U.S. Department of Defense Multiple-Parameter Biodosimetry Network

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.

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.

Nuclear and Radiological Emergencies: Biological Effects, Countermeasures and Biodosimetry

Atomic and radiological crises can be caused by accidents, military activities, terrorist assaults involving atomic installations, the explosion of nuclear devices, or the utilization of concealed radiation exposure devices. Direct damage is caused when radiation interacts directly with cellular components. Indirect effects are mainly caused by the generation of reactive oxygen species due to radiolysis of water molecules. Acute and persistent oxidative stress associates to radiation-induced biological damages. Biological impacts of atomic radiation exposure can be deterministic (in a period range a posteriori of the event and because of destructive tissue/organ harm) or stochastic (irregular, for example cell mutation related pathologies and heritable infections). Potential countermeasures according to a specific scenario require considering basic issues, e.g., the type of radiation, people directly affected and first responders, range of doses received and whether the exposure or contamination has affected the total body or is partial. This review focuses on available medical countermeasures (radioprotectors, radiomitigators, radionuclide scavengers), biodosimetry (biological and biophysical techniques that can be quantitatively correlated with the magnitude of the radiation dose received), and strategies to implement the response to an accidental radiation exposure. In the case of large-scale atomic or radiological events, the most ideal choice for triage, dose assessment and victim classification, is the utilization of global biodosimetry networks, in combination with the automation of strategies based on modular platforms.

Automatic reagent handling and assay processing of human biospecimens inside a transportation container for a medical disaster response against radiation

Biological materials can be shipped off-site for diagnostic, therapeutic and research purposes. They usually are kept in certain environments for their final application during transportation. However, active reagent handling during transportation from a collection site to a laboratory or biorepository has not been reported yet. In this paper, we show the application of a micro-controlled centrifugal microfluidic system inside a shipping container that can add reagent to an actively cultured human blood sample during transportation to ensure a rapid biodosimetry of cytokinesis-block micronucleus (CBMN) assay. The newly demonstrated concept could have a significant impact on rapid biodosimetry triage for medical countermeasure in a radiological disaster. It also opens a new capability in accelerated sample processing during transportation for biomedical and healthcare applications.

Transportation container for pre-processing cytogenetic assays in radiation accidents

We report a shipping container that enables a disruptive logistics for cytogenetic biodosimetry for radiation countermeasures through pre-processing cell culture during transportation. The container showed precise temperature control (< 0.01 °C) with uniform sample temperature (< 0.1 °C) to meet the biodosimetry assay requirements. Using an existing insulated shipping box and long shelf life alkaline batteries makes it ideal for national stockpile. Dose curve of cytogenetic biodosimetry assay using the shipping container showed clear dose response and high linear correlation with the control dose curve using a laboratory incubator (Pearson’s correlation coefficient: 0.992). The container’s ability of pre-processing biological samples during transportation could have a significant impact on radiation countermeasure, as well as potential impacts in other applications such as biobanking, novel molecular or cell-based assays or therapies.

Celebrating 60 Years of Accomplishments of the Armed Forces Radiobiology Research Institute1

Chartered by the U.S. Congress in 1961, the Armed Forces Radiobiology Research Institute (AFRRI) is a Joint Department of Defense (DoD) entity with the mission of carrying out the Medical Radiological Defense Research Program in support of our military forces around the globe. In the last 60 years, the investigators at AFRRI have conducted exploratory and developmental research with broad application to the field of radiation sciences. As the only DoD facility dedicated to radiation research, AFRRI's Medical Radiobiology Advisory Team provides deployable medical and radiobiological subject matter expertise, advising commanders in the response to a U.S. nuclear weapon incident and other nuclear or radiological material incidents. AFRRI received the DoD Joint Meritorious Unit Award on February 17, 2004, for its exceptionally meritorious achievements from September 11, 2001 to June 20, 2003, in response to acts of terrorism and nuclear/radiological threats at home and abroad. In August 2009, the American Nuclear Society designated the institute a nuclear historic landmark as the U.S.'s primary source of medical nuclear and radiological research, preparedness and training. Since then, research has continued, and core areas of study include prevention, assessment and treatment of radiological injuries that may occur from exposure to a wide range of doses (low to high). AFRRI collaborates with other government entities, academic institutions, civilian laboratories and other countries to research the biological effects of ionizing radiation. Notable early research contributions were the establishment of dose limits for major acute radiation syndromes in primates, applicable to human exposures, followed by the subsequent evolution of radiobiology concepts, particularly the importance of immune collapse and combined injury. In this century, the program has been essential in the development and validation of prophylactic and therapeutic drugs, such as Amifostine, Neupogen®, Neulasta®, Nplate® and Leukine®, all of which are used to prevent and treat radiation injuries. Moreover, AFRRI has helped develop rapid, high-precision, biodosimetry tools ranging from novel assays to software decision support. New drug candidates and biological dose assessment technologies are currently being developed. Such efforts are supported by unique and unmatched radiation sources and generators that allow for comprehensive analyses across the various types and qualities of radiation. These include but are not limited to both 60Co facilities, a TRIGA® reactor providing variable mixed neutron and γ-ray fields, a clinical linear accelerator, and a small animal radiation research platform with low-energy photons. There are five major research areas at AFRRI that encompass the prevention, assessment and treatment of injuries resulting from the effects of ionizing radiation: 1. biodosimetry; 2. low-level and low-dose-rate radiation; 3. internal contamination and metal toxicity; 4. radiation combined injury; and 5. radiation medical countermeasures. These research areas are bolstered by an educational component to broadcast and increase awareness of the medical effects of ionizing radiation, in the mass-casualty scenario after a nuclear detonation or radiological accidents. This work provides a description of the military medical operations as well as the radiation facilities and capabilities present at AFRRI, followed by a review and discussion of each of the research areas.

