Comparison of Isolated Lymphocyte and Whole Blood-Based CBMN Assays for Radiation Triage.

Following a mass-casualty nuclear/radiological event, there will be an important need for rapid and accurate estimation of absorbed dose for biological triage. The cytokinesis-block micronucleus (CBMN) assay is an established and validated cytogenetic biomarker used to assess DNA damage in irradiated peripheral blood lymphocytes. Here, we describe an intercomparison experiment between two biodosimetry laboratories, located at Columbia University (CU) and Health Canada (HC) that performed different variants of the human blood CBMN assay to reconstruct dose in human blood, with CU performing the assay on isolated lymphocytes and using semi-automated scoring whereas HC used the more conventional whole blood assay. Although the micronucleus yields varied significantly between the two assays, the predicted doses closely matched up to 4 Gy - the range from which the HC calibration curve was previously established. These results highlight the importance of a robust calibration curve(s) across a wide age range of donors that match the exposure scenario as closely as possible and that will account for differences in methodology between laboratories. We have seen that at low doses, variability in the results may be attributed to variation in the processing while at higher doses the variation is dominated by inter-individual variation in cell proliferation. This interlaboratory collaboration further highlights the usefulness of the CBMN endpoint to accurately reconstruct absorbed dose in human blood after ionizing radiation exposure.

Application of the Cytokinesis-Block Micronucleus Assay for High-Dose Exposures Using Imaging Flow Cytometry.

The cytokinesis-block micronucleus assay is a well-established method to assess radiation-induced genetic damage in human cells. This assay has been adapted to imaging flow cytometry (IFC), allowing automated analysis of many cells, and eliminating the need to create microscope slides. Furthermore, to improve the efficiency of assay performance, a small-volume method previously developed was employed. Irradiated human blood samples were cultured, stained, and analyzed by IFC to produce images of the cells. Samples were run using both manual and 96-well plate automated acquisition. Multiple parameter-based image features were collected for each sample, and the results were compared to confirm that these acquisition methods are functionally identical. This paper details the multi-parametric analysis developed and the resulting calibration curves up to 10 Gy. The calibration curves were created using a quadratic random coefficient model with Poisson errors, as well as a logistic discriminant function. The curves were then validated with blinded, irradiated samples, using relative bias and relative mean square error. Overall, the accuracy of the dose estimates was adequate for triage dosimetry (within 1 Gy of the true dose) over 90% of the time for lower doses and about half the time for higher doses, with the lowest success rate between 5 and 6 Gy where the calibration curve reached its peak and there was the smallest change in MN/BNC with dose. This work describes the application of a novel multi-parametric analysis that fits the calibration curves and allows dose estimates up to 10 Gy, which were previously limited to 4 Gy. Furthermore, it demonstrates that the results from samples acquired manually and with the autosampler are functionally similar.

Improving radiation dosimetry with an automated micronucleus scoring system: correction of automated scoring errors.

Radiation dose estimations performed by automated counting of micronuclei (MN) have been studied for their utility for triage following large-scale radiological incidents; although speed is essential, it also is essential to estimate radiation doses as accurately as possible for long-term epidemiological follow-up. Our goal in this study was to evaluate and improve the performance of automated MN counting for biodosimetry using the cytokinesis-block micronucleus (CBMN) assay. We measured false detection rates and used them to improve the accuracy of dosimetry. The average false-positive rate for binucleated cells was 1.14%; average false-positive and -negative MN rates were 1.03% and 3.50%, respectively. Detection errors seemed to be correlated with radiation dose. Correction of errors by visual inspection of images used for automated counting, called the semi-automated and manual scoring method, increased accuracy of dose estimation. Our findings suggest that dose assessment of the automated MN scoring system can be improved by subsequent error correction, which could be useful for performing biodosimetry on large numbers of people rapidly, accurately, and efficiently.

Foundations of identifying individual chromosomes by imaging flow cytometry with applications in radiation biodosimetry.

