Radiation Exposure Determination in a Secure, Cloud-based Online Environment

Background: In a major radiation incident, the speed of sample processing and interpretation of estimated exposures will be critical for triaging individuals. The Automated Dicentric Chromosome (DC) Identifier and Dose Estimator System (ADCI) selects and processes images to identify DCs and determines radiation dose without manual review. The goal of this study was to broaden accessibility and speed of this system with data parallelization while protecting data and software integrity. Methods: ADCI_Online is a secure web-streaming platform that can be accessed worldwide from distributed local nodes. Data and software are separated until they are linked for estimation of radiation exposures. Performance is assessed with data from multiple biodosimetry laboratories. Results: Dose estimates from ADCI_Online are identical to ADCI running on dedicated GPU-accelerated hardware. Metaphase image processing, automated image selection, calibration curve generation, and radiation dose estimation of a typical set of samples of unknown exposures were completed in <2 days. Parallelized processing and analyses using cloned software instances on different hardware configurations of samples at the scale of an intermediate-sized radiation accident (54,595 metaphase images) accelerated estimation of radiation doses to within clinically-relevant time frames. Conclusions: The ADCI_Online streaming platform is intended for on-demand, standardized radiation research assessment, biodosimetry proficiency testing, inter-laboratory comparisons, and training. The platform has the capacity to handle analytic bottlenecks in intermediate to large radiation accidents or events.

Early Biomarkers Associated with P53 Signaling for Acute Radiation Injury

Background: Rapid and accurate high-throughput estimation of radiation dose aims to help medical rescue in nuclear radiation accident. However, current methods of dose estimation are still lacking of speedy or accuracy. P53 signaling pathway plays an important role in DNA damage repair and cell apoptosis induced by ionizing radiation. The changes of radiation-induced P53 related genes in the early stage of ionizing radiation should compensate for the deficiency of lymphocyte decline and γ-H2AX analysis as novel biomarkers of radiation damage. Methods: Bioinformatic analysis was performed on previous data to find candidate genes from human peripheral blood irradiated in vitro. The radiation sensitivity and baseline levels of candidate genes were verified. The approximate threshold for guiding medical treatment was estimated for each gene, and four genes were combined to construct an effectively early dose estimation model of radiation.Results: Four p53-related genes, DDB2, AEN, TRIAP1 and TRAF4, were screened and verified their significant radiosensitivity. Their expressions were stable without gender or age difference in healthy population, but significantly up-regulated by radiation, with time specificity and dose dependence in 2h-24h after irradiation. Further studies showed these genes can be used as indicators for early medical treatment in acute radiation injury. The effective combination of the four genes could achieve a more accurate dose assessment and injury classification for large-scale wounded patients within 24 hours post exposure.Conclusions: This is the first time to investigate the potential biomarkers of ionizing radiation by systematic study. The effective combination of the four genes provides a new model for dose estimation and injury classification of a large number of exposed population in acute nuclear accidents, and also provides a new idea and method.