Machine learning methodology for high throughput personalized neutron dose reconstruction in mixed neutron + photon exposures

We implemented machine learning in the radiation biodosimetry field to quantitatively reconstruct neutron doses in mixed neutron + photon exposures, which are expected in improvised nuclear device detonations. Such individualized reconstructions are crucial for triage and treatment because neutrons are more biologically damaging than photons. We used a high-throughput micronucleus assay with automated scanning/imaging on lymphocytes from human blood ex-vivo irradiated with 44 different combinations of 0-4 Gy neutrons and 0-15 Gy photons (542 blood samples), which include reanalysis of past experiments. We developed several metrics that describe micronuclei/cell probability distributions in binucleated cells, and used them as predictors in random forest (RF) and XGboost machine learning analyses to reconstruct the neutron dose in each sample. The probability of "overfitting" was minimized by training both algorithms with repeated cross-validation on a randomly-selected subset of the data, and measuring performance on the rest. RF achieved the best performance. Mean R² for actual vs. reconstructed neutron doses over 300 random training/testing splits was 0.869 (range 0.761 to 0.919) and root mean squared error was 0.239 (0.195 to 0.351) Gy. These results demonstrate the promising potential of machine learning to reconstruct the neutron dose component in clinically-relevant complex radiation exposure scenarios.

Dose and Dose-Rate Effects in a Mouse Model of Internal Exposure from 137Cs. Part 2: Integration of Gamma-H2AX and Gene Expression Biomarkers for Retrospective Radiation Biodosimetry

Inhalation and ingestion of 137Cs and other long-lived radionuclides can occur after large-scale accidental or malicious radioactive contamination incidents, resulting in a complex temporal pattern of radiation dose/dose rate, influenced by radionuclide pharmacokinetics and chemical properties. High-throughput radiation biodosimetry techniques for such internal exposure are needed to assess potential risks of short-term toxicity and delayed effects (e.g., carcinogenesis) for exposed individuals. Previously, we used γ-H2AX to reconstruct injected 137Cs activity in experimentally-exposed mice, and converted activity values into radiation doses based on time since injection and 137Cs-elimination kinetics. In the current study, we sought to assess the feasibility and possible advantages of combining γ-H2AX with transcriptomics to improve 137Cs activity reconstructions. We selected five genes (Atf5, Hist2h2aa2, Olfr358, Psrc1, Hist2h2ac) with strong statistically-significant Spearman's correlations with injected activity and stable expression over time after 137Cs injection. The geometric mean of log-transformed signals of these five genes, combined with γ-H2AX fluorescence, were used as predictors in a nonlinear model for reconstructing injected 137Cs activity. The coefficient of determination (R2) comparing actual and reconstructed activities was 0.91 and root mean squared error (RMSE) was 0.95 MBq. These metrics remained stable when the model was fitted to a randomly-selected half of the data and tested on the other half, repeated 100 times. Model performance was significantly better when compared to our previous analysis using γ-H2AX alone, and when compared to an analysis where genes are used without γ-H2AX, suggesting that integrating γ-H2AX with gene expression provides an important advantage. Our findings show a proof of principle that integration of radiation-responsive biomarkers from different fields is promising for radiation biodosimetry of internal emitters.