Biodosimetry is an important tool for triage in the case of large-scale radiological or nuclear emergencies, but traditional microscope-based methods can be tedious and prone to scorer fatigue. While the dicentric chromosome assay (DCA) has been adapted for use in triage situations, it is still time-consuming to create and score slides. Recent adaptations of traditional biodosimetry assays to imaging flow cytometry (IFC) methods have dramatically increased throughput. Additionally, recent improvements in image analysis algorithms in the IFC software have resulted in improved specificity for spot counting of small events. In the IFC method for the dicentric chromosome analysis (FDCA), lymphocytes isolated from whole blood samples are cultured with PHA and Colcemid. After incubation, lymphocytes are treated with a hypotonic solution and chromosomes are isolated in suspension, labelled with a centromere marker and stained for DNA content with DRAQ5. Stained individual chromosomes are analyzed on the ImageStream®X (EMD-Millipore, Billerica, MA) and mono- and dicentric chromosome populations are identified and enumerated using advanced image processing techniques. Both the preparation of the isolated chromosome suspensions as well as the image analysis methods were fine-tuned in order to optimize the FDCA. In this paper we describe the method to identify and score centromeres in individual chromosomes by IFC and show that the FDCA method may further improve throughput for triage biodosimetry in the case of large-scale radiological or nuclear emergencies.

Interlaboratory comparison of high-throughput protein biomarker assay quantifications for radiation exposure classification.

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).

AOP report: Development of an adverse outcome pathway for deposition of energy leading to cataracts.

Cataracts are one of the leading causes of blindness, with an estimated 95 million people affected worldwide. A hallmark of cataract development is lens opacification, typically associated not only with aging but also radiation exposure as encountered by interventional radiologists and astronauts during the long-term space mission. To better understand radiation-induced cataracts, the adverse outcome pathway (AOP) framework was used to structure and evaluate knowledge across biological levels of organization (e.g., macromolecular, cell, tissue, organ, organism and population). AOPs identify a sequence of key events (KEs) causally connected by key event relationships (KERs) beginning with a molecular initiating event to an adverse outcome (AO) of relevance to regulatory decision-making. To construct the cataract AO and retrieve evidence to support it, a scoping review methodology was used to filter, screen, and review studies based on the modified Bradford Hill criteria. Eight KEs were identified that were moderately supported by empirical evidence (e.g., dose-, time-, incidence-concordance) across the adjacent (directly linked) relationships using well-established endpoints. Over half of the evidence to justify the KER linkages was derived from the evidence stream of biological plausibility. Early KEs of oxidative stress and protein modifications had strong linkages to downstream KEs and could be the focus of countermeasure development. Several identified knowledge gaps and inconsistencies related to the quantitative understanding of KERs which could be the basis of future research, most notably directed to experiments in the range of low or moderate doses and dose-rates, relevant to radiation workers and other occupational exposures.

The Imaging Flow Cytometry-Based Cytokinesis-Block MicroNucleus (CBMN) Assay.

The dose of ionizing radiation received by an individual can be determined using biodosimetry methods which measure biomarkers of exposure in tissue samples from that individual. These markers can be expressed in many ways, including DNA damage and repair processes. Following a mass casualty event involving radiological or nuclear material, it is important to rapidly provide this information to medical responders to assist in the medical management of potentially exposed casualties. Traditional methods of biodosimetry rely on microscope analysis, making them time-consuming and labor-intensive. To increase sample throughput following a large-scale radiological mass casualty event, several biodosimetry assays have been adapted for analysis by imaging flow cytometry. This chapter briefly reviews these methods with a focus on the most current methodology to identify and quantify micronuclei in binucleated cells within the cytokinesis-block micronucleus assay using an imaging flow cytometer.

Development of high-throughput systems for biodosimetry.

