The dicentric chromosome assay is the “gold standard” in biodosimetry for estimating radiation exposure. However, its large-scale deployment is limited owing to its time-consuming nature and requirement for expert reviewers. Therefore, a recently developed automated system was evaluated for the dicentric chromosome assay. A previously constructed deep learning-based automatic dose-estimation system (DLADES) was used to construct dose curves and calculate estimated doses. Blood samples from two donors were exposed to cobalt-60 gamma rays (0–4 Gy, 0.8 Gy/min). The DLADES efficiently identified monocentric and dicentric chromosomes but showed impaired recognition of complete cells with 46 chromosomes. We estimated the chromosome number of each “Accepted” sample in the DLADES and sorted similar-quality images by removing outliers using the 1.5IQR method. Eleven of the 12 data points followed Poisson distribution. Blind samples were prepared for each dose to verify the accuracy of the estimated dose generated by the curve. The estimated dose was calculated using Merkle’s method. The actual dose for each sample was within the 95% confidence limits of the estimated dose. Sorting similar-quality images using chromosome numbers is crucial for the automated dicentric chromosome assay. We successfully constructed a dose–response curve and determined the estimated dose using the DLADES.
The adverse effects of radiation are proportional to the total dose and dose rate. We aimed to investigate the effects of radiation dose rate on different organs in mice. The mice were subjected to low dose rate (LDR, ~3.4 mGy/h) and high dose rate (HDR, ~51 Gy/h) radiation. LDR radiation caused severe tissue toxicity, as observed in the histological analysis of testis. It adversely influenced sperm production, including sperm count and motility, and induced greater sperm abnormalities. The expression of markers of early stage spermatogonial stem cells, such as Plzf, c-Kit, and Oct4, decreased significantly after LDR irradiation, compared to that following exposure of HDR radiation, in qPCR analysis. The compositional ratios of all stages of spermatogonia and meiotic cells, except round spermatid, were considerably reduced by LDR in FACS analysis. Therefore, LDR radiation caused more adverse testicular damage than that by HDR radiation, contrary to the response observed in other organs. Therefore, the dose rate of radiation may have differential effects, depending on the organ; it is necessary to evaluate the effect of radiation in terms of radiation dose, dose rate, organ type, and other conditions.
The dicentric chromosome assay is the “gold standard” in biodosimetry for estimating radiation exposure. However, large-scale deployment is limited due to its time-consuming nature and requirement for expert reviewers. Therefore, a recently developed automated system was evaluated for dicentric chromosome assay. A previously constructed deep learning-based automatic dose-estimation system (DLADES) was used to construct dose curves and calculate estimated doses. Blood samples from two donors were exposed to cobalt-60 gamma rays (0–4 Gy, at 0.8 Gy/min). DLADES efficiently identified monocentric and dicentric chromosomes but showed impaired recognition of complete cells with 46 chromosomes. We estimated the chromosome number of each “Accepted” sample in DLADES and sorted similar-quality images by removing outliers using the 1.5IQR method. We confirmed that 11 of the 12 data points followed the Poisson distribution. Blind samples were prepared for each dose to verify the accuracy of the estimated dose generated by the curve. The estimated dose was calculated using Merkle’s method. The actual dose for each sample was within the 95% confidence limits of the estimated dose. Sorting similar-quality images using chromosome numbers is crucial for automated dicentric chromosome assay. We successfully constructed a dose-response curve and determined the estimated dose using DLADES.
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