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.

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.

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.

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.

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.

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.

Effects of Desiccation and Freezing on Microbial Ionizing Radiation Survivability: Considerations for Mars Sample Return.

Increasingly, national space agencies are expanding their goals to include Mars exploration with sample return. To better protect Earth and its biosphere from potential extraterrestrial sources of contamination, as set forth in the Outer Space Treaty of 1967, international efforts to develop planetary protection measures strive to understand the danger of cross-contamination processes in Mars sample return missions. We aim to better understand the impact of the martian surface on microbial dormancy and survivability. Radiation resistance of microbes is a key parameter in considering survivability of microbes over geologic times on the frigid, arid surface of Mars that is bombarded by solar and galactic cosmic radiation. We tested the influence of desiccation and freezing on the ionizing radiation survival of six model microorganisms: vegetative cells of two bacteria (Deinococcus radiodurans, Escherichia coli) and a strain of budding yeast (Saccharomyces cerevisiae); and vegetative cells and endospores of three Bacillus bacteria (B. subtilis, B. megaterium, B. thuringiensis). Desiccation and freezing greatly increased radiation survival of vegetative polyploid microorganisms when applied separately, and when combined, desiccation and freezing increased radiation survival even more so. Thus, the radiation survival threshold of polyploid D. radiodurans cells can be extended from the already high value of 25 kGy in liquid culture to an astonishing 140 kGy when the cells are both desiccated and frozen. However, such synergistic radioprotective effects of desiccation and freezing were not observed in monogenomic or digenomic Bacillus cells and endospores, which are generally sterilized by 12 kGy. This difference is associated with a critical requirement for survivability under radiation, that is, repair of genome damage caused by radiation. Deinococcus radiodurans and S. cerevisiae accumulate similarly high levels of the Mn antioxidants that are required for extreme radiation resistance, as do endospores, though they greatly exceed spores in radioresistance because they contain multiple identical genome copies, which in D. radiodurans are joined by persistent Holliday junctions. We estimate ionizing radiation survival limits of polyploid DNA-based life-forms to be hundreds of millions of years of background radiation while buried in the martian subsurface. Our findings imply that forward contamination of Mars will essentially be permanent, and backward contamination is a possibility if life ever existed on Mars.

Cross-platform validation of a mouse blood gene signature for quantitative reconstruction of radiation dose.

In the search for biological markers after a large-scale exposure of the human population to radiation, gene expression is a sensitive endpoint easily translatable to in-field high throughput applications. Primarily, the ex-vivo irradiated healthy human blood model has been used to generate available gene expression datasets. This model has limitations i.e., lack of signaling from other irradiated tissues and deterioration of blood cells cultures over time. In vivo models are needed; therefore, we present our novel approach to define a gene signature in mouse blood cells that quantitatively correlates with radiation dose (at 1 Gy/min). Starting with available microarray datasets, we selected 30 radiation-responsive genes and performed cross-validation/training-testing data splits to downselect 16 radiation-responsive genes. We then tested these genes in an independent cohort of irradiated adult C57BL/6 mice (50:50 both sexes) and measured mRNA by quantitative RT-PCR in whole blood at 24 h. Dose reconstruction using net signal (difference between geometric means of top 3 positively correlated and top 4 negatively correlated genes with dose), was highly improved over the microarrays, with a root mean square error of ± 1.1 Gy in male and female mice combined. There were no significant sex-specific differences in mRNA or cell counts after irradiation.

Inactivation Rates for Airborne Human Coronavirus by Low Doses of 222 nm Far-UVC Radiation.

Recent research using UV radiation with wavelengths in the 200-235 nm range, often referred to as far-UVC, suggests that the minimal health hazard associated with these wavelengths will allow direct use of far-UVC radiation within occupied indoor spaces to provide continuous disinfection. Earlier experimental studies estimated the susceptibility of airborne human coronavirus OC43 exposed to 222-nm radiation based on fitting an exponential dose-response curve to the data. The current study extends the results to a wider range of doses of 222 nm far-UVC radiation and uses a computational model coupling radiation transport and computational fluid dynamics to improve dosimetry estimates. The new results suggest that the inactivation of human coronavirus OC43 within our exposure system is better described using a bi-exponential dose-response relation, and the estimated susceptibility constant at low doses-the relevant parameter for realistic low dose rate exposures-was 12.4 ± 0.4 cm2/mJ, which described the behavior of 99.7% ± 0.05% of the virus population. This new estimate is more than double the earlier susceptibility constant estimates that were based on a single-exponential dose response. These new results offer further evidence as to the efficacy of far-UVC to inactivate airborne pathogens.

A practical approach for continuous in situ characterization of radiation quality factors in space.