Biomarkers for ionising radiation exposure have great utility in scenarios where there has been a potential exposure and physical dosimetry is missing or in dispute, such as for occupational and accidental exposures. Biomarkers that respond as a function of dose are particularly useful as biodosemeters to determine the dose of radiation to which an individual has been exposed. These dose measurements can also be used in medical scenarios to track doses from medical exposures and even have the potential to identify an individual's response to radiation exposure that could help tailor treatments. The measurement of biomarkers of exposure in medicine and for accidents, where a larger number of samples would be required, is limited by the throughput of analysis (i.e. the number of samples that could be processed and analysed), particularly for microscope-based methods, which tend to be labour-intensive. Rapid analysis in an emergency scenario, such as a large-scale accident, would provide dose estimates to medical practitioners, allowing timely administration of the appropriate medical countermeasures to help mitigate the effects of radiation exposure. In order to improve sample throughput for biomarker analysis, much effort has been devoted to automating the process from sample preparation through automated image analysis. This paper will focus mainly on biological endpoints traditionally analysed by microscopy, specifically dicentric chromosomes, micronuclei and gamma-H2AX. These endpoints provide examples where sample throughput has been improved through automated image acquisition, analysis of images acquired by microscopy, as well as methods that have been developed for analysis using imaging flow cytometry.

Monte Carlo modelling of experimental setup used for biodosimetry intercomparison.

When using biodosimetry techniques to assess absorbed dose from an ionising radiation exposure, a calibration curve is required. At Health Canada (HC), these curves are generated for a variety of radiation qualities and assays to translate biological damage into absorbed dose. They are produced by irradiating biological samples in custom-designed water-equivalent phantoms inside a cabinet X-ray machine. In the HC lab, two different phantoms can be used for irradiation that differs in material composition and internal geometry. To ensure consistency, the impact of using the phantoms interchangeably was investigated. This was done through lab measurements and the development of a Monte Carlo (MC) model. Differences up to 6.7% were found between the two experimental setups, indicating the need for careful consideration if using these setups interchangeably in the laboratory. Once validated, the MC model can be used to investigate different aspects of the experimental setup without the need for laboratory measurements.

Considerations for application of benchmark dose modeling in radiation research: workshop highlights.

BACKGROUND: Exposure to different forms of ionizing radiation occurs in diverse occupational, medical, and environmental settings. Improving the accuracy of the estimated health risks associated with exposure is therefore, essential for protecting the public, particularly as it relates to chronic low dose exposures. A key aspect to understanding health risks is precise and accurate modeling of the dose-response relationship. Toward this vision, benchmark dose (BMD) modeling may be a suitable approach for consideration in the radiation field. BMD modeling is already extensively used for chemical hazard assessments and is considered statistically preferable to identifying low and no observed adverse effects levels. BMD modeling involves fitting mathematical models to dose-response data for a relevant biological endpoint and identifying a point of departure (the BMD, or its lower bound). Recent examples in chemical toxicology show that when applied to molecular endpoints (e.g. genotoxic and transcriptional endpoints), BMDs correlate to points of departure for more apical endpoints such as phenotypic changes (e.g. adverse effects) of interest to regulatory decisions. This use of BMD modeling may be valuable to explore in the radiation field, specifically in combination with adverse outcome pathways, and may facilitate better interpretation of relevant in vivo and in vitro dose-response data. To advance this application, a workshop was organized on June 3rd, 2022, in Ottawa, Ontario that brought together BMD experts in chemical toxicology and the radiation scientific community of researchers, regulators, and policy-makers. The workshop's objective was to introduce radiation scientists to BMD modeling and its practical application using case examples from the chemical toxicity field and demonstrate the BMDExpress software using a radiation dataset. Discussions focused on the BMD approach, the importance of experimental design, regulatory applications, its use in supporting the development of adverse outcome pathways, and specific radiation-relevant examples. CONCLUSIONS: Although further deliberations are needed to advance the use of BMD modeling in the radiation field, these initial discussions and partnerships highlight some key steps to guide future undertakings related to new experimental work.

A comparitive assessement of cytokine expression in human-derived cell lines exposed to alpha particles and X-rays.

