PURPOSE:Early prediction of hematological acute radiation syndrome (H-ARS) saves lives. For H-ARS severity prediction, we established a four-gene panel (FDXR, DDB2, POU2AF1, WNT3) using leukemia patients and non-human primates. Further confirmation in 12 minipigs failed, due to a weak response of these genes after irradiation. MATERIALS AND METHODS:Here, we intended to confirm previous findings using a larger cohort (n = 19) and assess the impact of Myelo001 on clinical progression and gene expression. All minipigs received 2.1 Gy total-body irradiation (LD ≈ 40/30). The study included an irradiated control group and two irradiated groups treated with Myelo001 (11 or 15 days). Peripheral blood was collected six days before and on days 1-, 3-, and 10 after irradiation. RNA was isolated, reverse-transcribed, and analyzed by qRT-PCR using TaqMan assays. Differential gene expression (DGE) was calculated relative to pre-irradiation samples. RESULTS:WNT3 was undetectable in most animals. No significant difference in gene expression, survival, or clinical progression were found between Myelo001-treated and untreated animals, so treatment groups were pooled for DGE analyses. Across all time points, no significant changes in DGE were observed, except for slight DDB2 upregulation on day 3 (DGE = 2.3). The expected pattern of upregulated (DGE >2) FDXR/DDB2 with simultaneous downregulation (DGE <0.5) of POU2AF1, was absent (except on day one in one minipig). This missing pattern contrasted with an on average 5.5-fold reduction in lymphocyte counts, indicative of severe H-ARS. Also, no age or sex related changes were observed. CONCLUSION:This independent minipig study confirms previous work showing that these genes do not exhibit statistically significant radiation-responsiveness in this animal model. Under the experimental conditions applied, no significant age or sex related changes nor treatment-related effects of Myelo001 were observed, which may reflect model-specific limitations or a lack of efficacy in this setting, or a combination of both.

This invited commentary grew out of a presentation made at the 2025 ConRad Meeting in Munich, Germany, and summarizes talks made by researchers supported by the National Institute of Allergy and Infectious Diseases (NIAID) and the Bundeswehr Institute of Radiobiology (BIR) during a joint programmatic workshop held on September 11-12, 2024. The symposium focused on the global health readiness and responses to radiological or nuclear public health emergencies; the status of medical countermeasure development and models used to develop these countermeasures; identification of biomarkers of radiation injuries and biodosimetry tools, and recent advances in developing tools for triage, definitive dose assessment and predictive assays. Areas of common synergy between the two entities were also explored to inform potential future collaborative efforts. There are many tools at different stages of development, and emergence of substantive datasets that require cutting-edge machine learning approaches, multiparametric analyses, and integrated systems outcome to fully exploit the potential of this knowledge and accurately address radiological emergency preparedness. In these endeavors, now more than ever, it is critical to continue connecting with the world's scientific communities to accelerate scientific breakthroughs, close research gaps, and enhance radiation emergency readiness.

PURPOSE:The fast diagnosis of the life-threatening acute radiation syndrome is crucial, as the early prediction of the hematological acute radiation syndrome (H-ARS) can save lives. Previously, we validated a four-gene set (FDXR, DDB2, POU2AF1, WNT3) for H-ARS severity prediction in non-human primates and leukemia patients. In this study, we aim to validate this gene set in minipigs as a surrogate model. MATERIALS AND METHODS:12 Göttingen minipigs, irradiated with 1.8 or 2.1 Gray (LD≈40/30), were examined. METREPOL H-ARS severity degrees were determined using sequential blood cell count changes over time after irradiation. For quantitative Real-Time-PCR (qRT-PCR), peripheral whole blood was withdrawn before and on days 1, 3, and 10 after irradiation. Normalization was performed using 18S rRNA and PUM1 as housekeeping genes (HKG). Differential gene expression (DGE) relative to the pre-irradiated samples was calculated. RESULTS:All minipigs developed a 2-4 H-ARS-severity degree. 18S rRNA revealed significantly (p = .0005) about two-fold higher variance of raw Ct-values than PUM1. DGE was calculated for all genes except WNT3 (undetectable in most animals). All genes revealed a slight up-regulation over time in most animals, but DGE > 2 regarding FDXR or DDB2 and concomitant downregulation of POU2AF1 (DGE < 0.5) as expected given the H-ARS severity degrees, was not observed. CONCLUSION:None of the animals revealed the expected DGE pattern corresponding to a moderate to high H-ARS-severity degree. Hence, the Göttingen minipig did not qualify as another validation model for our specific gene set, which does not argue against their validity for other purposes.