The space radiation environment is qualitatively different from Earth, and its radiation hazard is generally quantified relative to photons using quality factors that allow assessment of biologically-effective dose. Two approaches exist for estimating radiation quality factors in complex low/intermediate-dose radiation environments: one is a fluence-based risk cross-section approach, which requires very detailed in silico characterization of the radiation field and biological cross sections, and thus cannot realistically be used for in situ monitoring. By contrast, the microdosimetric approach, using measured (or calculated) distributions of microdosimetric energy deposition together with empirical biological weighting functions, is conceptually and practically simpler. To demonstrate feasibility of the microdosimetric approach, we estimated a biological weighting function for one specific endpoint, heavy-ion-induced tumorigenesis in APC1638N/+ mice, which was unfolded from experimental results after a variety of heavy ion exposures together with corresponding calculated heavy ion microdosimetric energy deposition spectra. Separate biological weighting functions were unfolded for targeted and non-targeted effects, and these differed substantially. We folded these biological weighting functions with microdosimetric energy deposition spectra for different space radiation environments, and conclude that the microdosimetric approach is indeed practical and, in conjunction with in-situ measurements of microdosimetric spectra, can allow continuous readout of biologically-effective dose during space flight.

Quantitative modeling of carcinogenesis induced by single beams or mixtures of space radiations using targeted and non-targeted effects.

Ionizing radiations encountered by astronauts on deep space missions produce biological damage by two main mechanisms: (1) Targeted effects (TE) due to direct traversals of cells by ionizing tracks. (2) Non-targeted effects (NTE) caused by release of signals from directly hit cells. The combination of these mechanisms generates non-linear dose response shapes, which need to be modeled quantitatively to predict health risks from space exploration. Here we used a TE + NTE model to analyze data on APC(1638N/+) mouse tumorigenesis induced by space-relevant doses of protons, 4He, 12C, 16O, 28Si or 56Fe ions, or γ rays. A customized weighted Negative Binomial distribution was used to describe the radiation type- and dose-dependent data variability. This approach allowed detailed quantification of dose-response shapes, NTE- and TE-related model parameters, and radiation quality metrics (relative biological effectiveness, RBE, and radiation effects ratio, RER, relative to γ rays) for each radiation type. Based on the modeled responses for each radiation type, we predicted the tumor yield for a Mars-mission-relevant mixture of these radiations, using the recently-developed incremental effect additivity (IEA) synergy theory. The proposed modeling approach can enhance current knowledge about quantification of space radiation quality effects, dose response shapes, and ultimately the health risks for astronauts.

Effects of Low Dose Space Radiation Exposures on the Splenic Metabolome.

Future space missions will include a return to the Moon and long duration deep space roundtrip missions to Mars. Leaving the protection that Low Earth Orbit provides will unavoidably expose astronauts to higher cumulative doses of space radiation, in addition to other stressors, e.g., microgravity. Immune regulation is known to be impacted by both radiation and spaceflight and it remains to be seen whether prolonged effects that will be encountered in deep space can have an adverse impact on health. In this study, we investigated the effects in the overall metabolism of three different low dose radiation exposures (γ-rays, 16O, and 56Fe) in spleens from male C57BL/6 mice at 1, 2, and 4 months after exposure. Forty metabolites were identified with significant enrichment in purine metabolism, tricarboxylic acid cycle, fatty acids, acylcarnitines, and amino acids. Early perturbations were more prominent in the γ irradiated samples, while later responses shifted towards more prominent responses in groups with high energy particle irradiations. Regression analysis showed a positive correlation of the abundance of identified fatty acids with time and a negative association with γ-rays, while the degradation pathway of purines was positively associated with time. Taken together, there is a strong suggestion of mitochondrial implication and the possibility of long-term effects on DNA repair and nucleotide pools following radiation exposure.

Lung Cancer and Heart Disease Risks Associated With Low-Dose Pulmonary Radiotherapy to COVID-19 Patients With Different Background Risks.

PURPOSE: The respiratory disease COVID-19 reached global pandemic status in 2020. Excessive inflammation is believed to result in the most severe symptoms and death from this disease. Because treatment options for patients with severe COVID-19 related pulmonary symptoms remain limited, whole-lung low-dose radiation therapy is being evaluated as an anti-inflammatory modality. However, there is concern about the long-term risks associated with low-dose pulmonary irradiation. To help quantify the benefit-risk balance of low-dose radiation therapy for COVID-19, we estimated radiation-induced lifetime risks of both lung cancer and heart disease (major coronary events) for patients of different sexes, treated at ages 50 to 85, with and without other relevant risk factors (cigarette smoking and baseline heart disease risk). METHODS AND MATERIALS: These estimates were generated by combining state-of-the-art radiation risk models for lung cancer and for heart disease together with background lung cancer and heart disease risks and age/sex-dependent survival probabilities for the U.S. RESULTS: Estimated absolute radiation-induced risks were generally higher for lung cancer compared with major coronary events. The highest estimated lifetime radiation-induced lung cancer risks were approximately 6% for female smokers treated between ages 50 and 60. The highest estimated radiation-induced heart disease risks were approximately 3% for males or females with high heart disease risk factors and treated between ages 50 and 60. CONCLUSIONS: The estimated summed lifetime risk of lung cancer and major coronary events reached up to 9% in patients with high baseline risk factors. Predicted lung cancer and heart disease risks were lowest in older nonsmoking patients and patients with few cardiac risk factors. These long-term risk estimates, along with consideration of possible acute reactions, should be useful in assessing the benefit-risk balance for low-dose radiation therapy to treat severe COVID-19 pulmonary symptoms, and suggest that background risk factors, particularly smoking, should be taken into account in such assessments.