Alpha- (α-) particle radiation exposure has been linked to the development of lung cancer and has been identified as a radiation type likely to be employed in radiological dispersal devices. Currently, there exists a knowledge gap concerning cytokine modulations associated with exposure to α-particles. Bio-plex technology was employed to investigate changes in proinflammatory cytokines in two human-derived cell lines. Cells were irradiated at a dose of 1.5 Gy to either α-particles or X-rays at equivalent dose rates. The two cell lines exhibited a unique pattern of cytokine expression and the response varied with radiation type. Of the 27 cytokines assessed, only vascular endothelin growth factor (VEGF) was observed to be modulated in both cell lines solely after α-particle exposure, and the expression of VEGF was shown to be dose responsive. These results suggest that certain proinflammatory cytokines may be involved in the biological effects related to α- particle exposure and the responses are cell type and radiation type specific.

A high-level overview of the OECD AOP Development Programme.

BACKGROUND: The Organisation for Economic Co-operation and Development (OECD), through its Chemical Safety Programme, is delegated to ensure the safety of humans and wildlife from harmful toxicants. To support these needs, initiatives to increase the efficiency of hazard identification and risk management are under way. Amongst these, the adverse outcome pathway (AOP) approach integrates information on biological knowledge and test methodologies (both established and new) to support regulatory decision making. AOPs collate biological knowledge from different sources, assess lines of evidence through considerations of causality, and undergo rigorous peer-review before being subsequently endorsed by the OECD. It is envisioned that the OECD AOP Development Programme will transform the toxicity testing paradigm by leveraging the strengths of mechanistic and modeling based approaches and enhance the utility of high throughput screening assays. Since its launch, in 2012, the AOP Development Programme has matured with a greater number of AOPs endorsed, and the attraction of new scientific disciplines (e.g. the radiation field). Recently, a radiation and chemical (Rad/Chem) AOP Joint Topical Group has been formed by the OECD Nuclear Energy Agency High-level Group on Low-dose Research (HLG-LDR) under the auspices of the Committee on Radiological Protection and Public Health (CRPPH). The topical group will work to evolve the development and use of the AOP framework in radiation research and regulation. As part of these efforts, the group will bring awareness and understanding on the program, as it has matured from the chemical perspective. In this context, this paper provides the radiation community with a high-level overview of the OECD AOP Development Programme, including examples of application using knowledge gleaned from the field of chemical toxicology, and their work toward regulatory implementation. CONCLUSION: Although the drivers for developing AOPs in chemical sector differ from that of the radiation field, the principles and transparency of the approach can benefit both scientific disciplines. By providing perspectives and an understanding of the evolution of the OECD AOP Development Programme including case examples and work toward quantitative AOP development, it may motivate the expansion and implementation of AOPs in the radiation field.

Application of a semi-automated dicentric scoring system in triage and monitoring occupational radiation exposure.

The dicentric chromosome assay (DCA) is considered the gold standard for radiation biodosimetry, but it is limited by its long dicentric scoring time and need for skilled scorers. The automation of scoring dicentrics has been considered a strategy to overcome the constraints of DCA. However, the studies on automated scoring methods are limited compared to those on conventional manual DCA. Our study aims to assess the performance of a semi-automated scoring method for DCA using ex vivo and in vivo irradiated samples. Dose estimations of 39 blind samples irradiated ex vivo and 35 industrial radiographers occupationally exposed in vivo were estimated using the manual and semi-automated scoring methods and subsequently compared. The semi-automated scoring method, which removed the false positives of automated scoring using the dicentric chromosome (DC) scoring algorithm, had an accuracy of 94.9% in the ex vivo irradiated samples. It also had more than 90% accuracy, sensitivity, and specificity to distinguish binary dose categories reflecting clinical, diagnostic, and epidemiological significance. These data were comparable to those of manual DCA. Moreover, Cohen's kappa statistic and McNemar's test showed a substantial agreement between the two methods for categorizing in vivo samples into never and ever radiation exposure. There was also a significant correlation between the two methods. Despite of comparable results with two methods, lower sensitivity of semi-automated scoring method could be limited to assess various radiation exposures. Taken together, our findings show the semi-automated scoring method can provide accurate dose estimation rapidly, and can be useful as an alternative to manual DCA for biodosimetry in large-scale accidents or cases to monitor radiation exposure of radiation workers.

Benchmark dose modeling of transcriptional data: a systematic approach to identify best practices for study designs used in radiation research.

