteomic changes during the first week. Transcription factor proteins SRC, TGFß and NFATC2 were immediately induced at 1 day after irradiation with increased transcriptional activity as predicted by mRNA changes persisting up to 1 week. Cell counts revealed a mild / moderate hematopoietic acute radiation syndrome (H-ARS) reaction to irradiation with expected lymphopenia, neutropenia and thrombocytopenia that resolved within 30 days. Measurements of micronuclei per binucleated cell levels in cytokinesis-blocked T-lymphocytes remained high in the range 0.27-0.33 up to 28 days and declined to 0.1 by day 56. CONCLUSIONS: Overall, we show that the TBI 4 Gy dose in NHPs induces many cellular changes that persist up to 1 month after exposure, consistent with damage, death, and repopulation of blood cells.

Effect of Age and Sex on Gene Expression-Based Radiation Biodosimetry Using Mouse Peripheral Blood.

Blood-based gene expression profiles that can reconstruct radiation exposure are being developed as a practical approach to radiation biodosimetry. However, age and sex could potentially limit the accuracy of the approach. In this study, we determined the impact of age on the peripheral blood cell gene expression profile of female mice exposed to radiation and identified differences and similarities with a previously obtained transcriptomic signature of male mice. Young (2 months) and old (24 months) female mice were irradiated with 4 Gy X-rays, total RNA was isolated from blood 24 hours later and subjected to whole-genome microarray analysis. Dose reconstruction analyses using a gene signature trained on gene expression data from irradiated young male mice showed accurate reconstruction of 0 or 4 Gy doses with root mean square error of ±0.75 Gy (R2 = 0.90) in young female mice. Although dose reconstruction for irradiated old female mice was less accurate than young female mice, the deviation from the actual radiation dose was not statistically significant. Pathway analysis of differentially expressed genes revealed that after irradiation, apoptosis-related functions were overrepresented, whereas functions related to quantities of various immune cell subtypes were underrepresented, among differentially expressed genes from young female mice, but not older animals. Furthermore, young mice significantly upregulated genes involved in phagocytosis, a process that eliminates apoptotic cells and preserves tissue homeostasis. Both functions were also overrepresented in young, but not old, male mice following 4 Gy X-irradiation. Lastly, functions associated with neutrophil activation that is essential for killing invading pathogens and regulating the inflammatory response were predicted to be uniquely enriched in young but not old female mice. This work supports the concept that peripheral blood gene expression profiles can be identified in mice that accurately predict physical radiation dose exposure irrespective of age and sex.

High-throughput measurement of double strand break global repair phenotype in peripheral blood mononuclear cells after long-term cryopreservation.

Peripheral blood mononuclear cells (PBMCs) are a useful model for biochemical assays, particularly for etiological studies. We describe here a method for measuring DNA repair capacity (DRC) in archival cryogenically preserved PBMCs. To model DRC, we measured γ-H2AX repair kinetics in thawed PBMCs after irradiation with 3 Gy gamma rays. Time-dependent fluorescently labeled γ-H2AX levels were measured at five time points from 1 to 20 h, yielding an estimate of global DRC repair kinetics as well as a measure of unrepaired double strand breaks at 20 h. While γ-H2AX levels are traditionally measured by either microscopy or flow-cytometry, we developed a protocol for imaging flow cytometry (IFC) that combines the detailed information of microscopy with the statistical power of flow methods. The visual imaging component of the IFC allows for monitoring aspects such as cellular health and apoptosis as well as fluorescence localization of the γ-H2AX signal, which ensures the power and significance of this technique. Application of a machine-learning based image classification improved flow cytometry fluorescent measurements by identifying apoptotic cells unable to undergo DNA repair. We present here DRC repair parameters from 18 frozen archival PBMCs and 28 fresh blood samples collected from a demographically diverse cohort of women measured in a high-throughput IFC format. This thaw method and assay can be used alone or in conjunction with other assays to measure etiological phenotypes in cryogenic biobanks of PBMCs.

Machine learning approach for quantitative biodosimetry of partial-body or total-body radiation exposures by combining radiation-responsive biomarkers.