Computed tomography (CT) is a major source of low-dose ionizing radiation exposure in medical imaging. Risk assessment at this dose level is difficult and relies on the hypothetical linear no-threshold model. To address the response to such low doses in patients undergoing CT scans, we examined radiation-induced alterations at the transcriptomic and DNA damage levels in peripheral blood cells. Peripheral whole blood of 60 patients was collected before and after CT. Post-CT samples were obtained 4–6 h after scan (n = 28, in vivo incubation) or alternatively immediately after the CT scan, followed by ex vivo incubation (n = 32). The gene expression of known radiation-responsive genes (n = 9) was quantified using qRT-PCR. DNA double-strand breaks (DSB) were assessed in 12 patients through microscopic γ-H2AX + 53BP1 DSB focus staining. The mean dose–length product (DLP) across all scans was 561.9 ± 384.6 mGy·cm. Significant differences in the median differential gene expression (DGE) were detected between in vivo and ex vivo incubation conditions, implicating that ex vivo incubation masked the true effect in low-dose settings. The median DGE of in vivo-incubated samples showed a significant upregulation of EDA2R, MIR34AHG, PHLDA3, DDB2, FDXR, and AEN (p ranging from <0.001 to 0.041). In vivo, we observed a linear dose-dependent upregulation for several genes and an explained variance of 0.66 and 0.56 for AEN and FDXR, respectively. DSB focus analysis revealed a slight, non-significant increase in the average DSB damage post-exposure, at a mean DLP of 321.0 mGy·cm. Our findings demonstrate that transcriptional biomarkers are sensitive indicators of low-dose radiation exposure in medical imaging and could prove themselves as clinically applicable biodosimetry tools. Furthermore, the results underscore the need for dose optimization.

PurposeRadiation-induced alterations in gene expression show great promise for dose reconstruction and for severity prediction of acute health effects. Among several genes explored as potential biomarkers, FDXR is widely used due to high upregulation in white blood cells following radiation exposure. Nonetheless, the absence of a standardized protocols for gene expression-based biodosimetry is a notable gap that warrants attention to enhance the accuracy, reproducibility and reliability. The objective of this study was to evaluate the sensitivity of transcriptional biodosimetry to differences in protocols used by different laboratories and establish guidelines for the calculation of calibration curve using FDXR expression data.Material and MethodsTwo sets of irradiated blood samples generated during RENEB exercise were used. The first included samples irradiated with known doses including: 0, 0.25, 0.5, 1, 2, 3 and 4 Gy. The second set consisted of three 'blind' samples irradiated with 1.8 Gy, 0.4 Gy and a sham-irradiated sample. After irradiation, samples were incubated at 37 degrees C over 24 h and sent to participating laboratories, where RNA isolation and FDXR expression analysis by qPCR were performed using sets of primers/probes and reference genes specific for each laboratory. Calibration curves based on FDXR expression data were generated using non-linear and linear regression and used for dose estimation of 'blind' samples.ResultsDose estimates for sham-irradiated sample (0.020-0.024 Gy) and sample irradiated with 0.4 Gy (0.369-0.381 Gy) showed remarkable consistency across all laboratories, closely approximating the true doses regardless variation in primers/probes and reference genes used. For sample irradiated with 1.8 Gy the dose estimates were less precise (1.198-2.011 Gy) but remained within an acceptable margin for triage within the context of high dose range.ConclusionMethodological differences in reference genes and primers/probes used for FDXR expression measurement do not have a significant impact on the dose estimates generated, provided that all reference genes performed as expected and the primers/probes target a similar set of transcript variants. The preferred method for constructing a calibration curve based on FDXR expression data involves employing linear regression to establish a function that describes the relationship between the logarithm of absorbed dose and FDXR Delta Ct values. However, one should be careful with using non-irradiated sample data as these cannot be accurately represented on a logarithmic scale. A standard curve generated using this approach can give reliable dose estimations in a dose range from 50 mGy to 4 Gy at least.

