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In the event of a widespread radiological incident, thousands of people may be exposed to a wide range of ionizing radiation. In this unfortunate scenario, there will be a need to quickly screen a large number of people to assess the amount of radiation exposure and triage for medical treatment. In our earlier work, we previously identified and validated a panel of radiosensitive protein biomarkers in blood leukocytes, using the humanized-mouse and non-human primate (NHP) models. The objective of this work was to develop a high-throughput imaging flow-cytometry (IFC) based assay for the rapid measurement of protein biomarker expression in human peripheral blood samples irradiated ex vivo . In this assay design, peripheral human blood samples from healthy adult donors were exposed to 0–5 Gy X-irradiation ex vivo and cultured for up to 2 days. Samples were stained with a cocktail of surface antigens (CD66b, CD20, and CD3), fixed and permeabilized, and intracellularly stained for BAX (Bcl-2-associated X) protein, used here as a representative biomarker. Samples were interrogated by IFC, and a uniform analysis template was created to measure biomarker expression in heterogeneous and specific leukocyte subtype populations at each time point. In this human blood ex vivo model, we show that within gated populations of leukocyte subtypes, B-cells are highly radiosensitive with the smallest surviving fraction, followed by T-cells and granulocytes. Dose-dependent biomarker responses were measured in the lymphocytes, B-, and T-cell populations, but not in the granulocytes, with dose-response curves showing increasing fold changes in BAX protein expression up to Day 2 in lymphocyte populations. We present here the successful use of this ex vivo model for the development of radiation dose-response curves of a candidate protein biomarker towards future applications of dose reconstruction and biodosimetry.

In the event of a large-scale radiological or nuclear emergency, a rapid, high-throughput screening tool will be essential for efficient triage of potentially exposed individuals, optimizing scarce medical resources and ensuring timely care. The objective of this work was to characterize the effects of age and sex on two intracellular lymphocyte protein biomarkers, BAX and p53, for early radiation exposure classification in the human population, using an imaging flow cytometry-based platform for rapid biomarker quantification in whole blood samples. Peripheral blood samples from male and female donors, across three adult age groups (young adult, middle-aged, senior) and a juvenile cohort, were X-irradiated (0–5 Gy), and biomarker expression was quantified at two- and three-days post-exposure. Mixed-effects modeling and ensemble machine learning approaches were employed to evaluate the influence of Age and Sex on biomarker expression and develop predictive models for radiation exposure classification. Although some Age and Sex effects on biomarker expression levels were observed when the data was stratified by targeted conditions of biomarker, day, age group, and sex, these variables were ultimately not retained as significant predictors of exposure classification. A single ensemble model successfully classified radiation exposure across all tested cohorts, with ROC AUC values ranging from 0.85 to 0.95 at the 1 Gy threshold and 0.81 to 0.87 at the 2 Gy threshold, high sensitivity values (91–96%) and low false-negative rates across all classifications. These findings support the use of BAX and p53 biomarkers in a blood test for efficient triage in large-scale emergencies, excluding individuals below exposure thresholds from unnecessary medical care with minimal risk of denying care to those truly exposed.

Background Measurement of γ-H2AX foci levels in cells provides a sensitive and reliable method for quantitation of the radiation-induced DNA damage response. The objective of the present study was to develop a rapid, high-throughput γ-H2AX assay based on imaging flow cytometry (IFC) using the ImageStream® X Mk II (ISX) platform to evaluate DNA double strand break (DSB) repair kinetics in human peripheral blood cells after exposure to ionizing irradiation. Methods The γ-H2AX protocol was developed and optimized for small volumes (100 μL) of human blood in Matrix™ 96-tube format. Blood cell lymphocytes were identified and captured by ISX INSPIRE™ software and analyzed by Data Exploration and Analysis Software. Results Dose- and time-dependent γ-H2AX levels corresponding to radiation exposure were measured at various time points over 24 h using the IFC system. γ-H2AX fluorescence intensity at 1 h after exposure, increased linearly with increasing radiation dose ( R 2  = 0.98) for the four human donors tested, whereas the dose response for the mean number of γ-H2AX foci/cell was not as robust ( R 2  = 0.81). Radiation-induced γ-H2AX levels rapidly increased within 30 min and reached a maximum by ~ 1 h, after which time there was fast decline by 6 h, followed by a much slower rate of disappearance up to 24 h. A mathematical approach for quantifying DNA repair kinetics using the rate of γ-H2AX decay (decay constant, K dec ), and yield of residual unrepaired breaks (F res ) demonstrated differences in individual repair capacity between the healthy donors. Conclusions The results indicate that the IFC-based γ-H2AX protocol may provide a practical and high-throughput platform for measurements of individual global DNA DSB repair capacity which can facilitate precision medicine by predicting individual radiosensitivity and risk of developing adverse effects related to radiotherapy treatment.

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 R 2 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.