Radioprotection and Radiomitigation: From the Bench to Clinical Practice

The development of protective agents against harmful radiations has been a subject of investigation for decades. However, effective (ideal) radioprotectors and radiomitigators remain an unsolved problem. Because ionizing radiation-induced cellular damage is primarily attributed to free radicals, radical scavengers are promising as potential radioprotectors. Early development of such agents focused on thiol synthetic compounds, e.g., amifostine (2-(3-aminopropylamino) ethylsulfanylphosphonic acid), approved as a radioprotector by the Food and Drug Administration (FDA, USA) but for limited clinical indications and not for nonclinical uses. To date, no new chemical entity has been approved by the FDA as a radiation countermeasure for acute radiation syndrome (ARS). All FDA-approved radiation countermeasures (filgrastim, a recombinant DNA form of the naturally occurring granulocyte colony-stimulating factor, G-CSF; pegfilgrastim, a PEGylated form of the recombinant human G-CSF; sargramostim, a recombinant granulocyte macrophage colony-stimulating factor, GM-CSF) are classified as radiomitigators. No radioprotector that can be administered prior to exposure has been approved for ARS. This differentiates radioprotectors (reduce direct damage caused by radiation) and radiomitigators (minimize toxicity even after radiation has been delivered). Molecules under development with the aim of reaching clinical practice and other nonclinical applications are discussed. Assays to evaluate the biological effects of ionizing radiations are also analyzed.

A High Throughput Approach to Reconstruct Partial-Body and Neutron Radiation Exposures on an Individual Basis

Biodosimetry-based individualized reconstruction of complex irradiation scenarios (partial-body shielding and/or neutron + photon mixtures) can improve treatment decisions after mass-casualty radiation-related incidents. We used a high-throughput micronucleus assay with automated scanning and imaging software on ex-vivo irradiated human lymphocytes to: a) reconstruct partial-body and/or neutron exposure, and b) estimate separately the photon and neutron doses in a mixed exposure. The mechanistic background is that, compared with total-body photon irradiations, neutrons produce more heavily-damaged lymphocytes with multiple micronuclei/binucleated cell, whereas partial-body exposures produce fewer such lymphocytes. To utilize these differences for biodosimetry, we developed metrics that describe micronuclei distributions in binucleated cells and serve as predictors in machine learning or parametric analyses of the following scenarios: (A) Homogeneous gamma-irradiation, mimicking total-body exposures, vs. mixtures of irradiated blood with unirradiated blood, mimicking partial-body exposures. (B) X rays vs. various neutron + photon mixtures. The results showed high accuracies of scenario and dose reconstructions. Specifically, receiver operating characteristic curve areas (AUC) for sample classification by exposure type reached 0.931 and 0.916 in scenarios A and B, respectively. R² for actual vs. reconstructed doses in these scenarios reached 0.87 and 0.77, respectively. These encouraging findings demonstrate a proof-of-principle for the proposed approach of high-throughput reconstruction of clinically-relevant complex radiation exposure scenarios.

Transcriptomic responses in mouse blood during the first week after in vivo gamma irradiation

Due to limitations of available human models for development of gene expression based radiation biodosimetry, many such studies have made use of mouse models. To provide a broad view of the gene expression response to irradiation in the mouse, we have exposed male C57BL/6 mice to 0, 1.5, 3, 6 or 10 Gy of gamma rays, sacrificing groups of the mice at 1, 2, 3, 5, or 7 days after exposure. We then profiled global gene expression in blood from individual mice using Agilent microarrays. In general, we found increasing numbers of genes differentially expressed with increasing dose, with more prolonged responses after the higher doses. Gene ontology analysis showed a similar pattern, with more biological processes enriched among the genes responding to higher doses, and at later times after exposure. Clustering the timecourse expression data using maSigPro identified four broad patterns of response, representing different gene ontology functions. The largest of these clusters included genes with initially decreased expression followed by increased expression at later times, a pattern of expression previously reported for several genes following neutron exposure. Another gene cluster showing consistent down regulation suggests genes useful for biodosimetry throughout the first week after exposure can be identified.

Biodosimetry: A Future Tool for Medical Management of Radiological Emergencies

With the threat of future radiological or nuclear events, there is a need to model and develop new medical countermeasures for managing large-scale population exposures to radiation. The field of radiation biodosimetry has advanced far beyond its original objectives to identify new methodologies to quantitate unknown levels of radiation exposure that may be applied in a mass screening setting. New research in the areas of genomics, proteomics, metabolomics, transcriptomics, and electron paramagnetic resonance (EPR) applications have identified novel biological indicators of radiation injury from a diverse array of biological sample materials, and studies continue to develop more advanced models of radiation exposure and injury. In this article, we identify the urgent need for new biodosimetry assessment technologies, describe how biodosimetry diagnostics work in the context of a broad range of radiation exposure types and scenarios, review the current state of the science, and assess how well integrated biodosimetry resources are in the national radiological emergency response framework.