In gene expression (GE) studies, housekeeping genes (HKGs) are required for normalization purposes. In large-scale inter-laboratory comparison studies, significant differences in dose estimates are reported and divergent HKGs are employed by the teams. Among them, the 18S rRNA HKG is known for its robustness. However, the high abundance of 18S rRNA copy numbers requires dilution, which is time-consuming and a possible source of errors. This study was conducted to identify the most promising HKGs showing the least radiation-induced GE variance after radiation exposure. In the screening stage of this study, 35 HKGs were analyzed. This included selected HKGs (ITFG1, MRPS5, and DPM1) used in large-scale biodosimetry studies which were not covered on an additionally employed pre-designed 96-well platform comprising another 32 HKGs used for different exposures. Altogether 41 samples were examined, including 27 ex vivo X-ray irradiated blood samples (0, 0.5, 4 Gy), six X-irradiated samples (0, 0.5, 5 Gy) from two cell lines (U118, A549), as well as eight non-irradiated tissue samples to encompass multiple biological entities. In the independent validation stage, the most suitable candidate genes were examined from another 257 blood samples, taking advantage of already stored material originating from three studies. These comprise 100 blood samples from ex vivo X-ray irradiated (0-4 Gy) healthy donors, 68 blood samples from 5.8 Gy irradiated (cobalt-60) Rhesus macaques (RM) (LD29/60) collected 0-60 days postirradiation, and 89 blood samples from chemotherapy-(CTx) treated breast tumor patients. CTx and radiationinduced GE changes in previous studies appeared comparable. RNA was isolated, converted into cDNA, and GE was quantified employing TaqMan assays and quantitative RT-PCR. We calculated the standard deviation (SD) and the interquartile range (IQR) as measures of GE variance using raw cycle threshold (Ct) values and ranked the HKGs accordingly. Dose, time, age, and sex-dependent GE changes were examined employing the parametrical t-test and non-parametrical Kruskal Wallis test, as well as linear regression analysis. Generally, similar ranking results evolved using either SD or IQR GE measures of variance, indicating a tight distribution of GE values. PUM1 and PGK1 showed the lowest variance among the first ten most suitable genes in the screening phase. MRPL19 revealed low variance among the first ten most suitable genes in the screening phase only for blood and cells, but certain comparisons indicated a weak association of MRPL19 with dose (P = 0.02-0.09). In the validation phase, these results could be confirmed. Here, IQR Ct values from, e.g., X-irradiated blood samples were 0.6 raw Ct values for PUM1 and PGK1, which is considered to represent GE differences as expected due to methodological variance. Overall, when compared, the GE variance of both genes was either comparable or lower compared to 18S rRNA. Compared with the IQR GE values of PUM1 and PGKI, twofold-fivefold increased values were calculated for the biodosimetry HKG HPRT1, and comparable values were calculated for biodosimetry HKGs ITFG1, MRPS5, and DPM1. Significant dose-dependent associations were found for ITFG1 and MRPS5 (P = 0.001-0.07) and widely absent or weak (P = 0.02-0.07) for HPRT1 and DPM1. In summary, PUM1 and PGK1 appeared most promising for radiation exposure studies among the 35 HKGs examined, considering GE variance and adverse associations of GE with dose. (c) 2024 by Radiation Research Society