During a large-scale radiological event such as an improvised nuclear device detonation, many survivors will be shielded from radiation by environmental objects, and experience only partial-body irradiation (PBI), which has different consequences, compared with total-body irradiation (TBI). In this study, we tested the hypothesis that applying machine learning to a combination of radiation-responsive biomarkers (ACTN1, DDB2, FDXR) and B and T cell counts will quantify and distinguish between PBI and TBI exposures. Adult C57BL/6 mice of both sexes were exposed to 0, 2.0-2.5 or 5.0 Gy of half-body PBI or TBI. The random forest (RF) algorithm trained on ½ of the data reconstructed the radiation dose on the remaining testing portion of the data with mean absolute error of 0.749 Gy and reconstructed the product of dose and exposure status (defined as 1.0 × Dose for TBI and 0.5 × Dose for PBI) with MAE of 0.472 Gy. Among irradiated samples, PBI could be distinguished from TBI: ROC curve AUC = 0.944 (95% CI: 0.844-1.0). Mouse sex did not significantly affect dose reconstruction. These results support the hypothesis that combinations of protein biomarkers and blood cell counts can complement existing methods for biodosimetry of PBI and TBI exposures.

Dose-Dependent Transmissibility of Chromosome Aberrations in Human Lymphocytes at First Mitosis. II. Biological Effectiveness of Heavy Charged Particles Versus Gamma Rays.

Chromosome aberrations (CAs) are large scale structural rearrangements to the genome that have been used as a proxy endpoint of mutagenic and carcinogenic potential. And yet, many types of CAs are incapable of causing either of these effects simply because they are lethal. Using 24-color multi-fluor combinatorial painting (mFISH), we examined CAs in normal human lymphocytes exposed to graded doses of 1 GeV/nucleon accelerated 56Fe ions and 662 keV 137Cs gamma rays. As expected, the high-linear energy transfer (LET) heavy ions were considerably more potent per unit dose at producing total yields of CAs compared to low-LET gamma rays. As also anticipated, the frequency distribution of aberrations per cell exposed to 56Fe ions was significantly overdispersed compared to the Poisson distribution, containing excess numbers of cells devoid of aberrations. We used the zero-inflated negative binomial (ZINB) distribution to model these data. Based on objective cytogenetic criteria that are subject to caveats we discuss, each cell was individually evaluated in terms of likely survival (i.e., its ability to transmit to daughter cell progeny). For 56Fe ion irradiations, the frequency of surviving cells harboring complex aberrations represented a significant portion of aberration-bearing cells, while for gamma irradiation no survivable cells containing complex aberrations were observed. When the dose responses for the two radiation types were compared, and the analysis was limited to surviving cells that contained aberrations, we were surprised to find the high-LET 56Fe ions only marginally more potent than the low-LET gamma rays for doses less than 1 Gy. In fact, based on dose-response modeling, they were predicted to be less effective than gamma rays at somewhat higher doses. The major implication of these findings is that measures of relative biological effectiveness that fail to account for coincident lethality will tend to overstate the impact of transmissible chromosomal damage from high-LET particle exposure.

Ocular and Facial Far-UVC Doses from Ceiling-Mounted 222 nm Far-UVC Fixtures.

Far-UVC radiation, defined in this paper as ultraviolet (UV) radiation with wavelengths from 200 to 235 nm, is a promising tool to help prevent the spread of disease. The unique advantage of far-UVC technology over traditional UV germicidal irradiation lies in the potential for direct application of far-UVC into occupied spaces since antimicrobial doses of far-UVC are significantly below the recommended daily safe exposure limits. This study used a ceiling-mounted far-UVC fixture emitting at 222 nm to directly irradiate an indoor space and then evaluated the doses received upon a manikin. Radiation-sensitive film was affixed to the head, nose, lip and eyes of the manikin, and the 8-h equivalent exposure dose was determined. Variables examined included manikin height (sitting or standing position), manikin offset from directly below the fixture, tilt of the manikin, the addition of glasses, the addition of hair and different anatomical feature sizes. Importantly, at the manikin position with the highest dose to eyes, the average eye dose was only 5.8% of the maximum directly measured dose. These results provide the first experimental analysis of possible exposure doses a human would experience from an indoor far-UVC installation.