PURPOSE: Benchmark dose (BMD) modeling is a method commonly used in chemical toxicology to identify the point of departure (POD) from a dose-response curve linked to a health-related outcome. Recently, its application in the analysis of transcriptional data for quantitative adverse outcome pathway (AOP) development is being explored. As AOPs are informed by diverse data types, it is important to understand the impact of study parameters such as dose selection, the number of replicates and dose range on BMD outputs for radiation-induced genes and pathways. MATERIALS AND METHODS: Data were selected from the Gene Expression Omnibus (GSE52403) that featured gene expression profiles of peripheral blood samples from C57BL/6 mice 6 hours post-exposure to 137Cs gamma-radiation at 0, 1, 2, 3, 4.5, 6, 8 and 10.5 Gy. The dataset comprised a broad dose range over multiple dose points with consistent dose spacing and multiple biological replicates. This dataset was ideal for systematically transforming across three categories: (1) dose range, (2) dose-spacing and (3) number of controls/replicates. Across these categories, 29 transformed datasets were compared to the original dataset to determine the impact of each transformation on the BMD outputs. RESULTS: Most of the experimental changes did not impact the BMD outputs. The transformed datasets were largely consistent with the original dataset in terms of the number of reproduced genes modeled and absolute BMD values for genes and pathways. Variations in dose selection identified the importance of the absolute value of the lowest and second dose. It was determined that dose selection should include at least two doses <1 Gy and two >5 Gy to achieve meaningful BMD outputs. Changes to the number of biological replicates in the control and non-zero dose groups impacted the overall accuracy and precision of the BMD outputs as well as the ability to fit dose-response models consistent with the original dataset. CONCLUSION: Successful application of transcriptomic BMD modeling for radiation datasets requires considerations of the exposure dose and the number of biological replicates. Most important is the selection of the lowest doses and dose spacing. Reflections on these parameters in experimental design will provide meaningful BMD outputs that could correlate well to apical endpoints of relevance to radiation exposure assessment.

Evaluating the influences of confounding variables on benchmark dose using a case study in the field of ionizing radiation.

PURPOSE: A vast amount of data regarding the effects of radiation stressors on transcriptional changes has been produced over the past few decades. These data have shown remarkable consistency across platforms and experimental design, enabling increased understanding of early molecular effects of radiation exposure. However, the value of transcriptomic data in the context of risk assessment is not clear and represents a gap that is worthy of further consideration. Recently, benchmark dose (BMD) modeling has shown promise in correlating a transcriptional point of departure (POD) to that derived using phenotypic outcomes relevant to human health risk assessment. Although frequently applied in chemical toxicity evaluation, our group has recently demonstrated application within the field of radiation research. This approach allows the possibility to quantitatively compare radiation-induced gene and pathway alterations across various datasets using BMD values and derive meaningful biological effects. However, before BMD modeling can confidently be used, an understanding of the impact of confounding variables on BMD outputs is needed. METHODS: To this end, BMD modeling was applied to a publicly available microarray dataset (Gene Expression Omnibus #GSE23515) that used peripheral blood ex-vivo gamma-irradiated at 0.82 Gy/min, at doses of 0, 0.1, 0.5 or 2 Gy, and assessed 6 hours post-exposure. The dataset comprised six female smokers (F-S), six female nonsmokers (F-NS), six male smokers (M-S), and six male nonsmokers (M-NS). RESULTS: A combined total of 412 genes were fit to models and the BMD distribution was noted to be bi-modal across the four groups. A total of 74, 41, 62 and 62 genes were unique to the F-NS, M-NS, F-S and M-S groups. Sixty-two BMD modeled genes and nine pathways were common across all four groups. There were no differential sensitivity of BMD responses in the robust common genes and pathways. CONCLUSION: For radiation-responsive genes and pathways common across the study groups, the BMD distribution of transcriptional activity was unaltered by sex and smoking status. Although further validation of the data is needed, these initial findings suggest BMD values for radiation relevant genes and pathways are robust and could be explored further in future studies.