Radiosensitivity differs in humans and possibly in closely related nonhuman primates. The reasons for variation in radiosensitivity are not well known. In an earlier study, we examined gene expression (GE) pre-radiation in peripheral blood among male (n = 62) and female (n = 60) rhesus macaques (n = 122), which did or did not survive (up to 60 days) after whole-body exposure of 7.0 Gy (LD66/60). Eight genes (CHD5, CHI3L1, DYSF, EPX, IGF2BP1, LCN2, MBOAT4, SLC22A4) revealed significant associations with survival. Access to a second rhesus macaque cohort (males = 40, females = 23, total n = 63) irradiated with 5.8-7.2 Gy (LD29-50/60) and some treated with gamma-tocotrienol (GT3, a radiation countermeasure) allowed us to validate these gene expression changes independently. Total RNA was isolated from whole blood samples and examined by quantitative RT-PCR on a 96-well format. cycle threshold (Ct)-values normalized to 18S rRNA were analyzed for their association with survival. Regardless of the species-specific TaqMan assay, similar results were obtained. Two genes (CHD5 and CHI3L1) out of eight revealed a significant association with survival in the second cohort, while only CHD5 (involved in DNA damage response and proliferation control) showed mean gene expression changes in the same direction for both cohorts. No expected association of CHD5 GE with dose, treatment, or sex could be established. Instead, we observed significant associations for those comparisons comprising pre-exposure samples with CHD5 Ct values <= 11 (total n = 17). CHD5 Ct values <= 11 in these comparisons were mainly associated with increased frequencies (61-100%) of non-survivors, a trend which depending on the sample numbers, reached significance (P = 0.03) in males and, accordingly, in females. This was also reflected by a logistic regression model including all available samples from both cohorts comprising CHD5 measurements (n = 104, odds ratio 1.38, 95% CI 1.07-1.79, P = 0.01). However, this association was driven by males (odds ratio 1.62, 95% CI 1.10-2.38, P = 0.01) and CHD5 Ct values <= 11 since removing low CHD5 Ct values from this model, converted to insignificance (P = 0.19). A second male subcohort comprising high CHD5 Ct values >= 14.4 in both cohorts (n = 5) appeared associated with survival. Removing these high CHD5 Ct values converted the model borderline significant (P = 0.051). Based on the probability function of the receiver operating characteristics (ROC) curves, 8 (12.3%) and 5 (7.7%) from 65 pre-exposure RNA measurements in males, death and survival could be predicted with a negative and positive predictive value ranging between 85-100%. An associated odds ratio reflected a 62% elevated risk for dying or surviving per unit change (Ct-value) in gene expression, considering the before-mentioned CHD5 thresholds in RNA copy numbers. In conclusion, we identified two subsets of male animals characterized by increased (Ct values <= 11) and decreased (Ct values >= 14.4) CHD5 GE copy numbers before radiation exposure, which independently of the cohort, radiation exposure or treatment appeared to predict the death or survival in males. (c) 2024 by Radiation Research Society

As the war in Ukraine progresses, the radiological and nuclear threat has never been as real as now. The formation of life-threatening acute radiation syndrome (ARS), in particular after the deployment of a nuclear weapon or an attack on a nuclear power station, must be considered realistic. ARS is caused by massive cell death, leading to functional organ deficits and, via systemic inflammatory responses, finally aggravates into multiple organ failure. As a deterministic effect, the severity of the disease dictates the clinical outcome. Hence, predicting ARS severity via biodosimetry or alternative approaches appears straightforward. Because the disease occurs delayed, therapy starting as early as possible has the most significant benefit. A clinically relevant diagnosis should be carried out within the diagnostic time window of about 3 days after exposure. Biodosimetry assays providing retrospective dose estimations within this time frame will support medical management decision-making. However, how closely can dose estimates be associated with the later developing ARS severity degrees when considering dose as one among other determinants of radiation exposure and cell death? From a clinical/triage point of view, ARS severity degrees can be further aggregated into unexposed, weakly diseased (no acute health effects expected), and strongly diseased patient groups, with the latter requiring hospitalization as well as an early and intensive treatment. Radiation-induced gene expression (GE) changes occur early after exposure and can be quickly quantified. GE can be used for biodosimetry purposes. Can GE be used to predict later developing ARS severity degrees and allocate individuals to the three clinically relevant groups as well?

