International journal of radiation biology最新文献

Introduction: The need for accurate relative biological effectiveness (RBE) estimation for low energy therapeutic X-rays (corresponding to 50 kV nominal energy of a commercial low-energy IORT system (INTRABEAM)) is a crucial issue due to increased radiobiological effects, respect to high energy photons. Modeling of radiation-induced DNA damage through Monte Carlo (MC) simulation approaches can give useful information. Hence, this study aimed to evaluate and compare RBE of low energy therapeutic X-rays using Geant4-DNA toolkit and Monte Carlo damage simulation (MCDS) code.

Materials and methods: RBE calculations were performed considering the emitted secondary electron spectra through interactions of low energy X-rays inside the medium. In Geant4-DNA, the DNA strand breaks were obtained by employing a B-DNA model in physical stage with 10.79 eV energy-threshold and the probability of hydroxyl radical's chemical reactions of about 0.13%. Furthermore, RBE estimations by MCDS code were performed under fully aerobic conditions.

Results: Acquired results by two considered MC codes showed that the same trend is found for RBE_DSB and RBE_SSB variations. Totally, a reasonable agreement between the calculated RBE values (both RBE_SSB and RBE_DSB) existed between the two considered MC codes. The mean differences of 9.2% and 1.8% were obtained between the estimated RBE_SSB and RBE_DSB values by two codes, respectively.

Conclusion: Based on the obtained results, it can be concluded that a tolerable accordance is found between the calculated RBE_DSB values through MCDS and Geant4-DNA, a fact which appropriates both codes for RBE evaluations of low energy therapeutic X-rays, especially in the case of RBE_DSB where lethal damages are regarded.

Purpose: Radiation-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 methods: Two 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 °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.

Results: Dose 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.

Conclusion: Methodological 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 ΔCt 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.

Purpose: The dicentric chromosome assay (DCA), often referred to as the 'gold standard' in radiation dose estimation, exhibits significant challenges as a consequence of its labor-intensive nature and dependency on expert knowledge. Existing automated technologies face limitations in accurately identifying dicentric chromosomes (DCs), resulting in decreased precision for radiation dose estimation. Furthermore, in the process of identifying DCs through automatic or semi-automatic methods, the resulting distribution could demonstrate under-dispersion or over-dispersion, which results in significant deviations from the Poisson distribution. In response to these issues, we developed an algorithm that employs deep learning to automatically identify chromosomes and perform fully automatic and accurate estimation of diverse radiation doses, adhering to a Poisson distribution.

Materials and methods: The dataset utilized for the dose estimation algorithm was generated from 30 healthy donors, with samples created across seven doses, ranging from 0 to 4 Gy. The procedure encompasses several steps: extracting images for dose estimation, counting chromosomes, and detecting DC and fragments. To accomplish these tasks, we utilize a diverse array of artificial neural networks (ANNs). The identification of DCs was accomplished using a detection mechanism that integrates both deep learning-based object detection and classification methods. Based on these detection results, dose-response curves were constructed. A dose estimation was carried out by combining a regression-based ANN with the Monte-Carlo method.

Results: In the process of extracting images for dose analysis and identifying DCs, an under-dispersion tendency was observed. To rectify the discrepancy, classification ANN was employed to identify the results of DC detection. This approach led to satisfaction of Poisson distribution criteria by 32 out of the initial pool of 35 data points. In the subsequent stage, dose-response curves were constructed using data from 25 donors. Data provided by the remaining five donors served in performing dose estimations, which were subsequently calibrated by incorporating a regression-based ANN. Of the 23 points, 22 fell within their respective confidence intervals at p < .05 (95%), except for those associated with doses at levels below 0.5 Gy, where accurate calculation was obstructed by numerical issues. The accuracy of dose estimation has been improved for all radiation levels, with the exception of 1 Gy.