Adverse outcome pathway: a path toward better data consolidation and global co-ordination of radiation research.

BACKGROUND: The purpose of toxicology is to protect human health and the environment. To support this, the Organisation for Economic Co-operation and Development (OECD), operating via its Extended Advisory Group for Molecular Screening and Toxicogenomics (EAGMST), has been developing the Adverse Outcome Pathway (AOP) approach to consolidate evidence for chemical toxicity spanning multiple levels of biological organization. The knowledge transcribed into AOPs provides a structured framework to transparently organize data, examine the weight of evidence of the AOP, and identify causal relationships between exposure to stressors and adverse effects of regulatory relevance. The AOP framework has undergone substantial maturation in the field of hazard characterization of chemicals over the last decade, and has also recently gained attention from the radiation community as a means to advance the mechanistic understanding of human and ecological health effects from exposure to ionizing radiation at low dose and low dose-rates. To fully exploit the value of such approaches for facilitating risk assessment and management in the field of radiation protection, solicitation of experiences and active cooperation between chemical and radiation communities are needed. As a result, the Radiation and Chemical (Rad/Chem) AOP joint topical group was formed on June 1, 2021 as part of the initiative from the High Level Group on Low Dose Research (HLG-LDR). HLG-LDR is overseen by the OECD Nuclear Energy Agency (NEA) Committee on Radiation Protection and Public Health (CRPPH). The main aims of the joint AOP topical group are to advance the use of AOPs in radiation research and foster broader implementation of AOPs into hazard and risk assessment. With global representation, it serves as a forum to discuss, identify and develop joint initiatives that support research and take on regulatory challenges. CONCLUSION: The Rad/Chem AOP joint topical group will specifically engage, promote, and implement the use of the AOP framework to: (a) organize and evaluate mechanistic knowledge relevant to the protection of human and ecosystem health from radiation; (b) identify data gaps and research needs pertinent to expanding knowledge of low dose and low dose-rate radiation effects; and (c) demonstrate utility to support risk assessment by developing radiation-relevant case studies. It is envisioned that the Rad/Chem AOP joint topical group will actively liaise with the OECD EAGMST AOP developmental program to collectively advance areas of common interest and, specifically, provide recommendations for harmonization of the AOP framework to accommodate non-chemical stressors, such as radiation.

Deploying elements of scoping review methods for adverse outcome pathway development: a space travel case example.

PURPOSE: Health protection agencies require scientific information for evidence-based decision-making and guideline development. However, vetting and collating large quantities of published research to identify relevant high-quality studies is a challenge. One approach to address this issue is the use of adverse outcome pathways (AOPs) that provide a framework to assemble toxicological knowledge into causally linked chains of key events (KEs) across levels of biological organization to culminate in an adverse health outcome of significance to regulatory decision-making. Traditionally, AOPs have been constructed using a narrative review approach where the collection of evidence that supports each pathway is based on prior knowledge of influential studies that can also be supplemented by individually selecting and reviewing relevant references. OBJECTIVES: We aimed to create a protocol for AOP weight of evidence gathering that harnesses elements of both scoping review methods and artificial intelligence (AI) tools to increase transparency while reducing bias and workload of human screeners. METHODS: To develop this protocol, an existing space-health AOP in the workplan of the Organisation for Economic Co-operation and Development (OECD) AOP Programme was used as a case example. To balance the benefits of both scoping review tools and narrative approaches, a study protocol outlining a screening and search strategy was developed, and three reference collection workflows were tested to identify the most efficient method to inform weight of evidence. The workflows differed in their literature search strategies, and combinations of software tools used. RESULTS: Across the three tested workflows, over 59 literature searches were completed, retrieving over 34,000 references of which over 3300 were human reviewed. The most effective of the three methods used a search strategy with searches across each component of the AOP network, SWIFT Review as a pre-filtering software, and DistillerSR to create structured screening and data extraction forms. This methodology effectively retrieved relevant studies while balancing efficiency in data retrieval without compromising transparency, leading to a well-synthesized evidence base to support the AOP. CONCLUSIONS: The workflow is still exploratory in the context of AOP development, and we anticipate adaptations to the protocol with further experience. To further the systematicity, future iterations of the workflow could include structured quality assessment and risk of bias analysis. Overall, the workflow provides a transparent and documented approach to support AOP development, which in turn will support the need for rigorous methods to identify relevant scientific evidence while being practical to allow uptake by the broader community.