PURPOSE:In a previous baboon-study, a total of 29 genes were identified for clinical outcome prediction of the hematologic, acute, radiation, syndrome (H-ARS) severity. Among them, four genes (FDXR, DDB2, POU2AF1, WNT3) appeared promising and were validated in five leukemia patients. Within this study, we sought further in-vivo validation in a larger number of whole-body irradiated patients. MATERIAL AND METHODS:Peripheral blood was drawn from 10 leukemia patients before and up to 3 days during a fractionated (2 Gy/day) total-body irradiation (TBI) with 2-12Gy. After RNA-isolation, gene expression (GE) was evaluated on 31 genes widely used in biodosimetry and H-ARS prediction employing qRT-PCR. A customized low-density-array (LDA) allowed simultanously analyzing all genes, the 96-well format further examined the four most promising genes. Fold-changes (FC) in GE relative to pre-irradiation were calculated. RESULTS:Five patients suffering from acute-lymphoblastic-leukemia (ALL) respectively non-Hodgkin-lymphoma (NHL) revealed sufficient RNA-amounts and corresponding lymphocyte and neutrophile counts for running qRT-PCR, while acute-myeloid-leukemia (AML) and one myelofibrosis patient could not supply enough RNA. Generally, 1-2µg total RNA was isolated, whereas up to 10-fold differences in RNA-quantities (associated suppressed GE-changes) were identified among pre-exposure and exposure samples. From 31 genes, 23 were expressed in at least one of the pre-exposure samples. Relative to pre-exposure, the number of expressed genes could halve at 48 and 72h after irradiation. Using the LDA, 13 genes were validated in human samples. The four most promising genes (vid. sup.) were either undetermined or too close to pre-exposure. However, they were measured using the more sensitive 96-well format, except WNT3, which wasn´t detectable. As in previous studies, an opposite regulation in GE for FDXR in leukemia patients (up-regulated) relative to baboons (down-regulated) was reconfirmed. Radiation-induced GE-changes of DDB2 (up-regulated) and POU2AF1 (down-regulated) behaved similarly in both species. Hence, 16 out of 23 genes of two species showed GE-changes in the same direction, and up-regulated FDXR as in human studies were revalidated. CONCLUSION:Identified genes for H-ARS severity prediction, previously detected in baboons, were validated in ALL but not in AML patients. Limitations related to leukemia type, associated reduced RNA amounts, suppressed GE changes, and methodological challenges must be considered as factors negatively affecting the total number of validated genes. Based on that, we propose additional controls including blood cell counts and preferably fluorescence-based RNA quantity measurements for selecting promising samples and using a more sensitive 96-well format for candidate genes with low baseline copy numbers.