Conclusions: This study successfully demonstrates a high-precision dose estimation method across a general range up to 4 Gy through fully automated detection of DCs, adhering strictly to Poisson distribution. Incorporating multiple ANNs confirms the ability to perform fully automated radiation dose estimation. This approach is particularly advantageous in scenarios such as

Purpose: In this short tale, we describe a year of Pierre Chris Curry's ionizing radiation (IR) exposure, assessing and summarizing how much he has been exposed to over a year of his fictive life, cumulating the different types of exposures (either due to natural radiation, occupational and medical exposure), while staying reasonably credible. We have limited ourselves to IR exposure. As a recognized specialist in interventional cardiac surgery, Pierre provides lectures at international conferences requiring overseas flights. When not traveling, Pierre lives in Brittany in an area where there is high natural background radiation, owing to significant concentrations of radon, a radioactive gas produced from the natural radioactive decay of uranium found in rocks, granite in this case.

Conclusion: Natural exposures correspond to half of Pierre's total yearly exposure. Therefore, where you live, and your life habits have an important impact on your radiation exposure levels. Medical exposures take the second place in the ranking, but these exposures are punctual. Although his professional exposure is the lowest percentage, this represents a chronic exposure which is continuous over the duration of his working life, and alongside the natural exposure, is building on over-time. Although Pierre calculated total yearly dose was 58.4 mSv, significantly higher than the average in countries such as France, UK or even USA, his excess risk of death from cancer was still very low 0.292%.

Purpose: The Sex Differences in Radiation Research workshop addressed the role of sex as a confounder in radiation research and its implication in real-world radiological and nuclear applications.

Methods: In April 2022, HHS-wide partners from the Radiation and Nuclear Countermeasures Program, the Office of Research on Women's Health National Institutes of Health Office of Women's Health, U.S. Food and Drug Administration, and the Radiological and Nuclear Countermeasures Branch at the Biomedical Advanced Research and Development Authority conducted a workshop to address the scientific implication and knowledge gaps in understanding sex in basic and translational research. The goals of this workshop were to examine sex differences in 1. Radiation animal models and understand how these may affect radiation medical countermeasure development; 2. Biodosimetry and/or biomarkers used to assess acute radiation syndrome, delayed effects of acute radiation exposure, and/or predict major organ morbidities; 3. medical research that lacks representation from both sexes. In addition, regulatory policies that influence inclusion of women in research, and the gaps that exist in drug development and device clearance were discussed. Finally, real-world sex differences in human health scenarios were also considered.

Results: This report provides an overview of the two-day workshop, and open discussion among academic investigators, industry researchers, and U.S. government representatives.

Conclusions: This meeting highlighted that current study designs lack the power to determine statistical significance based on sex, and much is unknown about the underlying factors that contribute to these differences. Investigators should accommodate both sexes in all stages of research to ensure that the outcome is robust, reproducible, and accurate, and will benefit public health.

Purpose: The impact of the exposure to ionizing radiation in the offspring and next generation has been investigated in the last decades and currently is the subject of study of the ICRP Task Group 121. Studying the effects of radiation exposure in pre-conceptional and post-conceptional phases can be a challenge since potential effects to the fetus vary depending on the stage of fetal development. Epidemiology and radiobiology studies are the two sources of information one can use to correlate the radiation dose to the human body and tissues and the resulting effects. For a proper evaluation of the outcomes of such studies, and a correct appraisal of the exposure/dose-effect relationship, (i) reliable dosimetry, (ii) accurate reporting, and (iii) reproducibility of results are required. Although variables related to dose, including for instance source of radiation, geometry of irradiation, dose rate etc., are usually known, especially in radiobiology studies, often important details of the irradiation are not reported.