We investigated the cytogenetic and gene expression responses of peripheral blood cells of non-human primates (NHP, Macaca mulatta) that were whole-thorax irradiated with a single dose of 10 Gy. In this model, partial irradiation of NHPs in the thoracic region (Whole Thorax Lung Irradiation, WTLI) allows the study of late radiation-induced lung injury, while avoiding acute radiation syndromes related to hematopoietic and gastrointestinal injury. A transient drop in circulating lymphocytes and platelets was seen by 9 days, followed by elevations in respiratory rate, circulating neutrophils, lymphocytes, and monocytes at 60-100 days, corresponding to computed tomography (CT) and histologic evidence of pneumonitis, and elective euthanasia of four animals. To evaluate long-term DNA damage in NHP peripheral blood lymphocytes after 10 Gy WTLI, we used the cytokinesis-block micronucleus (CBMN) assay to measure chromosomal aberrations as post-mitotic micronuclei in blood samples collected up to 8 months after irradiation. Regression analysis showed significant induction of micronuclei in NHP blood cells that persisted with a gradual decline over the 8-month study period, suggesting long-term DNA damage in blood lymphocytes after WTLI. We also report transcriptomic changes in blood up to 30 days after WTLI. We isolated total RNA from peripheral blood at 3 days before and then at 2, 5 and 30 days after irradiation. We identified 1187 transcripts that were significantly changed across the 30-day time course. From changes in gene expression, we identified biological processes related to immune responses, which persisted across the 30-day study. Response to oxygen-containing compounds and bacteria were implicated by gene-expression changes at the earliest day 2 and latest, day 30 time-points. Gene expression changes suggest a persistent altered state of the immune system, specifically response to infection, for at least a month after WTLI.

Following a large-scale radiological event, timely collection of samples from all potentially exposed individuals may be precluded, and high-throughput bioassays capable of rapid and individualized dose assessment several days post-exposure will be essential for population triage and efficient implementation of medical treatment. The objective of this work was to validate the performance of a biomarker panel of radiosensitive intracellular leukocyte proteins (ACTN1, DDB2, and FDXR) and blood cell counts (CD19+ B-cells and CD3+ T-cells) for retrospective classification of exposure and dose estimation up to 7 days post-exposure in an in-vivo C57BL/6 mouse model. Juvenile and adult C57BL/6 mice of both sexes were total body irradiated with 0, 1, 2, 3, or 4 Gy, peripheral blood was collected 1, 4, and 7-days post-exposure, and individual blood biomarkers were quantified by imaging flow cytometry. An ensemble machine learning platform was used to identify the strongest predictor variables and combine them for biodosimetry outputs. This approach generated successful exposure classification (ROC AUC = 0.94, 95% CI: 0.90–0.97) and quantitative dose reconstruction (R 2  = 0.79, RMSE = 0.68 Gy, MAE = 0.53 Gy), supporting the potential utility of the proposed biomarker assay for determining exposure and received dose in an individual.

In the event of a widespread radiological incident, thousands of individuals will require rapid assessment of exposure using validated biodosimetry assays to inform clinical triage. In this scenario, multiple biodosimetry laboratories may be necessary for large-volume sample processing. To meet this need, we have developed a high-throughput assay for the rapid measurement of intracellular protein biomarkers in human peripheral blood samples using an Imaging Flow Cytometry (IFC) platform. The objective of this work was to harmonize and validate the reproducibility of our blood biomarker assay for radiation exposure across three IFC instruments, two located at Columbia University (CU) and the third at Health Canada. The Center for Radiological Research (CRR) at CU served as the central laboratory and reference instrument, where samples were prepared in triplicate, labeled with two radiation responsive leukocyte biomarkers (BAX and phosphor-p53 (Ser37)), and distributed for simultaneous interrogation by each IFC. Initial tests showed that significantly different baseline biomarker measurements were generated on each instrument when using the same acquisition settings, suggesting that harmonization of signal intensities is necessary. Subsequent tests harmonized biomarker measurements after irradiation by modulating laser intensity using two reference materials: unstained samples and standardized rainbow beads. Both methods generated measurements on each instrument without significant differences between the new and references instruments, allowing for the use of one master template to quantify biomarker expression across multiple instruments. Deming regression analyses of 0–5 Gy dose-response curves showed overall good correlation of BAX and p53 values across new and reference instruments. While Bland-Altman analyses indicated low to moderate instrument biases, ROC Curve analyses ultimately show successful discrimination between exposed and unexposed samples on each instrument (AUC values > 0.85).

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.

There are currently no available FDA-cleared biodosimetry tools for rapid and accurate assessment of absorbed radiation dose following a radiation/nuclear incident. Previously we developed a protein biomarker-based FAST-DOSE bioassay system for biodosimetry. The aim of this study was to integrate an ELISA platform with two high-performing FAST-DOSE biomarkers, BAX and DDB2, and to construct machine learning models that employ a multiparametric biomarker strategy for enhancing the accuracy of exposure classification and radiation dose prediction. The bioassay showed 97.92% and 96% accuracy in classifying samples in human and non-human primate (NHP) blood samples exposed ex vivo to 0–5 Gy X-rays, respectively up to 48 h after exposure, and an adequate correlation between reconstructed and actual dose in the human samples (R 2  = 0.79, RMSE = 0.80 Gy, and MAE = 0.63 Gy) and NHP (R 2  = 0.80, RMSE = 0.78 Gy, and MAE = 0.61 Gy). Biomarker measurements in vivo from four NHPs exposed to a single 2.5 Gy total body dose showed a persistent upregulation in blood samples collected on days 2 and 5 after irradiation. The data indicates that using a combined approach of targeted proteins can increase bioassay sensitivity and provide a more accurate dose prediction.