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- 2019
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Journal article (peer-reviewed)
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- Abend, M., et al.
(author)
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Inter-laboratory comparison of gene expression biodosimetry for protracted radiation exposures as part of the RENEB and EURADOS WG10 2019 exercise
- 2021
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In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1
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Journal article (peer-reviewed)abstract
- Large-scale radiation emergency scenarios involving protracted low dose rate radiation exposure (e.g. a hidden radioactive source in a train) necessitate the development of high throughput methods for providing rapid individual dose estimates. During the RENEB (Running the European Network of Biodosimetry) 2019 exercise, four EDTA-blood samples were exposed to an Iridium-192 source (1.36 TBq, Tech-Ops 880 Sentinal) at varying distances and geometries. This resulted in protracted doses ranging between 0.2 and 2.4 Gy using dose rates of 1.5-40 mGy/min and exposure times of 1 or 2.5 h. Blood samples were exposed in thermo bottles that maintained temperatures between 39 and 27.7 degrees C. After exposure, EDTA-blood samples were transferred into PAXGene tubes to preserve RNA. RNA was isolated in one laboratory and aliquots of four blinded RNA were sent to another five teams for dose estimation based on gene expression changes. Using an X-ray machine, samples for two calibration curves (first: constant dose rate of 8.3 mGy/min and 0.5-8 h varying exposure times; second: varying dose rates of 0.5-8.3 mGy/min and 4 h exposure time) were generated for distribution. Assays were run in each laboratory according to locally established protocols using either a microarray platform (one team) or quantitative real-time PCR (qRT-PCR, five teams). The qRT-PCR measurements were highly reproducible with coefficient of variation below 15% in >= 75% of measurements resulting in reported dose estimates ranging between 0 and 0.5 Gy in all samples and in all laboratories. Up to twofold reductions in RNA copy numbers per degree Celsius relative to 37 degrees C were observed. However, when irradiating independent samples equivalent to the blinded samples but increasing the combined exposure and incubation time to 4 h at 37 degrees C, expected gene expression changes corresponding to the absorbed doses were observed. Clearly, time and an optimal temperature of 37 degrees C must be allowed for the biological response to manifest as gene expression changes prior to running the gene expression assay. In conclusion, dose reconstructions based on gene expression measurements are highly reproducible across different techniques, protocols and laboratories. Even a radiation dose of 0.25 Gy protracted over 4 h (1 mGy/min) can be identified. These results demonstrate the importance of the incubation conditions and time span between radiation exposure and measurements of gene expression changes when using this method in a field exercise or real emergency situation.
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- Abend, M., et al.
(author)
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RENEB Inter-Laboratory Comparison 2021 : The Gene Expression Assay
- 2023
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In: Radiation Research. - 0033-7587 .- 1938-5404. ; 199:6, s. 598-615
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Journal article (peer-reviewed)abstract
- Early and high-throughput individual dose estimates are essential following large-scale radiation exposure events. In the context of the Running the European Network for Biodosimetry and Physical Dosimetry (RENEB) 2021 exercise, gene expression assays were conducted and their corresponding performance for dose-assessment is presented in this publication. Three blinded, coded whole blood samples from healthy donors were exposed to 0, 1.2 and 3.5 Gy X-ray doses (240 kVp, 1 Gy/min) using the X-ray source Yxlon. These exposures correspond to clinically relevant groups of unexposed, low dose (no severe acute health effects expected) and high dose exposed individuals (requiring early intensive medical health care). Samples were sent to eight teams for dose estimation and identification of clinically relevant groups. For quantitative reverse transcription polymerase chain reaction (qRT-PCR) and microarray analyses, samples were lysed, stored at 20°C and shipped on wet ice. RNA isolations and assays were run in each laboratory according to locally established protocols. The time-to-result for both rough early and more precise later reports has been documented where possible. Accuracy of dose estimates was calculated as the difference between estimated and reference doses for all doses (summed absolute difference, SAD) and by determining the number of correctly reported dose estimates that were defined as ±0.5 Gy for reference doses <2.5 Gy and ±1.0 Gy for reference doses >3 Gy, as recommended for triage dosimetry. We also examined the allocation of dose estimates to clinically/diagnostically relevant exposure groups. Altogether, 105 dose estimates were reported by the eight teams, and the earliest report times on dose categories and estimates were 5 h and 9 h, respectively. The coefficient of variation for 85% of all 436 qRT-PCR measurements did not exceed 10%. One team reported dose estimates that systematically deviated several-fold from reported dose estimates, and these outliers were excluded from further analysis. Teams employing a combination of several genes generated about two-times lower median SADs (0.8 Gy) compared to dose estimates based on single genes only (1.7 Gy). When considering the uncertainty intervals for triage dosimetry, dose estimates of all teams together were correctly reported in 100% of the 0 Gy, 50% of the 1.2 Gy and 50% of the 3.5 Gy exposed samples. The order of dose estimates (from lowest to highest) corresponding to three dose categories (unexposed, low dose and highest exposure) were correctly reported by all teams and all chosen genes or gene combinations. Furthermore, if teams reported no exposure or an exposure >3.5 Gy, it was always correctly allocated to the unexposed and the highly exposed group, while low exposed (1.2 Gy) samples sometimes could not be discriminated from highly (3.5 Gy) exposed samples. All teams used FDXR and 78.1% of correct dose estimates used FDXR as one of the predictors. Still, the accuracy of reported dose estimates based on FDXR differed considerably among teams with one team's SAD (0.5 Gy) being comparable to the dose accuracy employing a combination of genes. Using the workflow of this reference team, we performed additional experiments after the exercise on residual RNA and cDNA sent by six teams to the reference team. All samples were processed similarly with the intention to improve the accuracy of dose estimates when employing the same workflow. Re-evaluated dose estimates improved for half of the samples and worsened for the others. In conclusion, this inter-laboratory comparison exercise enabled (1) identification of technical problems and corrections in preparations for future events, (2) confirmed the early and high-throughput capabilities of gene expression, (3) emphasized different biodosimetry approaches using either only FDXR or a gene combination, (4) indicated some improvements in dose estimation with FDXR when employing a similar methodology, which requires further research for the final conclusion and (5) underlined the applicability of gene expression for identification of unexposed and highly exposed samples, supporting medical management in radiological or nuclear scenarios.