Validation of a High-Throughput Dicentric Chromosome Assay Using Complex Radiation Exposures.

Validation of biodosimetry assays is routinely performed using primarily orthovoltage irradiators at a conventional dose rate of approximately 1 Gy/min. However, incidental/ accidental exposures caused by nuclear weapons can be more complex. The aim of this work was to simulate the DNA damage effects mimicking those caused by the detonation of a several kilotons improvised nuclear device (IND). For this, we modeled complex exposures to: 1. a mixed (photons + IND-neutrons) field and 2. different dose rates that may come from the blast, nuclear fallout, or ground deposition of radionuclides (ground shine). Additionally, we assessed whether myeloid cytokines affect the precision of radiation dose estimation by modulating the frequency of dicentric chromosomes. To mimic different exposure scenarios, several irradiation systems were used. In a mixed field study, human blood samples were exposed to a photon field enriched with neutrons (ranging from 10% to 37%) from a source that mimics Hiroshima's A-bomb's energy spectrum (0.2-9 MeV). Using statistical analysis, we assessed whether photons and neutrons act in an additive or synergistic way to form dicentrics. For the dose rates study, human blood was exposed to photons or electrons at dose rates ranging from low (where the dose was spread over 32 h) to extremely high (where the dose was delivered in a fraction of a microsecond). Potential effects of cytokine treatment on biodosimetry dose predictions were analyzed in irradiated blood subjected to Neupogen or Neulasta for 24 or 48 h at the concentration recommended to forestall manifestation of an acute radiation syndrome in bomb survivors. All measurements were performed using a robotic station, the Rapid Automated Biodosimetry Tool II, programmed to culture lymphocytes and score dicentrics in multiwell plates (the RABiT-II DCA). In agreement with classical concepts of radiation biology, the RABiT-II DCA calibration curves suggested that the frequency of dicentrics depends on the type of radiation and is modulated by changes in the dose rate. The resulting dose-response curves suggested an intermediate dicentric yields and additive effects of photons and IND-neutrons in the mixed field. At ultra-high dose rate (600 Gy/s), affected lymphocytes exhibited significantly fewer dicentrics (P < 0.004, t test). In contrast, we did not find the dose-response modification effects of radiomitigators on the yields of dicentrics (Bonferroni corrected P > 0.006, ANOVA test). This result suggests no bias in the dose predictions should be expected after emergency cytokine treatment initiated up to 48 h prior to blood collection for dicentric analysis.

A machine learning method for improving the accuracy of radiation biodosimetry by combining data from the dicentric chromosomes and micronucleus assays.

A large-scale malicious or accidental radiological event can expose vast numbers of people to ionizing radiation. The dicentric chromosome (DCA) and cytokinesis-block micronucleus (CBMN) assays are well-established biodosimetry methods for estimating individual absorbed doses after radiation exposure. Here we used machine learning (ML) to test the hypothesis that combining automated DCA and CBMN assays will improve dose reconstruction accuracy, compared with using either cytogenetic assay alone. We analyzed 1349 blood sample aliquots from 155 donors of different ages (3-69 years) and sexes (49.1% males), ex vivo irradiated with 0-8 Gy at dose rates from 0.08 Gy/day to ≥ 600 Gy/s. We compared the performances of several state-of-the-art ensemble ML methods and found that random forest generated the best results, with R2 for actual vs. reconstructed doses on a testing data subset = 0.845, and mean absolute error = 0.628 Gy. The most important predictor variables were CBMN and DCA frequencies, and age. Removing CBMN or DCA data from the model significantly increased squared errors on testing data (p-values 3.4 × 10-8 and 1.1 × 10-6, respectively). These findings demonstrate the promising potential of combining CBMN and DCA assay data to reconstruct radiation doses in realistic scenarios of heterogeneous populations exposed to a mass-casualty radiological event.