Conclusions: Based on standards developed by the National Cancer Institute (NCI), the National Institute of Allergy and Infectious Disease (NIAID) and the National Institute of Standards and Technology (NIST), a review of the scientific studies used by the UNSCEAR to estimate the risk of hereditary effects, and by the ICRP in its current recommendations, was conducted to evaluate the way dosimetry was reported. Dosimetry and the related uncertainties were not adequately described in the vast majority of those studies. This does not necessarily mean that they do not provide relevant information, however it prevents from a thorough verification and reproduction of their findings. In order to guarantee the reliability and robustness of the process of revision of the estimates of risk and detriment it is therefore considered mandatory to include a careful check of the new relevant literature with regard to the criteria on the completeness and reproducibility of the dosimetric information.

Background: This study aimed to evaluate the clinical efficacy of coaxial percutaneous Iodine-125 (¹²⁵I) seed implantation in combination with arterial infusion chemotherapy for the treatment of advanced pancreatic cancer (PC) through a randomized controlled trial.

Methods: A total of 101 patients with advanced PC were randomized into two groups: control group treated with systemic intravenous chemotherapy and experimental group that received ¹²⁵I seed implantation in combination with arterial infusion chemotherapy. Outcomes, including tumor control, abdominal pain relief, and survival time were compared between these two groups (Trial Registration No. KYKT2018-65).

Results: Pretreatment abdominal pain scores were comparable between the two groups, whereas the abdominal pain scores at 1- and 3-month post-treatment were significantly lower in the control group than those in the experimental group (1-month: 3.74 ± 1.54 vs. 4.48 ± 1.46, p = .015; 3-month: 3.64 ± 2.21 vs. 5.40 ± 1.56, p < .001). At 3-month post-treatment, computed tomography (CT) scan revealed a significantly higher disease control rate in the experimental group than that in the control group (94.0% vs. 74.5%, p = .007). The median survival time in the experimental group was significantly longer than that in the control group (15-month vs. 9-month, p < .001).

Conclusion: The combination of coaxial percutaneous ¹²⁵I seed implantation with arterial infusion chemotherapy could significantly alleviate abdominal pain, improve tumor control rates, and prolong survival time in patients with advanced PC.

Purpose: Chromosomal dicentrics and translocations are commonly employed as biomarkers to estimate radiation doses. The main goal of this article is to perform a comparative analysis of yields of both types of aberrations. The objective is to determine if there are relevant distinctions between both yields, allowing for a comprehensive assessment of their respective suitability and accuracy in the estimation of radiation doses.

Materials and methods: The analysis involved data from a partial-radiation simulation study with the calibration data obtained through two scoring methods: conventional and PAINT modified. Subsequently, a Bayesian bivariate zero-inflated Poisson model was employed to compare the posterior marginal density of the mean of dicentrics and translocations and assess the differences between them.

Results: When employing the conventional method of scoring, the findings indicate that there is no notable disparity between the yield of observed translocations and dicentrics. However, when utilizing the PAINT modified method, a notable discrepancy is observed for higher doses, indicating a relevant difference in the mean number of the two types of aberrations.

Conclusions: The choice of scoring method significantly influences the analysis of radiation-induced aberrations, especially when distinguishing between complex and simple chromosomal formations. Further research and analysis are necessary to gain a deeper understanding of the factors and mechanisms impacting the formation of dicentrics and translocations.

Purpose: In order to achieve mutations with enhanced economic, productive, and nutritional characteristics in the two Egyptian cowpea varieties, Dokki 331 and Kaha 1, the application of gamma irradiation at different doses is employed. Additionally, this method aids in distinguishing between these mutations using simple sequence repeat (SSR) analysis.

Materials and methods: Two different cowpea cultivars were subjected to varying doses of gamma radiation ranging from 50 to 300 Gy. In order to analyze the effects of radiation, both unirradiated and irradiated seeds from both cultivars were planted using a randomized complete block design. This experiment was conducted over a span of six generations, namely M1, M2, M3, M4, M5, and M6, starting from April 2017 and continuing until 2022. Among the various radiation doses, the cultivar Kaha 1 produced promising traits when exposed to a dose of 150 Gy, while the cultivar Dokki 331 showed favorable traits when exposed to a dose of 300 Gy. These traits were further cultivated and studied until the M6 generation.