In times of war, radiological/nuclear emergency scenarios have become a reemphasized threat. However, there are challenges in transferring whole-blood samples to laboratories for specialized diagnostics using RNA. This project aims to miniaturize the process of unwieldy conventional RNA extraction with its stationed technical equipment using a microfluidic-based slide (MBS) for point-of-care diagnostics. The MBS is thought to be a preliminary step toward the development of a so-called lab-on-a-chip microfluidic device. A MBS would enable early and fast field care combined with gene expression (GE) analysis for the prediction of hematologic acute radiation syndrome (HARS) severity or identification of RNA microbes. Whole blood samples from ten healthy donors were irradiated with 0, 0.5 or 4 Gy, simulating different ARS severity degrees. RNA quality and quantity of a preliminary MBS was compared with a conventional column-based (CB) RNA extraction method. GE of four HARS severity-predicting radiation-induced genes (FDXR, DDB2, POU2AF1 and WNT3) was examined employing qRT-PCR. Compared to the CB method, twice as much total RNA from whole blood could be extracted using the MBS (6.6 ± 3.2 µg vs. 12.0 ± 5.8 µg) in half of the extraction time, and all MBS RNA extracts appeared DNA-free in contrast to the CB method (30% were contaminated with DNA). Using MBS, RNA quality [RNA integrity number equivalent (RINe)] values decreased about threefold (3.3 ± 0.8 vs. 9.0 ± 0.4), indicating severe RNA degradation, while expected high-quality RINe ≥ 8 were found using column-based method. However, normalized cycle threshold (Ct) values, as well as radiation-induced GE fold-changes appeared comparable for all genes utilizing both methods, indicating that no RNA degradation took place. In summary, the preliminary MBS showed promising features such as: 1. halving the RNA extraction time without the burden of heavy technical equipment (e.g., a centrifuge); 2. absence of DNA contamination in contrast to CB RNA extraction; 3. reduction in blood required, because of twice the biological output of RNA; and 4. equal GE performance compared to CB, thus, increasing its appeal for later semi-automatic parallel field applications.

GBM WHO CNS Grade 4 represents a major challenge for oncology due to its aggressive behavior. Conventional imaging has restrictions in detecting tumor recurrence. This prospective study aims to identify gene-based biomarkers in whole blood instead of isolating exosomes for the early detection of tumor recurrence. Blood samples (n = 33) were collected from seven GBM patients at time points before and after surgery as well as upon tumor recurrence. Four tumor tissue samples were assessed in parallel. Next-generation sequencing (NGS), including mRNA-seq and small RNA-seq, was used to analyze gene expression profiles in blood samples and tumor tissues. A novel filtering pipeline was invented to narrow down potential candidate genes. In total, between 6–93 mRNA and 1–19 small RNA candidates could be identified among the seven patients. The overlap of genes between the patients was minimal, indicating significant inter-individual variance among GBM patients. In summary, this prospective study supports the applicability of gene expression measurements in whole blood for the detection of tumor recurrence. It might provide an alternative to the challenging workflow of liquid biopsy after laborious exosome isolation from whole blood.

Stern W, Alaei P, Berbeco R, DeWerd LA, Kamen J, MacKenzie C, Moros EG, Poirier Y, Potter CA, Schaue D, Silvestre Patallo I, Abend M, Swarts S, Trompier F. Achieving Consistent Reporting of Radiation Dosimetry by Adoption of Compatibility in Irradiation Research Protocols Expert Roundtable (CIRPER) Recommendations. Radiat Res. 201, 267-269 (2024). (c) 2024 by Radiation Research Society