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- Gülk, Birte, 1994, et al.
(author)
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Impacts of Vertical Convective Mixing Schemes and Freshwater Forcing on the 2016-2017 Maud Rise Polynya Openings in a Regional Ocean Simulation
- 2024
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In: JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS. - 1942-2466. ; 16:5
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Journal article (peer-reviewed)abstract
- The correct representation of the Maud Rise open-ocean polynya in the Weddell Sea remains a challenge for ocean models. Here we reproduce the most recent polynya openings in 2016-2017 using a regional configuration, and assess their dependencies on vertical convective mixing schemes and freshwater forcing, both separately and in combination. We test three vertical convective mixing schemes: the enhanced vertical diffusion (EVD), the Eddy-Diffusivity Mass-Flux (EDMF) parameterization, and a modified version of EDMF accounting for thermobaric effects. Using simulations for the period 2007-2017, we find that the modified EDMF reproduces the observed climatological evolution of the mixed layer depth better than the original EDMF and the EVD, but a polynya fails to open due to excessive freshwater forcing. We thus use the modified EDMF to perform sensitivity experiments with reduced precipitation during 2012-2017. The imposed freshwater forcing strongly affects the number of years with polynyas. The simulation with the best representation of the 2016-2017 polynyas is analyzed to evaluate the triggering mechanisms. The 2016 polynya was induced by the action of thermobaric instabilities on a weak ambient stratification. This opening preconditioned the water column for 2017, which produced a stronger polynya. By examining the impacts of the different convective mixing schemes, we show that the modified EDMF generates more realistic patterns of deep convection. Our results highlight the importance of surface freshwater forcing and thermobaricity in governing deep convection around Maud Rise, and the need to represent thermobaric instabilities to realistically model Maud Rise polynyas. We investigate the impacts of representing numerical vertical mixing and surface freshwater forcing in a regional ocean model on polynyas (large openings in the pack ice) at Maud Rise, Southern Ocean. Maud Rise is prone to hosting polynyas, often associated with deep convection, which is a local vertical mixing process homogenizing the water column between surface and depths of several hundred meters. Numerical models often use simplistic strategies to represent this process, but improved parameterizations have recently become available. In this work, we test the impact of the representation of convective mixing in a particularly sensitive region. The last Maud Rise polynyas were observed in 2016 and 2017. Our regional simulation is capable of reproducing these polynyas, which has long been a challenge for ocean-sea ice models. We show that the 2016 polynya resulted from the action of a vertical instability at depth acting on weak ambient stratification. This event preconditioned the stronger 2017 polynya and deep convection. We conclude that representing convective plumes as a sub-grid scale process in models leads to a more realistic representation of open-ocean polynyas and associated convection events. The Eddy-Diffusivity Mass-Flux (EDMF) parameterization is tested in a regional simulation of the ocean around Maud Rise Thermobaric effects on convective plumes are enabled by modifying the EDMF parameterization Simulations of Maud Rise polynyas are highly sensitive to freshwater forcing and mixing schemes
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| 7. |
- Ostheim, Patrick, et al.
(author)
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Gene expression for biodosimetry and effect prediction purposes : promises, pitfalls and future directions – key session ConRad 2021
- 2022
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In: International Journal of Radiation Biology. - : Informa UK Limited. - 0955-3002 .- 1362-3095. ; 98:5, s. 843-854
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Research review (peer-reviewed)abstract
- Purpose: In a nuclear or radiological event, an early diagnostic or prognostic tool is needed to distinguish unexposed from low- and highly exposed individuals with the latter requiring early and intensive medical care. Radiation-induced gene expression (GE) changes observed within hours and days after irradiation have shown potential to serve as biomarkers for either dose reconstruction (retrospective dosimetry) or the prediction of consecutively occurring acute or chronic health effects. The advantage of GE markers lies in their capability for early (1–3 days after irradiation), high-throughput, and point-of-care (POC) diagnosis required for the prediction of the acute radiation syndrome (ARS).Conclusions: As a key session of the ConRad conference in 2021, experts from different institutions were invited to provide state-of-the-art information on a range of topics including: (1) Biodosimetry: What are the current efforts to enhance the applicability of this method to perform retrospective biodosimetry? (2) Effect prediction: Can we apply radiation-induced GE changes for prediction of acute health effects as an approach, complementary to and integrating retrospective dose estimation? (3) High-throughput and point-of-care diagnostics: What are the current developments to make the GE approach applicable as a high-throughput as well as a POC diagnostic platform? (4) Low level radiation: What is the lowest dose range where GE can be used for biodosimetry purposes? (5) Methodological considerations: Different aspects of radiation-induced GE related to more detailed analysis of exons, transcripts and next-generation sequencing (NGS) were reported.
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