Results: Induced mutations in two Egyptian cowpea varieties, Kaha 1 and Dokki 331, are subjected to varying doses of gamma radiation (0, 50, 100, 150, 200, 250, and 300 Gy). Morphological and genetic variations were observed, with mutations being induced at doses of 150 Gy for Kaha 1 and 300 Gy for Dokki 331. The mutation in Kaha 1 (beam 1) resulted in dwarfism, altered leaf shape, early flowering, increased peduncles, pods, and pod seed numbers, ultimately leading to enhanced seed production and acreage productivity. In Dokki 331, the mutations primarily affected pod color, resulting in greenish-brown pods with mosaic seeds, segregating black and gray seeds from the mosaic ones. These mutations led to an increase in the nutritional value of the seeds, including higher nitrogen content, total free amino acids, crude protein, total carbohydrates, and total sugars. The genetic diversity of the seven cowpea mutations was assessed using 20 microsatellite markers. The analysis revealed a total of 60 alleles, with an average of three alleles per locus. The allele frequency ranged from 0.2857 to 1.0, with an average of 0.6036. Gene diversity varied from 0.0 to 0.8163, while the heterozygosity was mostly zero, except for one primer (VM 37) with an average of 0.0071. The polymorphic information content (PIC) ranged from 0.7913 to 0.0, with an average of 0.4323. The Marker Index value ranged from 0.36 to 0.0, with an average of 0.152. Overall, our findings demonstrate the successful induction of mutations in Egyptian cowpea varieties using gamma rays, resulting in improved yield characteristics and nutritional value.

Conclusions: Radiation as a physical mutagen is highly regarded for its effectiveness, affordability, speed, and safety in inducing mutations. Utilizing gamma rays, we successfully derived a novel cowpea v

Purpose: Docetaxel (DXL), a noted radiosensitizer, is one of the few chemotherapy drugs approved for castration-resistant prostate cancer (CRPC), though only a fraction of CRPCs respond to it. CAV-1, a critical regulator of radioresistance, has been known to modulate DXL and radiation effects. Combining DXL with radiotherapy may create a synergistic anticancer effect through CAV-1 and improve CRPC patients' response to therapy. Here, we investigate the effectiveness and molecular characteristics of DXL and radiation combination therapy in vitro.

Materials and methods: We used live/dead assays to determine the IC₅₀ of DXL for PC3, DU-145, and TRAMP-C1 cells. Colony formation assay was used to determine the radioresponse of the same cells treated with radiation with/without IC₅₀ DXL (4, 8, and 12 Gy). We performed gene expression analysis on public transcriptomic data collected from human-derived prostate cancer cell lines (C4-2, PC3, DU-145, and LNCaP) treated with DXL for 8, 16, and 72 hours. Cell cycle arrest and protein expression were assessed using flow cytometry and western blot, respectively.

Results: Compared to radiation alone, combination therapy with DXL significantly increased CRPC death in PC3 (1.48-fold, p < .0001), DU-145 (1.64-fold, p < .05), and TRAMP-C1 (1.13-fold, p < .05) at 4 Gy of radiation. Gene expression of CRPC treated with DXL revealed downregulated genes related to cell cycle regulation and upregulated genes related to immune activation and oxidative stress. Confirming the results, G2/M cell cycle arrest was significantly increased after treatment with DXL and radiation. CAV-1 protein expression was decreased after DXL treatment in a dose-dependent manner; furthermore, CAV-1 copy number was strongly associated with poor response to therapy in CRPC patients.

Conclusions: Our results suggest that DXL sensitizes CRPC cells to radiation by downregulating CAV-1. DXL + radiation combination therapy may be effective at treating CRPC, especially subtypes associated with high CAV-1 expression, and should be studied further.