As the great majority of gene expression (GE) biodosimetry studies have been performed using blood as the preferred source of tissue, searching for simple and less-invasive sampling methods is important when considering biodosimetry approaches. Knowing that whole saliva contains an ultrafiltrate of blood and white blood cells, it is expected that the findings in blood can also be found in saliva. This human in vivo study aims to examine radiation-induced GE changes in saliva for biodosimetry purposes and to predict radiation-induced disease, which is yet poorly characterized. Furthermore, we examined whether transcriptional biomarkers in blood can also be found equivalently in saliva. Saliva and blood samples were collected in parallel from radiotherapy (RT) treated patients who suffered from head and neck cancer (n = 8) undergoing fractioned partial-body irradiations (1.8 Gy/fraction and 50–70 Gy total dose). Samples were taken 12–24 h before first irradiation and ideally 24 and 48 h, as well as 5 weeks after radiotherapy onset. Due to the low quality and quantity of isolated RNA samples from one patient, they had to be excluded from further analysis, leaving a total of 24 saliva and 24 blood samples from 7 patients eligible for analysis. Using qRT-PCR, 18S rRNA and 16S rRNA (the ratio being a surrogate for the relative human RNA/bacterial burden), four housekeeping genes and nine mRNAs previously identified as radiation responsive in blood-based studies were detected. Significant GE associations with absorbed dose were found for five genes and after the 2nd radiotherapy fraction, shown by, e.g., the increase of CDKN1A (2.0 fold, P = 0.017) and FDXR (1.9 fold increased, P = 0.002). After the 25th radiotherapy fraction, however, all four genes (FDXR, DDB2, POU2AF1, WNT3) predicting ARS (acute radiation syndrome) severity, as well as further genes (including CCNG1 [median-fold change (FC) = 0.3, P = 0.013], and GADD45A (median-FC = 0.3, P = 0.031)) appeared significantly downregulated (FC = 0.3, P = 0.01–0.03). A significant association of CCNG1, POU2AF1, HPRT1, and WNT3 (P = 0.006-0.04) with acute or late radiotoxicity could be shown before the onset of these clinical outcomes. In an established set of four genes predicting acute health effects in blood, the response in saliva samples was similar to the expected up- (FDXR, DDB2) or downregulation (POU2AF1, WNT3) in blood for up to 71% of the measurements. Comparing GE responses (PHPT1, CCNG1, CDKN1A, GADD45A, SESN1) in saliva and blood samples, there was a significant linear association between saliva and blood response of CDKN1A (R2 = 0.60, P = 0.0004). However, the GE pattern of other genes differed between saliva and blood. In summary, the current human in vivo study, (I) reveals significant radiation-induced GE associations of five transcriptional biomarkers in salivary samples, (II) suggests genes predicting diverse clinical outcomes such as acute and late radiotoxicity as well as ARS severity, and (III) supports the view that blood-based GE response can be reflected in saliva samples, indicating that saliva is a “mirror of the body” for certain but not all genes and, thus, studies for each gene of interest in blood are required for saliva.

A multiple-parameter based approach using radiation-induced clinical signs and symptoms, hematology changes, cytogenetic chromosomal aberrations, and molecular biomarkers changes after radiation exposure is used for biodosimetry-based dose assessment. In the current article, relevant milestones from Radiation Research are documented that forms the basis of the current consensus approach for diagnostics after radiation exposure. For example, in 1962 the use of cytogenetic chromosomal aberration using the lymphocyte metaphase spread dicentric assay for biodosimetry applications was first published in Radiation Research. This assay is now complimented using other cytogenetic chromosomal aberration assays (i.e., chromosomal translocations, cytokinesis-blocked micronuclei, premature chromosome condensation, γ-H2AX foci, etc.). Changes in blood cell counts represent an early-phase biomarker for radiation exposures. Molecular biomarker changes have evolved to include panels of organ-specific plasma proteomic and blood-based gene expression biomarkers for radiation dose assessment. Maturation of these assays are shown by efforts for automated processing and scoring, development of point-of-care diagnostics devices, service laboratories inter-comparison exercises, and applications for dose and injury assessments in radiation accidents. An alternative and complementary approach has been advocated with the focus to de-emphasize "dose" and instead focus on predicting acute or delayed health effects. The same biomarkers used for dose estimation (e.g., lymphocyte counts) can be used to directly predict the later developing severity degree of acute health effects without performing dose estimation as an additional or intermediate step. This review illustrates contributing steps toward these developments published in Radiation Research.