Radiation adverse outcome pathways (AOPs) are on the horizon: advancing radiation protection through an international Horizon-Style exercise.

PURPOSE: The Adverse Outcome Pathway (AOP) framework, a systematic tool that can link available mechanistic data with phenotypic outcomes of relevance to regulatory decision-making, is being explored in areas related to radiation risk assessment. To examine the challenges including the use of AOPs to support the radiation protection community, an international horizon-style exercise was initiated through the Organisation for Economic Co-operation and Development Nuclear Energy Agency High-Level Group on Low Dose Research Radiation/Chemical AOP Joint Topical Group. The objective of the HSE was to facilitate the collection of ideas from a range of experts, to short-list a set of priority research questions that could, if answered, improve the description of the radiation dose-response relationship for low dose/dose-rate exposures, as well as reduce uncertainties in estimating the risk of developing adverse health outcomes following such exposures. MATERIALS AND METHODS: The HSE was guided by an international steering committee of radiation risk experts. In the first phase, research questions were solicited on areas that can be supported by the AOP framework, or challenges on the use of AOPs in radiation risk assessment. In the second phase, questions received were refined and sorted by the SC using a best-worst scaling method. During a virtual 3-day workshop, the list of questions was further narrowed. In the third phase, an international survey of the broader radiation protection community led to an orderly ranking of the top questions. RESULTS: Of the 271 questions solicited, 254 were accepted and categorized into 9 themes. These were further refined to the top 25 prioritized questions. Among these, the higher ranked questions will be considered as 'important' to drive future initiatives in the low dose radiation protection community. These included questions on the ability of AOPs to delineate responses across different levels of biological organization, and how AOPs could be applied to address research questions on radiation quality, doses or dose-rates, exposure time patterns and deliveries, and uncertainties in low dose/dose-rate effects. A better understanding of these concepts is required to support the use of the AOP framework in radiation risk assessment. CONCLUSION: Through dissemination of these results and considerations on next steps, the JTG will address select priority questions to advance the development and use of AOPs in the radiation protection community. The major themes observed will be discussed in the context of their relevance to areas of research that support the system of radiation protection.

Biological Dosimetry by the Triage Dicentric Chromosome Assay - Further validation of International Networking.

Biological dosimetry is an essential tool for estimating radiation doses received to personnel when physical dosimetry is not available or inadequate. The current preferred biodosimetry method is based on the measurement of radiation-specific dicentric chromosomes in exposed individuals' peripheral blood lymphocytes. However, this method is labour-, time- and expertise-demanding. Consequently, for mass casualty applications, strategies have been developed to increase its throughput. One such strategy is to develop validated cytogenetic biodosimetry laboratory networks, both national and international. In a previous study, the dicentric chromosome assay (DCA) was validated in our cytogenetic biodosimetry network involving five geographically dispersed laboratories. A complementary strategy to further enhance the throughput of the DCA among inter-laboratory networks is to use a triage DCA where dose assessments are made by truncating the labour-demanding and time-consuming metaphase-spread analysis to 20 to 50 metaphase spreads instead of routine 500 to 1000 metaphase spread analysis. Our laboratory network also validated this triage DCA, however, these dose estimates were made using calibration curves generated in each laboratory from the blood samples irradiated in a single laboratory. In an emergency situation, dose estimates made using pre-existing calibration curves which may vary according to radiation type and dose rate and therefore influence the assessed dose. Here, we analyze the effect of using a pre-existing calibration curve on assessed dose among our network laboratories. The dose estimates were made by analyzing 1000 metaphase spreads as well as triage quality scoring and compared to actual physical doses applied to the samples for validation. The dose estimates in the laboratory partners were in good agreement with the applied physical doses and determined to be adequate for guidance in the treatment of acute radiation syndrome.