Increased radiological and nuclear threats require preparedness. Our earlier work identified a set of four genes (DDB2, FDXR, POU2AF1 and WNT3), which predicts severity of the hematological acute radiation syndrome (H-ARS) within the first three days postirradiation In this study of 41 Rhesus macaques (Macaca mulatta, 27 males, 14 females) irradiated with 5.8-7.2 Gy (LD29-50/60), including some treated with gamma-tocotrienol (GT3, a radiation countermeasure) we independently validated these genes as predictors in both sexes and examined them after three days. At the Armed Forces Radiobiology Research Institute/Uniformed Services University of the Health Sciences, peripheral whole blood (1 ml) of Rhesus macaques was collected into PAXgene® Blood RNA tubes pre-irradiation after 1, 2, 3, 35 and 60 days postirradiation, stored at -80°C for internal experimental analyses. Leftover tubes from these already ongoing studies were kindly provided to Bundeswehr Institute of Radiobiology. RNA was isolated (QIAsymphony), converted into cDNA, and for further gene expression (GE) studies quantitative RT-PCR was performed. Differential gene expression (DGE) was measured relative to the pre-irradiation Rhesus macaques samples. Within the first three days postirradiation, we found similar results to human data: 1. FDXR and DDB2 were up-regulated, FDXR up to 3.5-fold, and DDB2 up to 13.5-fold in the median; 2. POU2AF1 appeared down regulated around tenfold in nearly all Rhesus macaques; 3. Contrary to human data, DDB2 was more up-regulated than FDXR, and the difference of the fold change (FC) ranged between 2.4 and 10, while the median fold changes of WNT3, except days 1 and 35, were close to 1. Nevertheless, 46% of the Rhesus macaques showed down-regulated WNT3 on day one postirradiation, which decreased to 12.2% on day 3 postirradiation. Considering the extended phase, there was a trend towards decreased fold changes at day 35, with median-fold changes ranging from 0.7 for DDB2 to 0.1 for POU2AF1, and on day 60 postirradiation, DGE in surviving animals was close to pre-exposure values for all four genes. In conclusion, the diagnostic significance for radiation-induced H-ARS severity prediction of FDXR, DDB2, and POU2AF1 was confirmed in this Rhesus macaques model. However, DDB2 showed higher GE values than FDXR. As shown in previous studies, the diagnostic significance of WNT3 could not be reproduced in Rhesus macaques; this could be due to the choice of animal model and methodological challenges.

BACKGROUND:The tin (Sn) prefilter technique is a recently introduced dose-saving technique in computed tomography (CT). This study investigates whether there is an altered molecular biological response in blood cells using the tin prefiltering technique. METHODS:Blood from 6 donors was X-irradiated ex-vivo with 20 mGy full dose (FD) protocols (Sn 150 kV, 150 kV, and 120 kV) and a tin prefiltered 16.5 mGy low dose (LD) protocol on a CT scanner. Biological changes were determined by quantification of γH2AX DNA double-strand break (DSB) foci, and differential gene expression (DGE) relative to unexposed samples were examined for seven known radiation-induced genes (FDXR, DDB2, BAX, CDKN1A, AEN, EDA2R, APOBEC3H) and 667 microRNAs (miRNA). RESULTS:EDA2R and DDB2 gene expression (GE) increased 1.7-6-fold (p = 0.0004-0.02) and average DNA DSB foci value (0.31±0.02, p<0.0001) increased significantly relative to unexposed samples, but similarly for the applied radiation protocols. FDXR upregulation (2.2-fold) was significant for FD protocols (p = 0.01-0.02) relative to unexposed samples. miRNA GE changes were not significant (p = 0.15-1.00) and DGE were similar for the examined protocols (p = 0.10-1.00). An increased frequency of lower DGE values was seen in the Sn 150 kV LD protocol compared to the 120 kV FD and Sn 150 kV FD protocols (p = 0.001-0.008). CONCLUSIONS:The current ex-vivo study indicates no changes regarding transcriptional and post-transcriptional DGE and DNA DSB induction when using the tin prefilter technique and even a significant tendency to lower radiation-induced DGE-changes due to the dose reduction of the tin prefilter with equal image quality compared to classical CT scan protocols was found.